Beyond Neurotransmission - P. Katz (Oxford, 1999) WW

Beyond Neurotransmission

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Beyond Neurotransmission

Neuromodulation and its Importance for Information Processing

Edited by

Paul S. Katz

Department of BiologyGeorgia State University

OXFORDUNIVERSITY PRESS

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A catalogue record for this book is available from the British Library

Library of Congress Cataloging in Publication DataBeyond neurotransmission : neuromodulation and its importance forinformation processing / edited by Paul S. Katz.Includes bibliographical references and index.1. Neural transmission - Regulation. I. Katz, Paul S.[DNLM: 1. Neurotransmitters - physiology. 2. Neurons - physiology.3. Mental Processes - physiology. QV 126B573 1999]QP364.5.B49 1999573.8'54 - dc21DNLM/DLCfor Library of Congress 98-39256 CIP

ISBN 0 19 852424 2

Typeset by Technical Typesetting Ireland in BelfastPrinted in Great Britain by Bookcraft Ltd., Midsomer Norton, Avon

Forewordby Ronald M. Harris-Warrick

It wasn't very long ago that most neuroscientists thought the brain was ablack and white world: all chemical communication in the nervous systemwas mediated by either rapid excitatory or rapid inhibitory synaptic poten-tials, and the major role of neurons was to algebraically summate synapticinput and decide whether or not to spike. That time is now gone, as this fineintroduction to neuromodulation makes abundantly clear. We now knowthat there is a huge diversity of non-traditional modes of neuronal communi-cation, grouped under the general name of neuromodulation, which creates amulticolored rainbow of varied ways for neurons to be affected and to affectone another.

Paul Katz, one of the most innovative leaders in this field, has selected aninternational group of experts to bring together a superb summary of thecutting edge of research spanning the full range of this growing and excitingfield, from biochemical mechanisms of receptors and second messengers tobehavioral analyses of neuromodulation during learning. Since neuromodula-tion is ubiquitous and affects every part of nervous system function, neurosci-entists of all stripes can benefit from reading this book; it should provokenew research in a number of areas. Scientists studying molecular and cellularaspects of nervous system function will deepen their understanding of thecomplexities of molecular modulation. Systems neuroscientists working athigher levels will also see how neuromodulation permeates their field: it is nolonger possible to discuss sensory processing or motor coordination withouta full recognition of the many roles that non-traditional forms of neuronalactivity and communication play. Behavioral pharmacologists who workwith neuromodulators such as amines and peptides will recognize that theterms 'excitatory' and 'inhibitory' only hint at the complex functions thatcompound such as dopamine and serotonin play in affecting higher levelfunctions. Even high-level modelers and neurophilosophers will find usefulreminders of the fractal nature of the real nervous system in which eachneuron is an independent microprocessor, with variable baseline states andvariable non-linear input/output functions that are controlled by the modu-latory milieu. For all of us who study the brain, the moment-to-momentplasticity of properties of neurons and their connections is central to allhigher order cognitive function, and cannot be ignored.

By giving an accessible yet thorough survey of the field of modulation,Katz and his colleagues are showing all of us a better view of the machineryof the real brain. The reader should be prepared to accept a quantum leap intheir perception of the complexity of neural function. Thanks to the actionsof neuromodulators, the number of possible interactions and states of activity

vi Foreword

in the brain is inconceivably greater than was previously thought. Thisrevelation is delightful and exciting, and gives us a glimmer of understandinginto how magnificent human brains could have created Hamlet and The Artof the Fugue.

Preface

As neuroscientists, our goal is to understand how nervous systems processinformation. What steps occur in the brain during decision making? How doanimals perceive their environment? How do animals learn? One problemthat we face is that we don't know all of the forms that information takes inthe nervous system, nor how it is communicated. Often there is an underlyingassumption that information is transferred through the nervous system in theform of neurotransmission consisting of fast excitatory postsynaptic poten-tials (EPSPs) and fast inhibitory postsynaptic potentials (IPSPs); all otherneuronal actions, such as neuromodulation, are usually considered secondaryand not really involved in active information transfer. This view of informa-tion flow dismisses what may be some of the brain's most importantcomputational capabilities.

The aim of this book is to explore these other mechanisms of transferringinformation through the nervous system. The title of this book, BeyondNeurotransmission, is not meant to imply that we already understand all theimplications of neurotransmission. In fact, it can be said that we may bemisled by the apparent simplicity of neurotransmission. Rather, the pointthat we are making is that there are many other forms of neuronal communi-cation that also need to be considered when trying to understand hownervous systems process information.

Although the term neuromodulation has been in common usage for morethan 20 years, there is still a great deal of disagreement about what it means,as I found when I conducted an informal survey of my colleagues working inthe field. I asked them to label particular situations as either:

A) Neurotransmission,B) Neuromodulation,C) Neither,D) Both, orE) Cannot be determined from this information.

Here are the responses that I received from three of the situations:

Situation 1) Slow EPSPs such as peptidergic, muscarinic, or aminergic inputto sympathetic ganglia.

Responses:33% of the respondents said it was an example of neurotransmission because

the inputs caused a depolarization,33% said it was neuromodulation because these inputs have slow actions,

and33% said it was both neurotransmission and neuromodulation.

viii Preface

Situation 2) A morphologically defined synapse that uses G protein-coupledreceptors (i.e. metabotropic receptors).

Responses:25% of the respondents said that this would be considered neurotransmis-

sion because it was a morphologically defined synapse,25% said neuromodulation because anything with a metabotropic receptor is

modulatory,25% said it was both neurotransmission and neuromodulation, and25% said that it can't be determined from this information.

Situation 3) Presynaptic inhibition (e.g. GABA inputs onto axonal terminals).

Responses:40% said neurotransmission because it involves morphologically defined

synapses and ionotropic receptors and60% said this would be neuromodulation because the presynaptic inhibition

alters the strengths of synapses.

This informal poll convinced me that the book needed to begin by addressingwhat neuromodulation is. It is of little use to again attempt to strictly defineneuromodulation or coin new terms. This just leads to more disagreementsover semantics. The important point here is that, regardless of what we callthem, there are more modes for communication of information in thenervous system. In this case, neuromodulation is as good a term as any.

This book seeks to examine neuromodulation and its functional role ininformation flow and neural circuit flexibility. It has three functional divi-sions:

1. The first section of the book deals with the mechanisms of neuromodula-tion. It is intended to provide a basis for systems physiologists to catch upwith some of the latest cellular concepts in neuromodulation. It takes alarge volume of current literature and synthesizes some fundamentalprinciples for neuromodulation and cellular signaling.

• Chapter 1 begins by exploring some of the alternate forms of neuronalcommunication and why they are important for understanding how thebrain works.

• Chapter 2 discusses the roles that intercellular messengers play in bothneurotransmission and neuromodulation. It defines how neurons commu-nicate information and the roles that neurotransmitters and receptors playin defining the message.

• Chapter 3 reviews our current knowledge of intracellular second messen-ger processes involved in neuromodulation. This is a review of howmodulatory signals are translated into cellular actions.

Preface ix

• Chapter 4 examines how neurons change their behavior in response toneuromodulatory signals. The control of neuronal properties is whatreally defines neuromodulatory communication.

• Chapter 5 discusses the concept of metaplasticity where plasticity itselfcan be altered. This chapter offers a slightly different perspective on theimportance of heterosynaptic versus homosynaptic mechanisms in thecontrol of synaptic plasticity.

2. In order to understand the roles played by neuromodulation in vivo., it isnecessary to look at how systems of neurons use neuromodulation toprocess information. Therefore, the second section of the book focuses onthe use and control of neuromodulation. These chapters provide usefulexamples from many different systems. They serve to illustrate the impor-tance of neuromodulatory signaling in information flow in the nervoussystem. I hope these chapters will also inspire systems physiologists toconsider how neuromodulation might be operating in their own experi-mental systems.

• Beginning with information entering the nervous system, Chapter 6 ex-plores how neuromodulation affects sensory processing. It shows thatneuromodulation has effects at every stage of sensory processing.

• Chapter 7 looks at the output of the nervous system by examining howneuromodulation alters neuromuscular transmission and what role thatalteration plays in the production of muscular movements. This chapteralso gives a more general look at the role that neuromodulation plays inmatching input/output properties of senders and receivers.

• Chapter 8 examines how neuromodulation enables the nervous system togenerate different patterns of activity which are translated into move-ments. Here the actions of neuromodulators on the basic mechanisms ofmotor pattern generation are shown to enable neuronal circuits to pro-duce flexible outputs.

• Neuromodulation also plays many important roles in learning, memory,and attention, as is discussed in Chapter 9. This chapter is importantbecause it stresses the need for mechanisms that go beyond long-termpotentiation (LTP) in models of associative learning.

3. Finally, the last section of the book deals with the next level of complex-ity, modulation of modulation or metamodulation. Chapter 10 investi-gates the various ways that neuromodulation itself is controlled. I feel thatthis is the next direction for work in the field.

To answer questions about information processing in the nervous system,researchers begin by asking how individual systems of neurons operate toproduce particular forms of behavior. For example, one may study how theneurons in the abdominal nerve cord in a crayfish communicate with each

x Preface

other to enable the animal to produce a tail-flip escape response. Or one mayexamine what changes occur in the synapses of the hippocampus of a rat thatmight underlie the ability of that animal to form long-term memories. Each ofthese experimental systems has its own peculiarities and intricacies which areimportant for its operation and can keep researchers in that area arguing fordecades, but which may not be especially exciting to those working on otherparts of the nervous system. Therefore, it is useful to step back occasionallyfrom these systems to see what common principles of nervous system opera-tion have been uncovered from these varied neuronal networks. It is thesecentral principles that shape both our notions of how the nervous systemoperates and the questions that we choose to address in our research. Theaim of this book is to highlight the general principles that are being uncov-ered in a number of systems without becoming unnecessarily burdened by thespecifics of each particular system.

As detailed in the first four chapters, there is currently an explosion ofresearch on mechanisms of neuromodulation. Although this book cannotbegin to cover this extensive field, it is hoped that it will provide the readerwith a basis for understanding and organizing this vast literature. By examin-ing how alternate forms of neuronal communication play a role in systemsphysiology, this book seeks to bring together work at the subcellular levelwith our ideas about how ensembles of neurons process information. In thisway, we can move a tiny bit closer to understanding the nature of how thebrain functions.

Contents

List of contributors xii

1 What are we talking about? Modes of neuronal communication 1Paul S. Katz

2 The messenger is not the message; or is it? 29Barry A. Trimmer

3 The inside story: subcellular mechanisms of neuromodulation 83Elizabeth A. Jonas and Leonard K. Kaczmarek

4 Message received: cellular responses to neuromodulatory signals 121Gina G. Turrigiano

5 Metaplasticity: the plasticity of synaptic plasticity 160Benjamin D. Philpot, Mark F. Bear, and Wickliffe C. Abraham

6 Changing the way we perceive things: sensory systems modulation 198Alison R. Mercer

7 Flexibility of muscle control by modulation of muscle properties 241Scott L. Hooper, Vladimir Brezina,Elizabeth C. Cropper, and Klaudiusz R. Weiss

8 Making circuits dance: neuromodulation of motor systems 275Ole Kiehn and Paul S. Katz

9 Neuromodulation and memory function 318Michael E. Hasselmo and Christiane Linster

10 Metamodulation: the control and modulation of neuromodulation 349Paul S. Katz and Donald H. Edwards

Index 383

Contributors

Wickliffe C. AbrahamDepartment of Psychology and the Neuroscience Research Centre, University ofOtago, Dunedin, New Zealand

Mark F. BearDepartment of Neuroscience, Howard Hughes Medical Institute, Brown University,Providence, RI 02912, USA

Vladimir BrezinaDepartment of Physiology and Biophysics and the Fishberg Research Center inNeurobiology, Mount Sinai School of Medicine, New York, NY 10029, USA

Elizabeth C. CropperDepartment of Physiology and Biophysics and the Fishberg Research Center inNeurobiology, Mount Sinai School of Medicine, New York, NY 10029, USA

Donald H. EdwardsDepartment of Biology, Georgia State University, Atlanta, GA 30303, USA

Michael E. HasselmoDepartment of Psychology, Boston University, Boston, MA 02215, USA

Scott L. HooperDepartment of Biological Sciences, Ohio University, Athens, OH 45701, USA

Elizabeth A. JonasDepartment of Pharmacology, Yale University School of Medicine, New Haven, CT06520, USA

Leonard K. KaczmarekDepartment of Pharmacology, Yale University School of Medicine, New Haven, CT06520, USA

Paul S. KatzDepartment of Biology, Georgia State University, Atlanta, GA 30303, USA

Ole KiehnSection of Neurophysiology, Panum Institute, University of Copenhagen, 2200Copenhagen N, Denmark

Christiane LinsterDepartment of Psychology, Boston University, Boston, MA 02215, USA

Alison R. MercerDepartment of Zoology, University of Otago, Dunedin, New Zealand

Contributors xiii

Benjamin D. Philpot

Department of Neuroscience, Howard Hughes Medical Institute, Brown University,Providence, RI 02912, USA

Barry A. TrimmerDepartment of Biology, Dana Laboratory, Tufts University, Medford, MA 02155,USA

Gina G. TurrigianoDepartment of Biology and Center for Complex Systems, Brandeis University,Waltham, MA 02254, USA

Klaudiusz R. WeissDepartment of Physiology and Biophysics and the Fishberg Research Center inNeurobiology, Mount Sinai School of Medicine, New York, NY 10029, USA


1What are we talking about?Modes of neuronal communicationPAUL S. KATZ

1.1 Introduction

A basic principle of nervous system operation, arising out of the neurondoctrine itself, is that neurons communicate 'information' to one another.This information is passed from neuron to neuron through the nervoussystem, allowing animals to sense their environment, move through it, learnfrom it, and act on it. The information itself takes many forms and it isincreasingly evident that there are a great many ways that it is communicatedbetween neurons. Recognition of the variety of mechanisms used by thenervous system for the communication of information is necessary before wecan understand the cellular basis for complex types of behavior.

Commonly, chemical communication between neurons is thought to befast (millisecond time scale), point-to-point (neuron to neuron), and simple(either excitatory or inhibitory). These are hallmarks of what we generallycall neurotransmission (Fig. 1.1). Neurotransmission is almost universallyaccepted as the primary means of communication between neurons. Thus,most discussions of information flow and circuit organization in the nervoussystem include only neurotransmission. Yet there are many instances whereinterneuronal communication does not display all of these traits. In fact, thevast majority of substances that are synthesized and released by neurons havesome effects that would not fit this characterization of neurotransmission (seeChapter 2). Thus, to fully comprehend how information is conveyed in thebrain, we must look beyond simple neurotransmission and into other modesof neuronal communication.

1.2 Alternate forms of neuronal communication

There are many ways in which neuronal communication can differ fromclassical neurotransmission. In fact, there are so many variations in the modeof communication used by neurons that it has proven difficult to devise anadequate classification scheme. One term that is consistently used to describenon-classical effects is neuromodulation. Neuromodulation has been definedin a number of different ways (Dismukes 1979; Kupfermann 1979; Vizi

2 What are we talking about? Modes of neuronal communication

Fig. 1.1 Hallmarks of neurotransmission. This stylized neuronal network illustratesthe basic characteristics of neurotransmission: fast, point-to-point, and simple(excitation or inhibition). Neurons A and B synapse on neuron C. The electrodes andlines represent intracellular recordings of membrane potential. When neuron A firesaction potentials (bottom trace) it evokes postsynaptic potentials (PSPs) in neuron C.These PSPs are fast, lasting only a few milliseconds before decaying. They depolarizethe cell's membrane, bringing it closer to threshold for firing an action potential andare thus considered excitatory postsynaptic potentials or EPSPs. In contrast, actionpotentials in neuron B evoke inhibitory postsynaptic potentials (IPSPs) in neuron C,causing the membrane potential to become more negative and less likely to fire anaction potential. These neurotransmitting connections are specific; notice that neuronsA and B do not communicate directly. Also, the effects of each neuron on neuron Care specific: one is excitatory, whereas the other is inhibitory.

1984; Iversen and Goodman 1986; Kaczmarek and Levitan 1987; Lopez andBrown 1992; Powis and Bunn 1995). A seemingly straightforward definitionis:

Neuromodulation occurs when a substance released from one neuron alters thecellular or synaptic properties of another neuron (Kupfermann 1979; Kaczmarek andLevitan 1987).

Under this definition, neuromodulation is not directly excitatory or in-hibitory, but rather its effects are contingent on the activity of the neuronsthat are acted upon. Although this definition of neuromodulation fits withour common notion of the word modulation, it fails to encompass all of thenon-classical forms of communication between neurons. It also does not

Paul S. Katz 3

conform to many other definitions of neuromodulation in the literature.Moreover, this description fails to distinguish neurotransmission adequatelyfrom other forms of communication because even simple neurotransmissioncauses a change in membrane conductance thereby momentarily altering theintegration properties of that neuron. Rather than continue the decades-olddebate on the relative merits of each definition of neuromodulation, we willrefer to all non-classical communication by neurons as neuromodulation.That is:

Any communication between neurons, caused by release of a chemical, that is eithernot fast, or not point-to-point, or not simply excitation or inhibition will be classifiedas neuromodulatory.

This definition has the disadvantage of making the term neuromodulation abit vague, but it has the advantage of providing a single, easily comprehensi-ble label for a large variety of phenomena. Clearly there is a continuum ofcommunication modes, with a great deal of overlap between what we arecalling neurotransmission and neuromodulation. The point of this book isnot to classify all phenomena into one category or another, but to examinethe many functions of these non-classical actions in information processingby the nervous system.

1.2.1 The role of receptor type in neuronal communication

Neuronal communication generally involves a chemical substance releasedfrom one neuron contacting receptors on the surface of another neuron.(There are important exceptions to this generality, most notably gap junc-tions, where ions pass directly between neurons, and gaseous messengers,which do not act at membrane-bound receptors.) Although numerousmolecules can relay signals between neurons (see Chapter 2), there are twomain categories of cell-surface neurotransmitter receptors (Fig. 1.2), ligand-gated ion channels (ionotropic receptors) and G protein-coupled receptors(metabotropic receptors). These receptor types can be differentiated both bytheir structure and by how they act. Ionotropic receptors are limited tomerely increasing the permeability of the membrane to certain ions. Thisgenerally results in excitation (net positive charge entering the cell) orinhibition (net positive charge leaving the cell or negative charge entering). Incontrast, metabotropic receptors can have a large variety of second messen-ger-mediated effects (Levitan 1988). These include alterations in: membraneconductance (both increases and decreases), the properties of transmitterrelease, and the properties of other membrane receptors and transporters (seeChapter 3). Furthermore, second messenger cascades can alter many aspectsof the cell's physiology simultaneously, allowing a single receptor to havewidespread actions. Thus, metabotropic receptors endow neurons with agreat deal of flexibility in their communication.

A third class of cell surface receptors is receptor tyrosine kinases. These


Fig. 1.2 lonotropic and metabotropic receptors. There are two general types of cellsurface receptors, ionotropic and metabotropic receptors. A. lonotropic receptors, orligand-gated ion channels, are integral membrane proteins made up of several subunitsthat change their conformation when bound by a neurotransmitter. Thisconformational change results in the opening of a pore through the molecule thatallows ions to enter or leave the neuron. This results in a transient change inmembrane potential. B. Metabotropic, or G protein-coupled, receptors are alsointegral membrane proteins, but consist of a single protein with seven transmembranespanning regions. When bound by a neurotransmitter, they activate an associatedGTP-binding protein (G Protein). Once activated, a G protein breaks apart intosubunits which can have a variety of effects from directly altering the gating propertiesof ion channels to activating other second messenger pathways, such as adenylatecyclase. These other second messenger systems can then alter the properties of ionchannels and thus change cellular behavior.

receptors are membrane-bound enzymes that are generally activated bygrowth factors such as Nerve Growth Factor (NGF) or Brain-Derived Neu-rotrophic Factor (BDNF) or hormones such as insulin. Although many oftheir effects are related to developmental and growth functions, recentevidence suggests that they also play a role in short-term plasticity and act ona rapid time-scale (Berninger and Poo 1996) (see Chapter 3).

It may seem natural to label the ligand-gated ion channels as responsiblefor neurotransmission and the G protein-coupled receptors as responsible forneuromodulation. After all, ionotropic receptors mediate fast responses thatare either excitatory or inhibitory, whereas metabotropic receptors are slowerand often alter cellular properties. But this view may be too simplistic; insome instances, metabotropic receptors mediate what, by most accounts,would be termed neurotransmission, whereas ionotropic receptors mediatewhat many would call neuromodulation.

One example of metabotropic receptors mediating neurotransmission oc-curs in the retina (Fig. 1.3). The synaptic connections from photoreceptors toa type of retinal neuron called an on-bipolar cell are mediated by metabotropic

Paul S. Katz 5

Fig. 1.3 Neurntransrnission in the on-bipolar pa thway of tilt retina is mediated bymetabotropic receptors. The direct pathway for activation of one class of r e t i n a lganglion cells by light is through so-called on-bipolar cells (left side). Conephotoreeeptors hyperpolarize when i l luminated by l ight. This stops them from releasingglutamate. In the dark, the glutamate from the cones ac t iva tes a merabotropicglutamate receptor ( m G l u R ) on the bipolar cell. Activation of this receptor tu rns offan inward cG.VlP-gared sodium channel s imi la r to the one found in photoreccptors byactivating a phosphodicstcrase and thereby decreasing the resting concentration ofcGMP and closing the channel. When the glutamate ceases to be released from thecone, the sodium channel in the bipolar cell ceases to be inhibited, thus al lowing thebipolar cell to depolarize and release its own ncurotranstrutter, glutamate, to retinalganglion cells (RGC). The synapse from bipolar cells to retinal ganglion cells ismediated by ionotropic glutamate receptors (GluR). Although the pa thway foractivation of the retinal ganglion cell involves two metabotropic steps (the first is thephototransduction process itself involving opsin, a molecule related to metahotropicreceptors), the latency from l ight onset to the first spike in the retinal ganglion cell isonly about 40ms. The pathway involv ing off-bipolar cells (right side) is identicalexcept that glutamate released from cones direct ly activates an inward sodiumconductance via ionotropic receptors. Thus, off-bipolar cells are depola r izd in thedark, when glutamate is released from cones and hyperpolarized in the light whenphotoreceptors are hyperpolarized. The latency from the tune tha t the light is turnedoff to the f irst spike in the re t ina l ganglion cell is s imilar to the onset latency of theon-retinal ganglion cells,

g l u t a m a r e receptors (Massey and Magui re 1995). The on-bipolar cell gets its name from its excitatory response to light in the center ofits receptive field. In the dark, glutamate released from photoreceptorsinhibi ts on-bipolar cells by activating a metabotropic gluramate receptor


which suppresses an inward current. When photoreceptors in the center ofthe receptive field are illuminated, they hyperpolarize and stop releasingglutamate, freeing the inward current to depolarize the bipolar cell. Clearly,this metabotropic glutamate receptor is in the direct pathway that mediatesthe flow of visual information. Although its effect is inhibitory and fast, andby most accounts mediates neurotransmission, it is nonetheless a metabotropicreceptor.

Just as metabotropic receptors sometimes mediate neurotransmission,ionotropic receptors can mediate neuromodulatory effects. Neuronal nico-tinic acetylcholine receptors are ligand-gated ion channels found on axonterminals of neurons in the brain. They mediate presynaptic facilitation(McGehee and Role 1996) (Fig. 1.4). When activated by cholinergic inputneurons, these receptors allow calcium to enter the axon terminal. Thiscalcium influx does not in itself cause the terminal to fire an action potentialor release neurotransmitter. But if the target neuron were to fire an actionpotential due to its ongoing activity, that action potential would release moreneurotransmitter due to the added calcium influx. Thus, the effects of theneuronal nicotinic receptor are contingent upon the activity of the cell. This isa classic definition of a neuromodulatory effect, yet the receptor is ionotropic.

1.2.2 The time-scale of neuronal communication

Some researchers prefer to classify neurotransmission as fast synaptic eventsand neuromodulation as slow neuronal communication. This generally fol-lows from the ionotropic/metabotropic receptor distinction, where ionotropicreceptors typically mediate fast events (millisecond time-scale) andmetabotropic receptors ordinarily mediate slower events (hundreds of mil-liseconds to minutes). However, there is no firm temporal division betweenionotropic and metabotropic responses. Factors other than receptor type alsocontribute to differences in time-scale, such as the nature of the substancereleased by neurons, the proximity of the site of action, and the processesresponsible for inactivation of the substance (see Chapter 2). There is alsoevidence now for a class of proteins in the nervous system that helps controlthe speed of G protein-mediated processes (Neer 1997). Thus, some ionotropicpathways can be slower than others and some second messenger-mediatedeffects can be quite rapid. For example, in the on-bipolar pathway of theretina, discussed above, the latency for activation of on-retinal ganglion cellsis nearly the same as the latency for activation of the off-retinal ganglion cell(Kuffler 1953) despite the involvement of an additional metabotropic step inthe 'on' pathway. (The synapse from cones to off-bipolar cells is ionotropic.)

The importance of slow communication in the nervous system should notbe underestimated. Slow signals not only can adjust the gain of the fastsignals, but they also can alter the integration properties of the network

Paul S. Katz 7

Fig. 1.4 lonotropic receptors mediate neuromodulation of synaptic strength. A.Neuron 'b' synapses onto neuron 'c', evoking a PSP. B. When a cholinergic afferent(a) is activated, it releases acetylcholine onto the terminals of neuron 'b', allowingcalcium to enter those terminals through nicotinic acetylcholine receptors (nAChR).Subsequent action potentials in 'b', produce a larger efflux of neurotransmitter,resulting in a larger PSP in 'c'.

dynamically, thereby transforming the effects of any fast synaptic actions.There is sometimes a bias among neuroscientists to assume that fast synapticactions are the 'primary' mode of communication. Slow synaptic effects andother types of modulatory effects are viewed as merely altering the primaryinformation. Yet the primary signal for many types of information, such as


the information that an animal is alert or asleep, may be carried by modes ofcommunication slower than classical neurotransmission.

1.2.3 The many sites of neuronal communication

Neurotransmission occurs at synaptic junctions where there are anatomicallydefined pre- and post-synaptic elements juxtaposed across a narrow synapticgap. Traditionally, neurons are thought to receive synaptic input at theirdendrites and release neurotransmitter from axon terminals. In reality, synap-tic input and output can occur at any location on the cell (Fig. 1.5). Thelocation of synaptic specializations has profound consequences for informa-tion flow in the nervous system. For example, synaptic connections onto theaxon terminals, so-called axo-axonal synapses, play important roles in gatingthe release of neurotransmitter (Chesselet 1984; Nusbaum 1994; Arbuthnott1996; Langer 1997); presynaptic inhibition (Wu and Saggau 1997) or presy-naptic facilitation (Byrne and Kandel 1996) dynamically regulates the efficacyof synapses. This modulatory function is very different from the role ofsynaptic inputs in the dendritic arbor which are integrated by the neuron.The location of the synapse therefore determines the character of its effectand that effect can be modulatory in nature.

1.2.4 Non-synaptic communication

Although synaptic communication is considered to be the standard mode ofcommunication, there are also many ways that neurons can communicatenon-synaptically (Fig. 1.6). For example, neurotransmitter can escape fromsynaptic clefts to affect extrasynaptic receptors (Destexhe and Sejnowski1995; Zoli and Agnati 1996; Barbour and Husser 1997). Furthermore,neurons can broadcast substances into the blood (hormonal or neurohor-monal effects) or into extracellular space such that many neurons will beaffected (Vizi 1984; Iversen and Goodman 1986; Golding 1994). This lattermode of communication has also been referred to as 'volume transmission'because a volume of space is affected rather than a specified postsynaptictarget (Agnati et al. 1995; Zoli and Agnati 1996). These types of non-synaptic actions are of interest because the temporal and spatial dynamics ofthe communication process are very different from point-to-point synaptictransmission (Bach-y-Rita 1994).

Although neuromodulation does not always involve non-synaptic actions,the lack of specificity inherent in such a mode of communication provides thenervous system with another mechanism for flexibility of information flow.For example, volume transmission, mediated by nitric oxide, has been hy-pothesized to play a role in the enhancement of synaptic strength in localizedregions of the hippocampus among synaptic terminals that are not anatomi-cally interconnected (Schuman and Madison 1994).

Paul S. Katz 9

Fig. 1.5 Different locations for synaptic inputs onto neurons mediate different typesof actions. Synapses on distal dendrites (a) are thought to be the primary inputpathway for synaptic integration, but other synaptic sites have important roles inconveying information. Synapses that are made directly on cell bodies (b) have a muchstronger effect than those on distal dendrites for activating a neuron. Inhibitorysynapses near the spike initiation region of a neuron (c) can gate the output of thatneuron to all of its targets by preventing the transmission of spikes along the axon.Presynaptic input to the axon terminals (d, e) can gate transmitter release from thatsite without disrupting the synaptic outputs at other terminals. Presynaptic facilitation(d) can increase transmitter release at selected synapses, whereas presynaptic inhibition(e) can decrease transmitter release. Finally, neurons can release transmitter fromareas other than their axon terminals. There are many examples of dendro-dendriticsynapses (0. These often rely on graded synaptic release rather than spike-mediatedrelease.

1.2.5 Heterosynaptic vs. homosynaptic plasticity

There is a great deal of plasticity that occurs in the nervous system that is nota result of intercellular communication and therefore ought not to be classi-fied as neuromodulatory. For example, many synapses exhibit use-dependentchanges in efficacy such as synaptic depression, synaptic facilitation, aug-


Fig. 1.6 Transmission of informnvion tan occur at defined synopses or non-synaptieal ly through volume transmission. A. Synaptic sites contain a presynapticneuron (a) juxtaposed across a f ixed distance from a postsynaptic neuron (h) . Thepostsynaptie neuron has a concentration of receptors on its surface in the synapticregion. B. Non-synaptic transmission can occur if transmitter released from thepresynapcic neuron (a) escapes the synapric cleft and hinds to receptors on nearbyneurons (c). C. In volume transmission, a neuron releases some substance that affectsall appropriate receptors within the volume of space occupied by the messenger.

Paul S. Katz 11

A. No Plasticity B. Homosynaptic C. HomosynapticFacilitation Depression

Fig. 1.7 Homosynaptic plasticity arises as a result of a neuron's own activity.Different synapses display different types and degrees of plasticity. A. Some synapsesdo not change strength when repeatedly activated. B. Other synapses increase instrength purely as a result of their own repeated activity. C. Still other synapsesdecrease in strength as a result of their own repeated activity.

mentation, and post-tetanic potentiation. These types of changes are termedhomosynaptic plasticity because they are presynaptic changes caused solelyby the activity of the presynaptic neuron itself (Fig. 1.7). In contrast,neuromodulation of synaptic efficacy is a heterosynaptic alteration, where thesubstance released from one synapse changes the effectiveness of anothersynapse (Fig. 1.4).

Clearly, there is somewhat of a grey area between heterosynaptic andhomosynaptic plasticity in that heterosynaptic changes often occur throughthe same intracellular mechanisms as homosynaptic changes. For example,just as homosynaptic facilitation is due to an increase in transmitter releasedue to elevated calcium in the terminal, heterosynaptic facilitation mediatedby neuronal nicotinic receptors is also due to increased calcium in theterminal. Furthermore, homosynaptic plasticity can alter future plasticity atthe same site (see Chapter 5 for more on Metaplasticity). Thus, homosynapticplasticity can display some of the same qualities as heterosynaptic plasticityand, as we shall see, the two forms of plasticity interact.

Autoreceptors provide a particular form of homosynaptic plasticity wherebytransmitter released from a neuron acts on receptors located on the terminalsof that same neuron (Fig. 1.8) (Starke et al. 1989; Powis and Bunn 1995;Langer 1997). Often the function of autoreceptors is to down-regulatetransmitter release. As there is no intercellular communication involved inthis action of autoreceptors, one might not classify this type of action asneuromodulatory. Yet the same receptors can also respond to neurotransmit-


A. Autoreceptor B. Heteroreceptor

Fig. 1.8 The same receptors can participate in homosynaptic and heterosynapticplasticity. A. When transmitter released from a neuron (a) contacts autoregulatoryreceptors on that same neuron, these receptors are called autoreceptors. The sameneurotransmitter is also used to evoke postsynaptic actions on other neurons (b). B.Autoreceptors can be activated by nearby neurons that release the same transmitter(c). In this case the receptors would be termed heteroreceptors.

ter released from other neurons and thus function as so-called 'heterorecep-tors'. In this case, the same receptors would be used for both homosynapticand heterosynaptic plasticity.

There are also cases of synaptic plasticity that involve both homo- orheterosynaptic mechanisms. For example, long-term potentiation (LTP) is aphenomenon in which a synapse increases in strength following a periodwhere activity in the presynaptic neuron is coupled to strong depolarizationof the postsynaptic neuron. In many cases, a retrograde messenger (one thattravels from the 'postsynaptic' neuron to the original presynaptic cell) hasbeen implicated in changing the presynaptic side of the synapse (Schumanand Madison 1994; Medina and Izquierdo 1995). Thus, the synapse strength-ens itself as a result of its own activity, but intercellular communication isrequired.

A further convolution arises in that homosynaptic plasticity can be modi-fied through heterosynaptic mechanisms. For example, biogenic amines suchas dopamine have been shown to alter the extent of homosynaptic facilitationor depression and even LTP (Otmakhova and Lisman 1996; Kusuki et al.1997). Thus, even the plasticity exhibits plasticity (see Chapter 5).

1.2.6 Where does neuromodulation occur?It is well established that there are centers in the brain that are responsible for

PaulS. Katz

Fig. 1.9 Diffuse modulator)' centers such as the raphe nucler have divergentprojections to many areas of the brain and sp ina l cord. Shown here is a schematicrepresentation of serotnncrgic projections from the raphe nucler. The dorsal andmedian raphe nuclei project to the lumbie system, hypothalamus, s t r ia tum, and correx.The raphe magnus and raphe obscurus nuclei project ro the spinal cord. Serotonergicfibres also arise from the ventrolatcral medulla. Modified from Stone et al., (1990),

producing neuromodulatory effects. These centers, such as the raphe nuclei(Fig. 1.9), the substatrtia nigra, and rhc locus coeruletts, are small clusters ofneurons that have very diffuse projections to all areas of the brain. Neuronsin these clusters have similar transmitter phenotypes. For example, many ofthe neurons in the raphe nuclei contain serotonin, whereas substantia nigraneurons contain dopamine and locus coerulcus neurons are noradrenergic.Their divergent projection pattern and their aminergic content suggest thatthese neurons modulate activity in other areas of the brain. Thus, practicallyall nenronal circuits in the mammalian brain are subject to to euro modulationarising from modulatory centers.

Besides the modulatory centers, there are also many other sources ofneuromodulation. It is not an exaggeration to say that every synapse in thebrain has the potential for producing neuromodulatory effects. All knowntransmitters, with the possible exception of glycine, act at metabotropicreceptors either exclusively or in addition to acting at ionotropic receptors.For example, both glutamate and gamma-arninobutyric acid (GABA), thedominant excitatory and inhibitory neurotransmitters, act at both ionotropic


and metabotropic receptors (Nakanishi 1994; Pin and Duvoisin 1995;Bowery 1997). In addition, a large number of neurons co-release one or moreneuropeptides (Cuello 1982; Hoekfelt et al. 1987). The peptides tend to belonger-acting than the small neurotransmitters and therefore may have moremodulatory effects. Many neurons also co-release other neuromodulatorysubstances such as ATP, which is rapidly converted to adenosine and acts atpurinergic receptors (Porkka-Heiskanen et al. 1997). Thus, neuromodulation,by most definitions, may be a ubiquitous attribute of neuronal communica-tion and not just a feature of specialized brain areas.

1.2.7 Beyond neuromodulationAlthough neuromodulatory interactions provide nervous systems with manymore modes of interneuronal communication than simple neurotransmission,there are still other types of communication in the nervous system that do notinvolve the release of a chemical substance from a neuron that acts at areceptor, yet can alter the properties of neurons or synapses. For the mostpart, these forms of communication will not be covered in this book due tolack of space, but deserve consideration by researchers.

For example, a neuron can modulate the activity of other neurons throughchanges in extracellular potassium (Jefferys 1995). When one neuron fires abarrage of action potentials, enough potassium can exit the neuron into theconstricted extracellular space to depolarize neighboring axons. Dependingupon the conditions, this can result in excitation of those neighboringneurons, or inhibition due to inactivation of sodium conductances andpossible failure of propagating spikes.

Neurons can also affect one another indirectly through glial cells(Vernadakis 1996). Glial cells such as astrocytes act as potassium buffers,keeping the extracellular potassium constant by taking up the excess ions(Gommerat and Gola 1996). Glial cells also play an important role in thetermination of synaptic actions by taking up neurotransmitter and therebyremoving it from the synaptic cleft. Recent evidence suggests that thesefunctions of glial cells may be modifiable (Linden 1997; Wilson et al. 1998).Glial cells have receptors to neurotransmitters and thus can respond directlyto signals originating from neurons. In addition, glial cells can transmitsignals to each other in the form of calcium waves (Newman and Zahs1997). These signals may change the buffering properties of the glia andthereby indirectly change the activity of nearby neurons.

Signals arising from non-neuronal sites can also convey information toneurons and change their properties. For example, many neurons respond tosteroid hormones (McEwen et al. 1990; McEwen 1991; McCarthy and Pfaus1996; Spindler 1997). Steroids can alter the architecture of neurons, causingthem to grow more branches or spines. They can also affect neuronal celldeath, thereby regulating the ultimate participation of neurons in circuits.These hormones and other non-steroidal hormones as well as locally releasedtrophic factors can shape neuronal responses over the long term. There is

Paul S. Katz 15

increasing evidence that trophic actions occur not only during development,but throughout the course of an animal's life. Hormones and trophic factorsmay dynamically regulate the structure and responsiveness of neurons, therebygoverning the information flow through neuronal circuits (McEwen andSapolsky 1995; Weeks and Levine 1995; Woolley et al. 1997).

1.3 Why ponder the functions of neuromodulation?

In considering information flow in the nervous system, many of us haveconcentrated on the organization of fast synaptic communication. Artificialneural network modelling demonstrates that such simple networks, obeyingreasonably biological rules, but lacking neuromodulation, are capable ofperforming sophisticated processing (Gluck and Granger 1993). Yet thecomputational ability of these networks still lags far behind that of biologicalnetworks. It might be argued that this is due to the numerical simplicity ofartificial neural networks versus networks of real neurons. However, even ifthey were scaled up to include the same number of neurons and synapses astheir biological counterparts, without the inclusion of the plasticity impartedby neuromodulation, it is hard to see how these artificial networks couldperform all of the functions carried out by real neuronal networks.

Neural circuit diagrams for real and artificial networks are generally drawnshowing monosynaptic fast connections of neurons. By ignoring neuromodu-latory actions, these so-called 'ball and stick' diagrams (as in Fig. 1.1) do notrepresent adequately the richness of communication between neurons. Suchdiagrams can be very misleading because they imply that information flow isvery linear and restricted in time. In reality, neurons communicate with bothneurotransmission and neuromodulation simultaneously, providing a richenvironment where signals vary not only in time, space, and intensity but alsoin character.

What is meant by the variation in the character of a signal is that neuronscan communicate more than just excitation and inhibition, they can alter theproperties of other neurons and synapses. For example, neuromodulatorysubstances can modify the membrane conductances of a neuron to removespike frequency adaptation or turn on bursting pacemaker potentials.Synapses can be modulated in simple ways, such as a strengthening ofsynaptic responses, or in complex ways, such as alteration in the voltage-dependence of synaptic potentials. These types of neuromodulatory effectsare not merely excitatory or inhibitory, rather they are conditional upon theactivity of the cells being affected. For example, the neuromodulatoryenhancement of transmitter release has no effect unless that synapse isactivated. Using the analogy of computer logic gates, neuromodulatorycommunication can act as an 'AND' gate, passing information only if therehas been a synaptic event simultaneous with a modulatory event. But, as willbe seen in the following chapters, neuromodulatory communication is much


richer than simple binary switches; neurons exhibit many non-linear proper-ties that can be altered by neuromodulation. This leads to far more complexprocessing than is currently possible on any silicon-based computer.

To really appreciate the importance of modulatory actions, consider whathappens when neuromodulation is interrupted in diseases such as schizophre-nia and Parkinson's disease. Evidence suggests that both of these conditionshave as their basis a deficit in the modulatory actions of dopamine neurons(Hirsch 1994; Dolan et al. 1995). When these modulatory actions arealtered, there is a tremendous change in conscious perception or the ability toperform motor acts. Thus, these modulatory systems are essential for theproper control of information flow in the brain. Furthermore, consider thatmost major therapeutic and hallucinogenic drugs that affect the nervoussystem act on neuromodulatory pathways, not at sites of classical neurotrans-mission. It is therefore reasonable to assume that a deeper examination of theroles of neuromodulation in the nervous system would be beneficial to ourunderstanding of mental illness and drug addiction.

1.4 What is the nature of information in the nervous system?

In a computer, it is fairly straightforward to identify the information that ispassed between the central processing unit and the memory registers. It isencoded in binary numbers as a series of ones and zeros. From our perspec-tive at the very end of the twentieth century, we are comfortable with theidea that information is coded in a digital fashion in the nervous system aswell. Clearly, neurons are either on or off: they either fire an action potentialor they don't. Neuronal communication is therefore envisioned as the meansof causing neurons to fire action potentials. A simplistic view is that suchcommunication is the job of neurotransmission. However, neuromodulationplays just as direct a role in communicating such information.

1.4.1 Synaptic integration

To appreciate how neuromodulation can communicate information, considerhow neurons decide whether or not to fire an action potential. An oversimpli-fied scenario is that neurons merely tally their fast excitatory and inhibitoryinputs on a moment-by-moment basis and fire an action potential only if theexcitatory inputs surpass the inhibitory inputs by a given amount. Therationale behind this scenario is naive because many, if not most, neuronsexhibit some basal firing rate even in the absence of any synaptic input. Thus,fast synaptic inputs do not determine if a neuron will fire, but rathercontribute to determining how much and when it will fire. Slower actingsubstances with neuromodulatory actions also help shape the firing pattern ofneurons by biasing the membrane potential towards or away from spikethreshold. Furthermore, neuromodulatory inputs can change the pattern of

Paul S. Katz 17

neuronal firing, causing cells to fire bursts of action potentials instead ofconstant firing. Thus, neuromodulation directly communicates informationby changing firing patterns.

Information is coded in both the phasic timing and tonic frequency ofaction potential firing. For example, the phasic firing of motor neuronsinnervating leg muscles determines not only how much a muscle will con-tract, but when it will do so, thereby determining when the leg will move andhow much force it will generate. Yet the tonic firing of motor neuronsinnervating postural muscles is equally important for maintaining an animal'sbalance. The information from both phasic and tonic activity is necessary inorder for an animal to walk. Thus, neuromodulatory inputs that change thebasal firing rate of a neuron are transmitting crucial information even if theydo not contain timing information.

Indeed, when integration of fast synaptic input is important for transmit-ting timing information, as in the visual system, alteration of cellular proper-ties can modify the information carried by those pathways. For example, ithas been proposed that object coherency in visual cortex is dependent uponcoordinated 40 Hz oscillations in the firing responses of neurons whosereceptive fields combine to form an object (Singer 1993). The oscillations arenot produced by simple summation of synaptic input arriving from the retina,but rather they are a product of the intrinsic membrane properties of corticalneurons (Gray and McCormick 1996). Neuromodulatory inputs can causeneurons to display oscillatory properties or can interrupt ongoing oscillations(Harris-Warrick and Marder 1991; Liljenstrm and Hasselmo 1995). Thus,the information about what comprises an object viewed by our eyes isconveyed through the interaction of both modifiable cellular properties andsynaptic transmission.

1.4.2 Biochemical integration

The realization that neuromodulatory inputs to neurons are dynamicallyaltering the properties of those neurons leads to the notion of biochemicalintegration (Fig. 1.10). A fundamental concept in neurobiology is that neu-rons temporally and spatially integrate synaptic inputs through the accumula-tion and removal of ionic charge from the plasma membrane. This electricalintegration contributes to the neuron's 'decision' to fire an action potential.However, signals other than charge are also integrated by neurons.

For example, if a neuron receives modulatory input that increases cAMPand results in the phosphorylation of a synaptic release protein, then thatprotein acts as a site of integration through the accumulation and removal ofphosphate groups. The amount of transmitter released by an action potentialmay be determined by the degree to which the population of release proteinshas been phosphorylated. This will not be reflected in the membrane poten-tial of the cell. Yet the neuron will be integrating these biochemical inputs on


Fig. 1.10 Biochemical integration. In addition to evoking fast synaptic potentials inneuron C, neurons A and B may also have neuromodulatory actions that areexpressed independently of the membrane potential. For example, they may bothincrease the excitability of neuron C. The top graph could then represent the neuronC's excitability over time. This type of process can be called biochemical integrationbecause the neuron is integrating biochemical signals arising from second messengers,not electrical signals.

a moment-to-moment basis to determine the strength of its synaptic output.Thus, the rise and fall of second messengers such as Ca2+ and cAMP can

produce space- and time-variant signals within a neuron just as the rise andfall of voltage does (Fig. 1.11). Each of these different signaling pathways canevoke distinct cellular responses with independent time and length constants.Many sites in a neuron can integrate this biochemical information. Forexample, ion channels can integrate the relative activity of kinases andphosphatases. Molecules that control the transcription of particular genes canalso be sites of integration, increasing and decreasing the expression of genesin response to the levels of second messengers in the neuron.

A very nice example of a biochemical or molecular integrator is found inthe generation of circadian rhythms in Drosophila (Lee et al. 1996; Myers etal. 1996) (Fig. 1.12). There are two genes, per and titn, whose expression isrhythmical, showing a peak at a certain point in the day/night cycle. Part ofthis rhythmic expression is due to negative feedback coupled with a delay:after accumulating in the cytoplasm, the gene products form a dimer and aretransported back into the nucleus of the circadian pacemaker cells where they

Paul S. Katz 19

act to inhibit their own expression. The oscillator has properties which allowit to be reset by environmental changes; the gene product of tim is brokendown by light, allowing daylight to advance or delay the cycle dependingupon when it occurs. Note that none of this complex integration involves anyelectrical signal at all. It is purely biochemical in nature. Yet this biochemicaloscillator alters the functioning of the nervous system, even changing themale Drosophila's mating song (Kyriacou and Hall 1980).

Although we may be aware of biochemical integration, it is more difficultto observe than electrical integration. We can use microelectrodes to recordsynaptic potentials and measure membrane time constants. But how is itpossible to record the time-course of a change in the amount of proteinphosphorylation or the minute-by-minute changes in gene expression? Newimaging techniques may provide tools for viewing changes in biochemicalprocesses in real time, allowing us to directly observe and measure biochemi-cal integration in neurons (Hempel et al. 1996). Flash photolysis of cagedcompounds may then allow controlled stimulation of such biochemicalprocesses in much the same way that we presently inject current throughmicroelectrodes to depolarize a neuron (Wang and Augustine 1995). Perhapsif we could more easily visualize biochemical integration, we would incorpo-rate it more readily into our notions of nervous system function.

1.4.3 Can biochemical integration exist independently of electricalintegration?

It might be argued that biochemical integration merely alters electricalintegration and that information flow is primarily due to action potentialsand transmitter release. However, this view of the nervous system might bebiased by the historical development of recording techniques rather than anobjective assessment of the facts.

Consider, for example, if calcium imaging had been invented before micro-electrode recording. Researchers might then believe that calcium is the keysignal for neuronal communication. The rise and fall of Ca2+ in the cyto-plasm has time and length constants just as general ionic charges do (Fig.1.11). When Ca2+ concentrations rise in a cell, through release of calciumfrom intracellular stores or due to direct influx of calcium through ionotropicreceptors and membrane channels, it triggers the release of neurotransmitter,which can eventually lead to increased Ca2+ in the postsynaptic cell. In-creased calcium concentration is ultimately what causes muscle contractions.In neurons, increases in intracellular Ca2+ can also lead to activation of nitricoxide synthase (NOS) and production of nitric oxide (NO) gas which diffusesto neighboring cells (see Chapter 2). NO then activates guanylate cyclases inthe cytoplasm of other neurons, thereby communicating information to thosecells. Thus it would appear to researchers in this altered history that changesin Ca2+ concentrations were the primary mode of communication. Whenmicroelectrodes are later invented, researchers might think that the mem-


brane potential of a cell is just another means of elevating Ca2 + , not theprimary mode of communication as is now believed.

In fact, there are already examples of signaling that are completely inde-pendent of changes in voltage (Fig. 1.13). For example, many neurons releaseneurotransmitter in a graded fashion as a continuous function of membranepotential (Roberts and Bush 1981; Juusola et al. 1996). Neuromodulatorysubstances can alter the input/output relationships at such synapses, chang-ing the amount of neurotransmitter that is released at rest (Johnson andHarris-Warrick 1990; Johnson et al. 1995). Thus, the presence of a neuro-modulatory substance can change the signal received by a postsynapticneuron with no change in the membrane potential of the presynaptic neuron.

Furthermore, hormones can relay information without a change in themembrane potential of the neurons receiving the information. For example,we are familiar with the fact that steroid hormones such as testosterone andoestrogen can change the behavior of animals. Although the exact mechanismunderlying the behavioral changes may not be understood, it is known thatsteroids exert many of their effects by directly altering genomic expression(McEwen et al. 1990; McEwen 1991; Spindler 1997). This can cause changesin the morphology of neurons and peripheral targets which alter theirbehavioral functions. Thus, information about sexual receptivity and aggres-sion can be communicated through the nervous system independently of

Fig. 1.11 Synaptic voltage, calcium, and second messengers all have time constantsand length constants and produce different cellular effects. A. The time constant (T) ofa neuron is defined by the amount of time needed for a voltage to reach e-1 of itsinitial value. Similarly, the length constant (A) is defined as the distance over whichthe voltages decreases to e-1 of its initial value. In a uniform neurite, other factorssuch as internal calcium concentration ([Ca++]i) and cAMP concentration ([cAMP];)can also display time and length constants. B. Changes in voltage can spread and leadto activation of voltage-dependent channels which may result in the triggering ofaction potentials. C. Calcium dynamics also have their own time and length constantsdue to binding by molecules such as calmodulin or sequestration into intracellularorganelles such as the endoplasmic reticulum (ER). Elevation of intracellular calcium(for example, by influx through ionotropic receptors or through release from internalstores) can have a number of actions including activation of calcium-dependentenzymes such as calcium/calmodulin kinase (CamK) and nitric oxide synthase (NOS),or activation of calcium-dependent channels (ik-Ca). D. Second messengers such ascAMP also exhibit dynamics with time and length constants. Formation of cAMP canoccur through synaptic activation of metabotropic receptors. The G protein-coupledreceptor then activates adenylate cyclase (AC) which produces cAMP. Breakdown iscontrolled by phosphodiesterases (PDE). The cAMP can have many cellular effectsincluding activation of enzymes such as protein kinases (PK) and direct activation ofion channels.

Paul S. Katz 21

Fig. 1.12 Circadian rhythm in Drosopbila is controlled by a molecular oscillatorthat involves at least two genes, tini and per, and can be reset by light. The top graphshows rhc relative abundance of per mRNA over the course of a 24-hr Orcadian day.The effect of a light pulse at the end of eircadian night is to advance rhc oscillation(dotted line), whereas a light pulse during the subjective day delays the oscillation ofper RNA (dashed line). The bar represents A circadian day with the dark portionsrepresenting subjective night. During the subjective night, the gene products of per (P)and tim (T) hind as a dtmer to the UNA and inhibit the transcription of the per andtim genes (a). These proteins are eventually broken down, allowing transcription ofthe DNA to mRNA to occur and translation of the mRNA into protein to occur in thecytoplasm (b). As time progresses, per and tim gene products accumulate in thecytoplasm (c). They then form dimers which are transported back into the nucleus (d).Once in the nucleus, they again bind TO the DNA and inhibit their own production,starting the cycle over again (e). Light can reset the oscillation by directly breakingdown the tint protein. If a pulse of light is shitied towards the end of the subjectivenight, it speeds up the process of eliminating inhibition on transcription and causes aphase advance (f). If the light is shined on the cell during the subjective day, it slowsdown the accumulation of tim protein and thus delays the cycle (g). Dara adaptedfrom Lee et al. (1996).

22 What are we talking about? Modes of neuroma! communication

Paul S. Katz 23

Pig, 1.13 The threshold for graded release of neurotransmitrer can be modulated,turning on transmitter release with no change in presynaptic membrane potential. Fora synapse in the stomarogastric system of spiny lobsters, under control conditions(solid circles), the size of synaptic potentials is a continuous function presynapticmembrane potential with a threshold for measurable release around -60mV. In thepresence of octopamine (open triangles), the threshold for release of neurommsmitteris decreased to about -70 mV and the amplitude of evoked synaptic potentials isgreater than control for more depolarized presynaptic membrane potentials. At apresynaptic membrane potential of -60 mV, under control conditions, noneurotransmitter is released. If octopamine is present, then neurorransmitter can bereleased with no change in presynaptie membrane potential . Data adapted fromJohnson and Harris-Warrick (1990).


electrical integration (Panzica et al. 1996).

1.5 Summary

It therefore seems that there are multiple lines and modes of communicationwithin a neuron and between neurons. Within a neuron, signals such asCa2 + , second messengers, and even gene promotors can each exhibit theirown time and length constants and each evoke different effects (Fig. 1.11).There are many points of interaction between them, such as the voltage-dependence of calcium channels or the calcium-dependence of some potas-sium channels. There are also cases as we have seen where lines of communi-cation can be independent of one another; for example, membrane potentialdoes not have to change in order for a signal to be generated by nitric oxideand transmitter release can be altered with no change in membrane potential.This creates a difficulty for experimental physiologists who see events only interms of counting action potentials. Many important events that communi-cate information are not reflected in the spike train.

Between neurons there are also many modes of communication. Classical,fast neurotransmission is certainly an important form of interneuronal com-munication, but it is not the only kind. Neurons convey information to eachother through many other forms of communication, providing a great deal offlexibility to neuronal systems. The term neuromodulation has been appliedto a large variety of non-classical neuronal actions. Throughout this book, wewill continue to use this term in its broadest sense to mean any intercellularaction caused by the release of substance by a neuron that is either not rapid,not point-to-point, or not simply excitatory or inhibitory.

Almost all substances released by neurons have effects that can be classifiedas neuromodulatory. Therefore, neuromodulation must be playing an impor-tant role in the control of information flow in the brain. Yet most introduc-tory neuroscience texts have only a passing mention of neuromodulation. Ifwe are to unravel the cellular basis for neuronal computation, then moreattention needs to be paid to such non-classical forms of communication.

Acknowledgements

I would like to thank the participants in a session at a recent WinterConference on Brain Research including Irwin Levitan, David Ginty, andChris Hempel for their stimulating discussion about biochemical integration.I thank Sarah Pallas and Don Edwards for their helpful suggestions on themanuscript. Work in my laboratory is supported by a grant from theNational Institutes of Health.

Paul S. Katz 25

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The messenger is not the message; or is it?BARRY A. TRIMMER

2.1 Introduction

The discovery that chemical transmission is the predominant means ofintercellular communication in the nervous system has strongly influenced thedirection of neuroscience research during the last half -century (Katz 1996;Shephard and Erulkar 1997). During this time it has been established thatmany of the complex actions of the central nervous system (CNS) aredetermined by the properties of particular neurotransmitter systems and byinteractions between them. Accordingly, the nervous system is often viewedas a combination of subsystems partially defined by their transmitter con-tents. For example, in the mammalian brain it is useful to refer to theserotonergic raphe nuclei, the dopaminergic substantia nigra, and the adren-ergic locus coeruleus. Similarly, in the invertebrates, the mapping of seroton-ergic (Beltz and Kravitz 1983), octopaminergic (Schneider et al. 1993),dopaminergic, and peptidergic (Siwicki et al. 1987) neurons has helped toorganize the chemical architecture of the CNS.

One of the driving forces shaping this 'neurotransmitter system' approachto the CNS is the belief that different neurotransmitters have their own rolesin neural function (Sakharov 1991). This conceptual framework was ad-vanced by the dogma of 'Dale's Principle' (Eccles 1957) which states that agiven neuron secretes the same transmitter from all its terminals and thateach neuron is either excitatory or inhibitory. Although the basic premisethat the same neurotransmitter is used throughout a neuron has been impor-tant for sorting out pathways and localizing hundreds of neuroactive sub-stances, the usefulness of the other half of Dale's Principle has diminished. Infact, the exceptions to Dale's Principle have important implications forsignaling in the nervous system. Many substances are co-released from singlesites (Lundberg and Hokfelt 1983, see also Chapter 7) or selectively releasedby a neuron as its activity changes (Todorov et al. 1996). The action of eachtransmitter can be either excitatory or inhibitory and may depend on the siteof release from a single neuron (Wang et al. 1995a,b). Indeed, these changescan be dynamic such that excitatory or inhibitory actions of a transmitter canvary with the time of day (Wagner et al. 1997). Although this functionalcomplexity is well recognized it is still easier to identify messengers than todescribe what neurons actually 'understand' about signals sent to them.

30 The messenger is not the message; or is it?

Consequently, there is a huge body of knowledge about transmitter molecules,their synthesis, packaging into vesicles, release, breakdown, and immediateactions on receptors and signaling pathways (collectively called the transmit-ter system), but relatively little is known about the information content or thebehavioral relevance of most of these parameters.

Although transmitters provide a useful way to organize studies of thenervous system, they do not define functional units of information process-ing. In fact, the roles of different transmitter systems in transferring orintegrating information are poorly understood. This problem is particularlyevident when neurotransmission is defined broadly to include events lastinglonger than a few hundred milliseconds and spreading spatially beyond thereceptive site. Indeed, the functional distinctions between traditional 'fast-acting' transmitters, such as glutamate, and slow modulators, such as pep-tides, become blurred when the range of their effects is considered overbehaviorally relevant time-scales of seconds and minutes.

In spite of the fact that little is known about information processing bydifferent transmitter systems, their special chemical and biological propertiesmake it likely that some distinctions exist between them. This chapter willbegin by describing neural coding systems (the 'messages') thought to takepart in information processing in the brain. It will then discuss the possibleroles played by neurotransmitters in transferring or integrating signals atsynapses. Particular emphasis will be placed on the complex interplay thatcan occur between messages and messengers even at the simplest synapsesinvolving a single transmitter and a single receptor subtype. An argument willalso be made that transmitters are relatively poor indicators of signalingfunction. It is more appropriate to regard receptors and their associatedcellular effects as the primary mediators of information processing in theCNS. Finally, the importance of these interactions will be discussed in thecontext of neurotransmission and neuromodulation.

2.2 What is the message? Information encoding andsignal processing

For most studies on central synapses it is impossible to define the behav-iorally relevant information passing from cell to cell. This is partly a technicallimitation in that signals are processed in a parallel and distributive fashionso that all the inputs to a neuron cannot be identified (Tsau et al. 1994). Butit is also due to the fact that we often do not know exactly what informationis being sent. Even at the level of sensory input to the CNS, it is unclear whatinformation is being transferred because many external events are completelyignored and others are overemphasized. The aspects of a stimulus that areimportant to an animal might not correspond to the obvious componentsvisible to a human observer. By measuring behavioral or physiologicalresponses, it is possible to identify absolute sensory capabilities (e.g. theability to detect different wavelengths of light or discriminate between odors),

Barry A. Trimmer 31

but deciding which pieces of the sensory environment are retained and actedupon by the CNS requires a detailed knowledge of an animal's biology. Thisproblem is further complicated because the important information oftenchanges with context, experience, and internal state (see Chapter 6).

Not having an adequate knowledge of the information content beingtransferred makes understanding the coding of that information by thenervous system problematic. Nonetheless, some basic organizing principles ofinformation encoding have been established for sensory and motor systems,and these have been expanded to account for some more complex processingbetween interneurons.

2.2.1 Information conveyed by action potentials

Our best understanding of information processing ('messages') by and be-tween neurons comes from studies on sensory and motor systems. Becausethe sensory and motor apparatuses are generally some distance from theCNS, signals are commonly transmitted as trains of action potentials that canbe analysed for their information content. It is also relatively straightforwardto define the main elements of sensory or motor events. For example, allsensory systems, such as the visual system, carry information about theduration of the stimulus and its intensity. In addition, there is informationabout the quality of stimulus such as the wavelength of light.

In no case does the identity of the neurotransmitter convey informationabout the nature of the signal. All vertebrate motor neurons are cholinergicand sensory neurons are glutamatergic. In arthropods, the situation is re-versed, most sensory neurons are cholinergic and most motor neurons areglutamatergic (Lunt and Olsen 1988; Walker et al. 1996). Knowing that aretinal ganglion cell releases glutamate does not tell you the location of thevisual stimulus, its intensity or duration.

Practically all parameters of visual stimuli can be controlled experimen-tally, so it is possible to identify the coding of sensory events very precisely inthe initial stages of signal processing in the visual system. In some instancesthis coding can be followed through several serial synapses to the visualcortex. Interestingly, such studies have demonstrated that much of the infor-mation about the visual world is discarded or not detected at all. Instead,information about the occurrences of visual events in time and space (forexample the location, size, and movement of an object) is preferentiallyselected by successive layers of processing.

This transformation of sensory signals into trains of action potentials canoccur very early in the processing pathway (often in the receptor itself orafter a signal passes through one or two synapses). Each step of the codingprocess changes the information, so relatively little is known about theinformation carried by interneuronal connections in the CNS. For example,although the synapses between Schaffer collaterals and pyramidal cells of the


hippocampal CA1 region have been studied in considerable detail for almost20 years because they exhibit long-term potentiation (LTP) (Larkman andJack 1995), almost nothing is known about the behavioral informationcarried by the Schaffer axons or their targets (but see Treves 1995). Ameaningful analysis of signal transmission and integration between neuronsshould take into account the normal input and output activity of neurons.

By measuring neuronal responses to defined events in a wide variety ofsystems, a number of encoding mechanisms have been identified (Figs2.1-2.3). Detailed below, these strategies for encoding the information car-ried by action potentials are not all mutually exclusive.

Labeled line, population, and frequency codingPart of the information code is determined by the anatomy of synapticpathways themselves. Neurons communicate signals with one another atdiscrete locations (synapses) and axons project through defined fiber tracts.Thus, the information coming through the optic nerve is defined by thenervous system as 'visual' even if it is elicited by pressing or injuring the eye.When the identity of the axon determines the type of information, it istermed labeled line coding. This type of coding applies not only to sensorysystems but can be applied to motor systems as well; particular neurons'code' for movement of particular muscles simply because those are themuscles with which they synapse.

Although the identity of the axon provides some gross identification aboutthe information that it is conveying, further detail, such as the quality of thestimulus, its temporal dynamics, or its intensity, must be coded in thesequence of action potentials carried by that axon. Because each neuron in alabeled line system conveys only part of a complex stimulus, most events areencoded by multiple neurons, each responding to a slightly different aspect ofthe stimulus. Complete signals are therefore represented by the activity ofgroups of neurons each with a particular receptive field (a subset of effectivestimuli) or tuning curve (Fig. 2.1). This across-fiber or population codingimplies that information is present in the activity relationships of groups ofneurons. It also requires that information from these inputs must eventuallyconverge so that integration can take place. By splitting information intosmall components travelling in multiple channels, population coding is robust(unaffected by small disturbances or the loss of fibers) and versatile (moreinformation can be encoded in the combined activity patterns of severalchannels than can be encoded in the separate channels alone; see Correlationsand oscillations below).

Signal intensity is often communicated by the rate of action potentialproduction by individual neurons. In sensory systems, stronger stimuli gener-ally evoke higher firing frequencies, and for motor neurons, higher firingfrequencies cause stronger muscle contractions. The recognition of this fre-quency (or rate) code has been the mainstay of most models of neural

Barry A. Trimmer 33

Fig. 2.1 Population encoding of signals. In the upper part of the figure the responsecharacteristics (tuning curves) of four hypothetical neurons (A, B, C, and D) withinone sensory modality are illustrated. Each neuron responds to a different range of thestimulus (x-axis) and with different intensities of response (y-axis) but these tuningcurves overlap considerably. Information about particular stimuli (X and Y) isencoded by the response patterns of the four neurons (population encoding). Forexample, in the lower figure X stimulates A strongly, B and C weakly, and D not atall. Y activates D strongly, B weakly, and A and C not at all.

processing (Fig. 2.2). However, it has long been recognized that the genera-tion of action potentials by neurons is linear only over a restricted range ofresponses and that many sensory neurons decrease their firing rate or cease tofire in the presence of a sustained stimulus, a process called adaptation.Rapidly adapting (or phasic) systems act as high-pass filters (similar to an ACcoupled amplifier) and are used to highlight changes in a stimulus (signaldifferentiation). Slowly adapting (or tonic) systems monitor the state andduration of a stimulus (signal integration). The rate of adaptation can vary incomplex ways depending upon which cell responds and upon the intensityand presentation rate of the stimulus and this in turn is communicated withdifferent fidelity by each neurotransmitter system.

Temporal codingAlthough frequency and population encoding are adequate to transmit muchof the information carried by sensory and motor neurons, they do notaccount for the informational content of signals at successive layers in theCNS. It is becoming clear that changes in the firing pattern of neurons conveyinformation that is not present in the overall mean frequency (Miller 1994).


Fig. 2.2 Frequency encoding and adaptation. Traces A-C represent the responses ofthree hypothetical neurons to stimuli of different intensities (top trace). Neuron A is anon-adapting or tonic neuron; its firing frequency is proportional to the stimulusintensity with little or no duration-dependent changes. B is a slowly adapting orphasic-tonic neuron. In general, its spike rate increases with stimulus intensity, butstrong or long duration stimuli result in lower than expected spike rates because ofadaptation; this limits its overall response. C is a strongly adapting or phasic neuron.It responds primarily to changes in stimulus strength but not to a maintainedstimulus. A phasic neuron often has an 'off response after the stimulus ends. Itresponds poorly or not at all to slowly changing stimuli (such as the ramp) andtherefore acts as a high-pass AC filter.

For example, analysis of the responses of neurons in the primary visual andthe inferior temporal cortices show that although some information is presentin the accumulated response, most is contained in brief packets or bursts ofaction potentials (Heller et al. 1995). Within these time-varying responses,visual contrast is coded by signal latency and the stimulus orientation iscoded by firing rate (Richmond et al. 1997). Similarly, neural networkanalysis of auditory responses in the cat cortex suggests that sound location isencoded temporally (Middlebrooks et al. 1994). A simple example of tempo-ral coding is shown in Fig. 2.3, illustrating the way in which different aspectsof a complex stimulus can be carried within a stream of action potentials.This mechanism depends on a minimum time period for encoding and

Barry A. Trimmer 35

Fig. 2.3 A simple model of temporal encoding. Complex stimuli can be encoded bythe temporal relationship of action potentials in a response. In this simplified modeltwo stimuli (A and B) of similar mean intensity have different sinusoidal characteristics.Neuronal activity (lower trace) encodes the mean intensity by firing nine spikes duringeach stimulus. Information about the period of the sinusoid is contained in the latencybetween action potentials within a burst. In response to stimulus A the spikes areevenly distributed (encoding a sinusoid period of 2) but for stimulus B the spikes aregrouped closer together (encoding a sinusoid period of 1). Note that by monitoringthe overall mean spike frequency (the rate-average window, here equal to the durationof the stimulus), the mean stimulus intensity is independent of the sinusoidal parameter.This is true even if the averaging window is reduced in duration (it could convey thesame information during the first three spikes of each response). The temporalencoding window is equivalent to the time between spikes in a burst and requires onlythe first two action potentials to encode the sinusoid period.

decoding which is significantly shorter than that of individual bursts of actionpotentials. By narrowing the duration of this 'encoding window' differentlypatterned bursts of action potentials can convey additional information evenif their mean firing rate is identical. A definition of temporal encoding hasbeen proposed to distinguish it from window-averaged rate encoding(Theunissen and Miller 1995). This proposal uses the concept of singleidentifiable coding symbols to define the encoding window. Informationpassed on by such a window does not necessarily cause a neuronal effectitself but it is used by, and is part of, the overall signal transfer. In thisencoding system, each action potential (or its latency), in a stream of variable(or apparently random) spike rates, carries much more information than anaction potential in a regularly firing stream (Theunissen et al. 1996). Al-though not yet studied in detail, it is quite likely that dynamical analyses ofcomplex action potential streams using the mathematics of non-linear systems('chaos theory') will reveal even more information embedded in apparentlyrandom spike patterns.


Correlations, oscillations, and stochastic resonanceIn addition to labeled-line, population, temporal and frequency encoding,information is carried at a meta-systems level employing all these codes. Thisis most easily revealed by measuring correlations in the activity of groups ofneurons (Johnson and Alloway 1995). It has been proposed that informationcoded in such correlations is less subject to errors and losses inherent in singleneuron coding. In many systems, correlated activity in neuronal populationsis also oscillatory (Wehr and Laurent 1996) and it is well established thatoscillations (or more accurately frequency modulation coding) provide a veryeffective way of stabilizing or consolidating signals (Rapp and Berridge1981). For the olfactory system of insects, a coding system for odors has beenproposed that might also apply to some mammalian models (Laurent 1996).In this scheme, a combination of generalized oscillations, odor-specific pat-terns, and correlated activity between populations of neurons is thought toaccount for odor representation. Interestingly, two of these components,synchronization and patterning, can be separated pharmacologically to ex-plore their roles in sensory processing (MacLeod and Laurent 1996). Re-cently, this spatial coordination of activity in the olfactory system of thehoneybee has been visualized using optical imaging methods to create activity'maps' that are odor specific (Joerges et al. 1997). These maps show the samecombinatorial features thought to underlie odor perception.

One aspect of neural encoding that deserves attention is the ability ofsensory systems to detect very small signals against a background of noise. Ithas been estimated that the lower limit of visual perception in some mammalscan be fulfilled by the reception of a single photon (Hecht et al. 1942).Similarly remarkable detection limits have been noted for auditory systems(Hudspeth 1989). One mechanism thought to account for such sensitivity is aphenomenon called stochastic resonance (Traynelis and Jaramillo 1998).This is a statistical property of dynamic systems in which the addition ofnoise can enhance detection of a periodic signal provided there is a non-linearthreshold. Stochastic resonance has been demonstrated in several sensorysystems including crayfish and rat mechanoreceptors (Douglass et al. 1993),the cricket cereal system (Levin and Miller 1996), and crayfish caudalphotoreceptor interneurons (Pei et al. 1996). Stochastic resonance has alsobeen demonstrated at the level of ion channel gating (Bezrukov and Vodyanoy1995), but because the optimal noise level varies with the signal, it has beenargued that simple stochastic resonance cannot account for the enhancedsignal detection of most biological systems (Adair 1996). However, recently ithas also been shown that arrays of non-linear summing units are not subjectto these limitations (Collins et al. 1995) and other forms of stochasticresonance exist which do not rely on thresholds (Bezrukov and Vodyanoy1997). Therefore, it is possible that stochastic resonance can carry signals in aneural network but the implications of these findings for synaptic signalingand neuromodulation have not been explored.

Barry A. Trimmer 37

2.2.2 Local, analog encoding in the absence of action potentials

Although action potentials are a prominent feature of neural communication,there is ample evidence to suggest that non-spiking transmission of informa-tion is widespread (Roberts and Bush 1981; Juusola et al. 1996). Some of thefirst demonstrations of non-spiking neurons were from work on the controlof leg movements in the locust (Burrows and Siegler 1978), but examples arefound in sensory neurons, the CNS, and the stomatogastric ganglion ofcrustaceans (Graubard 1978; Reichert et al. 1982; Elson et al. 1992), thevertebrate retina (Ayoub and Matthews 1992), and in visual interneurons ofinsects (Uusitalo et al. 1995). Although some crustacean sensory neuronshave large enough length constants to use non-spiking transmission forcommunicating a signal up to a couple of centimeters (Elson et al. 1992),most examples of non-spiking transmission involve very local (within a fewmillimetres) transmission of signals. In such situations, microcircuits involv-ing dendro-dentritic synapses using non-spiking release of neurotransmitterplay an important role in neuronal computation (Shephard 1978). Therelease of transmitter from such cells is graded with membrane potential butwithout an obvious threshold (Fig. 2.4) (Manor et al. 1997). Because of thistight coupling between membrane voltage and transmitter release, the inte-gration of signals by the electrical properties of dendrites can directly influ-ence postsynaptic responses (Laurent 1993). In the crustacean stomatogastricsystem, and in the first-order visual interneurons of insects, neurons haveboth non-spiking neurotransmission and the ability to transmit signals overlong distances using action potentials, allowing them to serve both as localinterneurons and projection neurons (Harris-Warrick and Marder 1991).

Although spike-dependent and graded synaptic transmission are very dif-ferent in their properties (Fig. 2.4) there have been few attempts to comparethe relative rate at which information can be transmitted by these twomechanisms. Measurements of information transfer by graded synaptic trans-mission have been made in the synapses between photoreceptors and largemonopolar cells (LMCs) in the eye of the blowfly Calliphora vicina (deRuyter van Steveninck and Laughlin 1996). Intracellular recordings weremade from the receptors and LMCs of intact blowflies during the repeatedpresentation of complex contrast signals. Using Shannon's equations toestimate the rate of information transfer, these authors estimated that infor-mation could be processed by the LMCs at approximately 1650 bits persecond (bps), approximately five times the highest rates measured in spikingneurons. This study suggests that the transmission of signals between neuronsover very short distances can be achieved more quickly and reliably withoutaction potentials.

Another factor that might influence the evolution of non-spiking communi-cation is the high energy demand of signal transmission. In a recent study themetabolic cost of neural information processing has been estimated at the


Fig. 2.4 Signal transmission by graded potentials and by action potentials. A. Forgraded release, increasing the amplitude of a presynaptic depolarizing pulse (boxsymbols on the left) causes a progressive increase in transmitter release indicated bythe increasing size of the arrows. This increase in transmitter release evokes EPSPresponses that increase in a saturating but direct relationship with presynaptic voltage(shown graphically on the right). Based on data from Manor et al. (1997). B. Foraction potential-dependent release, small voltage changes (below about 45 mV) evokelittle if any release and no postsynaptic response. Above 45 mV the relationshipbetween presynaptic voltage change and transmitter release is very steep such thatsmall changes in amplitude dramatically affect the postsynaptic response (showngraphically on the right). Based on data from Katz and Miledi (1967).

graded (analog) synapses in the blowfly retina (Laughlin et al. 1998).Conductance changes were measured during signaling and used to estimatethe energy required to maintain the membrane potential. The results showthat it costs 104 ATP molecules to transmit one bit of information at achemical synapse from the photoreceptors, and 100 to 1000 times thisamount for graded signals in the large monopolar interneurons. In general,the cost per bit of information increases with the rate of information transfer.This could be an important factor for the large monopolar cells in the retinawhich transmit information at approximately 1600bps, much higher thanthat possible through spiking mechanisms. A calculation of the hypotheticalcost of transmitting information by action potentials in these interneuronspredicts that it is at least as expensive, even at low transmission rates. Duringspiking in small neurons the entire cell is transiently depolarized approxi-

Barry A. Trimmer 39

mately lOOmV, so action potentials do not increase metabolic efficiency insuch neurons. Another conclusion from these studies is that it is metabolicallyfavorable to transmit information at relatively low rates in parallel pathwaysrather than at high rates through single pathways. The results of this work,together with other estimates of the oxygen consumption of nervous systems,suggest that information processing is extremely energy costly and that itcould be a significant factor in the organization of neural pathways, neuralcoding, and synaptic function. In fact, if metabolic energy is limiting fornervous systems, many aspects of brain function will have evolved to reducemetabolic demands.

2.2.3 Basal transmitter release and information transfer

It is important to remember that the pattern of action potential firing andtransmitter release is not determined solely by the inputs that a neuronreceives. In most cases, the intrinsic properties of neurons provide cells with abasal firing pattern that they will display in the absence of synaptic input (seeChapter 3). For example, most cortical inhibitory interneurons display a highlevel of spontaneous tonic firing and many premotor interneurons andsecretory neurons fire bursts of action potentials due to endogenous mem-brane potential oscillations. This basal pattern of activity causes these cells torelease neurotransmitter in a temporal pattern even if they are not receivingany synaptic input. In non-spiking cells, the threshold for graded release ofneurotransmitter is often more negative than the resting potential, resulting intonic neurotransmitter release at rest. This provides the neurons with agreater dynamic range, allowing transmitter release to be decreased as well asincreased in response to synaptic or sensory input. For example, in theabsence of movement, inner ear hair cells release neurotransmitter, causingthe primary afferent neurons to display a basal level of firing. Movement ofthe cilia in one direction will inhibit the hair cell and decrease transmitterrelease, while movement in the other direction will increase transmitterrelease (Pickles and Corey 1992). This will correspondingly decrease orincrease the firing rate of the primary afferent neurons. Thus, the intrinsicproperties of the neurons themselves contribute to the coding of informationin the nervous system by producing a basal level of activity and transmitterrelease upon which inputs can act.

2.3 How do the messengers contribute to the message?

Although the information content transmitted by a neuron is determined inlarge part by the pattern of spiking or non-spiking neurotransmitter release,


Table 2systems

Group

Biogenicamines

Purines

Aminoacids

Cholinergics

Peptides

.1 Biochemical

Transmitters

Serotonin (5HT),dopamine,epinephrine,norepinephrine,octopamine,histamine

Adenosine,adenosinetriphosphate(ATP)

Glutamate, glycine,•y-aminobutyric acidacid (GABA)

(Taurine, aspartate

and /3-alanine)

Acetylcholine(Ach)

e.g. Substance-P,proctolin,NeuropeptideY(NPY),vasopression,FMRFamide,enkephalin

and cellular

Synthesis

From amino acidsby hydroxylation,decarboxylation,and methylation.

From a D-ribose5 -phosphate andpurine ringbiosynthesis toinosinic acid

Dietary source orde novo synthesisfrom glucose

GABA formed by

decarboxylationof glutamic acid

Acetylation ofdietary choline

Translationalprocessing ofmRNA inribosomesfollowed bypeptide cleavageand end-groupmodifications

properties of identified neurotransmitter

Storage/Release Inactivation

Vesicular Uptake by specificATP- and ion-dependent carrierproteins [1]

Vesicular [3] Metabolized byectonucleotidases[4]

Vesicular Uptake by specific[7,8] ATP and ion-

dependent carrierproteins [1]

Vesicular Metabolized byacetylcholin-esterase [12]

Vesicular Cleaved by[15, 16] extracellular

peptidases

Receptors

lonotropicMetabotropic [2]

lonotropicMetabotropic[5,6]

lonotropicMetabotropic[9-11]

lonotropic [13]Metabotropic[14]

lonotropic(FMRFamidegated channels)[17,18]Metabotropic

(For references, see Table 2.2.)

as we will see, the attributes of the transmitter substance or substances thatare released also play a role in determining the nature of the information thatis transmitted. The characteristics of the substances themselves, their syn-thetic pathways, and their modes of degradation cause some messengers to bewell suited for rapid, point-to-point transmission, whereas others will func-tion only for slow, diffuse broadcast communication.

2.3.1 What are the messengers?

The criteria for accepting substances as transmitters (Werman 1966) are verydifficult to fulfil in the CNS and have rarely been met for any particularcentral synapse. However, the weight of evidence from numerous techniquesand in many species has established a list of substances thought to act asneurotransmitters (Table 2.1). This list divides into two major groups, thesmall molecule transmitters (including the biogenic amines, purines, aminoacids, and acetylcholine) and the neuroactive peptides (of which there are

Barry A. Trimmer 41

Table 2.2

Group

Neurotrophins

Arachidonicacidmetabolitesand fatty-acid amides

Ions

Gases

Biochemical and cellular properties of putative neurotransmitter systems

Transmitters

Nerve growthfactor (NGF),brain-derivedgrowth factor(BDGF), NT3,NT4, NT6

Leuckotreines,prostaglandins,thromboxanes,12-HPETE

Oleamide,anandamide,prostanoids

Ca2+ ,H + ,Zn2 4

Nitric oxide

Synthesis

Translationalprocessing ofmRNA inribosomes

Specificphosphodiesterasescleave fattyacids frommembranephospholipids.Subsequentoxygenase andamidationreactions leadto activemetabolites.

Ubiquitouslypresent as freeions or bound tospecific carrierproteins

Produced fromarginine by anelectrontransport reactioninvolving nitricoxide synthase,calmodulin andmultiple [32]

Storage/ Release

Fromdendrites[19]

Released byde novosynthesis frommembranephospholipids[20]

Zn2 + in vesicles[28,29]

Released byde novosynthesis,penetratesand crosseslipidmembranes[33]

Inactivarion

By proteases andpossibly by bindingto low-affinityreceptors

15-Hydroxy-prostaglandindehydrogenase,PG-9-keto-reductase.

Fatty acid amidehydrolase[21]

Sequestration withproteins andcounter ions

Rapid spontaneousconversion toperoxynitrite andnitrite [34]

Receptors

Receptor tyrosinekinases(Trk A, B, C,andp75)[19]

Channelmodulation.Activation of themetabotropicreceptorsDP [22], PI[23],FP[24],IP [25], TP[26], and thecannabinoidreceptors, (CB1andCB2)E27]

Channelmodulation[29-31).Metabotropic(parathyroidextracellularCa2+ receptor)lonotropic(extracellularproton receptor,Na+-channel)

Activation ofheme-containingguanylatecyclase[35].ADP-ribosyitransferase [36].Active-site thio!modification ofproteins andredox chemistryactions [37],

1. Attwell and Mobbs (1994). 2. Tecott and Julius (1993). 3. Silinsky. and Redman (1996). 4. Plesner (1995). 5.Burnstock and Wood (1996). 6. Chen et at., (1995). 7. Maycox, et al. (1990). 8. Fykse. and Fonnum (1996). 9. Pin andBockaert (1995). 10. Cockcroft, et al. (1993). 11. Kuhse et al. (1995). 12. Changeux (1966). 13. McGehee. and Role(1995). 14. Felder (1995). 15. Vilim (19960). 16. Bean et al. (1994). 17. Green et al. (1994). 18. Lingueglia et al.(1995). 19. Thoenen (1995). 20. Cadas, et al. (1996d). 21. Cravatt, et al. (1996). 22. Boie, et al. (1995). 23. Funk, etal. (1993). 24. Abramovitz, et al. (1994). 25. Ogawa, et al. (1995). 26. Halushka, et al. (1995). 27. Abood and Martin(1996). 28. Dyck, et al. (1993). 29. Wu, et al. (1993). 30. Laube, et al. (1995). 31. Ricciardi and Malouf (1995). 32.Wang and Marsden (1995). 33. Subczynski, et al. (1996). 34. Snyder (1992). 35. Shah and Hyde (1995). 36. Schuman,et al. (1994). 37. Brune and Lapetina (1995).

hundreds of varieties). Both these groups of transmitters are released fromvesicles. In addition, other molecules are gaining acceptance as potentialneurotransmitters notwithstanding their unknown or decidedly non-vesicularmechanisms of release (Table 2.2). This diverse group includes several otheramino acids and their derivatives such as taurine, aspartate, and B-alanine,(Fykse and Fonnum 1996; Kamisaki et al. 1996), the neurotrophins (Berningerand Poo 1996), fatty acid derivatives such as the amides, oleamide and


anandamide (Devane et al. 1992), the ions Ca2+ (Brown et al. 1993), Zn2 +

(Ricciardi and Malouf 1995), and H+ (Waldmann et al. 1997), and thesoluble gas, nitric oxide (NO: Snyder 1992). It is likely that this list willcontinue to grow in number and diversity as so-called neuromodulators areaccepted as primary information transmitters. Because these molecules andions differ in their physical and chemical properties, their mode of release,and their reception by postsynaptic cells, each one may act as a uniqueinformation 'filter'.

Each of the transmitters in Tables 2.1 and 2.2 has its own biochemicalproperties and is released, regulated, and inactivated by specific mechanisms.These processes also differ in their kinetics and their distributions. Becausethe current models of information encoding and processing in the CNSdepend on spatial and temporal phenomena, each transmitter could be suitedto slightly different roles. The same considerations also place limits on thecapacity of different transmitters to convey information. The primary stagesof chemical trans-synaptic signaling are:

(1) the synthesis and processing of the transmitter;(2) its release in response to signals;(3) its diffusion and inactivation outside the cell;(4) its actions on the postsynaptic membrane.

These factors are interdependent in their contribution to information transferbut for convenience will be discussed separately.

2.3.2 Transmitter synthesis and storage

At most synapses, transmitter synthesis does not seem to play a major role ininformation transfer, but its regulation is essential for maintaining normalsynaptic function. Generally, sustained signaling is achieved by a close matchbetween the rate of transmitter synthesis and the rate of its release (Birks andMacintosh 1961). For the small molecule transmitters and others synthesizedenzymatically in the terminals, the rate of synthesis is dynamic, adjustingquickly to changing demands (Fig. 2.5A). Synthetic enzymes can be up- ordown-regulated by ions entering the terminal or the turnover rates canchange by mass action as transmitter is lost and substrates are recovered byuptake. For these transmitters a combination of rapid cycling and reservebuffering by vesicle storage means that synthesis is rarely a rate-limiting stepin synaptic transmission, although massive deficiencies in transmitter turnovercan have profound effects on brain function (Parkinson's and Huntington'sdiseases are associated with large decreases in the production of dopamine,GABA, and acetylcholine due to extensive loss of neurons).

In contrast to the rapid local production of small molecule transmitters,activity-dependent changes in peptide and neurotrophin synthesis are mea-sured over several hours or during development of the CNS (Marty et al.

Barry A, Trimmer 43

Fig. 2.5 Differences in the location and processes underlying synthesis of smallmolecule t ransmit ters and peptides, A. Small molecule neurotransmitters aresynthesized in and released from neuronal terminals. In many cases the new transmitteris metabolized in the extracellular space close to the synapse, and the breakdownproducts are taken up by the terminals and recycled as transmitter precursors. Hence,the entire synthesis of new transmitters and the loading of vesicles occur locally anddo not require a short-term transfer of information between the synapse and thenucleus. Over a longer time period the synthesis and transport of enzymes requiredfor transmitter production can be up- and down-regulated to adjust the rate oftransmitter production appropriately. B. In contrast, peptides are synthesized p r i m a r i l yin the soma close to the nucleus. Messenger RNA is transcribed and transported tothe endoplasmii: reticulum where it is translated into pre-peptides by polyribosomes.Subsequent processing of these pre-peptide chains rakes place in the (Golgi apparatus.The f inal peptides arc then packaged as secretory granules and transported down theaxon to the terminals for release. Hence, dynamic regulation of peptide productionand release in synapses requires the transfer of information back from the synapse andthroughout the entire neuron.

1996). Both neuropcptides and neurotrophins are translated directly frommessenger RNAs (mRNAs) which are located primarily in the soma, remotefrom the terminals (Fig, 2.5B). For these transmitters to he produced in adynamically regulated fashion, their release rates must be monitored andcommunicated from the terminals to the site of translation. The synthesizedmolecules must then he transported by fast anterograde transport from the


soma to the release site. Despite this apparent limitation and the lowconcentration of neuropeptides in the brain (Krieger 1983), there is littleevidence that peptide depletion occurs under normal signaling conditions.The only well-documented example of complete peptide depletion is thesecretion of the neuropeptides, eclosion hormone (EH) and eclosion trigger-ing hormone (ETH) in the caterpillar, Manduca sexta. These peptides stimu-late one another's release in a positive feedback cycle that depletes bothsignals to undetectable levels. The massive release of EH in the CNS thenactivates a network of peptidergic neurons that control ecdysis (moulting)(Ewer et al. 1997). Such massive depletion is possible because ecdysis isirreversible and occurs only infrequently in the life cycle of Manduca.

The highly regulated production of peptides by ribosomes and their subse-quent post-translational processing provides a type of signal regulation notseen with other transmitters. Most peptides are first formed as long proteins(in the hypothalamus these are called prohormones) consisting of manypotentially active peptides. A classical example of such processing is thepro-opiomelanocortin precursor molecule which is cleaved into a number ofactive molecules: adrenocorticotrophic hormone (ACTH), B-endorphin, a-and y-melanocyte stimulating hormone (MSH), corticotropin-like intermedi-ate peptide (CLIP) and B- and y-lipotropin (Krieger 1983). A similar varietyof potential transmitters is encoded by peptide genes in invertebrates (O'Sheaand Schaffer 1985). This diversity gives peptidergic neurons the potential toalter their complement of transmitters by translational and post-translationalprocesses. Such phenotypic switching certainly occurs during development(Tublitz and Sylwester 1990) but its use in altering particular types ofbehavior (e.g. Sheller et al. 1983) has not yet been tested.

One way that peptide synthesis could be rapidly altered to affect transmis-sion is by local synthesis. A great many mRNAs are transported out of thesoma and are found close to synaptic terminals, but most are confined todendrites and are not found in the axons (Rao and Steward 1991). Thisimplies that local peptide synthesis might play a role in signal reception or indendritic release of neuropeptides, as has been shown in the supraopticnucleus (Kombian et al. 1997).

2.3.3 Neurotransmitter release parameters

The process of synaptic transmission translates activity in the presynapticneuron into a temporally varying concentration of neurotransmitter releasedfrom discrete sites. The mechanism of release plays an important role indetermining how the message is translated. In many ways, the pattern ofaction potentials is matched to the type of release process and its time-dependent plasticity.

An important point to note is that for presynaptic events, the crucialelements of signal regulation are not the neurotransmitters themselves but

Barry A. Trimmer 45

rather the machinery of their release. Although Ca2 + plays a role in trigger-ing the release of both vesicles and non-vesicular transmitters, these Ca2 +

pools are distinct from one another. Consequently, through the extremelyclose association between particular Ca2 + channels and individual transmit-ter systems, the signals that are released can be coupled to separate parts of astimulus burst entering the synaptic terminal. These subcellular biochemicalprocesses have the capacity to act as terminal-specific presynaptic integrators.

Vesicular release: single transmitter considerationsThe evoked release of small molecule transmitters and peptides occurs fromvesicles docked at the presynaptic terminal. This release is gated by Ca2 +

entry during presynaptic depolarization. The release process itself is ex-tremely rapid and most of the synaptic delay is attributable to the kinetics ofthe voltage-sensitive Ca2+ channels (Llinas 1982). These channels are veryclose to, or coupled with, the docked vesicle complex so that the release ofsmall molecule transmitters is particularly suited to the transmission of fastrepetitive signals. The cascade of molecular interactions leading to vesicularrelease (Siidhof 1995) also provides a major site for rapid signal processing.Such presynaptic alteration can be intrinsic to the release mechanism orcontrolled by extrinsic factors from other neurons and cells.

Well-known intrinsic changes in release include synaptic depression (e.g.Charlton et al. 1982), synaptic facilitation (Magelby 1973) (Fig. 2.6), andpost-tetanic potentiation (FTP: Trimmer and Weeks 1991) (Fig. 2.7). Manymechanisms contribute to these changes, but a pivotal role is played by Ca2 +

entry and its accumulation or sequestration in the terminal (Zucker 1987,1996). All of these phenomena are activity dependent and can have anenormous impact on the passage of signals across a synapse. For example, insynaptic facilitation, the release of transmitter by an action potential can beincreased several fold if it is preceded by another spike. Such facilitation isfirst seen when the spikes are separated by less than about 100ms and itincreases exponentially as the time interval decreases (Trimmer and Weeks1991). By analogy with the neuromuscular junction, facilitation in the CNS isprobably mediated by a transient accumulation of Ca2 + .

The signaling role of facilitation has not been explored in detail but it hasbeen proposed as an essential element in synapse reliability, particularly wheninformation is encoded by bursts of action potentials (Lisman 1997). Thus,intrinsically unreliable (low p) synapses transmit with great fidelity when thedelay between action potentials is less than 25ms. The net effect is for thetransmitter system to act as a 'burst-pass' filter preventing single spikes fromevoking responses. This process works very well for systems using informa-tionally rich bursts of activity and it eliminates the possible destabilizinginfluence of aberrant spikes.

This idea can be extended to explain the role of other intrinsic presynapticfacilitatory processes such as long-term facilitation (Atwood and Wojtowicz1986), augmentation (Zucker 1987) and FTP (Lev-Tov and Rahamimoff


1980). These are all homosynaptic phenomena in which activity increases thesubsequent release of transmitter; they differ primarily in the required stimu-lation conditions and in their decay rates. For example, in the prolegwithdrawal circuit of the insect Manduca, PTP is initiated by stimulation ofan afferent for 20 s at 50 Hz and it consists of a two- to threefold increase inEPSP amplitude that recovers over several minutes (Fig. 2.7) (Trimmer andWeeks 1991). The conditions required to evoke this FTP are well within thenormal activity range of these afferents, so some degree of FTP will always bepresent. In this view, FTP is part of the ongoing signaling role of the synapsewhere it serves to regulate the release of transmitter dynamically. Althoughspeculative, it has been proposed that both synaptic facilitation and FTP actin sensory systems to emphasize changes in activity (bursts of activity afterquiescence or the cessation of high-frequency bursts), essentially amplifyingnovelty in particular inputs (Trimmer and Weeks 1991).

Although it is easy to see how increases in transmitter release might servesignaling functions, less attention has been paid to activity-dependent de-creases in release, collectively termed synaptic depression. In tonically activesystems, decreases in transmitter release can carry as much information asfacilitatory processes. Depression is common at synapses and is known tocontribute to several types of behavior (Byrne 1982; Charlton et al. 1982). Itis often complex, occurring over different stimulation frequencies (from 0.01to 100 Hz or more) (Zucker 1987; Trimmer and Weeks 1991) and with

Fig. 2.6 Synaptic facilitation and depression are intrinsic frequency-dependentalterations in synaptic transmission. A. Paired-pulse facilitation enhances transmissionof transient high-frequency signals. In the caterpillar Manduca the proleg motorneuron PPR receives direct synaptic input from mechanosensory neurons. Eachstimulated action potential in the sensory neurons (marked by the rapid downwardartefact in each trace) evokes a constant latency EPSP in the motor neuron. When thetime delay between action potentials is reasonably long (top trace), the EPSP sizeremains relatively constant. As the time delay is decreased (middle and bottom traces),the second EPSP becomes progressively facilitated. At a time delay of 5 ms, facilitationcan be as much as 300 per cent. Such facilitation is entirely homosynaptic, and cannotbe generated by stimulation of two separate sensory neurons (Trimmer and Weeks1991). B. In addition to the instantaneous paired pulse facilitation, continuousstimulation of a single afferent at different frequencies produces different sized EPSPs.For example, at 5 or 10 Hz the afferent can be stimulated for 2min without asignificant change in the EPSP amplitude. However, stimulation at 20 Hz results in aconsistently larger EPSP. This facilitation is stable over the 2min of stimulation.Increasing the frequency of stimulation to 30 Hz produces a momentary facilitationfollowed by a progressive but small depression of the EPSP amplitude. At 50 Hz notransient facilitation is detectable, instead there is a progressive depression of the EPSPto a stable level approximately 30 per cent that of the control. These resultsdemonstrate the complex results of frequency-dependent depression and facilitation ata single synapse using a single neurotransmitter.

Barry A. Trimmer 47

multiple recovery times. One role for depression has been suggested frommodeling studies of vertebrate cortical synapses. Here short-term depressionprovides a gain-control mechanism to equalize postsynaptic responses andallow the postsynaptic neuron to be sensitive to changes in synaptic inputrather than the absolute amount of input (Abbott et al. 1997).

Vesicular release: multiple transmitter considerationsIt is fast becoming the rule rather than the exception that neurons releasemore than one substance. In some cases, there may be differential release of


Fig. 2.7 High frequency stimulation can cause long-lasting changes in synapticefficacy such as post-tetanic potentiation (PTP). Using the direct monosynapticconnection described in Fig. 2.6, measurements were made of the EPSP amplitude inManduca motor neuron PPR in response to repetitive stimulation of a single sensoryneuron. Action potentials were stimulated at 1.5Hz for 60s to establish the basalEPSP amplitude, 50Hz for 60s, followed by a 3-min stimulation at 1.5Hz (indicatedby the time bar). Each point represents the amplitude of a single EPSP. Following thehigh-frequency stimulation there is a rapid recovery from depression and a prolongedincrease in the EPSP amplitude. At the peak of potentiation the average EPSPamplitude is twice as large as that prior to stimulation. The time taken for thepotentiation to decay halfway back to the control level was estimated to be 68 s. Theinsets show representative EPSPs recorded at the time points indicated by the arrows.(From Trimmer and Weeks 1991.)

cotransmitters, resulting in different translations of the same message. Sometransmitters are colocalized in the same vesicles (Todorov et al. 1996; Vilimet al. 1996 a), some (particularly peptides and small molecule transmitters)are clearly in separate vesicles (Bean et al. 1994; Vilim et al. 1996 a). Recentstudies on the vesicle fusion pore suggest that the contents of a vesicle are notreleased by simple diffusion but might involve a gel-phase transition so it ispossible that even transmitters sharing a vesicle can be released over adifferent time course (Robinson and Fernandez 1994). Such differentialrelease does not seem to occur for ATP and acetylcholine in frog motornerves (Silinsky and Redman 1996), but it is an interesting possibility thatcould affect signal transfer.

In the case of transmitter released from separate vesicles, experiments haveconcentrated on defining the conditions necessary for differential release.Much of this work has focused on peptide cotransmitters where invertebrateneuromuscular junctions have proved particularly tractable. In several ofthese preparations it has been possible to measure the release of peptides

Barry A. Trimmer 49

directly and to identify the most effective release stimuli (e.g. Tublitz andTruman 1985). The general finding is that the optimal stimulus for peptiderelease is a high-frequency or long-duration burst of action potentials. Forexample, the release of small cardioactive peptide (SCP) from the Aplysiamotor neuron B15 is much greater when stimuli are grouped in bursts ratherthan distributed evenly (e.g. ~ 9 Hz for 4 s separated by 3 s intervals ratherthan 5 Hz continuous) (Whim and Lloyd 1994), an effect that seems to becaused by a frequency-dependent increase in the amount of peptide releasedby each spike (Fig. 2.8) (Vilim et al. 1996b). To date, there is little evidencethat specific patterns of stimuli are required for peptide release even forneuron B15 (Vilim et al. 1996b), but this could be because such studiesconcentrate on motor systems that emphasize rate encoding of informationrather than temporal encoding. Interestingly, the release of SCP from otherAplysia motor neurons, Bl and B2, does not depend on bursts and theamount released per spike from these cells remains constant under differentstimulus paradigms (Whim and Lloyd 1994). This result suggests that neuro-transmitter release parameters are a function of the individual cell rather thanof the type of transmitter. Such specificity should not be surprising consider-ing that even separate synapses made by a single neuron can have differentrelease properties (Davis and Murphey 1993; Katz et al. 1993).

Transmitter release is also a major site for modulation by extrinsic factors.Common examples include presynaptic inhibition, heterosynaptic facilitation,long-term potentiation (LTP), and autoinhibition (a reduction in transmitterrelease mediated by the released transmitter itself). In general, these changesare mediated by the activation of receptors on the presynaptic terminalleading to alterations in Ca2+ gating or release dynamics. There do not seemto be any patterns to the types of receptor expressed on terminals; there areexamples of metabotropic (Kilbinger et al. 1993), ionotropic (McGehee andRole 1996), and receptor tyrosine kinases (Levine et al. 1995; Stoop and Poo1996) modulating release. There are also examples of presynaptic modulationby NO via either NO-sensitive guanylyl cyclases (Mothet et al. 1996) orADP-ribosyltransferase (Schuman et al. 1994).

Non-vesicular releaseAmphipathic neurotransmitters such as anandamide and NO can directlycross lipid membranes without complex vesicle docking machinery. For thesemolecules, release is primarily regulated by the synthetic enzymes themselves.Relatively little is known about the control of anandamide productionalthough the formation of its precursor N-arachidonoyl-phospatidyleth-anolamine (Di et al. 1994) appears to be regulated by Ca2+ and cAMP(Cadas et al. 1996a). Anandamide is then formed by the phosphodiesterasecleavage of this precursor which is located in the plasma membrane where itcan be quickly released into the extracellular space (Cadas et al. 1996 b).

Because of its important role in blood flow, stroke-induced neuron death,and LTP, the synthesis of NO has been studied in great detail (Snyder 1992)


Fig. 2.8 Peptides are generally released from neurons during bursts of spike activity.A. The release of small cardioactive peptide (SCP) from Aplysia motor neuron B15maintained in culture. Stimulation of B15 continuously at 5 Hz for 5min releasedapproximately 35 per cent of the peptide initially (before bursts) and this percentagedeclined over time (after bursts). However, stimulation of B15 with the same numberof spikes but grouped in bursts (9 Hz 4 s, 3s interburst) significantly increased releaseof SCP. Values are means plus or minus a standard deviation (n = 4). (From Whimand Lloyd 1994.) B. By varying different stimulation parameters of motor neuron B15(interburst interval, intraburst frequency, and burst duration), it was established thatthe release of peptides is not a function of the stimulation pattern. Recordings weremade from motor neuron B15 in vivo and the amount of peptide released per actionpotential was plotted as a function of the mean stimulation frequency. Over arelatively narrow physiological range, the release of peptide per spike was stronglydependent on the mean spike rate and was independent of the exact pattern of firing.The release amount is plotted relative to a reference pattern (12 Hz, 3.5s on, 3.5s off)indicated by a black diamond. (From Vilim et al. 1996 b.)

Barry A. Trimmer 51

and its complexity raises interesting issues for neuronal signaling. NO isproduced from argininc by nitric oxide synthase (NOS; Fig. 2.9). Threedifferent forms of NOS are known in the vertebrates and are termed neuronal(nNOS or NOS1), inducible (iNOS or NOS2), and epithelial (eNOS orNOS3), although all three are expressed in the brain (ladecola 1997). Theproduction of NO by NOS requires electrons from NADPH that are t rans-ported to a heme group by the cofactnrs FAD and FMN. The active heme siteis only formed when two NOS molecules dimerize (Xie et al. 1996) and thisin turn is regulated by another cofactor, tetrabydrobiopterin (THB) (Cho etal. 1995). The passage of electrons requires calmodulin binding which, forNOS1 and NOS3, is dependent on elevated Ca2+ (Nathan and Xie 1994),but is Ca2 -independent for NOS2 (Ruan et al. 1996). Interestingly, NOS1has alternative promoters and is produced in multiple transcripts by alternatesplicing (Wang and Marsden 1995). The requirement for a large number ofcofactors and the enzymatic differences between NOS isoforms suggest that

Fig. 2.9 Signaling by nitric oxide (NO). NO is produced from L-argininc by theenzyme ni t r ic oxide synthase (NOS) releasing citnilline as a hy-product. In addition tothe cofactor b i n d i n g domains for FMH, FAD, NMDPH, and calmodulin, ncumnalNOS (nNOS) as illustrated here also has a protein binding PDZ domain. The passageor electrons from the NADPH domain to the arginine binding region requirescalmodulin binding which for nNOS is calcium dependent. NO released from the cellbinds to the heme region of soluble guanylyl cyclase (sGC). Heterodimers of sGC arcactivated by NO and the catalytic domain synthesizes cGMP from GTP. cGMP candirectly open or close Nn + , K + , and Ga2+ channels. It can also activate G-kinase tostimulate cGMP-dependent protein phosphorylation.


NO production could be selectively regulated by neuronal activity.It is particularly striking that NOS1 has an extended amino terminal

sequence containing a PDZ motif (Fig. 2.9). (For more information aboutPDZ motifs used in protein-protein interactions, see Chapter 3.) Recently, ithas become clear how this protein binding domain might account for the veryclose coupling between Ca2+ entry through NMD A receptors and NOSactivation in the hippocampus. Using a yeast two-hybrid screening system,two proteins (PSD 93 and PSD 95) have been identified that can bind to thePDZ domain of NOS (Brenman et al. 1996). These proteins have multiplebinding domains and can also bind to the NMDA receptor. It is postulatedthat they serve to anchor NOS1 to the NMDA receptor so that very localchanges in Ca2+ can quickly influence NO production. This structuralconstraint is clearly important in the control of NO production because otherpools of Ca2+ have very little effect on NOS1. Another form of NOSregulation is suggested by the recent identification of an endogenous protein(PIN-1) that binds to and inhibits the catalytic domain of NOS1 (Jaffrey andSnyder 1996), but it is not known if this is used in controlling the productionof NO dynamically.

Despite the importance of NO in retrograde signaling during LTP induc-tion there has been no systematic study of the stimulation conditions neces-sary for its release. Presumably, trains of action potentials which activate theNMDA receptor (causing elevated glutamate release during postsynapticdepolarization) have the capacity to stimulate NOS1, but the subcellularregulation of NO production by stimuli of known informational content hasnot been explored.

2.3.4 Diffusion, inactivation, and receptor occupancy

One aspect of chemical transmission that is extremely important in signalingis the time course of transmitter in the synaptic cleft. Because the rate oftransmitter loss from the cleft affects both its concentration and the distanceover which diffusional signals can pass, the sequestering (or breakdown) of atransmitter is an important variable. Furthermore, the rate of transmitterclearance, coupled with the rate, affinity (Kd), and stoichiometry of bindingat the postsynaptic receptor will dictate the level of receptor occupancy (Fig.2.10). For many receptors these factors will also affect desensitization pro-cesses. It is thought that the peak concentration of the small moleculetransmitters can be as high as l-5mM and that clearance is biphasic withtime constants of 100 us and 2ms (Clements 1996). Through a combinationof experimental and modeling approaches it has been demonstrated that, inthe absence of re-uptake, a single pulse of transmitter can diffuse to adjacentterminals and rise to a concentration of 10 um at sites 2-3 um away within5ms (Clements 1996) (Fig. 2.11). For some postsynaptic responses the decayof the current is much slower than the clearance of transmitter. In these casesthe lifetime of the transmitter in the synaptic cleft does not control recoveryfrom stimulation but is more important for actions some distance away from

Barry A. Trimmer 53

Fig. 2.10 The speed and duration of neurotransmitter release has markedconsequences on the kinetics of the postsynaptic response. A A numeric kinetic modelwas used to simulate responses of a channel population to agonist activation. Onlythe open state allows current to pass. The arrows show permitted transitions and therelative rate constants of these changes. The transition rate from unbound to bound isthe product of the rate constant and agonist concentration [A]. The dotted lines in B,C, D, and E illustrate differing rates of agonist application, from very slow, through aprogressive ramp, to a step change. The solid lines in each of the figures represent theensemble channel responses expressed as open probability. The intrinsic channelkinetics are best represented during fast agonist rise times. In E, a very brief pulse ofagonist was applied and the decay was much faster than during a long pulse such asD. This difference reveals the contribution of agonist unbinding in shaping currentdecay. (From Jones and Westbrook 1996.)

Fig. 2.11 Transmitter diffusion. In the absence of inactivation or re-uptakemechanisms, small molecule neurotransmitters can diffuse quickly and attainphysiologically important levels several micrometers from the release site. Thedistribution of transmitter is illustrated following an instantaneous point release of2000 molecules. In this model the synaptic cleft is 1.5nm wide, extends to infinity inall directions, and does not include diffusion barriers or transmitter uptake. Thediffusion constant approximates to the free diffusion of glutamate (D = 7.6x106cm2 s-1). A. Using a Monte-Carlo simulation, snapshots of the distribution aretaken at 10, 20, and 50 us intervals. The transmitter distribution is approximatelyuniform throughout a typical synaptic cleft within 50 us of release. B. At longer timeintervals the concentration of transmitter can be 10 or 20 uM up to 2 um from thepoint of release. Uptake mechanisms and complex synaptic anatomy are likely toshape this diffusion profile significantly, particularly at long distances from the releasesite. (From Clements 1996.)

the terminal. The spread of such a message will be even more extensiveduring sustained release.


Barry A. Trimmer 55

Fig. 2.12 Transmitter spillover. At high release rates neurotransmitters can 'spillover'from a synapse and influence additional sites. In this example, glutamate accumulationaffects metabotropic receptors on presynaptic terminals to affect its own release.Glutamatergic responses of hippocampal CA3 pyramidal neurons of guinea pigs weremeasured during mossy fiber stimulation. NMDA receptor currents during high- andlow-frequency stimulation were compared in the presence of high-affinity (CPP;D-carboxypiparazinyl-propylphosphonic acid) and low-affinity (APA; amino pimelicacid) NMDA receptor antagonists. A. CPP was equally effective at blocking responsesto high- and low-frequency stimuli but APA was far less effective during high-frequencystimuli. This is consistent with the displacement of APA from glutamate receptorsduring high-frequency stimulation through an accumulation of glutamate. B. Onepotential role of this increased synaptic glutamate is to act on presynaptic metabotropicglutamate receptors (mGluRs). When stimulated by exogenously applied agoniststhese MGluRs cause a decrease in evoked release. Application of the mGluR antagonista-methyK4-carboxyphenyl)glycine (MCPG) was only effective in potentiating evokedresponses under conditions expected to increase glutamate in the synapse, such ashigh-frequency stimulation (1 Hz, shown here) or during glutamate uptake inhibition.(From Scanziani et al. 1997.)

The importance of diffusion in synaptic signaling has been elegantlydemonstrated at hippocampal mossy fiber synapses (Scanziani et al. 1997).First it was demonstrated that glutamate actually does accumulate in thesynapse during moderately high-frequency stimulation (1 Hz) (Fig. 2.12A).Then it was shown that the excess glutamate may spill over out of thesynapse to affect metabotropic glutamate receptors (MGluRs) located in


non-synaptic areas of the presynaptic terminal (Fig. 2.12B). These autorecep-tors cause a decrease in the evoked release, so the spillover may act as aself-regulatory mechanism to limit release during periods of strong activity.

Although these results were obtained with a small fast-acting molecule, it isquite likely that similar considerations apply to other types of transmitters.Hence, there is support for the rather intuitive concept that single or briefbursts of action potentials affect very local postsynaptic sites and high-frequency or long-duration bursts of action potentials have the capacity toinfluence targets in a much greater volume (Barbour and Hausser 1997). Ifthis has importance for neural signaling we can expect to find transmitterswhose release, inactivation, and reception are optimized for 'volume' signal-ing. Peptides certainly fit this description because they are released byhigh-frequency or long-duration bursts, are slowly inactivated, and are de-tected by receptors with very high affinities (see Table 2.1).

The rate of clearance of transmitter from the synaptic cleft also dictates thelocal concentration and this in turn affects which receptors can respond (seenext section) and the level of receptor occupancy. The effect of receptoroccupancy on synaptic signaling has been reviewed in some detail (Frerkingand Wilson 1996). There is evidence that in some systems the release of asingle vesicle is sufficient to saturate the receptors. In such systems, variationin the number of released vesicles or even in the amount of transmitterreleased will not be detected by the postsynaptic receptors and may have noadditional informational content (Clements 1996). This has implications inthe debate over the underlying cause and importance of quantal release in theCNS. If transmitter released from a single vesicle saturates the postsynapticsites, it is difficult to see how changes in quantal size can be detectedregardless of whether a quantum of transmitter is related to the number ofvesicles released or the number active sites.

One major limitation of most models of transmitter-receptor interactions isthat they rely upon data obtained under steady state or equilibrium condi-tions (e.g. Fig. 2.10). Synapses are unlikely to operate close to the steady stateand many of the assumptions used for estimating binding parameters (e.g. noligand depletion) will be invalid during synaptic transmission. Recently, newmodels of binding have begun to be developed based solely on the laws ofmass action and conservation of mass (Qazi et al. 1998). These explicitsolutions describe ligand binding dynamically for any initial ligand andreceptor concentrations at any time. It remains to be determined how wellthey can be applied to experiments testing the transfer of signals across realsynapses.

Given these limitations it is very difficult to make general statements on thesaturation of central receptors. However, it is interesting to speculate that thetransmission of information across a synapse, even for similar amounts ofreleased transmitter, could be 'gated' by altering the degree of receptorsaturation. This regulation might be achieved by dynamic changes in theaffinity of a receptor for its ligand. In fact, dramatic changes in ligand

Barry A. Trimmer 57

binding can be made by allosteric interactions (e.g. nicotinic receptors havetwo cooperative ACh binding sites; Changeux et al. 1984). It is alsopossible that multimeric receptors are regulated by changes in their subunitcompositions.

The inactivation of a neurotransmitter has consequences beyond its simpleremoval from the receptor. For example, it has been found that solublenucleotidases are released from stimulated sympathetic nerves in a Ca -dependent fashion together with the transmitters, ATP and norepinephrine(Todorov et al. 1997). This suggest that ATP will be quickly broken down toadenosine, progressively changing the relative amounts of all three transmit-ters in the cleft. Although it is has not been demonstrated directly, it ispossible that both ATP receptors (P2) and adenosine receptors (PI) arepresent on single cells. Such a combination could produce very complexresults, particularly given the diversity of purinoceptors (see next section:Burnstock and Wood 1996).

Similar considerations come into play for neuropeptides which arecleaved by peptidases in the extracellular space. Most peptides are post-translationally modified to resist certain types of enzymatic cleavage. Thismodification often involves carboxy terminal amidation through the cleavageof a glycine residue (e.g. FMRFamide and vasopressin), N-terminal acetyla-tion (e.g. a-MSH), or the addition of an N-terminal pyroglutamate (e.g.LHRH). Because the carboxy terminal is generally the most critical site forpeptide-receptor interactions, the length of the amino-terminal chain canaffect the persistence of a signal as the peptide is progressively cleaved byamino-exopeptidases. In contrast, endopeptidases directed at specific internalbonds can cleave peptides into segments and some of these can have pharma-cological actions or their own (e.g. Schober et al. 1996), although whetherthis is a physiologically important process is unknown.

From the standpoint of diffusion, NO is once again an interesting transmit-ter because it is a very soluble and highly diffusible gas. The half-life of NOin the extracellular space is estimated to be almost 10s (Snyder 1992) and itreacts with dissolved oxygen to spontaneously form nitrite and other nitrogenoxides. From estimates of NO diffusion rates in lipid and aqueous layers, amolecule of NO could conceivably diffuse 6-9 m during its lifetime(Subczynski et al. 1996). On a more biological scale this means that NO candiffuse about 200 um in 0.2 ms. Such widespread transmitter deployment isideal for rapidly communicating with multiple locations and for coordinatingdisparate but functionally coupled synaptic events. This process could havevery important repercussions during LTP in the hippocampus where NOproduced by NOS3 has been proposed as a retrograde message generated bypostsynaptic dendrites to increase transmitter release (Larkman and Jack1995). New findings using hippocampal cells in culture suggest that reducedtransmitter release during long-term depression is propagated backwardsthrough a neuron and its neural connections rather than in the anterogradedirection (Fitzsimonds et al. 1997). Although NO has not been implicated in


this process, it could play a critical role in reconfiguring functional circuits aspredicted by back-propagation models of memory consolidation.

NO also forms complexes with thiols, sugars, metals, and heme proteinsand can be transported long distances in the body. In vertebrates, NO issignificantly stabilized as an S-nitroso adduct of serum albumen. Uponglycosylation of such serum proteins, this protective effect is diminished,substantially reducing the half-life of NO circulating in the blood (Farkas andMenzel 1995; Hogg et al. 1996). It is possible that NO's access to sensitiveneurons is controlled by similar processes in the CNS itself, thereby restrict-ing or delivering NO in a more selective fashion. Much of NO's specificity isalso derived from a restricted subset of cellular targets and possibly throughthe dynamic regulation of responsive heme-containing enzymes.

2.4 The reception of the message

One of the major determinants of a transmitter's action is the receptormediating the target's response. This idea is so simple and self-evident that itis easy to forget that in the early days of chemical transmission research noone knew about receptors, so the possibility of receptor diversity was not aformal concept. Because it was assumed that a transmitter would define theresponse to a stimulus, fierce debate ensued about the different actionsattributed to acetylcholine and epinephrine (Eccles 1990). As it became clearthat a single transmitter could exert very different responses with differentlatencies and durations, the notion of receptors came into being. Except forNO signaling, all presently known neurotransmitter receptors belong to oneof four structurally distinct families: ionotropic receptors, metabotropic re-ceptors, receptor tyrosine kinases, and receptor guanylyl cyclases.

2.4.1 Ionotropic receptors

Most fast signaling in the nervous system utilizes ionotropic receptors, alsoknown as ligand-gated ion channels (Fig. 2.13: Barnard 1996). For these ionchannels, which are structurally related members of a large gene family, thebinding of agonist opens the ion channel. Since the receptor for the neuro-transmitter is part of the same molecule as the ion channel, the gatingmechanism is fast. No metabolic steps are required for opening the channel;however, there are many ways in which the process can be modulated (seeChapter 3).

Certain neurotransmitters are known primarily for their actions onionotropic receptors: glutamate, the major 'excitatory' neurotransmitter ofthe brain acts via AMPA and NMDA receptors (named after their bestexogenous agonists); GABA, the major 'inhibitory' neurotransmitter acts atGABAA receptors, and acetylcholine causes muscle contraction via nicotinicacetylcholine receptors. However, a number of substances commonly recog-

Barry A. Trimmer 59

Fig. 2.13 Ionotropic receptors. Ligand gated channels are mult imcric proteinsgenerally assembled from four or five subunits. A, The topography and combinationof subunits varies with receptor type. In one superfamily (receptors for ACh, GABA,glycine, and 5HT) the subunits are thought to cross the membrane four times with theamino and carboxy terminals outside the cell. The non-NMDA receptors for glutamareappear to have a hydrophobic region that does not penetrate the membrane so theyare predicted to have a uytoplasmic carboxy terminal. B. Several subunits combine toform A transmitter-gated channel. For the vertebrate muscle nicotinic AChR shownhere, f ive subunits (two a, B, y, 8) are arranged with radial symmetry about theion-selective pore which is lined p r imar i ly by the second transmembrane regions ofeach subunit.


nized as neuromodulatory also act at ionotropic receptors (Table 2.1). Forexample, the biogenic amine, serotonin, acts at the ionotropic 5HT3 receptor(Jackson and Yakel 1995) and dopamine can directly gate a channel in snailneurons (Green et al. 1996). Even neuropeptides can directly gate ionchannels (Green et al. 1994; Lingueglia et al. 1995). The purine messenger,ATP, also activates ionotropic receptors (Brake et al. 1994; Valera et al.1994; Burnstock and Wood 1996). Thus, the class of messenger does notnecessarily determine whether the receptor is ionotropic.

The gating of some ionotropic receptors can be modified by a number ofparameters, most notably voltage. The NMDA receptor is the most impor-tant example of a voltage-dependent ionotropic receptor (Daw et al. 1993;Mori and Mishina 1995). In order for the NMDA receptor/ channel to open,the membrane potential must be depolarized while the agonist is bound. Thedepolarization is required to remove a blocking Mg2+ ion from the mouth ofthe channel. Because of this requirement for both agonist binding andcoincident membrane depolarization, the NMDA receptor has been impli-cated in Hebbian mechanisms, such as long-term potentiation (LTP) (Asztelyand Gustafsson 1996). Gating of NMDA receptors is also influenced by thebinding of other substances, in particular glycine, which can alter the bindingof the primary agonist (Kemp and Leeson 1993). The interaction of factorsthat influence the gating of ionotropic receptors such as the NMDA receptormeans that ionotropic receptors do not merely convey information about thepresence of a neurotransmitter to the postsynaptic neuron. Rather, thesereceptors integrate other signals as well and therefore modify the informationbeing transmitted.

All ionotropic receptors are composed of multiple subunits and many shareconsiderable amino acid sequence similarity (Fig. 2.13A). Because ionotropicreceptors are assembled from several different subunits, an enormous varietyof receptor subtypes can be expressed, each with different properties. One ofthe best-described examples of this diversity comes from studies of vertebratenAChRs which are pentameric channels (Fig. 2.13B) assembled from combi-nations of nine a and four B subunits (also called non-a). Of these differentgene products, at least six a (a-2-a-9) and three B (B-2-B-4) subunits areexpressed in the CNS (Sargent 1993) and more than 1323 stoichiometricallyconstrained combinations are possible (Role 1992). The kinetic and conduc-tance properties of these nicotinic channels and their sensitivity to agonistssuch as nicotine are influenced by both a- and B-subunits (Wheeler et al.1993). For example, although they respond similarly to ACh, receptorscomposed of a-3/B-2 subunits are 17-fold less sensitive to nicotine, whilea-2/B-2 receptors are five times more sensitive to nicotine (Luetje and Patrick1991). In addition, the a-7, a-8 (found in chick brain), and a-9 (found in rat)subunits are capable of forming functional homomeric nAChRs (McGeheeand Role 1995). Because a-subunits contain the consensus sequence for AChbinding, these homomeric receptors might be expected to have unusual

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activation and desensitization kinetics, but this possibility has not yet beenexplored (Role 1992).

This enormous diversity of receptor subtypes for a single transmitter raisesquestions about the function of ligand-gated channels. Why are so manysubtypes needed if they all serve to transmit fast, faithful signals? Thisquestion is particularly intriguing in the mammalian CNS where, despite theenormous diversity of nAChRs, no definitive cholinergic synapses have beenfound (Sivilotti and Colquhoun 1995). It is further complicated becausemany individual neurons express genes coding for several receptor subunits.For example, neurons of the chick ciliary ganglion express a-3, a-5, a-7, B-2,and B-4 nAChR subunits (Corriveau and Berg 1993) and hippocampalCA1/CA2 neurons express glutamatergic AMPA receptors that are com-posed of homomeric Glul subunits or Glu2 subunits combined with Glul orGlu3 (Wenthold et al. 1996). Although they respond to a single transmitter,this diversity of subunits within single neurons implies that each receptorsubtype has a separate function in signaling.

Some clues to the functional roles of different subtypes have emerged in thedetails of receptor-ligand interactions and in the gating and permeabilityproperties of particular channels. The importance for neuronal signaling ofone of these channel properties, desensitization, has been nicely illustrated ina recent review (Jones and Westbrook 1996). Some channels such as thenAChRs of muscle are slow to desensitize (time constant > 20 ms) and quickto recover. At these receptors, short pulses of ACh are more likely to unbindthan to desensitize, allowing the receptor to follow pulsatile release veryfaithfully. Others, such as the glutamatergic AMPA receptors, desensitizequickly, even during a normal miniature excitatory postsynaptic current(mEPSC), and their slow recovery from desensitization is a rate-limiting stepto the unbound state. These properties limit the duration of postsynapticcurrents and attenuate the transmission of high-frequency signals. An evenmore intriguing aspect of desensitization comes from an analysis of GABAA

receptors that enter and recover from desensitization quickly (Fig. 2.14).Paradoxically, such receptors can have prolonged postsynaptic responsesbecause they 'flicker' between open and long desensitized states beforeunbinding. These transient openings increase the duration of channel activityafter a brief pulse of GABA (Jones and Westbrook 1996).

lonotropic receptor subtypes also differ in their permeability to differentions. For example, unlike their close structural relatives in muscle, the a-7homomeric nAChRs are highly permeable to Ca2+ (for a review seeMcGehee and Role 1995). This Ca2+ could play an important role in cellularphysiology because it can enter a cell during cholinergic stimulation even ifthe cell is prevented from depolarizing (Rathouz et al. 1996). Similarvoltage-independent Ca2+ entry has been proposed to occur through ATPreceptors (Edwards 1994).

Another important point to emerge from studies of subtype diversity is that

Fig. 2.14 Desensitization of receptors may play an important role in the dynamics ofsynaptic transmission. Fast desensitization can produce a paradoxical prolongation ofthe decay of GABA-induced currents. A. A brief pulse of GABA (3ms) to anoutside-out patch from a cultured rat hippocampal neuron elicits current that decayswith a double exponential time constant (six responses superimposed on the left). Asecond pulse given while the first current is decaying elicits a smaller response,suggesting that channels visit the desensitized states during the decay of the current. B.After a brief pulse of GABA, channel activity can persist for hundreds of millisecondsand involves frequent long closures followed by reopening (second trace). Thisprolonged response can be generated by microscopic desensitization in which thechannel flickers open from the desensitized state as modeled in the lower traces C. Inthis model the states are represented as open (O), closed (C), desensitized (D), bound(B) and unbound (U). This model has been used to generate the ensemble currentsshown in D where there is very good agreement between the patch clamp current andthe simulated open probability. The fast current decay arises in part from an increasedoccupancy of desensitized states. Reopening from this desensitized state is responsiblefor the expression of the slow decay phase. (From Jones and Westbrook 1996.)

ionotropic receptors are not always mediators of fast postsynaptic potentials.Recent work suggests that most nAChRs, and many other ionotropic recep-tors (reviewed in McGehee and Role 1996), in the CNS are presynaptic andserve to modulate transmitter release. Hence, nicotinic stimulation at theexcitatory synapse between medial habenula and interpenduncular neurons


Barry A. Trimmer 63

enhances glutamatergic neurotransmission (McGehee et al. 1995). Similarenhancement is seen at the cholinergic synapse between neurons of thevisceral motor nucleus of Terni and those of the lumbar sympathetic gan-glion. This increase in ACh release appears to be a Ca2+-dependent processmediated by non-homomeric complexes of the a-7 subunit (McGehee et al.1995). These results support much earlier findings of presynaptic nicotinicreceptors on the terminals of insect neurons (Blagburn and Sattelle 1987'a,b).

The diversity of responses mediated by ionotropic receptors is furthercomplicated by the startling new discovery that chloride-permeable GABAA

receptors can be excitatory or inhibitory on a daily cycle (Fig. 2.15; Wagneret al. 1997). In these experiments, GABA was applied to neurons of thesuprachiasmatic nucleus (SCN) at different times of the day. During thenight, GABA reversibly inhibited firing through an increase in chloridepermeability, an effect that is also a well-characterized action of GABAA

receptors in other neurons. However, during the day, GABA increased thefiring rate of SCN neurons, an effect that was blocked by the GABAA

antagonists, bicculline and picrotoxin. This role reversal is mediated bycyclical changes in the intracellular concentration of chloride, [Cl~],. Duringthe day, high [Cl~]i pushes the chloride equilibrium potential positive to themembrane potential so that GABA depolarizes neurons. At night, [Cl~]j isreduced and the chloride equilibrium potential falls below the membranepotential so that GABA hyperpolarizes the neurons. This is certainly a novelfinding and it illustrates very well how responses are not necessarily definedby a transmitter or even by a particular receptor.

2.4.2 Metabotropic receptors

The metabotropic receptors, or G'-protein-coupled receptors, are extremelyimportant in mediating diverse responses to transmitters. Many of the neuro-modulatory actions described in this book are mediated by metabotropicreceptors through their activation of second messenger systems. The details ofparticular intracellular pathways are covered in the next chapter.

Almost all conventional transmitter substances act on metabotropic recep-tors, either exclusively or in addition to ionotropic receptors (Table 2.1). Forexample, glutamate acts at the metabotropic glutamate receptors (mGluRs) inaddition to AMPA and NMD A receptors (Nakanishi 1994), GABA acts atthe metabotropic GABAB receptor in addition to the ionotropic GABAA

receptor (Bowery 1997), and acetylcholine activates muscarinic as well asnicotinic receptors (Walker et al. 1996). The large and growing number ofneuroactive peptides all activate metabotropic receptors as do the biogenicamines and the purine transmitter, adenosine. There are only a small numberof substances, including glycine, that have not (yet) been shown to activatemetabotropic receptors.


Fiji. 2.15 The effect of activating a receptor depends ult imately on [he shite of thecell. The actions of GABA on neurons of the rat superior suprachiasmatic nucleuschange with a daily cycle. During the day (left column) most neurons are excited byGABA (a) and at night (right co lumn) they are inhibited (h). These actions are dosedependent (c and d) and hoth responses are blocked by biccuculine and picrotoxin(not shown) suggesting they are mediated by the same GABA receptor. Responses areplotted as the mean spike frequency calculated over A 30s period. These changes arenot absolute for a population of cells, hut the distr ibution of responses changessignif icant ly between day and night as shown in (c). (From Wagner el al. 1997.)

Metahotropic receptors are heptahchcal, consisting of a single polypeptidechains with seven distinctive hydrophobic domains presumed to span themembrane (Fig. 2.16). Members of this superfami ly are highly conservedwithin these domains, but they can be divided into families by comparingtheir overall amino acid or gene sequences (Fryxell 1995). This basic proteinstructure is apparently very 'successful' and adaptable as a molecular detectorand transducer. In addition to being used as the receptor for all the classical

Barry A. Trimmer 65

neurotransmitters and peptides, it is also found in receptors for cicosanoinds,prostanoids, and other lipid metabolites, cyclic AMP, and Or"1" (see Tables2.1 and 2.2 for references). The structure is also used as a phototransducer;rhodopsin is in the same molecular family as metabotropic receptors (Fryxelland Meverowitz 1991). Structural relatives are also proposed to account forthe detection of an enormous number of chemical odorants (Buck 1992). Allof these receptors are thought to generate intracellular signals through theirinteractions with membrane-bound G-proteins (Fig. 2.16).

For each transmitter, there are several metabotropic receptor subtypesproduced by different genes or by alternate splicing of mRNA. Each subtypecouples preferentially to particular intracellular pathways, but this is not a

hig. 2.16 Metabotropic receptors. The metaborropic or G protein-linked receptorsshare a common predicted membrane topography consisting of seven hytlrophobicdomains. The amino terminal of the peptide is thought to be outside the membraneand the car boxy terminal wi th in the cytoplasm. The receptor binding domain isformed from pockets wi th in the grouped transmembrane regions. The intracellular (3loop is very important for mediating interactions with G-proteins. Activated (c-proteinsbind GTP, displacing bound GDP, and the Go( subunit separates from the GBycombination. Both C-protein fragments can go on to mediate cell signaling by directlyacting ion channels or by stimulating and inhibiting various cell effectors such asadenylate cvclase (Redrawn from Wickman and Glapham 1995.)


fixed property and some receptors couple promiscuously to several secondmessenger systems. For example, human muscarinic ACh receptors(mAChRs) are produced by five genes (Bonner et al. 1988). Types m2 andm4 generally couple to pertussis toxin-sensitive G-proteins and inhibit adeny-late cyclase activity. In contrast, types m1, m3, and m5 generally couple topertussis toxin-insensitive G-proteins to stimulate inositol phosphatemetabolism (Richards 1991). When expressed in different cell types, ml, m3,and m4 subtypes can also activate phospholipases (A2, C, and D), tyrosinekinases, and Ca2+ channels, m2 and m4 subtypes can activate phospholipaseA2 (Felder 1995), and m5 subtypes can activate NOS (Wang et al. 1994).These various pathways can excite or inhibit neurons by coupling to ionchannels (Jones 1993), or they can have longer-term effects on proteinphosphorylation, transmitter synthesis, and release or cell growth and trans-formation (Felder 1995). A similar complexity of metabotropic receptors isseen for serotonin receptors (Tecott and Julius 1993), dopamine receptors(Grandy and Civelli 1992), GABA receptors (Kaupmann et al. 1997), and inparticular for glutamate receptors of which eight genes have been cloned andseveral splice variants may exist (Pin and Bockaert 1995).

As described for the ionotropic receptors, multiple subtypes of a particularmetabotropic receptor can be expressed by single neurons (Gold et al. 1997;McKinnon et al. 1997). Presumably, the response specificity of these recep-tors arises through differential coupling to G-proteins and second messengerpathways (e.g. Raffa and Stone 1996). The potential of diverse metabotropicreceptors to influence the biochemistry and physiology of neurons is obvi-ously immense and it brings into focus the need for detailed studies ofbiochemical integration in functionally defined neural systems.

2.4.3 Receptor tyrosine kinases

Many growth factors, such as insulin or the neurotrophins, exert theirlong-term effects via membrane-spanning proteins with extracellular ligandbinding domains and intracellular tyrosine kinase activity, known as receptortyrosine kinases (Fig. 2.17). Four types of these receptors were originallyidentified as proto-oncogenes (trkA, trkB, trkC, and p75). All the neu-rotrophins bind to the p75 receptor with low affinity, but each neurotrophinbinds with high affinity and activates different members of the family; nervegrowth factor (NGF) activates the TrkA receptor protein, brain-derivedneurotrophic factor (BDNF) and the neurotrophin NT4/5 activate TrkB, andthe neurotrophin NT3 activates TrkC. NT3 also interacts with TrkA andTrkB but at higher concentrations. Non-signaling truncated forms of TrkBand TrkC are also produced. Activation of these receptors by neurotrophinsleads to receptor dimerization and autophosphorylation. These phos-phorylated tyrosine residues mediate binding by src-homology 2 (SH2)-domain-containing proteins which in turn are activated to stimulate second

Barry A, Trimmer 67

Fig. 2,17 Receptor tyrosine kinases (neurotrophin receptors). A. Ncurutrophmreceptors (NTRs) arc membrane spanning proteins with a ligand binding domain onthe extracellular side, a hydrophobia trailsmembrane domain, and a signalingintracellular domain. The p75 NTR has four cysteine-rich regions extending outsiderhe membrane and it hinds all neurotrophins wi th low a f f i n i t y . Activation of th isreceptor stimulates ceramidc production which is thought to mediate trophic influenceson neurons. The protein intermediates that couple this receptor to the sphmgomyclincycle have not been determined. B. The receptor tyrosinc kinase family includes thespecific neurotrophin receptors TrkA, TrkK and TrkC. In addition to their distinctiveextracellular structure, these proteins have kinase homology domains extending intothe cytoplasm. When activated by a ligand, these receptors dimenze, activate intrinsic-protein kinase catalytic activity, and autophosphorylate one another. The transmissionof signals into the cytoplasm is generally mediated by peptides containing SRChomology domain, (Adapted from Dechant and Barde 1997.)

messengers and other effector enzymes {Berninger and Poo 1996; Heumann1994) (for more information see Chapter 3).

Most of these mechanisms have been established in relation to slow trophiceffects; however, many neurotrophins exert relatively fast signaling eventsthat could certainly he involved in information processing (reviewed inBerninger and Poo 1996). For example, NCiF acts to change growth cone


motility within 1 min of application, substantially before it affects geneexpression or protein synthesis. An exciting but unexplained finding is thatwithin seconds of its application to hippocampal neurons, BDNF increasesNMDA-mediated Ca2+ influx (Jarvis et al. 1995). It has also been shownthat BDNF application increases transmitter release from hippocampal neu-rons within minutes (Levine et al. 1995) and both BDNF and NT4/5 canincrease the effectiveness of hippocampal synapses through fast postsynapticmechanisms (Levine et al. 1995). Although it is possible that these effects aremediated by undiscovered receptors, the pharmacological profile of theresponses (e.g. Levine et al. 1996), assays of phosphorylation activity inspecific pathways (Marsh and Palfrey 1996), and the effectiveness of tyrosinekinase inhibitors in preventing most changes (Blochl and Sirrenberg 1996),strongly argue a key role for receptor tyrosine kinases. Recently, the possiblerole of tyrosine phosphorylation in synaptic transmission was also tested atthe squid giant synapse (Llinas et al. 1997) but its physiological significanceis unknown.

2.4.4 Receptor guanylyl cyclasesMany cells respond to signals by elevating cGMP levels through the activa-tion of guanylyl cyclases (GCs). The cytoplasmic GCs appear to be activatedby NO (see below), but a different class of transmembrane GCs that bindextracellular ligands and directly respond by synthesizing cGMP has beenidentified. These receptor guanylyl cyclases (rGCs) were first discovered insea urchin sperm, but at least six isoforms have now been cloned in verte-brates (Fig. 2.18; Garbers and Lowe 1994). The natural ligand for these rGCsare the natriuritic peptides and the heat stable enterotoxins/guanylins. Threeof the isoforms are found in sensory neurons (retina and olfactory epithe-lium). Similar rGCs have also been cloned in insects (McNeil et al. 1995;Nighorn et al. 1995; Nighorn et al. 1998) but their roles in cell signalinghave not been identified.

2.4.5 Receivers for NONO readily crosses cell membranes (Subczynski et al. 1996) and can act bothas an intercellular and an intracellujkar messenger. Because it is so diffusible, itis possible that an NO emitter communicates with all possible NO receivers.In this case, the targets determine specificity and the NO producer has nocontrol over the destination of its signal. However, it is likely that chemicalbarriers limit NO diffusion. For example, many neurons contain high concen-trations of /3- and y-linked dipeptides such as carnosine (/3-alanyl histidine),homocarnosine (y-aminobutyrylhistidine), and glutathione (y-glutamylcys-teinylglycine) which are capable of sequestering NO and other free radicals(Philbert et al. 1995; Hogg et al. 1996). Although such barriers could be veryimportant, the emerging picture is that NO specificity, like that of otherneurotransmitters, is largely defined by a multitude of NO-responsive path-ways. The main targets identified so far are heme-containing soluble guanylyl

Barry A. Trimmer 69

Fig. 2.18 Receptor guany ly l cyclases. The receptor guanylyl cyclases consist ofproteins with an extracellular ligand binding domain, a hydrophobia transineinhraneregion, and cytoplasmic regions that bind nucleotides and mediate the cyclic CMPcatalytic activity. The active form of these receptors is thought to be a dinner whichforms through interactions in the putative amphipathic a-helieal region between thetwo intracdiular domains. (Based on Garhers and Lowe 1994.)

cydases (sGCs) and ADT-ribosyltransferase.The sGCs art; heterodimcrs containing a- and /3-subunits each of which

contains a consensus catalytic domain (Fig. 2.9). In expression studies, botha- and 0-forms must be expressed to obtain functional GC activity. Three a-and two /3-forms have been cloned in vertebrates (Yuen ct at. 1994),suggesting that GCs are heterogeneous and subject to cel lular regulation. Infact, different combinations of these subunits differ more than sixfold in the i ractivity in response to NO. In addition to control by subunit composition,some of the cloned forms have potential regulatory or membrane bindingdomains (Shah and Hyde 1995). Because of their ho mo logy to dynamicallyregulated rGCs (Garhers and Lowe 1994), it is possible that sGCs are alsomodulated by multiple signaling pathways.


Various non-cGMP mechanisms are also proposed to mediate the actionsof NO including actions on redox chemistry (ladecola 1997), active-site thiolmodification of proteins (Brune and Lapetina 1995), and changes in ADP-ribosyltransferase activity (Schuman et al. 1994). The signaling role of twosuch pathways has recently been explored in the CNS of the mollusk,Aplysia. NO produces opposite effects on ACh release from identifiedsynapses depending on their functional role. Excitatory synapses from thepleural-abdominal connective onto cell R15 are enhanced by NO, whereasinhibitory connections between cells B4/B5 and B3/B6 are suppressed(Mothet et al. 1996). All of the excitatory enhancement is attributed to aGC-dependent mechanism because it is blocked with methylene blue, but thedepressing effect is only partially prevented with this GC inhibitor. However,the effect of NO on the inhibitory synapse is blocked by the ADP-ribosyltransferase inhibitor, nicotinamide, suggesting that protein ribosyla-tion plays a role in the actions of NO at this synapse (Mothet et al. 1996).These results illustrate once again that signaling by a transmitter, even one asmobile and transient as NO, is strongly dependent on the location andbiochemistry of the receiver.

In addition to its well-characterized actions on transmitter release, NO iscapable of eliciting postsynaptic responses that are remarkably similar tothose generated by more traditional transmitters. For example, in two differ-ent molluskan systems (Aplysia and Lymnaea) stimulation of NOS-containing neurons leads to the production of EPSPs with delays as short as200ms (e.g. Jacklet 1995; O'Shea and Park 1996). These EPSPs are blockedby NOS inhibitors and NO-buffers, or mimicked with puffs of dissolvedexogenous NO (O'Shea and Park 1996; Park et al. 1998). Although slowerthan many ionotropic responses, the delay and duration of these NO-media-ted EPSPs are comparable to those mediated by metabotropic receptors. Thisis very interesting from a signaling point of view because NO release is notconfined to synaptic structures. It highlights the need for establishing func-tional rather than anatomical connections, because NO can signal rapidlybetween neurons that are completely separate from one another.

2.5 An overview

From the examples presented here it is clear that the messenger is not themessage; neurotransmitters do not define the signals being sent from oneneuron to another. Even so, identifying a neurotransmitter in a signalingprocess is still very important for understanding communication betweenneurons. This is because nervous systems transmit information along definedpathways and individual neurons express only a subset of the availabletransmitters. Hence channels of information are partly identified by theirneurotransmitter content. From an experimental point of view it helps toknow which transmitters are employed at a synapse so that specific pharma-

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cological tools can be used to dissect the signaling events. Identifying trans-mitters is also useful in defining some of the broader properties and limita-tions that can be expected in a system. In general, small molecule transmittersare appropriate for fast and rapidly changing signals, peptides and neu-rotrophins for slower and more distant transmission, and NO or otheramphiphilic molecules are potentially fast and long-distance broadcast mes-sengers.

To understand the role of a given transmitter in a system, it is crucial topay attention to the appropriate encoding and decoding of information. Ifcritical information is contained in very brief bursts of activity, only fast-responding neurotransmitter systems will pass on the message. But even here,attention must be paid to slower systems coexisting with the fast transmitters;these might detect patterns of activity over longer periods and distribute thisinformation to numerous units. Such signaling can no longer be regarded as'modulatory' because it is an integral part of the transfer of informationbetween neurons; it merely happens on a longer time-scale and involves moretargets.

Even if the transmitter and its receptor are identified in a system, it mustnot be assumed that the signaling role is known. Because of complex releaseprocesses, diffusion, inactivation, and dynamic ligand-receptor interactions, asingle neurotransmitter can convey signals at various time-scales and throughmultiple pathways. Key roles in these signaling events are played by thereceptors themselves because they interpret signals in ways that are appropri-ate for particular neurons. This is obvious in systems where a transmitter canexcite or inhibit neurons by acting on separate receptors. It is even moredramatic when a single receptor varies its function on a daily basis (Wagneret al. 1997).

Receptors are diverse, even when they are structurally related and respondto the same transmitter. It is interesting to speculate that this diversity arisesbecause receptors are the primary site of selective adaptation of a transmittersystem. This possibility has been discussed with reference to the ionotropic(Ortells and Lunt 1995) and metabotropic receptors (Fryxell and Meyerowitz1991; Fryxell 1995). It is easy to imagine that many variations of a singlereceptor are produced through mutations and other biological events. Someof these will be functional but slightly different from their relatives, mimick-ing phenotypic variety within a species. Each variety of receptor is thensubject to selection, those serving to improve information processing in aparticular task are more likely to persist and those doing a poor job will beselected against. In this way, receptors come to be associated with particularfunctions and in particular locations according to their unique properties.This process could operate at an evolutionary level through the reproductivesuccess of individuals, or at a developmental level within an individual as thenervous system shapes itself by experience. An alternative (although some-what tautological) argument in support of this notion is that, for selection tohave maintained such variety, receptors rather than the transmitters must


play an important role in the signal processing functions of neurotrans-mission.

Our concepts of neurotransmission and neuromodulation have been shapedby a tendency to study signal transmission over restricted time-frames and atspecific locations. This reductionist approach is natural and necessary whenfaced with the immense complexity of nervous systems. However, to makemore progress in understanding how the brain functions, these mechanisticapproaches must be based on a sound knowledge of the information beingprocessed. It is particularly important to identify signals that are relevant foradaptive behavior, even if that 'behavior' is the output of a small circuitembedded in a bigger network. This type of analysis should include the fullrange of time-scales appropriate for the function of the network. By acknowl-edging that traditional fast-acting neurotransmitters can also mediate slowerevents, and by including neuromodulators in our analysis of informationprocessing, we are more likely to identify some of the basic mechanismsunderlying behavior. One way to make this expanded approach manageableis to concentrate on the things that really do happen between neurons in arealistic context, rather than attempting to define all the actions of a neuro-transmitter. The result should be a focus on the messages processed bynervous systems rather than the messengers produced by them.

Acknowledgements

I would like to thank all the members of my laboratory for their commentson earlier drafts of this chapter; in particular, Dr Sanjive Qazi who has beeninstrumental in directing my attention to the importance of transmitter-receptor interactions in neural signaling. His depth of knowledge and criticalinsights into ligand binding have proved invaluable. Research in my labora-tory is funded by NIH/NINDS grant NS30566 and NSF grant IBN9723507.

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The inside story: subcellular mechanisms ofneuromodulationELIZABETH A. JONAS AND LEONARD K. KACZMAREK

3.1 Introduction

The mechanisms of neuromodulation lie within individual neurons.Understanding these mechanisms helps us to understand how informationcontained in neuromodulatory signals is translated into a cellular action.Neuromodulatory signaling is often accomplished through chemical activa-tion of a cell surface receptor that turns on a biochemical pathway within thetarget cell and produces a second messenger. The second messenger isgenerally a small, soluble molecule that activates an intracellular effector suchas a protein kinase. The kinase then phosphorylates any one of a number ofsubstrates within the neuron to cause the modulatory effect. This chapter willreview some of the common biochemical pathways used in neuromodulationand discuss exciting evidence that modulation of neuronal properties takesplace on a molecular scaffold that links ion channels to the enzymes thatregulate them, and to the cytoskeleton of the cell (Pawson and Scott 1997).

Many of the biochemical pathways and intracellular signaling mechanismsthat are used by neurons are common to most cell types, although higherconcentrations of many of the proteins involved in such signaling are foundin the brain than elsewhere in the body. Neurons, however, differ from othercell types in a number of features, including their morphology, their ability tosustain patterns of electrical activity and conduct it along axonal and den-dritic processes, and their ability to transmit signals synaptically (see Levitanand Kaczmarek 1997). Due to these unique features of neurons, the effects ofsubcellular biochemical signaling pathways are quite distinct from those inother cell types and eventually lead to short-term and long-term changes inelectrical excitability or synaptic efficacy.

The processes within a neuron that are subject to modulation includechanges in amplitude or kinetics of the ion channels, the insertion or removalof ion channel proteins from the membrane, changes in the types of ionchannels expressed or their localization within the neuron, and changes inrelease of neurotransmitter from the synaptic terminal. One relatively re-cently recognized feature of signaling pathways in neurons is that minute-to-minute variations in ion channel properties can be brought about by chang-ing the physical association of the ion channel with its modulating elements.

84 Subcellular mechanisms of neuromodulation

Finally, activation of biochemical pathways that signal to the nucleus canproduce long-term modulation of neuronal excitability by increasing ordecreasing the synthesis of proteins required for ion channel expression andfunction. These mechanisms provide the means whereby one neuron can alterthe properties of another neuron and are thus crucial for plasticity observedin the nervous system.

3.2 Receptors and second messengers

A neuron receives information from other neurons chiefly through receptorsfor neurotransmitters and other factors at the plasma membrane (Moore1993; Shepherd and Erulkar 1997). There are three main types of receptorsinvolved in neuron-to-neuron signaling (Fig. 3.1) (Barnard 1996). The first isthe class of neurotransmitter-gated ion channels (ionotropic receptors) (Fig.3.1 A). The signal relayed by these receptors is an alteration of postsynapticmembrane potential or a rapid change in the concentration of ions, such ascalcium ions, in the cytoplasm. It is ionotropic receptors that are most oftenassociated with rapid neurotransmission, but as we will see, calcium influxthrough these ion channels can also cause neuromodulatory actions.

The second type of receptor, the metabotropic receptor, is responsible for alarge majority of what is generally recognized as neuromodulatory signaling.These receptors are also known as G-protein coupled receptors because theyactivate intracellular effectors through a guanosine nucleotide-binding protein(G-protein) (Fig. 3.IB). The intracellular effector molecule is typically anenzyme that produces a second messenger that can diffuse into the cytoplasmor along the plasma membrane (Worley et al. 1987). These second messen-gers trigger biochemical cascades by activating protein kinases or by mobiliz-ing intracellular calcium. Protein kinases catalyze the transfer of a charged

Fig. 3.1 Different receptor systems. A. Ionotropic receptor or ligand-gated ionchannel. Binding of a ligand directly opens the ion channel. B. Metabotropic orG-protein-coupled receptor. Ligand binding activates a G-protein, comprised of threesubunits (a, B, y), causing GDP (not shown) to be replaced by GTP. This leads to adissociation of the a subunit from the fiy subunits. The a subunit then activates aneffector enzyme, in this case phospholipase C (PLC). The effector enzyme produces adiffusible second messenger: in this example, PLC converts phosphatidylinositol (PI)into inositol trisphosphate (IP3) and diacylglycerol (DAG). The second messengersthen activate secondary effector enzymes; in this case, DAG activates protein kinase C(PKC). The PKC then phosphorylates substrates such as ion channels, thereby changingthe activity of the neuron. C. Receptor tyrosine kinase activates intracellular signalingmolecules leading to phosphorylation of an ion channel on serine or threonineresidues. (Adapted from Kandel et al. 1991 and Alberts et al. 1994).

E. A. Jonas and L. K. Kaczmarek 85

phosphate group from ATP to specific ammo acid residues of proteins, anevent that is termed pbospborylation. The addition of a phosphate group


alters the charge on proteins such as ion channels and can also bring about aconformational change, thereby altering the electrical behavior of a channel(Levitan 1994; Jonas and Kaczmarek 1996; Smart 1997).

The third class is a receptor that is itself a protein kinase (Boxall andLancaster 1998) (Fig. 3.1C). Such receptor tyrosine kinases, when activated,directly cause the close physical association of a number of key signalingmolecules, each of which can trigger a cascade of cellular events that bothregulate ion channels acutely and signal the nucleus of the neuron to alter itsprogram of gene expression.

3.2.1 Pathways mediated by metabotropic receptors

The most widely studied family of receptors in the field of neuromodulationis that of the G-protein coupled receptors (Gudermann et al. 1997). Mosttransmitter substances activate metabotropic receptors either exclusively, asin the case of most neuropeptides, or in addition to activating ionotropicreceptors. For example, acetylcholine activates both nicotinic (ionotropic)and muscarinic (metabotropic) receptors. Thus, this signal transductionmechanism is extremely prevalent in the nervous system.

The binding of neurotransmitters to a G-protein coupled receptor starts asignaling pathway (Neer 1995) (Fig. 3.IB). In the resting state, the G-proteinis bound to GDP. When a neurotransmitter binds to a metabotropic receptor,that receptor interacts with the G-protein, causing GTP to displace GDP. Thisactivates the G-protein and causes its three subunits (a, B, y) to separate.The B and y subunits stay bound to each other and remain associated withthe cell membrane. The a subunit holds on to the GTP and binds to aneffector enzyme whose catalytic domain resides at the inner surface of theplasma membrane. Such enzymes include adenylate cyclase, phospholipaseC, and phospholipase A2. These enzymes catalyze the production of intracel-lular second messengers which either can influence ion channels directly orcan activate protein kinases that, in turn, modify ion channel activity. The asubunit retains GTPase activity and thus catalyzes the conversion of the GTPthat is bound to it back to GDP, thus ending its own activation and allowingthe a subunit to reunite with the )8 and y subunits.

The second messenger systems activated by metabotropic pathways pro-vide a means of signal amplification and dispersal. For each intracellularsystem, a small diffusible molecule is synthesized in response to activation ofa metabotropic receptor. Multiple second messenger molecules are synthe-sized for each activation of a metabotropic receptor, resulting in an amplifi-cation of the signal. The diffusion of these molecules away from the receptorprovides a means of dispersing the signal within the cell. For example,activation of the effector enzyme, phospholipase A2, hydrolyses themembrane phospholipid, phosphoinositol (PI), releasing arachidonic acid.Arachidonic acid can then be converted into a number of differentmetabolic products each of which has different physiological actions.

E, A. Jonas and L. K. Kaczmarek 87

3.2.2 cAMP and protein kinase AThe three effector enzymes mentioned above activate separate second messen-ger systems. For example, the receptors for many neurotransmitters such asnorepinephrine or neuropeptides activate the G-protein, Gs, which triggers anincrease in the activity of adenylate cyclase (Neer 1995). This enzymecatalyzes the formation of cAMP from ATP. cAMP can produce a number ofintracellular actions, most notably the activation of protein kinase A (PKA).PKA was the first protein kinase shown to have an effect on neuronalexcitability (Castellucci et al, 1980; Kaczmarek et al. 1980). This enzyme is atetramer consisting of two regulatory and two catalytic subunits. cAMP bindsto the two regulatory subunits, thereby freeing the two catalytic subunits (seeFig. 3.7). These in turn catalyze the transfer of a phosphate from ATP tohydroxyl groups of serine and threonine residues in the target protein. Thetarget protein contains a specific sequence of amino acids (a consensussequence) that permits phosphorylation of the protein by PKA. Once they arereleased from the regulatory subunits, the catalytic subunits of PKA candiffuse from their site of activation to a target ion channel. As we shall seelater, in cases where long-term regulation of an ion channel takes place, PKAcan even activate transcription of channel genes by translocating to thenucleus where it phosphorylates the cAMP response element-binding protein(CREB). This protein, in turn, binds to DNA, enhancing transcription ofparticular genes (Frank and Greenberg 1994; Gan et al. 1996).

3.2.3 Protein kinase CIn contrast to cAMP, which is a soluble cytoplasmic messenger, some secondmessengers are confined to the plasma membrane, permitting very localmodulation of ion channels and other membrane proteins. One such signal-ing pathway is linked to activation of the membrane-bound enzyme phospho-lipase C by metabotropic receptors that are coupled to the G-protein knownas Gq. Phospholipase C cleaves the membrane lipid phosphatidylinositolbisphosphate (PIP2) to generate two important signaling molecules: inositoltrisphosphate (IP3) and diacylglycerol (DAG) (Fig. 3.IB). DAG activates theserine/threonine protein kinase known as protein kinase C (PKC). Fullactivation of PKC requires the membrane phospholipid phosphatidylserine,as well as DAG and calcium. Although PKC is a soluble enzyme, uponactivation it becomes very tightly associated with the membrane, where thesenecessary factors reside (Mosior and Epand 1997). There exist several differ-ent isozymes of PKC, which may be present in different locations within thecell, and serve various functions at different membrane-associated sites. It isalso important to point out that some forms of PKC do not require calciumfor activation (Sossin et . 1996).

3.2.4 Calcium as a second messengerCalcium can act as a second messenger and produce long-term consequences


for a cell (Ghosh and Greenberg 1995). There are three main mechanismsthat lead to elevation of intracellular calcium. The first is through voltage-dependent calcium channels, allowing the cell's own electrical activity toelevate internal calcium. The second means by which calcium can enter thecell is through ionotropic receptors such as NMDA receptors, some AMPAreceptors (Burnashev 1996; Gu et al. 1996), purinergic ATP receptors, andneuronal nicotinic acetylcholine receptors (Rogers et al. 1997). In this way,ionotropic receptors can cause neuromodulatory effects. The third mecha-nism for elevating cytoplasmic calcium is through release from intracellularstores by IP3 which is produced by metabotropic receptor activation ofphospholipase C (Berridge 1993).

Calcium concentration is normally extremely low (<0.1 uM) in the cy-tosol and high in the extracellular space or within the lumen of the endoplas-mic reticulum. The large gradient for calcium across these membranes causesa rush of calcium into the cytosol when calcium conducting channels open inthese membranes. Energy-dependent pumps at the plasma membrane and theendoplasmic reticulum restore the cytoplasmic calcium concentration to lowlevels after such an influx. In this way, cytosolic calcium levels can becontrolled exquisitely by the cell so that this ion is a useful signal bothglobally in the cell and locally within different parts of the cell (Alberts et al.1994).

Calcium plays a number of different signaling roles within the cell. Cal-cium in the cytoplasm can regulate the further release of calcium from theendoplasmic reticulum and other intracellular calcium-containing organelles.Calcium binding to the ryanodine receptor can directly release calcium frominternal stores (Striggow and Ehrlich 1996). In addition, calcium is needed asa cofactor for, and regulates the function of, the IP3 receptor calcium-releasechannel. That is, the ability of the IP3-gated channel to release calcium intothe cytosol from intracellular organelles is dependent on the concentration ofintracellular calcium as well as on the concentration of IP3. At relatively lowintracellular concentrations of IP3, during the initial phases of calciumrelease, levels of cytoplasmic calcium are still fairly low. In this situation,calcium binds to the IP3 receptor and enhances the open probability of thechannel. However, after more prolonged calcium release, when cytoplasmiccalcium levels rise to concentrations greater than about 200 nM, the bindingof calcium to the channel has less of an effect on the opening of the channel.As a result, relatively less calcium is released when calcium levels are alreadyhigh in the cytosol (Bezprozvanny et al. 1991).

Calcium has other important intracellular signaling roles. Most obvious isthat the amount of calcium entering through voltage-dependent calciumchannels determines the extent of neurotransmitter release at synapses. Cal-cium also plays a role in the gating of some plasma membrane ion channels;it activates calcium-dependent potassium channels and it causes inactivationof some voltage-gated calcium channels. Finally, calcium is important as acofactor for several different kinases, for example protein kinase C andCa2+/calmodulin-dependent protein kinases.


3.2.5 Calcium/calmodulin-dependent kinase (CaM-kinase)

When cytosolic calcium concentration is elevated, calcium is taken up intointracellular compartments, pumped out of the cell by energy-dependentpumps, or bound to calcium binding proteins such as calmodulin. Calmod-ulin has no inherent enzymatic activity. When bound to calcium, however, itcan activate the plasma membrane Ca2+-ATPase to cause calcium to beextruded from the cell. It can also activate a group of serine/threoninekinases called Ca2+/calmodulin-dependent kinases (CaM-kinases) (Schulman1993; Picciotto and Nairn 1994). There are many CaM-kinases that havespecific targets, and others, such as CaM-kinase II, that have multiplefunctions. CaM-kinase II is expressed at high levels at neuronal synapses.One action of this enzyme seems to be to activate the synthesis of neurotrans-mitters such as norepinephrine and dopamine (Colbran and Soderling 1990)that are secreted in response to calcium influx. In addition, CaM-kinase II isbelieved to play a role in the regulation of neurotransmitter release byphosphorylating synapsin J, a protein that controls the association betweensynaptic vesicles and the cytoskeleton at presynaptic nerve terminals (Llinaset al. 1985; Benfenati et al. 1989). CaM-kinase II is found at high concentra-tions in the postsynaptic density, just under the plasma membrane, where itsfunction is unknown, but may involve modulation of ion channels (Nicolland Malenka 1995).

One interesting aspect of the activity of CaM-kinase II is that it has thepotential to function as a molecular memory device (Lisrnan 1994; Putney1998; De Koninck and Schulman 1998). When exposed to calcium andcalmodulin, the kinase phosphorylates itself, and can then continue to au-tophosphorylate in the absence of calcium. It therefore keeps a record of itsexposure to calcium by remaining in an active state long after calcium levelshave fallen to normal, and may provide a mechanism to integrate calciumtransients temporally (De Koninck and Schulman 1998).

3.3 Actions of protein kinases

As we have seen, a variety of different protein kinases are activated bydistinct second messenger systems. These enzymes can alter a number ofcellular properties through phosphorylation of particular membrane proteins.This placement of a phosphate group on a protein can have very divergenteffects, depending on the nature of the protein being phosphorylated.

3.3.1 Modulation of ionotropic receptors

One target of phosphorylation is ionotropic receptors (Huganir and Green-gard 1990; Wang and Salter 1994). There are a number of properties ofionotropic receptors that impact on their signaling capabilities. One of thesefeatures is desensitization of the receptor, which limits the time course over


which the receptor can respond. After the binding of neurotransmitter causesthe receptor channel to open, continued presence of the ligand produces anintrinsic conformational change that decreases channel opening and rendersthe channel unresponsive to the ligand (Fig. 3.2). At some synapses, desensiti-zation only becomes apparent upon repetitive stimulation of presynapticinputs, whereas at others, it is the key process that determines the time courseof postsynaptic potentials (Jones and Westbrook 1996; Otis et al. 1996).

Although the process of desensitization itself is intrinsic to the channelprotein, the rate of desensitization of receptors can be modified by intracellu-lar pathways. For example, the nicotinic acetylcholine receptor (AChR) canundergo phosphorylation by a number of protein kinases, including the PKA,PKC, and tyrosine kinases (Swope et al. 1995). Phosphorylation of thereceptor by these kinases has been shown to increase its rate of desensitiza-tion (Fig. 3.2) (Huganir et al. 1986; Hopfield et al. 1988; Huganir andGreengard 1990). As we shall see later, such phosphorylation can also beimportant for the normal spatial localization of receptors.

3.3.2 Modulation of membrane ion channels

Besides acting at synaptic receptors, protein kinases can phosphorylate a widerange of membrane ion channels that help shape the electrical activity of theneuron. In particular, PKA has been shown to modulate voltage-dependentand calcium-dependent ion channels. Such channels determine the duration,timing, and patterns of action potentials during sustained stimulation of aneuron, and also control the spontaneous pattern of activity. The first studiesto show that PKA influences these aspects of a neuron were experiments inwhich the catalytic subunit of PKA was injected into the somata of neuronsof Aplysia and was found to enhance the amplitude of action potentials(Castellucci et al. 1980; Kaczmarek et al. 1980). Experiments on the samespecies with cyclic AMP analogues and with the Walsh inhibitor, a proteininhibitor of PKA, demonstrated that the pattern of spontaneous bursting ofthe Aplysia neuron R15 was altered by this enzyme (Adams and Levitan1982). Over the past 10 years, the genes for a large number of ion channelshave been isolated and a very large number of these have consensus sites forphosphorylation by PKA (Jonas and Kaczmarek 1996).

Another example of how PKA can modify neuronal excitability is found inthe pyramidal neurons of mammalian hippocampus and cortex (Madison andNicoll 1986; Pedarzani and Storm 1993). Certain neurotransmitters, such asnorepinephrine and serotonin, are believed to control the transition betweenstates of sleep and arousal. One of the actions of norepinephrine is to modifya calcium-activated K+ current in certain cortical pyramidal cells. Thiscurrent is activated by calcium entry during a train of action potentials, suchas those evoked by depolarizing currents (Fig. 3.3). The resulting outwardcurrent repolarizes the neuron and leads to a prolonged overshoot of themembrane potential that is termed the after-hyperpolarization (AHP). This


Fig. 3.2 Phosphorylation of the nicotinic acetylcholine receptor increases its rate ofdesensitization. A. Single channel activity at +100 mV from purified receptorconstituted into lipid vesicles. After treatment with acetylcholine, channel activityobserved for 60 s is at first robust and then declines until the frequency of channelopenings approaches zero. B. The number of channel openings over time in a patchtreated with acetylcholine undergoes exponential decay. C. A patch recorded from apreparation of receptors with a higher level of tyrosine phosphorylation showed morerapid decay in number of channel openings over time. The level of phosphorylationwas determined in biochemical assays on the purified preparations of receptor.Adapted from Hopfield et al. (1988).


Fig. 3.3 Regulation of the firing pattern of a pyramidal neuron in the mammalianhippocampus. In response to a depolarizing current pulse, activation of ahyperpolarizing potential (AHP) normally prevents repetitive firing (top left). TheAHP that follows the depolarization is also shown on a slower time-scale (bottomleft). After activation of PKA, by treatment with an analogue of cAMP, thehyperpolarization is reduced (bottom right) and repetitive firing of the neuron occurs(top right). Adapted from Madison and Nicoll (1986).

hyperpolarizing current is slow in onset and decays slowly, and, once it isactivated, prevents neurons from firing additional action potentials. Such aprogressive loss of the ability of a neuron to fire repetitively during amaintained stimulus of a pyramidal neuron is known as accommodation.

A variety of experimental approaches have been used to show thatnorepinephrine regulates the AHP through the activation of PKA. Whennorepinephrine is added to pyramidal cells recorded in hippocampal slices, itproduces a depolarization of their resting membrane potential and a decreasein the amplitude of AHPs evoked by depolarizing currents, resulting indecreased accommodation (Fig. 3.3). The actions of norepinephrine can bemimicked by application of cAMP analogues or by drugs that activateadenylate cyclase. Furthermore, intracellular application of the Walsh in-hibitor of PKA blocks the ability of an agonist of norepinephrine, isopro-terenol, to suppress the AHPs (Pedarzani and Storm 1993). The conclusionthat can be drawn from these studies is that when PKA is activated byneurotransmitters it phosphorylates a protein that regulates the AHP, possi-bly the potassium channel itself.


3.3.3 Modulation of neurotransmitter release

Although modulation of transmitter release has been observed in a number ofdifferent systems, aside from alteration of calcium currents associated withvesicle release, there is little known about the mechanisms underlying directmodulation of exocytosis. In theory, enhanced vesicle fusion with the mem-brane can be brought about by regulation of several different aspects ofpresynaptic function: (i) enhanced influx of calcium across the plasma mem-brane, (ii) release of calcium from intracellular stores adjacent to release sites,(iii) modification of the proteins that regulate fusion, for example by phos-phorylation, (iv) modulation of the cellular scaffold that links synaptic vesicleproteins to calcium channels at release sites, (v) modulation of the size of thereadily releasable pool of synaptic vesicles (Fig. 3.4). We shall now brieflyreview some selected examples of modulation of transmitter release byprotein kinases and describe some directions in which research is progressingin this very new field.

Modulation of calcium entry in presynaptic terminalsThere now exist numerous studies of the regulation of calcium currents inneurons, and of processes that influence calcium entry. For example, modula-tion of synaptic function has been studied extensively in the sensory-motorsynapses in Aplysia that underlie the behavior of gill, tail, and siphonwithdrawal in response to sensory stimulation. Alterations in this behaviorhave long been regarded as examples of components of learning seen inmammals (Byrne and Kandel 1996). Studies have teased apart differentaspects of regulation of neurotransmitter release. For example, it has beenfound that in response to activation of presynaptic serotonin receptors, anelevation of cAMP levels leads to broadening of presynaptic action potentialsand enhanced excitability by suppressing the amplitude of a potassiumcurrent, IKS (Klein et al. 1982, 1986). Using calcium imaging, it was foundthat the change in action potential shape led to enhanced calcium influxthrough dihydropyridine-insensitive calcium channels near release sites (Eliotet al. 1993). In mammalian preparations, cAMP has also been found to be animportant second messenger that influences the induction of long-termchanges in synaptic release. At mossy fiber synapses in the hippocampus, anincrease in cAMP levels and increased activation of PKA are necessary forsynaptic plasticity, and seem to be dependent on an elevation of presynapticcalcium concentrations (Nicoll and Malenka 1995).

Regulation of intracellular calcium storesStores of intracellular calcium have been found to be important for theregulation of synaptic release (Tang and Zucker 1997). One example of thisis found in the peptidergic bag cell neurons of Aplysia (Jonas et al. 1997) inwhich, as will be described later, PKC regulates calcium currents. Theseneurons also express a tyrosine kinase that is activated by insulin. When bag


Fig. 3.4 Modulation of synaptic release of transmitter, (i) Modulation of cakiumentry by altering potassium or calcium channels, (ii) Regulation of calcium releasefrom intraceliular stores may alter transmitter release, (iii) Direct regulation ofexocytosis proteins may alter the probability of fusion of individual vesicles, (iv)Modulation of the interaction between calcium channels and synaptic vesicle proteinsmay alter the efficacy of action potentials ro trigger release, (v) Changes in vesicletrafficking and dynamics can alter the availabili ty of vesicles for release,

cell neurons are exposed to insulin, cakium is released from mmicellularstores. In the absence of action potential firing, the resultant elevation ofcalcium causes significant release of neuropeptide, suggesting that neuropep-tide release is, at least in part, dependent on intracellular calcium mobiliza-tion. In bag cell neurons, this internal calcium store appears not to be the IP3regulated calcium store described earlier, but may be the secretory vesiclesthemselves, or a closely related organdie.

Direct modulation of synaptic vesicle exocytosisRegulated transmitter release in neurons occurs through the process of

E. A. Jonas and L K. Kaczmarek 95

exocytosis. Exocytosis is controlled by several proteins that are found abun-dantly in preparations of synaptic vesicles. Synaptobrevin is a synaptic vesicleprotein that is found almost entirely on the cytoplasmic face of the vesicle.Syntaxin resides on the cytoplasmic face of the plasma membrane. Theinteraction of these two molecules and a third, termed SNAP-25, a proteinclosely associated with the plasma membrane, provides the specificity fordocking of the synaptic vesicle with the plasma membrane. Other proteins,including NSF (N-ethylmaleimide sensitive factor) and SNAPs (soluble NSFaccessory proteins), regulate fusion, while yet another type of protein, synap-totagmin, may be the sensor for calcium during the process of calcium-depen-dent fusion. Although it has been shown biochemically that these proteins aresubject to phosphorylation by a variety of protein kinases (Hirling andScheller 1996), direct physiological evidence for modulation has been difficultto obtain. Indirect evidence using hippocampal neurons in culture, however,suggests that, in the absence of calcium influx or intracellular calcium release,the facilitation of synaptic transmission that is dependent on cAMP is causedby an increase in the probability of release of individual vesicles (Trudeau etal. 1996).

Linkage of calcium channels to synaptic vesiclesAlthough little is as yet known about the regulation of exocytosis proteins byprotein kinases, it has been demonstrated that N-type calcium channels binddirectly to the synaptic complex of synaptobrevin, syntaxin, and SNAP-25(Mochida et al. 1996; Rettig et al. 1997). Introduction of inhibitory peptidesinto presynaptic neurons of the superior cervical ganglion disrupts the bind-ing of calcium channels to synaptic vesicles and reversibly inhibits synaptictransmission, as measured by the amplitude of EPSPs at the postsynaptic cell.Although some evoked release persists after inhibition of this interaction, theremaining component of release depends on a higher level of calcium,presumably because the calcium channels no longer reside very close to thesynaptic vesicle fusion machinery. These findings suggest that modulation ofsynaptic release may occur if phosphorylation of calcium channels or ofsynaptic vesicle proteins alters their interactions with each other withinpresynaptic terminals.

Regulation of the readily releasable pool of neurotransmitterThere are a variety of processes that influence the size of the pool ofneurotransmitter that is available for release at synaptic junctions. Forexample, the supply of neurotransmitter may be affected by changes in therate of movement of secretory granules or of synaptic vesicle componentsalong the axon (Azhderian et al. 1994). One example of an acute form ofmodulation that possibly reflects transmitter availability exists in the Aplysiasensory motor synapse described above. At this synapse it was found thatenhancement of transmitter release could occur in response to serotonin evenin the absence of spike broadening (Braha et al. 1990). This process is


entirely independent of calcium influx, and seems to involve mobilization ofvesicles or an enhancement of functioning of the exocytosis machinery. Evenin the absence of action potentials, serotonin under certain conditions wasable to enhance spontaneous release of transmitter from sensory neurons inculture (Dale and Kandel 1990). This effect was blocked by treating culturedcells with an inhibitor of PKC, and PKC stimulators were able to facilitateevoked release without causing action potential broadening, suggesting thatthis enzyme is responsible for the component of facilitation that does notdepend on spike broadening.

Related findings have also been described in bovine chromaffin cells, amodel system used widely as a model for neuronal release processes (Gillis etal. 1996). In these cells, the process of exocytosis can be monitored bymeasuring changes in membrane capacitance, which is a direct measure of theamount of vesicle membrane added to the plasma membrane during exocyto-sis. A phorbol ester activator of PKC causes a twofold increase in the changein membrane capacitance that is produced by depolarization of the mem-brane. This effect could not be accounted for by an increase in calciumcurrent or by a change in the peak or basal calcium levels in the cells. Bycarefully analyzing the rate of decay of capacitance during repeated testdepolarizations, it was found that the pool of vesicles waiting to fuse with themembrane (the readily releasable pool) was increased in size by the activatorof PKC.

3.4 Localization of signals within neurons

Investigators of second messenger pathways have for many years been awareof the 'compartmentalization' of responses within a cell. Only recently,however, has the molecular basis of such compartmentalization come tolight. Receptors, kinases, ion channels, and other effectors may be clusteredto each other and to the cellular cytoskeleton by specific linker molecules.Such linkage to a cellular scaffold can be essential to the normal transductionof signals. Moreover, such molecular clustering can limit the spatial extent ofcertain signals. In this section we shall give some specific examples of howthese spatial interactions influence neuronal responses.

3.4.1 Anchoring of ionotropic receptors

Ligand-gated receptor channels provide a very clear example of the impor-tance of subcellular localization. Adequate activation of postsynaptic recep-tors is normally produced only when the receptors are tightly clustered atsynaptic junctions. This is achieved by a network of adapter proteins whosefunction is to link membrane proteins to specific components of the underly-ing cytoskeleton. One such adapter protein for the AChR is rapsyn, a 43 kDa

E. A, Jonas and L. K. Kaczmarek 97

Fig. 3.5 Linkage of the acetylcrioline receptor (AchR) to the eytoskeli-'ton and tocomponents of the extracellular matrix through Rapsyn. Sec text for details.

protein that couples the receptor to dystruglycan, a protein that is a compo-nent of the dystrophin-glycoprotein complex that l inks the AChR to thecytoskeleton (Fig. 3.5) (Apel et al. \ 995). Clustering of the AChR, by bindingto the subsynaptic cytoskeleton, is regulated by the extracellular protein,ctgrin, which causes the receptors to become phosphorylated on tyrosineresidues (Swope et al. 1995). A high level of tyrosine phosphorylation of theAChRs is present in the mature neuromuscular junction (Huganir and Green-gard 1990). Thus, tyrosine phosphorylation of the receptor influences cluster-ing and, as mentioned previously, induces a rapid rate of descnsitization,both of which are important characteristics of normal synaptic transmission.

The targeting and anchoring of neurotransmitter-gated ion channels tosynapses is aided by specific sites on the receptor proteins that bind to theadapter proteins. In several types of ion channels, conserved sequences in theC-terminus of the ion channel protein bind to special regions known as PDZdomains contained within specific anchoring proteins (Sheng 1996; Hsueh etal. 1997). PDZ domains are made up of approximately 90 ammo acids andwere initially recognized as sequence repeats in three unrelated molecules:postsynaptic density protein-95kDa (PSD-95), the homologue for theDrosophila gene discs large (Dig), and a tight junction protein zo-1. Theseanchoring proteins are thought to cluster ion channels together, linking themto the cytoskeleton. The PDZ domains arc signature sequence modules withinthese molecules that foster such protein-protein interactions.

The first protein containing a PDZ domain that was found to influence ionchannel clustering in transfected cells was PSD-95 (Kim et al. 1995).


Fig. 3.6 Linkage of the AMPA class of glutamate (Glu) receptors to the cytoskeletonthrough PDZ domains on the glutamate receptor interacting protein (GRIP). See textfor details.

Although the channels that this protein clustered were Shaker-type voltage-dependent potassium channels, it was soon shown that a synaptic PDZdomain-containing protein was also important in the clustering of AMPAreceptors at excitatory synapses in the brain (Dong et al. 1997). The proteinwas named GRIP for glutamate receptor interacting protein (Fig. 3.6). GRIPcontains no fewer than seven PDZ domains but apparently has no intrinsicenzyme activity. It appears, therefore, to function as a binding or an adapterprotein involved in the clustering of AMPA-type glutamate receptors. Thedifferent PDZ domains found within the molecule may have different speci-ficities for peptide substrates, indicating that GRIP may also link AMPAreceptors to other proteins in the synapse. Such links to protein kinases maybe essential for regulation by second messengers.

3.4.2 Anchoring proteins localize kinases and channels tospecific parts of the cell

Just as unique proteins exist for clustering ionotropic receptors, evidence nowshows that PKA may be anchored and compartmentalized to specific subcel-lular locations (Mochly-Rosen 1995). There exist several isoforms of PKA,which differ primarily in the characteristics of the regulatory subunits. Inbiochemical fractionation experiments, one form of this enzyme (type II PKA)is found in the cell particulate fraction, often anchored near its protein


Fig. 3.7 Regulation of AMP A receptors through the cyclic AMP dependent messengersystem. A metabotropic receptor (left) couples to adenlylate cyclase (AC) through thea subunit of the G protein Gs. The resultant synthesis of cAMP causes thedisassociation of the regulatory (R) and catalytic (C) subunits of the cAMP-dependentprotein kinase (PKA), thereby activating this enzyme. Free catalytic subunit is shownas phosphorylating the channel receptor. Localization of the kinase near its substrateis achieved by the A-kinase anchoring protein (AKAP), which binds to the regulatorysubunit of PKA, and GRIP, which binds to the AMPA receptor. For simplicity, GRIPand AKAP are shown as binding to a common cytoskeletal element, although thedetails of these interactions are not yet understood.

substrates through its regulatory domain. Binding of cAMP to PKA releasesthe catalytic subunits in close proximity to its substrate, ensuring rapidphosphorylation of localized substrates in response to a global increase in theintracellular concentration of cAMP. The proteins that anchor PKA are calledA kinase anchoring proteins (AKAPs) (Fig. 3.7).

Direct evidence that modulation of ion channels by PKA requires itssubcellular localization through AKAPs has come through experiments on theAMPA subtype of glutamate receptor that we discussed above (Rosenmundet al. 1994). In cultured hippocampal neurons, agents that elevate cAMPlevels and activate PKA enhance the amplitude of currents mediated byAMPA receptors. A basal level of phosphorylation by PKA also appears to berequired to maintain AMPA currents. It has been found that intracellularperfusion of cultured hippocampal neurons with peptides that block thebinding of the kinase to its AKAP prevents the PKA regulation of the AMPAcurrents and also of the fast excitatory synaptic currents that are presumablymediated by AMPA receptors. Furthermore, the actions of these inhibitorypeptides are prevented by adding the purified catalytic subunit of PKA,


suggesting that the effect of PKA on the AMPA receptor depends on the localconcentration of that enzyme. The results support the hypothesis that prox-imity of the enzyme to its substrate is important at sites where rapidmodulation is needed. During rapid synaptic transmission, for example,AKAPs may act as the glue that links the enzyme to its substrate atpostsynaptic sites. Taken further, the results also suggest that a cytosolicenzyme such as the catalytic subunit of PKA could alter the function of amembrane ion channel in one specific location within the cell, and then,perhaps with a slight delay, diffuse to other parts of the cell to coordinate theactivities of that ion channel with important cellular events.

It is not yet known whether AKAPs participate in the regulation ofpotassium channels by PKA. Like ionotropic receptors such as the AMPAreceptors, some potassium channels are known to be linked to the cyto-skeleton and other cellular components through adapter proteins. For exam-ple, many channels in the Shaker subfamily of K+ channels can be clusteredby binding to the postsynaptic density protein (PSD)-95 family of proteins.These adapter proteins have multiple PDZ domains, as well as a region thatresembles guanylate kinases. The carboxy-terminal cytoplasmic tails of theK+ channel subunits bind to the PDZ domains of the PSD-95 protein (Kim etal. 1995). Such protein-protein interactions may couple potassium channelsto PKA or other protein kinases.

3.4.3 Direct phosphorylation of ion channelsBecause ion channels may be linked in a cellular array of proteins, some ofwhich may modulate the properties of the channels, a key question is whetherthe ion channel itself undergoes phosphorylation or whether phosphorylationof some other protein is responsible for the changes in ion channel properties.Most of the ion channels whose genes have been cloned have consensus sitesfor phosphorylation. A typical sequence for phosphorylation by PKA isArg-Arg-X-Ser in which two basic amino acids are followed by a non-criticalamino acid (X), and then by the serine or threonine that is to be phosphory-lated (Pearson and Kemp 1991). Similarly, for PKC the consensus site is aserine or threonine followed by one or more basic residues (Arg or Lys)(Pearson and Kemp 1991). There are a variety of experimental tests that havebeen applied to test whether an ion channel is directly phosphorylated by akinase. In this section, we shall illustrate some of these for the Kv3.4voltage-dependent potassium channel.

The Kv3.4 channel produces a rapidly inactivating potassium current orA-current (Covarrubias et al. 1994). In neurons, the A-current contributes tothe repolarization of action potentials and, in repetitively firing neurons,plays an important role in regulating the membrane voltage between actionpotentials (Connor and Stevens 1971). The rate of inactivation of A-currentalso determines the delay between the onset of synaptic depolarization andthe first action potential that is evoked (Byrne 1980; Strong and Kaczmarek1986). Several channel proteins, including the Kv3.4 channel, whose currents


Fig. 3.8 Regulation of inactivation of Kv3.4 by PKC. The Kv3.4 potassium channelgene, expressed in a Xenopus oocyte, produces a rapidly inactivating current. Exposureof the oocyte to activators of PKC results in the progressive elimination of theinactivation. The superimposed traces represent whole oocyte recordings obtained byrepetitive 112 ms step depolarizations to +30 mV from a holding potential of —100 mVat 30 s intervals after exposure to the PKC activator. Adapted from Covarrubias et al.(1994).

inactivate rapidly, share a sequence near the N-terminus of the protein thathas been termed the 'ball and chain' region. These N-terminal regions arethought to act as inactivation gates, moving in front of the open channel toblock K+ ion conductance through the channel (Hoshi et al. 1990). Thepresence of serine residues in sequences that resembled PKC consensusphosphorylation sites in this region of the Kv3.4 channel suggested toinvestigators that the inactivation gate could be regulated by protein phos-phorylation (Covarrubias et al. 1994). Consistent with this hypothesis, whenthe Kv3.4 channel gene is expressed in a cell that does not have manyendogenous potassium currents, such as a Xenopus oocyte, it generates arapidly inactivating A-type potassium current. Exposure of the oocytes toPKC activators, however, results in the elimination of the rapid inactivation,presumably through a structural change in the inactivation gate caused byphosphorylation (Fig. 3.8).

To determine if the N-terminal region of Kv3.4 is indeed phosphorylatedby PKC, Covarrubias et al. (1994) synthesized a peptide that matched theamino acid sequence of the first 28 amino acid residues of the N-terminus ofKv3.4, which contains the PKC consensus sites. When this synthetic peptidewas incubated with PKC and radiolabelled ATP, it was found that phos-phorylation of the peptide was enhanced tenfold over control by the presenceof the kinase. Similar experiments demonstrating direct phosphorylation ofchannel peptides or entire channel proteins have been carried out for anumber of different channels (Jonas and Kaczmarek 1996).

As a direct test of the role of the specific N-terminal consensus sequences in


the control of inactivation, Covarrubias et al. (1994) made a mutation of theKv3.4 gene so as to eliminate phosphorylation. In particular, the serineresidues in the sequence were mutated to alanine, a residue that is similar insize to serine but which cannot accept a phosphate group. When the mutatedchannel was expressed in Xenopus oocytes, it was found that the effect ofactivators of PKC on the inactivation kinetics of the expressed channel wasgreatly reduced. The results indicate that, at least for the Kv3.4 channel,direct phosphorylation of the protein is able to cause structural changes thatalter the channel's inactivation behavior.

3.4.4 The maxi-K channel is closely associated with its kinasesand phosphatases

Earlier in this chapter, we discussed a potassium channel activated by calciumthat is responsible for spike frequency adaptation or accommodation incortical neurons. Several of these Ca2+-activated K+ channels are known(Kohler et al. 1996; Joiner et al. 1997), and they regulate many properties ofneurons including frequency of neuronal firing, secretion of neurotransmitter,and the shaping of presynaptic calcium signals responsible for the release oftransmitter. Another type of Ca2+-activated K+ channel, which is sensitive toboth calcium and to voltage, is a large-conductance channel known asmaxi-K. Like the purely voltage-dependent potassium channels, the maxi-Kchannel is believed to play a role in the repolarization of action potentials.The properties of this channel can be readily studied in isolation from otherchannels by preparing membrane fractions from the nervous system and thenreconstituting them into synthetic lipid bilayer membranes.

Using such reconstituted channels, it has been found that the activity of themaxi-K channel can be increased simply by the addition of ATP to thecytoplasmic face of the channel (Fig. 3.9). The effect of ATP does not requireany exogenous kinase (Chung et al. 1991). This finding suggested that thechannels may have their own kinase that is intimately associated with thechannel protein. To probe this hypothesis further, Reinhart and Levitan(1995) tested the actions of drugs that block the activity of protein phos-phatases. Phosphatases are enzymes that remove phosphate groups fromproteins, and therefore reverse the actions of protein kinases. When phos-phatase activity in the lipid bilayer preparation was blocked by the inhibitormicrocystin, it was found that the ability of ATP to increase channel activitywas significantly enhanced. Conversely, when an inhibitor of PKC was used,the channel activity slowly declined, suggesting that the kinase associatedwith the channel is PKC or a closely related enzyme (Fig. 3.9). It is importantto realize that, in these experiments performed on lipid bilayers, the channelhad been isolated and diluted away from other cellular components. Thesimplest explanation for the results, therefore, is that there exist both a kinaseand a phosphatase so closely linked with the channel that when preparationsof isolated membrane containing the channel are made, the channel cannotbe easily separated from these regulatory enzymes. These regulating agents


Fig. 3.9 The maxi-K channel is intimately associated with PKC. Control panel showsa single channel recording from a lipid bilayer. When ATP was added directly to thecytoplasmic face of the channel, the activity of the channel increased (middle group ofrecordings). An inhibitor of protein kinase C blocked the effect of ATP (bottompanel). Adapted from Reinhart and Levitan (1995).

are presumed to provide continual reversible regulation of the channel withina neuron so that its open probability is always appropriate for the requiredpatterns of electrical activity.

3.4.5 Linkage of PKC and channels through the InaDadapter protein

How, exactly, are ion channels linked intimately with their modulators? Oneof the clearest molecular pictures that we now have of the interaction of achannel with a kinase, and of the importance of this physical interaction forcellular signaling, is found in the Drosophila phototransduction cascade (Fig.3.10) (Ranganathan et al. 1995; Scott and Zucker 1997; Tsunoda et al.1997). This takes place within the photoreceptors in highly structured subcel-


Fig. 3.10 The Drosophila phorotransduction cascade. A. Light activates rhodopsin,which activates a G-protem coupled ro phospholipase C. This in turn activates thetransient receptor potential (TRP) channel by a pathway that has not been fullycharacterized. After light opens the channel, PKC inhibits its activity. B. The InaDprotein serves as a scaffold that keeps the regulatory elements close to the TRPchannel. The InaD protein has five PDZ domains. I'DZ domains 3, 4, and 5 hind theTRP channel, PKC, and P[,C-B respectively.

lular compartments called rhabdomeres. The rhabdomeres contain thousandsof tightly packed microvilli on which the light transduction reaction takesplace. In these rhabdomeres, light activation of rhodopsin activates a Gqprotein a subunit (Gqa) which activates PLC-B. As described above, phos-pholipasc C catalyzes the breakdown of PIP, into IP, and DAG. In thephotoreceptor, this leads to the opening and modulation of ion channels


termed TRP channels (transient receptor potential channels). At the end of alight stimulus, calcium-dependent processes, including activation of an iso-form of PKC, mediate deactivation of the light response. A complex protein,known as InaD, holds all these signaling molecules together in close proxim-ity to the TRP channel (Tsunoda et d. 1997).

The InaD protein is an adapter protein with five PDZ domains that acts asan organizing scaffolding for the photoreceptor signaling complexes (Fig.3.10). InaD interacts directly with the TRP channel, PLC-B, and PKC. Inorder to determine if specific PDZ domains are dedicated to interaction withparticular signaling molecules, Tsunoda et al. (1997) synthesized five differ-ent short peptides mimicking the five PDZ domains (with their immediateflanking regions that are important for binding specificity). Using thesepeptides they determined that the third PDZ domain specifically binds to thelight-regulated ion channel TRP. The fourth interacts with PKC and the fifthwith PLC-B. As yet, the proteins that bind to the first two PDZ domains arenot known.

Mutant InaD proteins have yielded more information about the binding ofthe signaling complexes and their importance to the functioning of the TRPchannel. The mutant InaD1 encodes a truncated InaD peptide and fails togenerate any functional InaD protein. In the cells homozygous for the InaD1

allele, TRP, PLC-B, and the PKC isoform are completely mislocalized; theyare no longer present at the rhabdomeres, but are found randomly distributedthroughout the plasma membrane (in the case of TRP) or the cytoplasm (inthe case of PLC-B and PKC). Cells expressing this mutant InaD respondabnormally to light, only reacting to very high intensities and with alteredresponse kinetics. When their scaffolding has been eliminated, the signalingmolecules are also unstable and exist at low levels in the cell .

In contrast to the InaD1 mutant, there exist mutations where only one PDZdomain is affected, resulting in abnormal recruitment of only that one targetprotein to the signaling complex (Tsunoda et al. 1997). For example, whenthere is a missense mutation in the third PDZ domain, the interaction of TRPwith InaD is disrupted. The TRP channels in cells expressing this mutantwere found to be mislocalized, randomly distributed throughout the plasmamembrane, and to decline in number with age of the animal, while thelocalization and levels of the other signaling molecules remained intact. Inanother PDZ mutation that affects the binding of PLC-B, the cells displayedmajor defects in response kinetics: latency, activation, and deactivation of thelight responses were all markedly slowed. This was true even at a develop-mental time period when levels of PLC-B in the mutant cells were normal,indicating that it was the location, and not the level of the transductionprotein, that was responsible for the abnormal phototransduction. Takentogether, all these experiments support the hypothesis that the existence ofthe highly organized scaffold is necessary for effective and efficient signalingin the Drosophila phototransduction cascade.


3.5 Signaling cascades of tyrosine kinases

Up until now we have been describing in this chapter ion channel modulationby receptors and second messenger kinases that reside in close physicalproximity to the channels they modulate. In certain cases, however, it may bebeneficial for the cell to use signaling pathways that act on ion channels onlyindirectly. This may occur when multiple cellular processes need to beactivated in synchrony. The function of certain protein kinases is to coordi-nate such activities. In most second messenger cascades, enzymes and adapterproteins are activated sequentially in a chain. Inherent in this organization isthe possibility that branches of signaling pathways will form off the mainchain so that different systems throughout the cell can be regulated. Onesimple example of such a cascade is the membrane phospholipid pathway.There, PLC causes the breakdown of PIP2 into DAG and IP3. As we haveseen previously, DAG activates PKC, but IP3 is made simultaneously (Berridge1993). This is a separate second messenger with a separate pathway ofactivity, and a separate function, causing the release of calcium from intra-cellular stores.

Protein kinases that phosphorylate their substrates on tyrosine residues aretypical elements in signaling cascades that regulate many aspects of cellfunction. These tyrosine kinases were initially characterized in the control ofcell growth, differentiation, and oncogenesis (Cantley et al. 1990), duringwhich multiple cell processes are coordinated by the activation of kinasecascades. Recently, protein tyrosine kinases have been found to modulateneuronal ion channels acutely (Jonas and Kaczmarek 1996), raising thepossibility that neuronal differentiation and the modulation of neuronalexcitability share common pathways. If tyrosine kinases regulate neuronaldifferentiation and excitability simultaneously, they could coordinate theseprocesses during development or at times of neuronal plasticity in the adultnervous system, such as for enhanced use of a synaptic connection duringlearning. Activities that could result from activation of multiple signalingsystems include modulation of ion channel properties, enhanced insertion orremoval of channels from the membrane, and signaling to the nucleus totranscribe genes into the proteins needed for growth and movement of theneuron, for new ion channels, and for the cytoskeletal rearrangements in-volved in the formation of new synaptic connections.

3.5.1 Receptor tyrosine kinases are both receptors and kinases

The receptor tyrosine kinases are different structurally and functionally fromthe kinases we have discussed previously. Examples of receptor tyrosinekinases are the receptors for insulin, fibroblast growth factor (FGF) and nervegrowth factor (NGF), each of which are found on neurons of the centralnervous system. As their name implies, they phosphorylate proteins ontyrosine residues (Schlessinger and Ullrich 1990). They do not depend on


G-proteins to transduce their signal. Receptor tyrosine kinases also differfrom other types of receptors in that the kinase is an integral part of thereceptor (Fig. 3.1C). Structurally, receptor tyrosine kinases are single trans-membrane proteins that contain an extracellular binding domain and anintracellular kinase region. In many cases, upon binding of the ligand to theextracellular component, the receptor dimerizes. Each partner of the dimercan then phosphorylate the other on specific tyrosine residues (Schlessingerand Ullrich 1990). This type of phosphorylation is known as cross-phosphorylation or autopbosphorylation. In this active form, the receptortyrosine kinase then activates a series of downstream effector proteins thatcan link effects on ion channels to actions on other aspects of cell function.As one example, the insulin receptor tyrosine kinase can modulate ionchannel activity by increasing the amplitude of calcium and potassiumcurrents (Jonas et al. 1996), by causing increased insertion of ion channelsinto the membrane (perhaps by influencing vesicular trafficking) (Wan et al.1997), and by signaling to the nucleus (Levin and Errede 1995) to synthesizemore channel protein.

Many of the components of the kinase cascade activated by receptortyrosine kinases have been elucidated. For example, when activated byinsulin, the insulin receptor tyrosine kinase binds and phosphorylates aprotein termed IRS-1 (Fig. 3.11) (Sun et al. 1991). This protein, in turn,binds other proteins. Some of these proteins, such as PI3 kinase (Rudermanet al. 1990), are enzymes that catalyze the synthesis of second messengermolecules within the cell. Other proteins, however, do not have enzymeactivity, but act as adapter proteins that foster protein-protein interaction(Egan et al. 1993). A number of specific domains have been identified onthese adapter proteins and on the proteins with which they interact. One suchdomain is the Src homology region 2 (SH2) domain named for its similarityto regions in the Src tyrosine kinase, a non-receptor tyrosine kinase wherethese regions were first described (Schlessinger 1994). These SH2 regionsallow a protein to attach to phosphorylated tyrosine residues on otherproteins, including the autophosphorylated receptor tyrosine kinases. An-other domain that allows protein-protein interactions is the SH3 domain,which recognizes specific proline-containing hydrophobic sequences in theproteins to which it binds (Cohen et al. 1995). Key adapter molecules thatcontain SH2 and SH3 binding domains and that become active on stimula-tion of certain receptor tyrosine kinases are the Grb2, She, and Sos-1proteins. Sos-1 is a protein that binds to Ras, a G-protein, triggering a kinasecascade that signals to the nucleus, as well as to other parts of the cell (Segaland Greenberg 1996).

3.5.2 The MAP kinase pathway

Activation of ras proteins can alter the expression of genes that are importantfor neuronal electrical activity. The ras proteins belong to a large superfamily


Fig. 3.11 Signal ing pathways of the ryrosine kinase receptor that binds insulin. Theinsu l in receptor, once activated, phosphorylarcs I K S - 1 on tyrosine residues, 1RS-1activates PU-kinase or h inds to Grb-2. Another pathway activated by the i n s u l i nreceptor tyrosine kinasc is the direct tvrosine phosphorylation of She by the activatedreceptor, which activates Ras and eventual ly leads to changes in the transcription ofspecific genes. See text for deta i ls ,

of GTPases. They contain a covalenrly attached prenyl group that links theprotein to the cytoplasmic face of the plasma mem brant. The ras proteinsrelay signals from receptor tyrosine kinases to the nuc leus by activatinganother kinase cascade which involves the mitogen-activated protein kinase( MAP-kitiase). The activation of this enzyme converts a tyrosine phosphory-lation cascade into a serine/threonine phosphorylation cascade, becauseMAP kinase requires phosphorylation on both a ryrosine and a threonineresidue (Anderson el al. 1990). MAP kinase can be activated only by theenzyme MAP-kinase-kinase (Segal and Greenberg 1996), which has thiscapability. The activation of MAP-kinase by MAP-kinase-kinase results inphosphorylation of many different cell proteins among which are generegulatory proreins that initiate the transcriprion of genes known as immedi-ate early genes (Treisman 1996), Transcription of these genes leads tolong-term changes in cells .

Changes in the transcription of a gene that codes for an ion channel havebeen demonstrated to lead to alterations in the excitability of neurons. The


Kv3.1 channel is a voltage-dependent potassium channel that is expressed athigh levels in auditory pathways and in neurons capable of firing actionpotentials at a high frequency. Increases in the level of Kv3.1 current arebelieved to allow a neuron to generate higher rates of firing in response tosynaptic inputs (Kanemasa et al. 1995; Perney and Kaczmarek 1997; Wanget al. 1998). Transfection of activated ras into cells that express the Kv3.1gene has been found to greatly increase the levels of Kv3.1 mRNA and toincrease the amplitude of potassium current (Hemmick et al. 1992). Thiseffect is likely to be mediated by the MAP kinase pathway and by immediateearly genes.

The promoter of the Kv3.1 gene (i.e. the genomic DNA that regulates thetranscription of the gene) has been isolated and found to contain regulatoryregions that allow its rate of transcription to be controlled by external stimuli(Gan et al. 1996). In addition to regulatory sites that may allow the synthesisof the channel to be controlled by immediate early genes, the promoter has asite for the binding of the CREB protein. As we mentioned when discussingthe cAMP pathway, this protein undergoes phosphorylation upon elevationof cAMP. It can also be phosphorylated by CaM-Kinase IV, acalcium/calmodulin-dependent enzyme such as those described earlier (Pic-ciotto and Nairn 1994). Elevations of cAMP, or depolarization of cells thatleads to calcium entry through calcium channels, have been found to increasethe activity of the promoter (Gan et al. 1996). For example, sustaineddepolarization of neurons in the inferior colliculus elevates Kv3.1 mRNAlevels and increases the amplitude of Kv3.1-like potassium currents, leadingto enhanced repolarization of action potentials (Liu and Kaczmarek 1998).This change in the electrical properties of these auditory neurons is likely toenhance their ability to sustain prolonged trains of action potentials at highfrequencies (Perney and Kaczmarek 1997; Wang et al. 1998).

3.5.3 Non-receptor tyrosine kinases

In contrast to receptor tyrosine kinases, non-receptor tyrosine kinases haveno transmembrane regions and do not bind extracellular ligands. Theseenzymes are typically used as components in signaling pathways activated byplasma membrane receptors, and many of the known non-receptor tyrosinekinases, such as the enzymes src and PYK2, which are discussed below, arepresent at much higher levels within the nervous system than in other tissues.

3.5.4 Calcium activates the PYK2 non-receptor tyrosine kinases

An example of how tyrosine kinases function within a kinase cascade hasbeen provided by the study of the tyrosine kinase PYK2 and its effects on ionchannel modulation (Lev et al. 1995). PYK2 is widely expressed in themammalian nervous system. It is a non-receptor tyrosine kinase with no


Hig. 3.12 PYK2 is LI nun-receptor tyrosine kinase that is shown as a central elementjo in ing several signaling cascades. PYK2 is activated by G-protein coupled orlonotropic receptors that allow calcium to enter the cell or cause the release ofcalcium from inrracdlubr stores. The activity of PYK2 is also regulated by PKC. Afteractivation, PYK2 directly modulates potassium channel activity and activates theMS/MAP kinase pathway that signals to the nucleus.

transmembrane region to transduce extracellular signals. Within the PYK2protein is a proline-rich domain that can bind the adapter protein (Grb2, Theactivation of PYK2 (Fig. 3.12), which involves its phosphorylation on ryro-sine residues, can be brought about by stimulation of a number of membranereceptors, such as the ionotropic rticotinic acetylcholine receptor and themetabntropic bradykinin receptor. What these receptors have in common isthat they increase levels of cytosolic calcium, either by opening ion channelsin the cell membrane or by causing the release of ca lc ium from intraceilularstores as a result of IP, synthesis. Although the full pathway leading to PYK2activation is not understood, activation seems to be dependent on thiselevation of cytosolic calcium.

The activation of PYK2 may have several consequences for a cell. WhenPYK2 is co-expressed with the Kv 1.2 channel, a voltage-dependent potassiumchannel known to be modulated by tyrosme kinases, Kvl .2 currents aredecreased by the activated enzyme (Lev et al. 1995). Furthermore, the Kv 1.2protein undergoes increased levels of phosphorylation on tyrosine residuesafter exposure to activated PYK2 but not to an inactive mutant of PYK2 oran unrelated tyrosine kinase. Immunopreci pi fated PYK2 has been found to


phosphorylate the channel protein in vitro, suggesting that tyrosine phospho-rylation of the channel by PYK2 is direct.

PYK2 also stimulates a pathway that signals to the nucleus. It does this bybinding to Grb2, which, as described above, leads to activation of theras/MAP kinase pathway. Not all components of this pathway are known,but stimulation of Grb2 in this setting depends on G-protein receptor-mediated mobilization of intracellular calcium and subsequent activation ofPYK2. The MAP kinase system is responsible for signaling to the nucleus,and has been implicated in the induction of transcriptional events (Hersko-witz 1995; Segal and Greenberg 1996). PYK2 is therefore an example of atyrosine kinase that responds to extracellular signals by stimulating a kinasecascade with at least two branches. These branches of the pathway modulateion channels in the short term and stimulate gene transcription, possibly tobring about long-term regulation of neuronal excitability through the synthe-sis of new channel proteins.

3.5.5 Regulated insertion and removal of ion channels fromthe membrane

The existence of a highly organized scaffolding for colocalizing signalingmolecules and ion channels suggests yet another way in which regulation ofchannels can occur: by their insertion and removal from the membrane. It isknown that rapid removal of proteins from the plasma membrane can occurin the process of down-regulation of receptors. Substance P receptors, whichare present in certain pain afferents in the spinal cord, have been shown to beinternalized acutely in response to the glutamate agonist, NMDA (Liu et al.1997). In fetal rat brain neurons, activation of voltage-dependent Na +

channels by a-scorpion toxin leads to their down-regulation by internaliza-tion, but this process has not yet been shown to depend on the activity of anymodulatory kinase (Dargent et al. 1995). The effect on the Na+ channelscould be blocked, however, by agents that disrupt the acidic environment ofthe endosomal compartments, implying that endocytosis is required for thedown-regulation of these channels.

The molecular mechanisms that control the endocytosis of ion channels areunknown, but are very likely to involve direct protein-protein interactionsbetween the channel and adapter molecules regulated by protein kinases. Forexample, there is evidence that adapter molecules such as Grb2 may directlycontrol the removal of membrane proteins. It has been found recently thattyrosine kinase receptors can regulate the process of endocytosis (Wang andMoran 1996). When activated, the tyrosine kinase receptor epidermal growthfactor receptor (EGFr) binds to Grb2 which then interacts via its SH3 domainwith dynamin, a guanosine triphosphatase that regulates endocytosis (Fig.3.13). The EGFr itself undergoes internalization in response to ligand bind-ing, and disruption of the interaction of Grb2 with dynamin, by microinjec-

112 Subcellular mechanisms of neurornodulation

Fig. 3.13 Receptor regulation by endocytosis may have similarities at the molecularlevel to regulation of ion channel endocyrosis. The tyrosine kinase receptor F.GF bindsgrb-2, which contains protein-protein interaction sites, (irb-2 interacts with dynamin(Dyn) which regulates endocytosis of the receptor. A postulated mechanism of ionchannel endocytosis through activation of receptor tyrosine kinases is also shown, butthe sites of interaction between the ion channe l and signaling molecules are speculative.Other synapttc activities are also shown schematically: a pathway for ion channeldegradation and .1 pathway for the packaging of neurotransmitrer.

tion of an inhibitory synthetic peptide, prevents this internalization. In otherstudies, it has been shown that disruption of the interactions of dynamin withanother SH3 domain-containing protein, a tnphiphysin , inhibi ts synapric vesi-cle endocytosis, with a resulting distortion of synapric architecture andimpaired release of neurocratismitrer (Shupliakov ct al. 1997), Although thesites on ion channels that may be required for their internalization are not yetknown, certain ion channels interact directly with non-receptor tyrosinekinases by binding of SH3 domains on these tyrosine kinases to proline-richsequences on the ion channels (Holmes et al. 1996). Thus it is possible thatprotein-protein interactions between ion channels and signaling adaptermolecules may also regulate their rates of endocytosis.

In contrast to the removal of ion channels by endocvtosis, recruitment of


channels to the plasma membrane from intracellular vesicles has been hy-pothesized as a mechanism through which current amplitude can be en-hanced. This assumption is based on a variety of lines of evidence in Aplysiabag cell neurons, a group of cells that control egg-laying behavior in thisspecies. In response to activation of protein kinase C, there is an increase inthe voltage-dependent calcium current that contributes to the potentiation ofthe amplitude of action potentials (DeRiemer et al. 1985). The enhancementof calcium current occurs through the recruitment of a new subtype ofcalcium channel to the plasma membrane. The single channel biophysicalproperties of the recruited channel differ from those of the channel that ispermanently resident in the plasma membrane (Strong et al. 1987). Also inresponse to activation of protein kinase C, there is an enlargement of theneurite endings, and these enlarged areas coincide with new sites of calciumentry (Knox et al. 1992), suggesting that recruitment of calcium channels isassociated with the addition of membrane from intracellular organelles inreadiness for enhanced neuropeptide secretion.

Current evidence suggests that the enhancement of calcium current andneurotransmitter release that occur during egg laying behavior can be at-tributed to the recruitment of alA calcium channel subunits from intracellu-lar organelles to the plasma membrane. These neurons express two types ofcalcium channel subunits, alD and alA. Staining with antibodies againstthese two channels has demonstrated that they are found in very differentcellular locations (White and Kaczmarek 1997). The alD-type calcium chan-nel is located in the plasma membrane, while the «1A channel is locatedprimarily within intracellular organelles. The alA channel subunit is alsolocalized preferentially within neurite endings and, during development, itspresence on intracellular organelles is tightly correlated with the ability of thecells to enhance their calcium current (White and Kaczmarek 1997; White etal. 1998).

As we might expect, based on their role in neuronal growth and release sitematuration (Wu and Goldberg 1993; Thomas et al. 1995), tyrosine kinasesmay also control channel insertion at release sites. In hippocampal neurons,the rapid recruitment of functional GABAA receptors has been shown to beregulated by insulin, the ligand for the insulin receptor tyrosine kinase foundin these cells (Havrankova et al. 1978), and this appears to result in amodification of synaptic efficacy in the hippocampus (Wan et al. 1997).

3.6 Conclusions

This chapter has covered a variety of biochemical pathways that influence theexcitability of neurons. Second messenger pathways that are activated inresponse to the actions of neurotransmitters can influence ion channelsacutely. In many cases, modulation of ion channels requires that many of themolecular components, such as the channels themselves and their regulatory


kinases and phosphatases, be present within a complex of proteins heldtogether by adapter molecules and by specific protein-protein interactiondomains on the enzymes, channels, and adapters. Longer term changes inneuronal excitability are brought about by protein kinase cascades that signalto the nucleus. Finally, an emerging body of evidence suggests that the releaseof neurotransmitter at release sites is also acutely regulated by secondmessengers and kinases.

Acknowledgements

L. K. K. is supported by NIH grant NS-18492 and E. A. J. is supported by agrant from the Yale Diabetes and Endocrine Research Center and theAmerican Association for the Study of Headache/Glaxo Wellcome HeadacheResearch Award.

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Message received: cellular responses toneuromodulatory signalsGINA G. TURRIGIANO

4.1 Introduction

Many computational models of neural circuits treat neurons as 'integrate andfire' devices that linearly sum excitatory and inhibitory inputs and fire anaction potential when they pass threshold. While some aspects of neuralcomputation can be successfully captured in this way, these models ignore arich palette of intrinsic cellular properties that play important roles ingenerating the output of biological neural circuits. Neurons that fire bursts ofaction potentials intrinsically, for example, are present in various regions ofthe central nervous system (CNS), including the spinal cord (Rossignol andDubuc 1994), the thalamus (Steriade et al. 1991), and the cortex (Conners etal. 1982; Llinas 1988). The role of such intrinsic bursting in generatingrhythmic motor outputs in invertebrates (Marder and Calabrese 1996) and inspinal locomotor networks (Rossignol and Dubuc 1994) is well understood,but ideas about the function of complex intrinsic cellular properties are stilllargely speculative in many other systems. Nonetheless it is clear that mostneurons possess a complex array of ion channels that produce conductanceswhich help shape the response of the neuron to synaptic inputs, influencesynaptic plasticity, and bestow very non-linear response properties upon theneurons in which they are expressed. These voltage-dependent conductancescan interact in complex ways; and an interesting observation that hasemerged from conductance-based neuronal models is that small changes inthe balance of conductances can dramatically alter a neuron's firing proper-ties (Rinzel and Lee 1987; Guckenheimer et al. 1993; Turrigiano et al.1995).

In the previous chapters we saw that common targets for neuromodulatorysignals are the ion channels that determine neuronal firing properties. Be-cause neuronal firing properties are sensitive to small changes in the magni-tude of ionic conductances, neuromodulators can dramatically alter theseproperties by modifying the biophysical characteristics of specific ion chan-nels. This can take the extreme form of switching neurons between tonicfiring and burst firing modes, or can have a more subtle expression such aschanging the degree of spike frequency accommodation shown by a neuron

122 Cellular responses to neuromodulatory signals

during prolonged firing. In addition, neuromodulators can produce coordi-nated changes in presynaptic and postsynaptic conductances that dramati-cally change the input-output function of the neuron. As a consequence, themodulated neuron may behave very differently in the circuit in which it isembedded, and in some systems targeted modulation of individual neuronscan switch entire circuits into radically different firing modes. Seeminglysubtle modulatory changes in neuronal conductances can thus have a pro-found effect on neural circuits and on behavior.

The sensitivity of neuronal firing properties to small changes in the balanceof ionic conductances raises an interesting problem. How do neurons main-tain the relative balance of a large array of conductances in the right range topreserve particular firing patterns? The ability of neurons to regulate theirconductances has important consequences for the modulation of neuronalfiring properties because the effect a modulator has on these properties willdepend critically on the background of conductances the neuron expresses.Recent work suggests that a number of mechanisms exist to regulate thecellular and synaptic properties of neurons, keeping them balanced correctly.The ongoing activity of neuronal networks can homeostatically regulate bothmembrane and synaptic conductances to maintain neuronal activity withinfunctional boundaries (LeMasson et al. 1993; Turrigiano et al. 1994, 1998).These processes serve a stabilizing function during development when theproperties of neurons and circuits are still highly plastic and many cellularand synaptic properties must be adjusted in concert to produce correctlywired networks. By regulating the balance of membrane and synaptic con-ductances, these mechanisms may also ensure that modulation of theseconductances produces consistent effects on circuit function.

The picture that is emerging from several decades of research on theregulation and modulation of intrinsic neuronal conductances is that nervoussystems possess a rich array of modulatory mechanisms that can influenceinformation processing over many different temporal and spatial scales.These mechanisms are likely to play important roles both in switchingnetworks between different states, for instance in transitions between sleepingand waking states or motivational states (McCormick and Bal, 1997), and inthe moment-to-moment demands of neural computation by complex net-works.

4.2 Modulation of firing properties

In the classic Hodgkin-Huxley description of neuronal firing, only twovoltage-dependent conductances generate the action potential: a fast, rapidly-inactivating (so-called Hodgkin-Huxley) sodium current, and the delayed-rectifier potassium current (Hodgkin and Huxley 1952). Subsequently, itbecame clear that neurons also possess a large array of other conductances,

Gina G. Turrigiano 123

including a wide variety of potassium and calcium currents, several differentsodium currents, and a number of mixed cation currents. Each of theseconductances has a unique set of activation and inactivation properties thatcan depend on voltage and other factors such as the internal calciumconcentration (Hille 1992). The identity of neurons in different regions of thenervous system is a function not only of differences in morphology andconnectivity, but also in the unique array of conductances each neuronexpresses, which in turn produces a unique physiological phenotype. Thereare probably as many unique physiological phenotypes as there are morpho-logically distinct neurons, and below we consider only a few of the betterknown and understood variations on intrinsic firing properties and theirmodulation.

4.2.1 Control of firing rate and spike frequency adaptation

The spike threshold of a neuron is determined by the array of ionic conduc-tances that are active in the voltage range around the threshold. The spikethreshold is the voltage at which the inward sodium current activated by adepolarizing input is greater in magnitude than the outward currents active atthe same voltage. Once the inward current predominates, the neuron willdepolarize further, which opens up more voltage-dependent sodium channelsand initiates a positive feedback cycle that produces the large regenerativedepolarization of the action potential. As a consequence, any modulator thatregulates the magnitude of ionic conductances that are active in the voltagerange between the resting potential and the spike threshold will modify theamount of synaptic current needed to initiate firing, and this will have aprofound effect on neuronal excitability.

In every neuron type studied, several conductances that are active close tothe resting voltage interact to control neuronal excitability. In cortical andhippocampal pyramidal neurons, for example, excitability is influenced by anM-type potassium current and several calcium-dependent potassium currents(Madison and Nicoll 1982, 1984; Brown 1988; McCormick and Williamson1989). The M-current (so named because it is suppressed by muscarinicagonists) is a voltage-dependent potassium current that activates close to rest,and acts to slow firing by generating a hyperpolarizing current as the neuronis depolarized (Brown and Adams 1980). The firing rate in response to agiven synaptic current will therefore be a function of the amount of M-cur-rent expressed. In addition, many neurons will decrease their firing rate overtime when they are continuously depolarized. This property is known asspike frequency adaptation (SFA) or accommodation (Fig. 4.1 A, left). SFAcan be produced by a number of different mechanisms. One such mechanisminvolves the interaction between calcium influx during spiking and theactivation of a calcium-dependent potassium current which produces a hyper-polarizing current following the spike that slows or inhibits further spiking(Madison and Nicoll 1984; McCormick and Williamson 1989). Because this


Fig. 4.1 A. An intracellular recording from a hippocampal pyramidal neuron,showing the response of the neuron to a prolonged injection of depolarizing current.Under control conditions, the neuron shows strong SFA, and fires only at thebeginning of the current injection (left trace). When the neuromodulatornorepinephrine is applied, the SFA is strongly reduced. B. In the presence of TTX andTEA to block sodium currents and some potassium currents, these neurons firecalcium-dependent action potentials and show a large AHP due to the activation ofcalcium-dependent potassium currents. Norepinephrine strongly reduces the magnitudeof the AHP. Adapted with permission from Madison and Nicoll (1986).

current produces an after-hyperpolarization (AHP) following the spike (Fig.4.IB, left), it is known as IAHP. SFA acts as a temporal filter that allowsneurons to fire at the beginning of an input and then damps out the responseif the input persists. Networks of neurons that express strong SFA willtherefore transform a prolonged excitatory input into a more transient signal.This property could be important in helping to prevent runaway excitation innetworks with strong recurrent excitatory connections, such as cortex.

Both the M-current and IAHP are under neuromodulatory control (Marrion1997). In hippocampus and many regions of cortex, both of these currentsare reduced by cholinergic and noradrenergic agonists (Madison and Nicoll1982, 1984, 1986; McCormick and Williamson 1989) (Fig. 4.1B). Acetyl-choline (ACh) and norepinephrine (NE) therefore increase both the excitabil-ity of the neurons and their ability to fire repetitively in response to pro-longed inputs (Fig. 4.1 A). NE and ACh are released from fibres that projectdiffusely throughout hippocampus and cortex, and arise from nuclei in thebrainstem and forebrain. The increase in pyramidal neuron excitability pro-duced by these inputs is thought to contribute to state changes such as


Fig. 4.2 Neurons can fire tonically or in bursts depending on the magnitude of theionic conductances they express. A model neuron, showing the currents flowingduring either tonic firing or burst firing. In both states the model has both rapid andpersistent sodium curents (INa

and INapX a delayed-rectifier potassium current (IKd),a calcium current ( Ica) , and a calcium-dependent potassium current (fKCa)- A. Themodel fires tonically when the IKd and IKCa conductances are high and the ICa

conductance is low. B. The model fires in bursts when IKd and IKCa conductances arelow and 7Ca conductance is high. The conductance for INap is identical in both cases,but INap is more strongly activated during the burst, and provides some of the drivethat initiates the burst. The horizontal lines next to each current trace indicate zerocurrent for the current traces, and 0mV for the voltage traces. Adapted withpermission from Turrigiano et al. (1995).

transitions between sleep and wakefulness or inattention and attention (Nicollet al. 1990; Steriade and McCarley 1990).

4.2.2 Bursting and pacemaker potentials

Neurons in many invertebrate circuits and in many parts of the vertebratecentral nervous system have the property of firing action potentials in bursts,either when depolarized or during spontaneous rhythmic activity (Silva et al.1991; Huguenard and McCormick 1992; Grey and McCormick 1996; Marderand Calabrese 1996) (Fig. 4.2). These bursts are characterized by slow wavedepolarizations and hyperpolarizations that periodically bring the membranepotential of the neuron over the threshold for firing action potentials. Anumber of mechanisms for producing such bursts have been described and asingle neuron can utilize a different mix of conductances to produce bursting


under different modulatory conditions (Harris-Warrick and Flamm 1987). Acommon form of bursting arises through interactions between calcium cur-rents and calcium-dependent potassium currents (although a number of otherionic conductances also help to initiate and shape the burst) (Adams 1985).Activation of voltage-dependent calcium and slow sodium currents producesthe characteristic slow depolarizing phase of the burst, and when thesecurrents bring the neuron over the spike threshold, the neuron fires (Fig. 4.2).The repolarizing phase of the burst is due to a combination of factorsincluding inactivation of calcium currents and activation of calcium-dependent potassium currents. In some neurons, sodium currents contributeto the depolarizing phase of the burst (Fig. 4.2; Harris-Warrick and Flamm1987; Opdyke and Calabrese 1994; Turrigiano et al. 1995; Guatteo et al.1996), and in others activation of the hyperpolarization-activated inwardcurrent (Ih) helps to initiate the burst (Angstadt and Calabrese 1989;McCormick and Pape 1990; Huguenard and McCormick 1992; Kiehn andHarris-Warrick 1992). Variations on this burst mechanism underlie burstfiring in a diverse array of neurons, including the identified neuron R15 inAplysia (Adams 1985; Canavier et al. 1991), crustacean stomatogastricganglion neurons (Harris-Warrick and Flamm 1987; Turrigiano et al. 1995),and relay cells in the vertebrate thalamus (McCormick and Pape 1990;Huguenard and McCormick 1992). In other cell types, such as corticalchattering cells, the ionic mechanisms underlying bursting have not yet beendetermined (Gray and McCormick 1996).

The term 'bursting' or 'burst firing' has been used to describe a wide rangeof firing behavior which produces very different neuronal response proper-ties. For example, many invertebrate neurons produce bursting pacemakerpotentials that allow the neurons to fire in spontaneous bursts withoutrequiring any input (Marder and Calabrese 1996). In contrast, cortical'intrinsic bursting' neurons fire a single burst of action potentials upondepolarization and then fall silent (Chagnac-Amitai et al. 1990; Kasper et al.1994), whereas 'chattering' cells burst repeatedly during a prolonged depolar-ization but are silent at rest (Gray and McCormick 1996). Thalamic relayneurons fire tonically unless their membrane potential is hyperpolarized.Hyperpolarization simultaneously activates Ih, and removes inactivationfrom a low-threshold calcium current, thus allowing the burst generatingmechanism to be expressed (McCormick and Pape 1990; Huguenard andMcCormick 1992; McCormick and Bal 1994). In each neuron type, the arrayof conductances and the biophysical properties of these conductances areslightly different, thus producing a wide range of electrophysiological pheno-types. A common feature of bursting, however, is that the timing andfrequency of firing is regulated and shaped by the intrinsic properties of theneuron rather than the timing and frequency of synaptic inputs. While burstsmay be triggered or entrained by synaptic inputs, the resulting activity will berelatively stereotyped, with the shape of the burst, the number of actionpotentials, and the frequency of bursting controlled by the complex balanceof interacting intrinsic conductances.


An interesting observation that has emerged from computational work onthe expression of burst properties is that small changes in the magnitude ofinward and outward currents can move neurons back and forth betweenbursting and tonic firing states (Fig. 4.2A,B) (Rinzel and Yi 1987;Guckenheimer et al. 1993; Turrigiano et al. 1995). In order for the slowdepolarizing wave of a burst to be initiated, the net current flow must beinward over the voltage range of the depolarization. This means, for exam-ple, that inward calcium currents must be greater than the sum of outwardcurrents flowing at a given voltage; if the net calcium current is a shadesmaller than the net outward current, the neuron will not burst. If neuronsare sitting close to this bifurcation point, very small changes in the magnitudeof calcium or potassium currents can shift the net current from inward tooutward, or vice versa, thus producing transitions between tonic and burstfiring (Fig. 4.3). As we shall see below, this allows neuromodulators toinitiate bursting in some neurons by modifying the balance of inward andoutward currents.

4.2.3 Modulation of burst firing

Many neurons that can generate bursts of action potentials do so in aconditional manner; that is, they can be switched between bursting andnon-bursting states. This switching is produced by neuromodulators whichalter the properties of the ionic conductances underlying bursting. One of thefirst examples described in the literature is the modulation of the identifiedAplysia neuron R15 by the monoamine serotonin (5-HT) (Benson and Adams1987; Lotshaw and Levitan 1987; Levitan and Levitan 1988). Acting throughthe second messenger cAMP, 5-HT is able to induce burst firing in aquiescent R15, or enhance bursting in a weakly bursting neuron (Fig. 4.4).Voltage clamp studies have demonstrated that 5-HT produces these effects bytargeting both calcium and potassium conductances. This has the dual effectof enhancing the inward currents underlying the depolarizing phase of theburst, while simultaneously enhancing the potassium currents that generatethe interburst hyperpolarization. The increased interburst hyperpolarizationin turn helps to remove inactivation from the inward currents, and thuscontributes to the enhancement of the depolarizing phase of the burst. Thisillustrates the principle that modulatory substances often target a coordinatedarray of conductances that act synergistically to modify and shape neuronalresponse properties.

What function do such transitions serve? The role of R15 in behavior isnot well understood, but in several other systems it is clear that transitionsbetween tonic and burst firing states can have profound effects on behavioraloutput. In the vertebrate spinal networks that control locomotion, interneu-rons and motor neurons can be switched between bursting and non-burstingor plateau states by 5-HT and NMDA (Hounsgaard et al. 1988; Hounsgaardand Kiehn 1989; Grillner and Matsushima 1991). This correlates well withthe ability of these modulatory substances to initiate walking behavior in


Fig. 4.3 Model neuron with the conductances shown in Fig. 4.2. The effects ofvarying the inward conductances together (Y axis) and the outward conductancestogether ( X axis) is shown. In the white region (lower left) the neuron is largely silent.In the striped region the neuron fires tonically. In the hatched region the neuron firesin bursts. The transition between tonic firing and bursting behavior is sharp, andrequires only a small change in the total inward or total outward conductance if theneuron is in the correct region of the map. Reprinted with permission from Turrigianoetal. (1995).

spinal cats when perfused into the spinal cord (Pearson and Rosignol 1991).These studies suggest that modulator-induced transitions between quiescentor tonic states and burst firing can act to initiate or terminate locomotorbehavior in a variety of organisms (Pearson 1993) (see Chapter 8).

In the stomatogastric ganglion (STG) of decapod crustaceans, modulator-induced transitions between tonic and bursting states can initiate or modifythe motor programs for feeding by targeting neurons that participate in the


Fig. 4.4 Modulation of bursting in neuron R15. Under control conditions R15 firesin weak bursts. The application of serotonin increases the amplitude of the burst, thedepth of the interburst hyperpolarization, and the spike frequency within the burst.Adapted with permission from Levitan and Levitan (1988).

feeding-related central pattern generators (Harris-Warrick et al. 1992; Turri-giano and Heinzel 1992). The pacemaker neuron AB, for example, is aconditional buster and can be induced to burst by a variety of neuromodula-tors. In addition, modulators can produce a variety of other changes in thecellular and synaptic properties of CPG neurons to initiate a variety of uniquemotor programs (Fig. 4.5). Neuromodulation of intrinsic neuronal conduc-tances has emerged as a prominent model for how behavioral flexibility isgenerated in motor circuits (see Chapter 8).

Burst firing may play important roles not only in motor circuits, but also insensory perception and learning (Huerta and Lisman 1993, 1995; Singer andGrey 1995; Gray et al. 1997). For example, thalamic relay neurons in thelateral geniculate nucleus relay visual input from the retina to primary visualcortex, and can be switched between tonic and burst firing modes byneuromodulatory inputs from the brainstem (Steriade and McCarley 1990).Both ACh and NE depolarize these neurons by reducing a 'leak' potassiumcurrent (McCormick and Prince 1987; McCormick 1992). This depolariza-tion inactivates the low-threshold calcium current necessary for burst firing,and results in a transition from burst firing to tonic firing. The significance ofthis transition is still speculative, but one idea is that in tonic firing mode,these neurons faithfully encode the frequency of retinal inputs, whereas inbursting mode, the firing is stereotyped and no longer faithfully transmitssensory information (Fig. 4.6) (McCormick and Feeser 1990; Steriade et al.1993). In this view, brainstem neuromodulatory inputs perform a 'gating'function that regulates the flow of sensory information from the periphery tothe cortex (see Chapter 6).

Recently, it has been suggested that burst firing, rather than representing astate in which information is transferred poorly, may act to enhance informa-


Fig. 4.5 Modulation of the pyloric network of the stomatogastric ganglion by avariety of modulatory substances. Traces show intracellular recordings from twoidentified neurons, LP and PD, and an extracellular recording from the Ivn nervecontaining the axons of several pyloric neurons. Application of the muscarinic agonistpilocarpine, serotonin, dopamine, or the peptides proctolin, SDRNFLRFamide,TRNFLRFamide, or RPCH, sets up a unique pattern of activity. Each of thesesubstances has been shown to be present in the neuropil of the stomatogastricganglion. Each trace is 10s in length. The maximum amplitude of the LP bursts inpilocarpine is 40 mV. Adapted with permission from Marder and Weimann (1992).

tion transfer and synaptic plasticity under some conditions (Lisman 1997). Incentral circuits such as hippocampus and cortex where synapses have a lowprobability of transmitter release, single presynaptic spikes are unlikely toresult in transmitter release and are therefore unlikely to excite the postsy-naptic neuron. In contrast, a presynaptic burst of two or more closely spacedspikes will lead to a build-up of presynaptic calcium and enhanced release onthe second spike, producing a reliable postsynaptic response. Under thesecircumstances burst firing could provide a means of picking out weak signalsfrom a noisy background. In the hippocampus, synchronized bursting can beinitiated by cholinergic modulation and enhances synaptic plasticity, suggest-ing that it may play an important role in hippocampal function (Fig. 4.7)(Huerta and Lisman 1993, 1995).

4.3 Presynaptic modulation of synaptic transmission

The role a neuron plays in the circuit in which it is embedded is a function ofboth its intrinsic firing properties and the properties of its synaptic inputs.


Fig. 4.6 Thalamic relay neurons in burst firing or tonic firing mode have differentabilities to follow high frequency stimuli. A. When in burst firing mode, the neuroncould not follow inputs at frequencies greater than 6 Hz; by 10 Hz, the neuron failedto respond after the first several stimuli. B. When depolarized, the neuron firedtonically rather than in bursts, and faithfully followed the stimuli at much fasterfrequencies. Adapted with permission from McCormick and Feeser (1990).

Neuromodulators can target not only the membrane conductances that shapeneuronal firing properties, but also ionic conductances expressed in thepresynaptic terminal. These conductances influence the degree of calciuminflux when a spike invades the terminal, and thus the amount and probabil-ity of transmitter release. This can modify the degree of excitation orinhibition received by the postsynaptic neuron, and can also have a profoundimpact on the dynamics of synaptic transmission.

4.3.1 Presynaptic facilitation of transmitter release

When a spike invades a synaptic terminal, the depolarization produced bysodium influx opens high-threshold calcium channels, leading to calciuminflux and fusion of synaptic vesicles. By targeting receptors expressed on thepresynaptic terminal, neuromodulators can selectively modify the propertiesof potassium or calcium conductances expressed in the terminal to raise orlower the calcium concentration during a spike. A classic example of this isserotonergic modulation of sensory neuron to motor neuron terminals in the


Fig. 4.7 Cholinergic agonist-induced theta oscillations in the hippocampus enhanceLTP. A. In the presence of the cholinergic agonist carbachol, theta-frequencyoscillations are produced by a hippocampal slice, and can be recorded extracellularlyas slow oscillations in the field potential (lower trace). When a brief train of stimuli isgiven at the peak of a theta oscillation, it is sufficient to induce LTP. The expandedregion indicated by the dashed lines shows the response to four stimuli delivered at100 Hz; the asterisks mark the stimulation artefact. B. A plot of EPSP slope vs. timefollowing the stimulus shown in A. The grey bar indicates the time of carbacholapplication. Carbachol reduced the amplitude of the EPSP via presynaptic modulation.For the stimulated pathway (Test), the stimulus, applied at the peak of the thetaoscillation (Pk), produced a long-lasting enhancement of the EPSP slope, a commonmeasure of LTP. In a control pathway there is no long-lasting change in EPSP slope(Control). The inset shows extracellularly recorded potentials at the time pointsindicated on the graph (a,b,c,d). In the absence of cholinergic modulation the samestimulus is not sufficient to produce LTP (not shown). Adapted with permission fromHuerta and Lisman (1995).

Aplysia gill and siphon-withdrawal reflex (Byrne and Kandel 1996). Thisreflex can be sensitized by an aversive stimulus applied to the tail, and thissensitization can be mimicked by application of 5-HT to the sensory to motorneuron terminals. 5-HT enhances both presynaptic excitability and release oftransmitter from the sensory neuron terminals, thus increasing the probabilitythat a stimulus to the siphon will fire the motor neuron and produce siphon


withdrawal (Castellucci and Kandel 1976; Klein et al. 1986). There areinterneurons in Aplysia that contain 5-HT, as well as several other modula-tory substances, and are activated by sensitizing stimuli. The model that hasemerged for sensitization is therefore that activation of these interneuronsreleases a modulator or modulators, which then enhance presynaptic releaseof transmitter.

5-HT has a number of effects on sensory neuron terminals that contributeto increased release of transmitter (see Chapter 6). One effect of 5-HT is toincrease cAMP in the presynaptic terminal, which activates protein kinase A(PKA). 5-HT also activates protein kinase C (PKC), and the relative contribu-tion of these two kinases depends on the state of the presynaptic terminal(Byrne and Kandel 1996). These kinases in turn phosphorylate several potas-sium channels, including one that contributes to spike repolarization and onethat helps to control neuronal excitability (Baxter and Byrne 1989). Byreducing these potassium conductances the threshold for spike initiation islowered, and in addition each spike is prolonged in duration. This prolonga-tion leads to an increase in calcium influx into the terminal following thespike. Each spike therefore releases more transmitter, and the synapse isfacilitated. In addition to spike broadening, 5-HT also facilitates releasethrough a spike-broadening-independent mechanism that is not well under-stood, but may involve direct modulation of the release machinery (Byrneand Kandel 1996). The facilitation resulting from 5-HT release can last formany minutes, presumably until endogenous phosphatases return the ionchannels in the terminal to their original state.

Presynaptic facilitation of transmitter release has now been described in anumber of systems. In the marine mollusc Tritonia, for example, interneu-rons intrinsic to the central pattern generator (CPG) for swimming release5-HT onto the terminals of the identified neuron C2, a member of the CPG.This enhances the strength of the connection from C2 onto its targets.Strengthening this connection is instrumental in switching this network froma state in which it produces a simple withdrawal reflex into a state in which itproduces a coordinated swim motor program (Katz and Frost 1995). In thevertebrate CNS, ACh enhances transmitter release through presynaptic nico-tinic receptors at both excitatory and inhibitory synapses (McGehee et al.1995; Lena and Changeux 1997), and dopamine (DA) can enhance transmis-sion at central inhibitory synapses through Dl receptors (Cameron andWilliams 1993).

4.3.2 Presynaptic depression of transmitter release

Most examples of presynaptic modulation of excitatory synaptic transmissionin the vertebrate CNS involve depression of synaptic transmission (Fig. 4.8).ACh, NE, 5-HT, DA, adenosine, and agonists of metabotropic glutamatereceptors and GABAB receptors have all been reported to reduce transmis-sion at excitatory cortical and/or hippocampal synapses (Valentino and


Fig. 4.8 Dopamine (DA) decreases excitatory synaptic transmission in thehippocampus. An intracellular recording from a hippocampal pyramidal neuronbefore (A) and after application of several different doses of DA (B-E). The size of theEPSP produced by stimulation of the Schaffer collaterals is decreased by dopamine,while the input resistance of the neuron (as measured with intracellular currentinjection) does not change. F. The effects of DA are reversible. G. Overlay of A-E.Reprinted with permission from Hsu (1996).

Dingledine 1981; Prince and Stevens 1992; Burke and Hablitz 1994; Rhoadeset al. 1994; Hsu 1996; Isaacson and Hille 1997). Some of these modulatorsact as negative feedback signals that reduce excitatory transmission whenactivity rises. For example, it is thought that high levels of synaptic transmis-sion in the central nervous system produce a build-up of adenosine in thesynaptic cleft, which then activates presynaptic adenosine receptors on excita-tory axon terminals to reduce transmitter release (Thompson et al. 1992;Manzoni et al. 1994). Interestingly, inhibitory synaptic transmission is unaf-fected by adenosine (Lambert and Teyler 1991; Thompson et al. 1992). Thisselective reduction in excitatory transmission may help to control excitabilityin the positive feedback circuits arising from pyramidal-to-pyramidal neuronexcitatory connections in cortex and hippocampus.

4.3.3 Presynaptic modulation by neurotrophins

Although most presynaptic modulators in the vertebrate CNS depress synap-tic transmission, a new class of neuromodulators has recently been describedthat acts to enhance synaptic transmission at excitatory central and periph-eral synapses, and in many cases these effects are predominantly presynaptic.These are the neurotrophins. Neurotrophic factors, including nerve growthfactor (NGF), neurotrophic factor 3 (NT-3), and brain-derived neurotrophicfactor (BDNF), are a family of peptide factors that promote survival anddifferentiation in a variety of neural tissues. Recently, a new role for thesefactors in the acute modulation of synaptic transmission has been identified.For example, at the Xenopus neuromuscular junction both BDNF and NT-3potentiate evoked and spontaneous release from presynaptic terminals (Fig.4.9) (Lohoff et al. 1993; Stoop and Poo 1996), and NGF acts presynaptically


Fig. 4.9 BDNF increases the frequency of spontaneous synaptic currents and theamplitude of evoked synaptic currents at the Xenopus neuromuscular junction inculture. A. Synaptic currents were evoked by stimulating the motor neuron at 0.05 Hz.BDNF application increased the amplitude of the evoked events. B. Continuousrecord of spontaneous events recorded in the same preparation. The arrow marks thetime of addition of BDNF to the culture medium. BDNF increased the frequency ofthe spontaneous events without changing their quantal amplitudes (inset). Reprintedwith permission from Stoop and Poo (1996).

to increase the strength of sympathetic synaptic transmission (Lockhart et al.1997). The effects of neurotrophins in neocortex and hippocampus are morecomplex and probably involve changes in both excitation and inhibition, butin most cases the net effect is to potentiate excitatory transmission (Kim et al.1994; Kang and Schuman 1995; Akaneya et al. 1997; Tanaka et al. 1997).Some of these central effects are likely to be presynaptic (Kang and Schuman1995), whereas in some cases there is evidence for a postsynaptic site ofaction (Levine et al. 1995; Tanaka et al. 1997).

The functional role of this modulation is still controversial. BDNF may beimportant for the normal expression of synaptic plasticity at both hippocam-pal and cortical synapses, although the exact role played by BDNF remainsunclear (Kang and Schuman 1995; Korte et al. 1995, 1996, Figurov et al.1996; Tanaka et al. 1997). Neurotrophins are generally thought of astarget-derived factors, released by postsynaptic targets and taken up by oracting on presynaptic terminals, but the sources of neurotrophins, the condi-tions under which they are released, and the location of activated receptorsare still unclear in most central circuits. An interesting possibility is that


neurotrophins are released locally by the postsynaptic neuron in response tosynaptic inputs. If they act in this way, neurotrophins could provide amechanism for selectively potentiating active connections. This could beimportant during development in determining which connections are main-tained and which are lost.

4.3.4 Coordinate regulation of presynaptic andpostsynaptic properties

Many neuromodulators target both postsynaptic receptors and presynapticreceptors located on synaptic terminals. For example, both ACh and NE havepresynaptic and postsynaptic effects in cortical circuits. These modulatorsreduce excitatory synaptic transmission by acting presynaptically to reducetransmitter release from pyramidal neuron terminals (Valentino andDingledine 1981; Hasselmo et al. 1997). At first glance this would seem to beat odds with the postsynaptic effects of these modulators, which are toincrease the excitability of pyramidal neurons by reducing M-current andIAHP as described above (Madison and Nicoll 1982, 1984, 1986; McCormickand Williamson 1989). These modulators are simultaneously increasing firingrates and the ability to fire repetitively, while decreasing the amount ofexcitatory input received by each neuron.

A possible functional role for these combined effects becomes apparent ifone considers the short-term dynamics of synaptic transmission. A prominentfeature of cortical synapses is synaptic depression, a form of short-termplasticity that operates over several time-scales from milliseconds to seconds(Tsodyks and Markram 1997; Varela et al. 1997). Synaptic depression ischaracterized by a progressive decrease in the amplitude of successive synap-tic potentials during repetitive spiking, and is thought to result from deple-tion of a pool of readily releasable vesicles in the synaptic terminal (Fig. 4.10,control). Like SFA, synaptic depression acts to enhance transient signals anddamp out the response to prolonged or high-frequency inputs (Abbott et al.1997). These considerations suggest that SFA and short-term synapticplasticity should be closely matched. In circuits with pronounced synapticdepression, SFA may actually enhance excitatory transmission by preventingneurons from firing in a regime where synapses will be strongly depressed. Inaddition, these two properties will act synergistically to selectively transmittransient or novel stimuli.

Neuromodulators can increase or decrease the amount of synaptic depres-sion by modulating transmitter release (Tsodyks and Markram 1997; Varelaet al. 1997). Increased release will enhance depression by depleting vesiclesmore quickly, whereas decreased release will decrease depression by slowingthis depletion down (del Castillo and Katz 1954). Thus, in lamprey reticu-lospinal neurons 5-HT depresses synaptic transmission and reduces vesicledepletion (Shupliakov et al. 1995).


Fig. 4.10 Modulation of short-term plasticity by adenosine. Control: whole-cellrecording from a pyramidal neuron from a rat visual cortical slice. Each conditionrepresents the average of eight trials. Under control conditions, the excitatory inputsto this neuron (activated with extracellular stimulation) depress in amplitude during atrain of stimuli. When the same train was delivered in the presence of adenosine, theamplitude of the first response was reduced, and there was a net facilitation of theresponse during the train. Unpublished data courtesy of Juan Varela and SachaNelson.

Similarly, when cortical synaptic transmission is depressed by adenosine,these synapses shift from exhibiting a net depression of transmission during atrain of stimuli to exhibiting a net facilitation (Fig. 4.10, adenosine). Byreducing transmitter release from cortical pyramidal neurons, ACh and NEmay therefore decrease synaptic depression, and thus paradoxically increasethe ability of synaptic inputs to follow prolonged or high-frequency signals.The effect of these modulators on release will therefore be synergistic withthe effects on neuronal excitability. Together, modulation of both release andfiring properties will move these neurons between states where they areselective for either prolonged and high-frequency, or transient and low-frequency, signals. Coordinate regulation of pre- and postsynaptic conduc-tances is likely to emerge as an important principle of circuit regulation.

138 Cel lular responses to neuromodulatory signals

4.4 Modulation of dendritic conductances

4.4.1 Dendritic conductances and synaptic integration

While invertebrate neurons have long been known to express active conduc-tances in their neurites, neurons in the vertebrate CNS were, until recently,thought to have purely passive dendrites. This view has changed dramaticallywith the demonstration that many CNS neurons, including cerebellarPurkinje neurons and hippocampal and cortical pyramidal neurons, havevoltage-dependent sodium, calcium, and potassium conductancesexpressed in their dendritic trees (Llinas and Hess 1976, Ross and Werman1987; Jaffe et al. 1992; Magee and Johnston 1995; Schiller et al. 1995;Hoffman et al. 1997). These conductances may influence dendritic integra-tion of synaptic inputs in important ways (Miller et al. 1985; Nicoll et al.1993, Stuart and Sakmann 1995). For example, excitatory synaptic inputswill sum non-linearly if they depolarize the dendrite sufficiently to activatevoltage-dependent conductances. Counter-intuitively, inhibitory inputs couldactually produce a transient increase in dendritic excitability if they removeinactivation from low-voltage activated calcium currents (Magee and John-ston 1995).

4.4.2 Dendritic conductances and synaptic plasticity

As well as influencing synaptic integration, dendritic conductances contributeto some forms of Hebbian synaptic plasticity. Sodium current expressed inthe dendrites can support action potentials if they are initiated in the soma,leading to 'backpropagation' of action potentials from the soma to thedendrites (Fig. 4.11) (Stuart and Sakmann 1994; Stuart et al. 1997). Whenbackpropagating action potentials are temporally associated with incomingsynaptic potentials, these synapses are selectively modified. One of the mostinteresting aspects of this plasticity is that the direction of modificationdepends on the temporal relationship between spike and postsynaptic poten-tial (Fig. 4.12). PSPs that precede the spike by 10ms (and thus were likely tohave contributed to firing the postsynaptic cell) are enhanced, whereas PSPsthat follow the spike by 10ms (and therefore did not contribute to firing thecell) are depressed (Markram et al. 1997). Backpropagating spikes maytherefore provide a global dendritic signal that allows each synaptic strengthto be modified depending on its efficacy at firing the neuron.

The net effect this plasticity will have on the strength of a synapse dependscritically on the function relating spike timing to synapse strength. Thisfunction has not yet been determined, and may vary significantly at differentsynapses (Bell et al. 1997). In particular, at high firing rates, PSPs will besimultaneously following and preceding postsynaptic spikes within the timewindow for modification, and so it is unclear what the net effect on PSPamplitude will be. In addition, there is evidence that inhibitory inputs can


Fig. 4.11 Action potentials recorded in the soma, apical dendrite, and axon of acortical pyramidal neuron. The structure of the neuron, showing the axon (bottom)the soma (middle) apical dendrite (top), and three recording sites (axon, soma, andapical dendrite). Action potentials elicited in the soma propagate back into the apicaldendrite, where they are slower and more attenuated than in the soma or the axon.Reprinted with permission from Stuart et al. (1997).

shunt backpropagating action potentials and prevent them from invading thedendrites, suggesting that when neurons are receiving a high degree ofinhibition, as they do in vivo, this form of plasticity will not be active(Tsubokawa and Ross 1996; Svoboda et al. 1997). An interesting possibilityis that this form of plasticity is 'gated' by inhibition. This would have theeffect of selectively modifying excitatory inputs that are active withoutsignificant simultaneous inhibition. The question of whether inhibitorysynaptic strengths are also modulated by backpropagating action potentials isstill open.

4.4.3 Modulation of dendritic excitability

Backpropagating spikes may also be gated by neuromodulators. For example,recent data suggest that the ability of action potentials to backpropagate intothe dendrites can be modulated by ACh (Fig. 4.13). Without cholinergicinput, all spikes after the first or second in a train are strongly attenuated inthe dendrites, suggesting that at high firing rates spikes will not effectivelydepolarize the dendrites. In the presence of ACh, however, this attenuation isreduced, and the ability of spikes to backpropagate at high frequencies isgreatly enhanced (Tsubokawa and Ross 1997). This suggests that cholinergicinputs, and possibly other modulatory inputs as well, may enhance plasticity


Fig. 4.12 Coincidence between backpropagating action potentials and synapticpotentials modifies synaptic efficacy. Recordings from two reciprocally connectedlayer 5 pyramidal neurons from a rat cortical slice. A. The postsynaptic neuron wasfired either before (—10ms) or after (+10ms) an EPSP was elicited by firing thepresynaptic neuron. B. The effects of this pairing on the amplitude of the synapticconnections between the two neurons. Pairs were elicited every 100ms beginning atthe arrow, and the amplitudes of the EPSPs were plotted over time. Repeatedly firingthe postsynaptic neuron +10ms after the presynaptic neuron (n) resulted in anenhancement of the synaptic connection, whereas repeatedly firing the postsynapticneuron 10ms before the EPSP (•) resulted in a decrease in the strength of theconnection. Firing the postsynaptic neuron either 100ms before (•) or 100ms after(O) the EPSP evoked by the presynaptic neuron has no affect on synaptic efficacy.Adapted with permission from Markram et al. (1997).

that depends upon backpropagating spikes. If ACh enhances backpropaga-tion by enhancing dendritic excitability, it may also influence dendriticintegration of synaptic inputs.

4.5 Short-term and long-term effects of neuromodulators

A number of neuromodulatory substances have been shown to have bothacute effects, generally due to phosphorylation of ion channels, and long-termeffects that are the result of changes in gene expression and protein synthesis.In some cases the long-term effects are stable extensions of the short-termeffects, whereas in other cases the acute and prolonged effects of neuromodu-lators can be quite different. Rather than operating over a single discrete timeframe, there is a continuum of time courses in modulatory signaling, and the


Fig. 4.13 The effects of the muscarinic agonist carbachol (CCh) on backpropagationof action potentials. A. A recording 300 /am up the apical dendrite in a CA1hippocampal pyramidal neuron. Synaptic potentials were elicited with trains ofextracellular stimulation. The first three potentials in a train are shown; the synapticpotential often elicited an action potential that could be recorded in the dendrites. Thesecond stimulus was more likely to elicit an action potential than the first, due tofacilitation. The third stimulus elicited an action potential that was much attenuatedrelative to the first or second in the train. B. CCh decreases the attenuation ofdendritic action potential amplitude during a train of stimuli, and this effect isblocked by atropine. Reprinted with permission from Tsubokawa and Ross (1997).

effects of a neuromodulator may depend critically on the length of exposureto the modulatory substance.

4.5.1 Heterosynaptic facilitation in Aplysia

One of the first examples of both long-term and short-term effects of a


neuromodulator on the same target was heterosynaptic facilitation in Aplysia.Whereas a single facilitating stimulus produces short-term facilitation of thesensory to motor-neuron connection (as described above), several successivestimuli can produce facilitation lasting 1-2 days (Mauelshagen et al. 1996).Like short-term facilitation, long-term facilitation operates through activationof PKA and PKC. Unlike short-term facilitation, however, long-term facilita-tion requires protein synthesis for its expression, and is accompanied bychanges in neurite outgrowth, the number of synaptic contacts between thetwo neurons, and changes in the postsynaptic expression of receptors(Schacher et al. 1990; Trudeau and Castellucci 1995; Byrne and Kandel1996). Thus, repetitive activation of the same second messenger machinerycan result in long-term, stable changes in synaptic function, that are similar tothe acute effects of the modulator.

How the transition from short-term to long-term facilitation occurs is notcompletely understood, but recent evidence suggests that the two processesare independent, as long-term facilitation can occur in the absence of short-term facilitation (Emptage and Carew 1993). An interesting aspect of long-term facilitation is that stimuli that are spaced far apart in time (termed'spaced training') are much more efficacious at inducing long-term facilitationthan are stimuli that occur close together. This suggests that there are longtime-constant events triggered by the second messenger cascades involved infacilitation that determine the optimal duration for producing synergy be-tween stimuli (Tully et al. 1994). The phenomenon of spaced training hasnow been observed in a variety of organisms, and appears to be a generalproperty of long-term memory formation. This may be important in allowingthe nervous system to prevent the induction of long-term facilitation byrandom events that are not a predictable and repeatable part of theenvironment.

4.5.2 Acute and long-term effects of neurotrophins

Neurotrophins were first described as trophic agents that supported neuronalsurvival. These trophic effects are mediated through complex intracellularkinase cascades that ultimately influence gene expression, which in turnregulates growth, survival, and differentiation (Fig. 4.14). Recently, it hasbecome clear that in addition to their long-term effects, neurotrophins have avariety of acute modulatory effects on synaptic transmission. In cortex, forexample, the neurotrophin BDNF has been shown to acutely potentiatecortical activity (Carmignoto et al. 1997), in addition to its long-term effectson outgrowth (McAllister et al. 1995), survival (Ghosh et al. 1994), and thelong-term regulation of synaptic strengths (Rutherford et al. 1997, 1998).

BDNF is produced in an activity-dependent manner in cortex, and isthought to be involved in several developmental processes, including thesegregation of thalamic inputs into ocular dominance columns (Cabelli et al.1995, 1997). However, it is not yet clear where BDNF is acting to influence


Fig. 4.14 Neurotrophins regulate dendritic outgrowth in ferret visual cortical slicecultures. Basal dendrites of layer 4 neurons. The indicated neurotrophins were appliedfor 36 h. NT-3 had little effect, while BDNF and NT-4 increased the elaboration ofbasal dendritic arbors. Reprinted with permission from McAllister et al. (1995).

ocular dominance column segregation, nor have the relative contributions ofacute and long-term modulation been determined. Whereas acute exposure toBDNF acts to enhance activity in in vitro cortical circuits, long-term expo-sure decreases cortical excitability by regulating the relative strengths ofexcitatory and inhibitory intracortical synapses (Rutherford et al. 1997,1998). Both the acute and the long-term effects of BDNF on cortical activitycould have profound effects on cortical development.

4.6 Activity-dependent regulation of membrane andsynaptic conductances

As we have seen, intrinsic neuronal conductances influence a number ofimportant properties of neurons and neural circuits, including patterning ofspikes, temporal response properties, and synaptic integration and plasticity.In addition, we have seen that small changes in the relative magnitudes ofionic conductances can dramatically change these properties. This sensitivityprovides tremendous flexibility to the nervous system, but also raises severalproblems. During the lifetime of a neuron, for example, its input resistancewill change, the channels in its membrane will turn over thousands of times,and the branching structure of its dendritic tree may increase or decrease incomplexity, and yet the neuron can retain the same function and even


maintain similar firing properties despite these constant fluctuations in itsproperties. Recent work suggests that neurons accomplish this by using theirongoing activity to self-regulate the balance of ionic conductances theyexpress (LeMasson et al. 1993; Turrigiano et al. 1994, 1995, 1998; Seigal etal. 1994). This regulation operates on both intrinsic and synaptic conduc-tances, and has a number of important consequences for circuit function. Aswell as allowing neurons to maintain stability in intrinsic firing properties,these regulatory processes may be very important in ensuring that the effectsof modulating particular conductances are consistent over time.

4.6.1 Homeostatic regulation of intrinsic conductances by ongoingelectrical activity

How do neurons maintain stable intrinsic firing properties? Theoretical andexperimental work has shown that this problem can be solved with a simplehomeostatic mechanism that links the expression of conductances to theongoing electrical activity of the neuron (LeMasson et al. 1993; Turrigianoet al. 1994; Liu et al. 1998). The model that has emerged is that the balanceof inward and outward conductances is regulated by the intracellular calciumconcentration, which is well correlated with activity. For example, when thefiring rate of the neuron is low, the intracellular calcium concentration is alsolow, and conductances are regulated so as to increase firing and raise thecalcium concentration. Conversely, when activity is high, intracellular cal-cium is high, and conductances are regulated so as to decrease activity.

These ideas were first tested using neurons from the crustacean stomato-gastric ganglion (STG). As described above, STG neurons normally fire inbursts as a consequence of both intrinsic conductances and synaptic andmodulatory inputs from other neurons. When acutely isolated from thesesynaptic and modulatory influences, the majority of STG neurons fire toni-cally rather than in bursts (Fig. 4.15A). Interestingly, when chronicallyisolated from their normal inputs for several days, STG neurons change theirintrinsic firing properties from tonic firing to burst firing (Turrigiano et al.1994, 1995), due to a coordinated increase in inward current densities anddecrease in outward current densities (Turrigiano et al. 1995) (Fig. 4.15B).Rhythmic drive that approximates the normal pattern of synaptic inputsreverses this transition through a mechanism mediated by a rise in intracellu-lar calcium (Fig. 4.16) (Turrigiano et al. 1994). This suggests that the normalrhythmic drive these neurons receive suppresses intrinsic bursting by raisingintracellular calcium, which modifies the balance of ionic conductances.These studies show that a neuron's level of activity can profoundly alter itsintrinsic electrical properties, and that these properties are in part a functionof its recent history of synaptic input.

Cortical pyramidal neurons show a similar, though less dramatic, form ofactivity-dependent regulation of conductances. When deprived of all activityfor two days, these neurons undergo a shift in the slope of the curve relating


Fig. 4.15 Activity regulates the intrinsic properties of stomatogastric ganglionneurons. A. In situ these neurons fire in bursts due to synaptic and modulatory drive,and fire tonically when pharmacologically isolated from these inputs. B. Whenchronically isolated in culture, their intrinsic firing properties are gradually transformedover several days until they acquire the ability to burst endogenously in response totonic depolarizing current injection. Adapted with permission from Turrigiano et al.1994.

firing rate (F) to current injection (I) (the FI curve). Activity deprivationshifts the FI curve so that neurons produce more spikes for a given level ofcurrent injection, indicating that the intrinsic excitability of the neurons hasincreased. As with STG neurons, this shift is produced by a coordinatedchange in both inward and outward conductances (Desai et al. 1997).

The studies described above suggest that activity-dependent regulation ofintrinsic conductances has several important consequences for the function ofneural circuits. The first is that it allows neurons to maintain relatively stableactivity patterns despite changes in growth or ion channel turnover. Theseprocesses will influence the current densities generated by individual ionicconductances, making it difficult to correctly adjust the balance of inwardand outward currents by simply specifying the synthesis and insertion of agiven ratio of channels. By actively adjusting the ratio of conductances tomaintain particular activity patterns, neurons avoid this problem.

This mechanism also allows neurons to compensate for changes in synaptic


Fig. 4.16 Artificially manipulating the activity of cultured stomatogastric ganglionneurons can transform their intrinsic firing properties. Rhythmic stimulation thatapproximates the synaptic drive these neurons receive in situ reverses the transitionfrom tonic firing to burst firing in chronically isolated neurons. Neurons were drivenintracellularly by giving rhythmic hyperpolarizing current pulses that elicited calcium-dependent rebound bursts (inset). After 1 h of this drive, the intrinsic properties of theneuron transformed from burst firing (control) to tonic firing (stimulation). This effectreverses after 1 h without stimulation (reversal). Adapted with permission fromTurrigiano et al. (1994).

drive, such as those due to changes in the number and strength of synapticinputs. For example, if synaptic drive were to increase and raise the averagefiring rate of the neuron for a prolonged period of time (perhaps hours ordays), the neuron would respond by increasing potassium conductances anddecreasing inward conductances, thus lowering its intrinsic excitability. Con-versely, if synaptic drive were to decrease, then intrinsic excitability would beincreased. This provides a mechanism that acts to stabilize firing rates in ahomeostatic manner, and acts in concert with changes in synaptic strength aswe shall see below. While there may be flexibility in the time-scale over whichthis process operates, it is important that the neuron measure activity over atime scale that is long relative to the transient changes in activity related torapid signaling.

Another important consequence of activity-dependent regulation of mem-brane conductances is that the intrinsic firing properties maintained byneurons will depend on the temporal (and perhaps spatial) patterns ofsynaptic input they receive (Fig. 4.17). The same total amount of synapticcurrent will have different effects on intrinsic excitability depending onwhether it is patterned in a way that results in high intracellular calcium orlow intracellular calcium. This will in turn depend on the intrinsic firingproperties of a particular neuron. For example, STG neurons in culture firecalcium-dependent bursts upon release from inhibition, whereas tonic depo-larization tends to inactivate the burst mechanism by inactivating calcium


Fig. 4.17 A model neuron in which the balance of inward and outward conductancesis regulated by activity. The same total amount of current delivered to this neuron hasvery different effects on intrinsic properties depending on how the input is patterned.A. Medium-duration, medium-frequency stimulation (bars) results in a silent neuron.B. Short-duration, high-frequency input results in a tonically firing neuron. C. Long-duration, low-frequency input results in a neuron that fires spontaneously in doublets.Adapted with permission from LeMasson et al. (1993).

currents. Rhythmic inhibition (the pattern of activity they receive in vivo) isthus the most efficacious stimulus for decreasing intrinsic excitability in theseneurons.

As well as depending on the temporal pattern of synaptic input, activity-dependent regulation of intrinsic conductances may also depend on thespatial pattern of inputs to a neuron (Seigal et al. 1994). To date experimen-tal studies have looked exclusively at the effects of global changes in activity,and have not addressed the question of whether regulation of intrinsicconductances also occurs locally in particular regions of the neuron. An


interesting possibility is that local dendritic calcium influx following synapticactivation can modify not just synaptic strengths, as has been extensivelydocumented, but also the local balance of conductances that control theexcitability of a small region of dendrite. This in turn could have importantconsequences for synaptic integration and plasticity (see Chapter 5).

A final consideration is that the effect that modulating a conductance hason neuronal firing properties will depend on the background of otherconductances the neuron expresses. For example, increasing calcium currentsby 10 per cent can either have very little discernible effect on a neuron, or cancompletely change the mode of firing from tonic firing to burst firing,depending on the magnitudes and characteristics of the potassium currentsthat oppose the burst. One role of the homeostatic regulation of intrinsicconductances may be to keep ionic conductances balanced so that modula-tory signals have the appropriate effects on neuronal firing properties.

4.6.2 Global regulation of synaptic strengths by neuronal firing rates

As has been stressed in this chapter and in other chapters in this book, theproperties of a circuit arise from a complex interaction between intrinsicfiring properties and the properties of synaptic connections. What role doesongoing activity play in regulating the properties of synapses? A tremendousamount of effort has gone into characterizing the selective potentiation ordepression of individual synapses as a function of correlated presynaptic andpostsynaptic activity, but until recently very little attention had been paid tocharacterizing the role of activity in globally regulating the total strength of aneuron's synapses. Nonetheless, there are powerful computational reasons tosuppose that such global regulation should occur, and recent experimentalwork suggests that synaptic strengths, like intrinsic conductances, are regu-lated in a homeostatic manner by ongoing electrical activity.

While correlation-based learning rules like long-term potentiation (LTP)and long-term depression (LTD) imbue circuits with tremendous computa-tional power, they also raise several problems for the functioning of thenervous system. Artificial networks that employ Hebbian correlation-basedlearning rules are inherently unstable, because they lead to runaway potentia-tion between even weakly correlated inputs (Bienenstock et al. 1982; Millerand MacKay 1993; Miller 1996). When the synaptic strength between twoneurons is potentiated, the presynaptic cell will drive the postsynaptic cellmore strongly, leading to higher postsynaptic firing. This in turn willincrease the correlation between pre- and postsynaptic firing and thus willlead to additional potentiation. This positive feedback means that the synapsewill grow in strength until it reaches its limit. In addition, inputs that werepreviously uncorrelated with the postsynaptic neuron will become correlated,due to the increased postsynaptic firing rates. Without some additionallearning rules to prevent this from occurring, every synapse in the networkwill eventually saturate. During development there are additional problems in


implementing Hebbian learning rules, because the number of synaptic inputsbetween neurons are increasing dramatically, thus strongly influencing thetotal amount of synaptic excitation each neuron receives. One importantlesson that has emerged from these theoretical considerations is that mecha-nisms that contribute to stability in firing rates and prevent runaway potenti-ation are as essential for information storage and activity-dependent develop-ment as correlation-based synaptic modifications (Bienenstock et al. 1982;Miller 1996).

A number of mechanisms have been proposed that could stabilize neuronalfiring rates in the face of developmental or activity-dependent synapticstrengthening. First, associative or heterosynaptic LTD, where active inputssuppress less active or uncorrelated inputs, has been suggested as a mecha-nism that could balance long-term potentiation (Stent 1973; Linden andConnor 1995). There is growing evidence that the same synapses that canundergo LTP can also undergo LTD (Derrick and Martinez 1996; Heynen etal. 1996; Scanziani et al. 1996). While LTD is likely to be an importantmechanism that allows synaptic weakening to contribute to the activity-dependent sculpting of neural circuit connectivity, loss of excitation throughLTD would have to exactly balance gain of excitation through LTP toprevent either saturation or silencing of postsynaptic firing rates. There is noevidence to date for such a careful and coordinated balancing of synapticstrengths through LTP and LTD. Another proposal is that neurons may havea sliding plasticity threshold that depends on postsynaptic firing rate (Bienen-stock et al. 1982; Bear 1995). This idea is supported by recent evidence thatthe threshold for LTP induction may depend on recent activity (Bear 1995;Kirkwood et al. 1996) and is discussed further in the next chapter.

Another way to achieve stability in synaptic strengths that does not dependon carefully balancing the strength of each synapse is to directly regulatepostsynaptic firing rates to maintain them within certain boundaries. Inprinciple, there are several ways to achieve this. First, as described above,activity could regulate the intrinsic conductances of neurons to modify firingproperties (LeMasson et al. 1993).

An additional mechanism is to use firing rates as a feedback signal toglobally increase or decrease the strength of a neuron's synaptic inputs.Recent work suggests that just such a process occurs in cortical pyramidalneurons. The strength of AMPA-mediated excitatory synaptic connectionsbetween pyramidal neurons can be globally scaled up or down as a functionof postsynaptic firing rate: increasing neuronal firing rates decreases thestrength of these excitatory connections, whereas decreasing firing ratesincreases synaptic strengths (Fig. 4.18). This occurs though the scaling of allof a neuron's synaptic strengths by the same multiplicative factor. Thismultiplicative scaling allows the total synaptic strength of a neuron to bemodulated up or down, while preserving the relative differences in strengthbetween individual inputs (Turrigiano et al. 1998).

This homeostatic regulation helps to stabilize neuronal firing rates. In


Fig. 4.18 Activity regulates the quantal amplitude of AMPA-mediated excitatorysynaptic currents in visual cortical pyramidal neurons. A. To record AMPA quantalamplitudes, whole-cell voltage clamp recordings were obtained whilepharmacologically blocking spike-mediated transmission and other synaptic currents.Under these conditions miniature excitatory synaptic currents (minis) can be recorded,which are the result of spontaneous release of individual quanta of transmitter. Minisfrom a control culture, a sister culture grown in TTX, or one grown in bicuculline toblock GABAA-mediated inhibition, are shown. To the left is shown a stretch of theraw current trace, and to the right is shown the average kinetics of the AMPA minisfor the cell on the left. After 48 h of activity blockade with TTX, the minis increase inamplitude, whereas raising firing rates with bicuculline for 48 h reduces the miniamplitude. B. The average quantal amplitude for a large number of neurons grown ineach condition is shown. TTX-treatment approximately doubled the average quantalamplitude, while bicuculline reduced it. When these waveforms are scaled andoverlaid, it can be seen that these manipulations do not influence mini kinetics.Adapted with permission from Turrigiano et al. (1998).

cultured cortical networks, raising firing rates artificially results in network-wide changes in synaptic and intrinsic properties that act to return firing ratesclose to their original values (Desai et al. 1997; Rutherford et al. 1997a,b;Turrigiano et al. 1998). As well as preventing runaway synaptic potentiation,this process could be very important during development when the numberand strength of synaptic inputs to a neuron are changing dramatically, andthe total amount of synaptic current received by the neuron may increaseover many orders of magnitude. Processes that act to stabilize firing ratescould allow neurons to fire in response to inputs early in development, whensynaptic drive is low, while preventing firing rates from saturating later indevelopment when synaptic drive is high.

In cortical networks, regulation of excitatory and inhibitory synapticstrengths occurs in concert. For example, alterations in neuronal firing ratesproduce reciprocal changes in inhibitory and excitatory inputs to corticalpyramidal neurons, thus regulating the balance of excitation and inhibition


(Rutherford et al. 1997, 1998; Turrigiano et al. 1998). Maintaining thisbalance is extremely critical in cortical networks with extensive recurrentexcitatory connections. Small alterations in the relative amount of excitationand inhibition can move these networks from a regime where firing isdesynchronized into a regime where firing is highly synchronized and essen-tially 'epileptic'. By allowing each neuron to independently regulate its firingrate, these homeostatic processes may allow complex networks composed ofrecurrent excitatory and inhibitory connections to achieve and maintain adesynchronized state in which information, in the form of changes in thepattern or rate of inputs, can be readily transferred through the circuit. Inaddition, this conjoint regulation of intrinsic and synaptic properties mayhelp to maintain circuits in the correct regime to respond appropriately toneuromodulatory signals.

4.7 Concluding remarks

As we have seen, the intrinsic and synaptic conductances expressed byneurons influence many aspects of information processing in neural circuits.Neurons display a wide variation in electrophysiological phenotypes thatdepend on the type, magnitude, and distribution of conductances. Neuronswith SFA or bursting properties will respond very differently to synapticinputs than will tonically firing neurons. Intrinsic conductances can tuneneurons to respond preferentially to particular frequencies or durations ofinputs. Dendritic conductances can influence some forms of synaptic plastic-ity as well as the manner in which synaptic inputs interact and are integratedby the neuron.

This complexity in intrinsic electrophysiological properties is enhanced bythe extensive modulation that appears to be a ubiquitous feature of neuralcircuits. Neuromodulatory substances can dramatically alter the intrinsicproperties of neurons in very complex ways, and so can influence all of theprocesses described above, including synaptic integration, plasticity, andtuning of neurons to particular properties of their inputs. This suggests that itis essential that different properties of neural circuits should be modulatedtogether in a coordinated manner to ensure that the circuits function prop-erly. By coordinately regulating presynaptic release, postsynaptic responsive-ness, and firing patterns of neurons, modulators may completely transformthe input-output properties of a neural circuit.

During development, neural circuits must fine-tune synaptic and intrinsiccellular properties through activity-dependent processes, and in adult animalsthese circuits must continue to operate correctly despite turnover of ionchannels, changes in growth or the number of inputs, and learning-inducedchanges in synaptic strengths. As we have seen, a number of mechanismsexist that allow activity to adjust the intrinsic and synaptic properties ofneural circuits to maintain them within some optimal range. These processes


promote stability, as they act to homeostatically regulate activity through theadjustment of intrinsic and synaptic conductances. Studies into these homeo-static processes are just beginning, and further work is likely to uncover adetailed set of mechanisms that continuously regulate and coordinate theproperties of neural circuits.

Acknowledgements

I wish to thank Sacha Nelson for many interesting discussions on the topic ofneuromodulation. This work was supported by K02 NS01893, RO1NS36853, and a Sloan Foundation Fellowship.

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Metaplasticity: the plasticity ofsynaptic plasticityBENJAMIN D. PHILPOT, MARK F. BEAR, AND WICKLIFFE C. ABRAHAM

5.1 Introduction

Activity-dependent modifications of synaptic efficacy are essential both forthe developmental organization of the brain and for the storage of informa-tion. It is now well established that the pattern of synaptic activation helpsdirect whether a synapse is strengthened or weakened. For example, in manyregions of the brain, high-frequency stimulation (HFS) of afferents results in along-term potentiation (LTP) of synaptic efficacy, while low-frequency stimu-lation (LFS) frequently yields long-term depression (LTD) of synaptic strength(Bear and Malenka 1994). However, the direction and degree of this synapticplasticity is governed by more than simply the pattern of synaptic activationand the, initial synaptic efficacy; prior synaptic activity can shape subsequentuse-dependent synaptic modifications. Thus, the plasticity of synapses variesas a function of their activation history. This modulation of synaptic plastic-ity has been termed 'metaplasticity', and accumulating evidence suggests thatthis phenomenon is a ubiquitous property of the brain, not only in mammals(for reviews see Abraham and Bear 1996; Abraham and Tate 1997), but inprimitive vertebrates (Yang and Faber 1991) and invertebrates (Fischer et al.1997) as well.

5.1.1 Definition of metaplasticity

Metaplasticity has been defined as the plasticity of synaptic plasticity and issaid to have occurred if prior synaptic or cellular activation leads to apersistent change in the magnitude or direction of synaptic plasticity evokedby a given pattern of synaptic activation (Abraham and Bear 1996). Becausecellular activation can affect subsequent plasticity, the prefix 'meta' is used toindicate a higher level of regulation that is beyond immediate and directactivity-dependent modifications.

Neuromodulation, as defined in other chapters in this book, may or maynot cause metaplasticity. If the prior exposure to a modulator (e.g. acetyl-choline or norepinephrine) produces a persistent change (e.g. a change thatoutlasts the binding of the ligand to receptor) in the properties of activity-dependent synaptic plasticity (e.g. LTP/LTD), then we would say that theactivation of the cell by the modulator causes metaplasticity. Central to the

B. D. Philpot, M. F. Bear and W. C. Abraham 161

Fig. 5.1 Prior stimulation can impair the subsequent induction of LTP in area CA1of the hippocampus. A. The population excitatory postsynaptic potential (EPSP) wasrecorded in two separate pathways (control and test) that received interleavedstimulation. Prior weak tetanic stimulation (30 Hz, 150ms; indicated by smalldownward arrows) inhibited the induction of LTP by a strong tetanus (100 Hz,500ms; large downward arrow) delivered 20min later. B. The inhibition by priorsynaptic stimulation was transient, as LTP could be elicited 90 min after the primingstimulation. Reprinted with permission from Huang et al. (1992).

metaplasticity concept is the notion that the history of cellular/synapticactivation is a key determinant of how synapses modify in response tospecific patterns of activity. However, no extrinsic neuromodulator isrequired for metaplasticity. Indeed, the concept arose primarily from con-sideration of how the history of postsynaptic electrical activity alters themathematical function that relates instantaneous pre- and postsynaptic activ-ity to long-term changes in synaptic plasticity.

To illustrate metaplasticity, consider the effects of a short burst of synapticstimulation on the subsequent induction of LTP or LTD in the CA1 region ofthe hippocampus (Fig. 5.1). By itself, a brief burst (5 pulses at 30 Hz) ofsynaptic stimulation results in only a transient short-term potentiation (STP)of evoked responses that rapidly decays back to baseline levels (Malenka1991; Huang et al. 1992). However, although the short burst of synapticactivation does not cause overt, long-lasting changes in synaptic strength, thismanipulation does alter ensuing synaptic plasticity; there is an inhibition ofthe subsequent induction of LTP that would normally be evoked by HFS(Huang et al. 1992; Malenka 1991). In addition to inhibiting LTP, similarpriming protocols have been shown to facilitate the subsequent induction ofLTD by LFS (Wexler and Stanton 1993). Thus, a seemingly innocuousstimulation can leave a lasting trace that influences the ability to inducesubsequent synaptic plasticity.

162 Metaplasticity: the plasticity of synaptic plasticity

It is often difficult to assess whether a neuromodulatory change falls underthe rubric of metaplasticity. For example, stress hormones can often remainelevated for a long period after a stressful event. Therefore, a change insynaptic plasticity following a stressful event might be due to either aneuronal change induced by the transient past elevation of stress hormones(metaplasticity) or to continued elevation of the hormones above basal levels.Therefore, caution should be exercised when assigning the term metaplastic-ity to events involving neuromodulator-mediated plasticity.

5.1.2 Overview of metaplasticity

For the purposes of this chapter, metaplasticity has been subdivided intocell-wide and input-specific types of metaplasticity. Cell-wide metaplasticity issaid to occur when prior activity results in a modification in the induction ofsubsequent plasticity at all modifiable synapses throughout the cell. Input-specific metaplasticity is said to occur if prior activity modifies subsequentplasticity only at the synaptic sites that experienced the prior synapticactivity. Paradoxically, there is a very strong theoretical foundation for thebiological role of cell-wide metaplasticity but sparse experimental evidence,while there is abundant experimental evidence for input-specific metaplastic-ity but less theoretical understanding. The remainder of this chapter willpresent evidence for both cell-wide and input-specific metaplasticity as well asdiscuss putative mechanisms underlying these phenomena. In addition, thechapter will discuss recent findings that neuromodulators can mediate meta-plasticity, as evidenced by the fact that the effects of extrinsic neuromodula-tors on synaptic plasticity can outlast their presence.

The chapter will also examine the putative biological relevance of meta-plasticity. For example, metaplasticity provides a means by which synapsescan integrate a response across temporally spaced episodes of synapticactivity. Furthermore, metaplasticity might serve to maintain synaptic func-tion within a dynamic range, thus preventing runaway or saturated LTP/LTD.Because metaplasticity has been most thoroughly characterized in the hip-pocampus and visual cortex, much of the discussion will focus on excitatorysynapses in these regions of the brain, although every indication suggestsmetaplasticity is observed throughout the brain, at many stages of develop-ment, and in many species (e.g. Benuskova et al. 1994). Indeed, metaplasticproperties are likely to be intrinsic to all neurons. The chapter will end byproviding an overview of metaplasticity and will attempt to marry theconcepts of cell-wide and input-specific metaplasticity.

5.2 Cell-wide metaplasticity

To a large degree, metaplasticity existed as a theoretical concept beforeexperimental support was provided. Bienenstock, Cooper, and Munro devel-oped a model of experience-dependent synaptic plasticity that embodies the


Fig. 5.2 The modification function, <f>, of Bienenstock et at. (1982). The modificationof excitatory synaptic weight (ra) is determined by the product of the input activity(d) and a function, <f>, of the integrated postsynaptic response (c). Figure adaptedfrom Bienenstock et al. (1982) with permission.

concept of cell-wide metaplasticity (Bienenstock et al. 1982). The so-calledBCM theory was designed to model accurately the plasticity of visual cortexsynapses during development. The model has two main tenets. First, synapticmodification varies as a non-linear function (<£) of the integrated postsynap-tic activity, such that low levels of postsynaptic activity result in weakening(i.e. LTD) of the active synapses, while higher levels of postsynaptic activitystrengthen those synapses (i.e. LTP). The point of crossover from synapticweakening to synaptic strengthening has been termed the modificationthreshold, 9m (Fig. 5.2). The second critical feature of the BCM model is that6m is dynamic rather than fixed. The crossover from LTD to LTP variesaccording to a time-average history of prior integrated postsynaptic activity.That is, 6m represents a dynamic variable, the value of which depends on thepast levels of cellular activity. Thus, the idea that prior activity can modifythe subsequent induction of synaptic plasticity underlies the modern conceptof metaplasticity. An important feature of the BCM model, however, is thatthe 'sliding threshold' for synaptic modification is a cell-wide event. That is,regardless of which synapses contributed to the postsynaptic activity thatdrives 9m, the value changes for all modifiable synapses on the postsynapticneuron. The shift in the modification threshold at all modifiable synapsesdefines cell-wide metaplasticity.

5.2.1 The appeal of the BCM theory

The BCM model is appealing because it overcomes many problems encoun-tered when modelling activity-dependent organization of sensory systems orwhen modelling learning and memory processes. The BCM theory wasdesigned to account for developmental plasticity in primary visual cortex and


assumes that there must be a mechanism for use-dependent decreases (LTD)in synaptic strength as well as increases (LTP). Furthermore, the modelpresents the idea that the extent to which a given synapse exhibits LTP orLTD depends not only on the immediately preceding pre- and postsynapticactivities but also on a slowly varying time-averaged value of the postsynapticresponse. Thus, high levels of coordinated activity can strengthen synapticconnections, but the resultant increase in postsynaptic activity can also shiftthe modification threshold to the right, thus limiting further induction ofLTP. Conversely, low levels of integrated postsynaptic activity can shift themodification threshold to the left, allowing LTP to be produced at lowerfiring frequencies. As such, the sliding threshold of synaptic modificationallows the pattern of synaptic weights to reach a stable state but maintainsthe cell within a dynamic range for future modifications, thus enablingsynaptic competition across time. These postulates of the BCM theory accu-rately account for the development and use-dependent modification of orien-tation selective cells within primary visual cortex. Moreover, the BCM modelis consistent with experimental data from monocular and binocular depriva-tion studies showing the use-dependent modification of ocular dominanceselectivity (Bienenstock et al. 1982; Law and Cooper 1994; Shouval et al.1996).

Another appeal of the BCM model is that the theory is general enough toexplain plasticity in different sensory systems and is applicable to both thedeveloping and mature brain. For example, the sliding threshold of synapticmodification has been used successfully to model experience-dependent plas-ticity in adult rat barrel cortex (Benuskova et al. 1994). BCM-based modelsof barrel cortex neuron responses accurately predict electrophysiologicalresponses from adult rats with either a full complement of vibrissae or withall but two adjacent vibrissae trimmed. Specifically, the cortical neuronsassociated with paired vibrissae initially exhibit potentiation that eventuallyreaches asymptotic values, although some of the initial potentiated inputsbecome depressed; the change from potentiation to depression probablyreflects a shift in the modification threshold.

The BCM is also attractive because it can apply to learning and memorytheories. All models of learning and memory have a feature that acts tostabilize synaptic weights. The BCM sliding threshold is a novel solution tothe problem and ensures that cellular activity is maintained within a dynamicrange. A practical consequence of the sliding threshold is that input patternscompete with one another for 'control' of the cell, thus yielding, as a naturalconsequence, stimulus selectivity.

5.2.2 Evidence for the BCM theory

Theoretically, the BCM theory is obviously very attractive. Thus, it is quitesatisfying that there is now experimental evidence to support the two maintenets of the model: bidirectional control of synaptic plasticity and the sliding


threshold of synaptic modification. Although there has been strong evidencefor LTP for some time, the BCM theory helped to drive the search forhomosynaptic LTD, which is now a well-established synaptic characteristic.The model also motivated the search for a sliding threshold of synapticmodification. Experimental data in the visual system are emerging thatcontinue to validate the BCM model.

Bidirectional control of synaptic plasticityThe BCM and other models assume that there must be both use-dependentdecreases and increases in synaptic strength to account for development ofvisual cortex. Bliss and L0mo (1973) first observed LTP in the hippocampus,and since then, LTP has been evidenced in many regions throughout thebrain, including visual cortex (Artola and Singer 1987; Kirkwood et al.1993). The search for homosynaptic LTD was inspired by the BCM model.Dudek and Bear (1992) discovered that systematically varying afferent stimu-lation frequency to the CA1 region of the hippocampus produced a fre-quency-dependent modification of synaptic efficacy, such that LFS results inLTD whereas HFS causes LTP. The frequency dependence of synaptic modifi-cation has since also been demonstrated in visual cortex (Kirkwood et al.1993, 1996), suggesting that this is a common neuronal feature. In concertwith the BCM theory, the systematic varying of the postsynaptic responseresults in a graded pattern of LTP and LTD that mirrors the (j> function, with0M represented by the value of postsynaptic response at which the directionof synaptic modification switches from LTD to LTP. Further characterizationhas demonstrated that LTD, like LTP, depends on calcium entry through theNMDA-type receptor (Bear and Malenka 1994). Thus, the correlation of pre-and postsynaptic activity might determine whether LTP or LTD is inducedvia the level of postsynaptic calcium entry or calmodulin availability, asdiscussed below.

Sliding threshold of synaptic modificationOne of the predictions made by the BCM model is that attenuated activityduring development would shift the modification threshold to the left, en-hancing the likelihood that subsequent activity will induce LTP while dimin-ishing the probability of LTD induction. Kirkwood and colleagues (1996)have now supported this hypothesis by demonstrating that visual corticalsynapses from dark-reared rats exhibit enhanced LTP and attenuated LTDcompared with age-matched light-reared controls (Fig. 5.3). Control experi-ments suggested that the alteration in synaptic plasticity after dark-rearing isrestricted to visual cortex, as similar changes are not observed in hippocam-pus. These findings support the concept that the modification thresholdvaries according to the activation history of the cortex.

To test further the hypothesis that the modification threshold does indeedadjust to cortical changes in afferent activity, visually deprived rats wereexposed to light for various times, and the effects of LFS were subsequently


Fig. 5.3 Bidirectional plasticity of synaptic responses in light-deprived and norm.ilrar v isual cortex. A, The stimulation-recording arrangement normally used to study[,TP and [.'I'll in the superf icial layers of v isual cortex. B. The effects of a 20 Hz,reianus (upward arrow) delivered to layer IV on synaptic responses in layer III. Solidsymhols arc data from light-deprived animals; open symhols arc from controls. Allanimals were approximately 5 weeks of age; light deprivation was from birth, C. Theeffecrs of a 1 H/ tetanus (downward arrow) in light-deprived and control an imals . I),l-'requency-rcsponse functions in light-deprived and control animals. Data replottedfrom Kirkwood et al. (\996L


examined. The magnitude of LTD evoked by LFS in light-deprived visualcortex returns nearly to control levels after only 2 days of light exposure(Kirkwood et al. 1996). These data are consistent with the hypothesis thatthe modification threshold slides to the right as average cortical activityincreases.

Direct evidence for a cell-wide shift in the modification threshold has beenrecently demonstrated in the hippocampal slice preparation. Holland andWagner (1998) demonstrated that repeated trains of strong tetanic stimula-tion on one synaptic input modify the subsequent induction of long-termdepression and depotentiation on another input converging on the samepostsynaptic cells in the CA1 region of the hippocampus. Priming stimulation(two sets of three HFS trains) enhance LTD induction by LFS. Furthermore,priming enhances depotentiation by a 5 Hz stimulation protocol. Thus, thetype of stimulation protocols that homosynaptically induce long-lasting po-tentiation also induce a cell-wide shift in the modification threshold, suchthat episodes of LFS are more likely to depress synaptic responses.

5.2.3 Mechanisms for the sliding threshold

Currently, there are strong candidates, but no definitive answers, for theunderlying mechanisms of cell-wide metaplasticity. Because both LTP andLTD are calcium-dependent events, most proposed mechanisms involve eitherdirect or indirect calcium influences. These candidate mechanisms are brokendown into two broad categories: (1) modifications in calcium current flux or(2) intracellular mechanisms that control or respond to calcium (Fig. 5.4).Since a range of putative mechanisms have been reviewed previously (Abra-ham and Bear 1996; Abraham and Tate 1997), the following discussion willfully explore one candidate mechanism involving the control of calciumcurrent flux and one candidate mechanism involving intracellular mecha-nisms. While other putative mechanisms will be mentioned only briefly, itshould be noted that, currently, there is no strong reason to favor onehypothesis over another.

Modifications in calcium currentBecause most forms of synaptic plasticity rely on calcium flux across theplasma membrane, one obvious way to control the threshold of synapticmodification is through the regulation of this calcium influx. Calcium hasseveral routes of entry, including through the NMDA receptor and voltage-dependent calcium channels. The discussion below will examine how theregulation of postsynaptic calcium currents can alter the modification thresh-old, focusing on NMDA receptor changes as an example.

NMDA receptor changes as a model for the control of calcium fluxBecause both LTP and LTD typically require calcium entry via the NMDA-type receptor, changes in the localization, number, or kinetics of the NMDAreceptor provide a likely mechanism for the sliding threshold. For example,


Fig. 5.4 Schematic illustrating mechanisms mediating the sliding threshold. A.Synaptic activation leads to calcium influx. Postsynaptic rises in calcium can activateeffectors of synaptic plasticity and are regulated by calcium buffering and diffusion. B.Modifications in calcium currents can shift the modification threshold. Here, anincrease in calcium current slides the modification threshold to the left, thus favoringthe induction of LTP. C. Intracellular mechanisms can shift the modification threshold.Here, buffering and diffusion of intracellular calcium is attenuated while effectormechanisms are augmented, thus sliding the threshold to the left.

activity via the NMD A receptor is more effective at driving neuronal re-sponses in neonatal, compared to adult, visual cortex, and the loss of NMDAreceptor function is delayed by dark-rearing (Tsumoto et al. 1987; Fox et al.1992). Carmignoto and Vicini (1992) have elegantly shown that the durationof NMDA receptor-mediated currents is attenuated during visual cortexdevelopment. Theoretical studies suggest that even a small shift in theduration of NMDA receptor currents can have dramatic consequences onpostsynaptic rises in free calcium following tetanic stimulation (Gold andBear 1994). The attenuation of NMDA receptor efficacy correlates with thecritical period of visual cortex (Carmignoto and Vicini 1992). Furthermore,


Fig. 5.5 There is a developmental decrease in the duration of NMDA receptorexcitatory postsynaptic currents (EPSCs) in layers 2/3 of somatosensory cortex. A.Averaged NMDA receptor EPSCs from a neuron from a postnatal day 4 (P4) and a P9neuron, each fit with a single exponential. B. Decrease in the mean ( + SEM) decaytime constant of the exponential fit to NMDA receptor EPSCs at P3/4 and P8/9.Asterisk denotes significant difference. Adapted with permission from Flint et al.(1997).

dark-rearing delays the shortening of NMDA receptor-mediated currents.Recent evidence suggests that the shortened duration of NMDA receptor-

mediated currents may be controlled by a shift in the heteromeric subunitcomposition of the receptor (Fig. 5.5; Flint et al. 1997; Shi et al. 1997).Accordingly, the ratio of the NR2A to NR2B subunit composition increasesduring development (Williams et al. 1993; Monyer et al. 1994), mirroringthe decrement in NMDA receptor current duration. Furthermore, recent datasuggest that dark-rearing delays the shift in NMDA receptor subunit compo-sition (Nase et al. 1997; Philpot and Bear 1998; Quinlan et al. 1998). Theidea that NMDA receptor subunit composition is regulated by activity isattractive because it provides a cell-wide mechanism by which the thresholdfor synaptic modification can slide. To illustrate, in the visual cortex, apredominance of the NR2B to NR2A subunits would prolong NMDAreceptor-mediated currents, thus favoring more calcium entry and the induc-tion of LTP. However, as connections are established in visual cortex, theremight be an activity-dependent shift to a predominance of the NR2A subunit,a corresponding attenuation of NMDA receptor-mediated currents, and aresulting shift to the right of the modification threshold.

It is quite plausible that activity regulates NMDA receptor subunit compo-sition, and thus function, as there is a precedence in skeletal muscle for anactivity-driven shift in receptor subunit composition. In developing skeletalmuscle, there are two types of acetylcholine receptor (AChR) channels thatdiffer dramatically in their mean channel open time and conductance(Fischbach and Schuetze 1980; Siegelbaum et al. 1984). The difference in


channel properties is a result of different receptor subunit composition. Thereis a developmental shift in AChR subunit composition such that the esubunit replaces the y subunit to form the a2/3eS receptor complex, and thisshift corresponds to a reduction in the mean channel open time (Mishina etal. 1986; Witzemann et al. 1987; Gu and Hall 1988). Synaptic activityappears to be the key element regulating receptor subunit composition, asdenervated muscle re-express -/-containing receptors (Goldman and Staple1989; Brenner et al 1990).

In a manner analogous to the neuromuscular junction, NMDA receptorsubunit composition in the cerebellum is controlled by synaptic activation ofNMDA receptors and the expression of factors known as neuregulins (Ozakiet al. 1997). In the hippocampus, evidence is also beginning to accumulatethat LTP-inducing synaptic activity can up-regulate the expression of NMDAreceptor subunits, and this may occur differentially across the NR1, NR2A,and NR2B subunits (Thomas et al. 1994; Williams et al. 1997). Thus,afferent activity can clearly play a large role in determining receptor subunitcomposition and, thereby, dramatically shape channel properties.

Another intriguing possibility for the involvement of NMDA receptorchanges in metaplasticity is that synaptic activity can regulate the clusteringof NMDA receptors. Recently, Rao and Craig (1997) have shown thatactivity can drive NMDA receptors away from synapses while inactivity canincrease NMDA receptor clustering at postsynaptic sites. An increase inNMDA receptor clustering at synaptic sites would favor LTP induction.Thus, the history of cellular activity can modulate NMDA receptor distribu-tion and, consequently, the ability to undergo subsequent activity-dependentsynaptic plasticity. Notably, the time course for this event is over the courseof days, similar to the time course observed for the reversal of dark-rearingeffects. However, whether NMDA receptor clustering is a cell-wide or homo-synaptic event under physiological conditions in vivo remains to be deter-mined.

Additional scenarios can be envisioned for NMDA receptor modificationsthat contribute to the sliding threshold of synaptic modification. For exam-ple, NMDA receptor function can be modified by post-translational phospho-rylation and by interactions with other proteins in the postsynaptic density,thus enhancing the efficacy of NMDA receptor-mediated responses (Kornauet al. 1995; Niethammer et al. 1996; Rosenblum et al. 1996; Rostas et al.1996). Regardless of the means by which the NMDA receptor is modified,changes in NMDA receptor function are a strong candidate for regulatingmetaplastic events and deserving of more thorough investigation.

Regulation by inhibitionThe rise in postsynaptic calcium can be regulated by a number of factorsother than direct modifications of NMDA receptor function. Because mostcalcium influx is voltage-dependent, one powerful site of regulation is theeffectiveness of impinging inhibitory synapses. Thus, changes in inhibition


might indirectly modify the threshold for synaptic modification through thecontrol of postsynaptic calcium entry and downstream second messengerresponses. It is now well established that inhibition of gamma-aminobutyricacid (GABA) release during HFS promotes LTP by allowing strong activationof NMDA receptors; pharmacological blockade of GABA often facilitates theinduction of LTP (Abraham et al. 1986; Wigstrom and Gustafsson 1986;Artola and Singer 1987; Bear et al. 1992). GABAergic influences have alsobeen shown to influence the induction of LTD, as GABA B receptor activationis necessary for LTD induction in hippocampal slices from young animals,whereas GABAA receptor antagonists enhance LTD in slices from matureanimals (Kerr and Abraham 1995; Wagner and Alger 1995). The strongregulation of synaptic plasticity by GABAergic influences suggests that long-lasting modifications of inhibition might indirectly contribute to metaplastic -ity. For example, LTP of IPSPs has been demonstrated in visual cortex(Komatsu 1994), and this would be expected to limit severely the subsequentinduction of LTP at excitatory synapses.

Interestingly, Steele and Mauk (1994) have shown that application ofpicrotoxin, a GABAA receptor antagonist, shifts the frequency dependentinduction of LTP/D in CA1 such that the induction of LTP is favored (Fig.5.6). Conversely, application of the GABAA agonist muscimol shifts themodification threshold such that the induction of LTD is more pronounced.Thus, large-scale modifications in inhibitory tone are likely to influence themodification threshold.

There are some indications that a change in inhibition might contribute tometaplastic changes in visual cortex. For example, there are wide-scalereductions in GABA and glutamic acid decarboyxlase in light-deprived ani-mals (Hendry and Jones 1986; Benevento et al. 1992; Hendry and Carder1992), and these reductions are consistent with the compromised inhibitionobserved in electrophysiological recordings (Benevento et al. 1992). In vitrostudies demonstrate that attenuated activity causes a loss of GABA expres-sion that can be prevented by application of brain-derived neurotrophicfactor (Rutherford et al. 1997). Reduction in the magnitude of inhibition,and the corresponding increase in cellular excitability, could help facilitateLTP induction and influence metaplastic events.

Other regulators of calcium fluxNumerous mechanisms can regulate calcium flux and are likely to contributeto metaplasticity. For example, changes that facilitate postsynaptic depolar-ization are likely to enhance calcium entry due to activation of voltage-dependent calcium channels or removal of magnesium block of the NMDAreceptor. Any biochemical change that alters postsynaptic input resistance orcationic currents is, thus, likely to alter the subsequent induction of synapticplasticity (see Abraham and Tate 1997). For instance, reduction of theinhibitory after-hyperpolarization can decrease spike frequency adaptation,


Fig. 5.6 GABAergic influences on the frequency-response function in rat CA1. A.Application of the GABAA receptor antagonist picrotoxin shifts the frequency-dependent induction of LTP/D in CA1 such that the induction of LTP is favored. B.Conversely, application of the GABAA agonist muscimol shifts the modificationthreshold such that the induction of LTD is more pronounced. C. Percentage differencebetween control and experimental conditions. The circles are picrotoxin minus controland the triangles are muscimol minus control. Adapted with permission from Steeleand Mauk (1994).

enhance calcium entry following a burst, and facilitate the induction of LTP(Blitzer et al. 1995; Cohen and Abraham 1996). Thus, any mechanisms thataffect postsynaptic membrane properties might contribute to the activity-de-pendent response of a neuron.


Intracellular mechanismsMetaplasticity might be induced by altering the sensitivity of elements thatrespond to calcium. Some data suggest that the levels of intracellular calciumneed not change dramatically, but that a shift in the intracellular sensitivity tocalcium might contribute to the sliding threshold of synaptic modification.For example, the pharmacological depletion of intracellular calcium storesblocks the induction of LTD at naive synapses in CA1, but this manipulationdoes not block depotentiation (Reyes and Stanton 1996). Thus, metaplastic-ity may become manifest by a change in the intracellular response to a givencalcium flux.

Regulation of free calmodulin as a model intracellular mechanismThe induction of both LTD and LTP requires postsynaptic calcium entry andthe subsequent binding of calcium to calmodulin. Low levels ofcalcium/calmodulin are thought to activate a series of protein phosphatases(Mulkey et al. 1994), and high levels are thought to trigger LTP by activatinga network of protein kinases (Malenka et al. 1989; Malinow et al. 1989).Thus, the induction of synaptic plasticity is powerfully regulated by proteinsthat determine intracellular free calmodulin availability. Two such proteins,RC3 and CaMKII, have received particular attention for their putative role indetermining the threshold for synaptic modification.

Regulation of calcium/calmodulin-dependent protein kinase II (CaMKII) isa potential mechanism for regulating the sliding threshold (Bear 1995;Deisseroth et al. 1995; Mayford et al. 1995). One of the consequences ofpostsynaptic depolarization and calcium entry is activation of CaMKII, amajor postsynaptic protein (reviewed by Hanson and Schulman 1992). Theactivation of CaMKII results in autophosphorylation at Thr286 that (1)causes the protein to become calcium-independent and (2) increases theaffinity of the enzyme for calmodulin by 1000-fold (Hanson and Schulman1992). These properties allow CaMKII to be active well after intracellularcalcium levels have returned to basal levels. The amount of CaMKII trappedin an autonomous state is proportional to the level of free calmodulin in thepostsynaptic spine and can, thus, regulate the modification threshold. Inaddition to the theoretical and experimental observations that suggest CaMKIIactivation could help maintain LTP (Lisman 1994), activation of CaMKIImight also hold the memory that shifts the threshold of synaptic modification(Bear 1995; Mayford et al. 1995).

Recent studies using transgenic mice have supported the role of CaMKII inthe sliding threshold. Transgenic mice created with replacement of Thr286with Asp have twice the level of constitutively active CaMKII than wild-typecontrols (Mayford et al. 1995). Remarkably, transgenics exhibit a similarmagnitude of LTP in CA1 of the hippocampus induced by HFS of theSchaffer collaterals. However, a marked difference in the induction of LTPappears when LFS protocols are examined. Specifically, stimulation at 5 Hz,which typically evokes a slight potentiation in CA1 of adult wild-type mice,


Fig. 5.7 Molecular mechanism for a sliding modification threshold. Thephosphorylation of CaMKII shifts the modification threshold to the right, favoringthe induction of LTD. Adapted from Bear (1995) with permission.

causes a significant depression in the transgenics. These data suggest that themodification threshold has shifted to the right in mice expressing high levelsof autonomous CaMKII activity.

The shift in the modification threshold in transgenics appears to occur viaa similar mechanism as in wild-type mice. For example, after priming HFS tothe Schaffer collaterals, the subsequent magnitude of LTD induced by 5 Hzstimulation is similar in wild-types and transgenics (Mayford et al. 1995).Thus, the overexpression of constitutively active CaMKII occludes the effectsof prior HFS. These data suggest that enhancement of LTD by HFS inwild-type mice is due to an elevation of autonomous CaMKII. Therefore, anelevation in calcium-independent CaMKII shifts the modification threshold tothe right, facilitating the expression of LTD (Fig. 5.7).

There are suggestions that the level of autonomous CaMKII is closelyrelated to the value of the modification threshold. First, LTD is more robustearly in postnatal life and declines with increasing age (Dudek and Bear1993). Autonomous CaMKII activity declines with a similar developmentaltime course (Molloy and Kennedy 1991). Second, the magnitude of LTDelicited by 5 Hz stimulation in wild-type and mutant mice is positivelycorrelated to the level of autonomous CaMKII activity (Mayford et al. 1995).Notably, the magnitude of LTD after 1 Hz stimulation is similar in wild-typeand transgenic mice, suggesting that transgenics maintain the mechanism forLTD induction but the threshold for LTD induction is altered.

The role of CaMKII in the sliding threshold may coexist with the role ofCaMKII in the generation of LTP. For example, LTP induces AMPA receptorphosphorylation that is probably mediated by CaMKII (Barria et al. 1997).Although CaMKII autophosphorylation is thought to help maintain LTP


(Lisman 1994), the part of the LTP induction pathway involving CaMKIImight also be used to modulate subsequent LTP by sliding the modificationthreshold (Bear 1995). Regardless of the ultimate role of CaMKII in plasticityand metaplasticity, the enzyme certainly has a behavioral significance, asCaMKII mutant mice have marked deficits in spatial memory (Silva et al.1992; Bach et al. 1995). However, the role of CaMKII needs to be exploredfurther.

Recently, Gerendasy and Sutcliffe (1997) posited that RC3, a protein thatcan also regulate free calmodulin, could work in concert with CaMKII todetermine the threshold for synaptic modifications. RC3 regulates calmodulinavailability in dendritic spines by releasing calmodulin slowly in response tosmall increases in calcium and rapidly in response to large calcium loads. Inaddition, phosphorylation of RC3 by protein kinase C (PKC) serves toamplify calcium mobilization (Cohen et al. 1993) and increases theavailability of free calmodulin (Gerendasy and Sutcliffe 1997). As such,phosphorylation of RC3 and the subsequent increase in calcium and calmod-ulin availability would slide the modification threshold to the left, thusfavoring LTP. Gerendasy and Sutcliffe (1997) present a theoretical argumentthat the ratio of phosphorylated to unphosphorylated forms of RC3 andCaMKII might be able to predict accurately the modification threshold.Although the theoretical evidence for such a role of RC3 is intriguing, thetheory still lacks experimental support. For example, the induction of LTPleads to an early and sustained increase in RC3 phosphorylation (Chen et al.1997; Ramakers et al. 1997), but a subsequent decrease in RC3, as predictedby the theory, has yet to be observed. Although the role of RC3 in the slidingthreshold has yet to be proven, the theory presents another possible pathwayby which the sliding threshold can be modified. Furthermore, the theoreticalrole of RC3 in metaplasticity might apply to other regulators of intracellularcalcium and calmodulin.

Spine morphologyBecause postsynaptic rises in intracellular free calcium are crucial for theinduction of both LTP and LTD, a simple way to slide the modificationthreshold would be to alter calcium accumulation and sequestration. Forinstance, a simple change in the volume or geometric structure of dendriticspines could dramatically affect calcium diffusion through the spine (Fig.5.8). Models by Gold and Bear (1994) demonstrate that a fivefold increase inspine neck diameter, a change that is within physiological limits, could resultin a 15-fold decrease in levels of free calcium within the dendritic spine. Thus,long-lasting changes in LTP and LTD induction might result from physiologi-cal changes in spine morphology. Such activity-dependent changes in spinemorphology have been widely observed. For example, HFS that is sufficientto activate NMDA receptors and induce LTP in CA1 neurons also results inboth transient and lasting changes in spine morphology (Lee et al. 1980;Chang and Greenough 1984). Notably, there is a significant increase in the


Fig. 5.8 The effects of buffering and spine neck diameter on the accumulation ofcalcium in the dendritic spine in response to synaptic activation of NMDA receptors.Compartment 1 represents the spine head and compartment 8 represents the dendriticshaft (see Gold and Bear 1994). Intracellular calcium concentrations are given versustime for all compartments for two different values of buffer concentration and spineneck diameter. A. Buffer at 150 /xM and neck width of 0.2 ^im. B. Buffer at 350 /uMand neck width of 0.4 /urn. Adapted with permission from Bear et al. (1994).

number of 'sessile' spines, suggesting a shortening and widening of the spineneck following stimulation. Such a change would result in a marked increasein the diffusion of free calcium from the dendritic spine, and thus thepostsynaptic site of interest. An immediate and transient increase in the widthof the spine neck might explain why LTP is more difficult to evoke after priorLTP induction (Huang et al. 1992). More permanent changes in spinemorphology might cause a lasting shift in the threshold of synaptic modifica-


tion. That is, a long-lasting shortening and widening of the spine neck woulddampen the localized rise in postsynaptic free calcium, thus favoring LTD.On the other hand, an elongation and narrowing of the spine neck wouldfacilitate sharp rises in calcium and, thus, shift the modification threshold tothe left.

Calcium buffersCalcium buffers provide another means by which postsynaptic calcium levelscan be regulated. Models have demonstrated that calcium buffers can dra-matically shape the induction of LTP and other forms of synaptic plasticity(e.g. Holmes and Levy 1990). Interestingly, there are numerous examplesdemonstrating that calcium-binding proteins are regulated by neuronal activ-ity (Cellerino et al. 1992; Carder et al. 1996; Caicedo et d. 1997; Philpot etal. 1997). For example, calbindin-immunoreactivity decreases markedly invisual cortical neurons, but not lateral geniculate neurons, that are deprivedof patterned visual stimulation (Mize and Luo 1992). Conversely, strongelectrical stimulation of the perforant path causes an almost twofold increasein calbindin mRNA in dentate gyrus granule cells (Lowenstein et al. 1991).Modelling studies demonstrate that these types of changes in calcium-bindingproteins are likely to affect the threshold of synaptic modification (Fig. 5.8;Gold and Bear 1994). A high level of calcium-binding proteins could rapidlysequester postsynaptic rises in free calcium and favor the induction of LTD.However, low concentrations of calcium buffers in the spine might bepermissive to rapid and large elevations in calcium that favor the induction ofLTP.

Calcium storesAnother important regulator of intracellular calcium levels is by membrane-bound sequestration of calcium. The majority of intracellular calcium issequestered within intracellular membrane-bound organelles such as theendoplasmic reticulum, Golgi complex, and mitochondria (Pozzan et al.1994), and calcium availability can be modified by changing the efficacy ofcalcium sequestration within these compartments. Each of these compart-ments has its own mechanism for controlling calcium storage and release. Forexample, in the endoplasmic reticulum, activation of either the IP3 receptorby mGluR stimulation or the calcium-sensitive ryanodine receptor can pro-mote the release of stored calcium. A number of regulatory elements havebeen identified for the IP3 receptor, and altering any one of these regulatoryelements could dramatically shape calcium sequestration. In mitochondria,the membrane potential and degree of ATP synthesis are important regulatorsthat affect the buffering calcium response of the organelle. Notably, thehistory of recent calcium levels can alter subsequent calcium release frommitochondrial calcium stores. In the chick nucleus magnocellularis, for in-stance, neuronal activity regulates the number and function of mitochondria,thus altering calcium regulation (Mostafapour et al. 1997). Specifically,mitochondrial number and function appear to increase in response to im-


posed calcium loads. Furthermore, mitochondrial gene expression is up-regulated by synaptic stimulation in the hippocampus (Williams et al. 1998).There clearly are many sites for altering intracellular calcium sequestration,and these sites can be modified by changes in afferent activity. Alteringintracellular calcium sequestration or release is likely to alter dramatically thethreshold of synaptic modification. Processes that facilitate rapid intracellularsequestration are likely to shift the modification threshold to the right, whilethose processes that are permissive to calcium release from intracellular storeswill shift the threshold to the left.

Other intracellular mechanismsThere are numerous other possibilities for intracellular control of metaplastic-ity. For example, the regulation of protein synthesis is likely to play a largerole in the control of metaplasticity, and this hypothesis has been fullydescribed by Abraham and Tate (1997). Recent evidence that NMDA recep-tor activation can alter postsynaptic protein synthesis by inducing phosphory-lation of eucaryotic translation elongation factor 2 continues to support thisas a potential mechanism (Scheetz et al. 1997). Another putative site ofregulation of metaplasticity is via plasticity proteins located at the post-synaptic density (Abraham and Tate 1997). Molecular interactions at thepostsynaptic membrane might direct the cascade of events associated withpostsynaptic depolarization. For instance, postsynaptic density proteins, suchas PSD-95, are thought to anchor receptor subunits and perhaps clusterregulatory proteins at receptor channels. Changes in PSD-95 function arelikely to translate into, for example, altered NMDA receptor function orlocalization. Although there are many potential sites of regulation for meta-plastic events, very few have been explored. The value for the threshold ofsynaptic modification might be determined by any mechanism that can altereither intracellular calcium regulation or the neuronal response to a givencalcium load.

5.3 Input-specific metaplasticity

In the BCM model, as noted above, the setting of the modification thresholdby neural activity is a cell-wide effect. That is, when the threshold is changedfor a given cell, the change is expressed at all the excitatory synapses on thecell, regardless of whether any particular synaptic site contributed to the cellfiring or not. This makes sense given that the overall level of firing activity bythe postsynaptic cell is the critical determinant of the modification threshold.Since the cell firing rate is a function of the total aggregation of synapticactivity, relatively quiescent synapses play as much a role in determining thefiring rate as the relatively active ones. Indeed, in the case of low levels ofactivity, which shift the modification threshold to the left (e.g. duringbinocular occlusion), it could be argued that the inactive synapses play a


particularly important role in establishing that pattern of reduced activity.Therefore, the fact that all synapses play a role in determining the rate ofneural activity, combined with the fact that the cell cannot predict whichsynapses will be active from moment to moment to induce plasticity, lendstheoretical justification to the BCM postulate that the modification thresholdchanges across the host of synapses present.

Can there, however, be changes in synaptic plasticity thresholds that maybe more confined spatially and temporally than that proposed for the BCMmodel? A growing number of experiments suggest that, indeed, physiologicalpatterns of synaptic activity can dynamically vary plasticity thresholds in aninput-specific manner. While cell-wide metaplasticity involves a shift in themodification threshold at all modifiable synapses throughout the cell, input-specific metaplasticity suggests that prior episodes of activity can induce atime-varying change in synaptic efficacy only at the synapses that evoked thechange. While there are few examples of cell-wide metaplasticity, there arenumerous data demonstrating input-specific metaplasticity. Input-specificmetaplasticity has been most fully explored using in vitro and in vivohippocampal preparations, although there are examples in other brainregions. Below we will provide examples of input-specific metaplasticity,and we will discuss how metabotropic glutamate receptor (mGluR) andNMDA receptor activation can compete in the induction of input-specificmetaplasticity.

5.3.1 Examples of input-specific metaplasticity

Prior activity can impair LTPIn an early study of input-specific metaplasticity, Fujii et al. (1991) reportedthat LFS (IHz, 1000 pulses) of the Schaffer collateral fibers synapsing onCA1 pyramidal cells elicited very little change in the efficacy of the stimulatedsynapses. However, the LFS stimulation caused a profound impairment in theability to produce LTP 60min later by HFS of the same pathway. Thisremarkable finding was confirmed by Huang et al. (1992), who employedseveral brief trains of HFS (30 Hz, 150ms) to inhibit subsequent LTP (Fig.5.1). There were four important features of this latter effect. First, while theinitial tetani produced short-term potentiation of the evoked response lastingseveral minutes, the train duration (100-200 ms) and pulse frequency (33 Hz)were too low to induce LTP by themselves. Thus, the block of LTP occurredwithout a lasting change in the baseline-evoked response, supporting thefindings of Fujii et al. (1991). Second, the effect is input-specific because LTPcould be normally induced at naive synapses. That is, while the prior synapticactivation blocked LTP induction for that same pathway, LTP induction by adifferent set of Schaffer collateral fibers converging onto the same postsynap-tic cells was unaffected. Third, the block of LTP lasted between 60 and90min (Fig. 5.IB), although there are some reports that the effect can last forseveral hours (Frey et al. 1995). Finally, the block of LTP could be overcome


by giving a stronger intensity tetanus (by increasing the stimulation strength)at the time of LTP induction, suggesting that mechanisms of LTP remainedintact but the threshold for LTP induction was shifted to the right. Thefinding that prior stimulation can inhibit subsequent LTP induction has sincebeen replicated by several groups (Izumi et al. 1992 a, b; Wexler and Stanton1993; Fujii et al. 1996; Abraham and Huggett 1997).

Prior activity can enhance LTDIn a study contemporaneous to those described above, Christie and Abraham(1992) reported that prior stimulation can also enhance the induction ofLTD, using the lateral perforant path input to the dentate granule cells inbarbiturate-anesthetized rats as a model system. Low-frequency primingstimulation (8 trains of 10 pulses at 5 Hz) of the lateral path synapsessignificantly facilitated subsequent lateral path LTD, induced by an associa-tive protocol involving short bursts of stimulation to the medial path andinterleaved single pulses to the lateral path. The priming stimulation did notevoke a generalized facilitation of synaptic plasticity, however, because LTPinduction in the lateral path by repeated theta-burst stimulus (TBS) trains wasinhibited by the prior 5 Hz stimulation, replicating the above findings by Fujiiet al. (1991) and Huang et al. (1992). It is notable that the facilitation ofLTD induction had similar properties to the inhibition of LTP. Thus, thepriming effect did not involve a long-lasting change in synaptic strengthfollowing the priming stimulation, was input-specific, and lasted about 2h.The facilitation of LTD bears some resemblance to the depotentiation effectobserved previously, wherein LTD/depotentiation could be induced by LFSonly if prior LTP had been established (Barrionuevo et al. 1980; Staubli andLynch 1990). However, the experiment by Christie and Abraham (1992) hadthe advantage of employing a priming protocol that did not induce a changein synaptic strength, thus making it clear that the priming was facilitatingLTD and not simply inducing depotentiation. Because prior activity iscapable of enhancing subsequent LTD induction without altering baselinesynaptic transmission, this metaplastic change is clearly not an epiphenom-enon of LTP.

Prior activity can facilitate LTPPrior activity does not always shift the threshold to the right. Certainstimulation protocols can actually enhance the probability that LTP will besubsequently induced. For example, mild stimulation (5 Hz, 80 pulses) of thelateral perforant path in vivo facilitates subsequent LTP induction in thedentate gyrus (Christie et al. 1995). The facilitation in the dentate gyrus,observed lOmin after priming, is input-specific and has been observed withstimulation protocols near the threshold of LTP induction (2-3 trains ofTBS). However, the mild priming protocol does not always involve a simpleshift in the modification threshold to the left. The same priming thatfacilitates LTP with near threshold stimulation can actually impair LTP


induction using stronger stimulation protocols (8 trains of TBS). Althoughthese data demonstrate that prior activity can enhance subsequent LTPinduction, they also demonstrate that there are complex interactions betweenprior activity and subsequent alterations in the modification threshold. Fur-thermore, these experiments demonstrate the importance of testing a range ofLTP (or LTD) induction protocols in these kinds of studies to characterizefully the altered inducibility of synaptic plasticity.

5.3.2 Induction mechanisms of input-specific metaplasticity

A number of lasting changes in the molecular structure or function ofsynapses have been proposed to account for the metaplasticity phenomenadescribed above. These include long-term changes in: NMDA receptor-mediated currents, GABAergic synaptic inhibition, mGluR function and/or phosphoinositide turnover, activation of voltage-dependent calciumchannels, levels of calcium-binding proteins, the activation state of CaMKII,clustering of plasticity-related molecules at the postsynaptic density, and thestate of readiness of synaptically located protein synthesis machinery. Thesevarious possibilities have been recently reviewed in-depth elsewhere (Deis-seroth et al. 1995; Abraham and Tate 1997), and will not be discussedfurther here. Note, however, that many of the mechanisms of input-specificmetaplasticity are similar to those discussed above for cell-wide metaplastic-ity, with the exception that the metaplastic change is specific to the site ofsynaptic activity rather than being cell-wide. For example, while cell-widemetaplasticity might employ a general alteration in protein expression,input-specific modifications might involve site-directed modifications. Theobservation that protein synthesis machinery exists at dendritic spines sug-gests that both translational and post-translational changes might occur atspecific synaptic sites (Steward 1997), thus providing the potential for a greatdiversity of synaptic function.

In general, very little is known about the signaling cascades or the expres-sion mechanisms underlying metaplasticity at any level. The field is ripe forsuch pioneering investigations. Although the cellular mechanisms of input-specific metaplasticity need to be explored further, the receptor-mediatedinduction of input-specific metaplasticity has been examined in detail. Theinput pathways of the hippocampus that were described above as showinginput-specific metaplasticity use glutamate as the neurotransmitter. It can bepresumed, therefore, that activation of one or more of the glutamate receptorsubtypes is essential for inducing the metaplasticity effects. Since both NMDAreceptors and the mGluRs couple to second messenger systems postsynapti-cally and have been strongly linked to the induction of traditional synapticplasticity, it is not surprising that these receptor subtypes have also beenfound to play a prominent role in the induction of metaplasticity. The role ofAMPA receptors in metaplasticity has been less well studied and is deservingof more attention.


There are no clear distinctions, but a heuristic is that mGluR-mediatedactivity is necessary to shift the modification threshold to the left, whileNMD A receptor activation can shift the threshold to the right, favoring LTD.Below we will briefly discuss NMDA receptor and mGluR-mediated induc-tion of input-specific metaplasticity.

NMDA receptor-mediated induction of input-specific metaplasticityThere have been a number of reports that 'untimely' activation of NMDAreceptors has the paradoxical effect of inhibiting the subsequent induction ofNMDA receptor-dependent LTP. For example, following LFS of CA1 slicesin a low magnesium bathing solution, LTP cannot be elicited by a standardHFS paradigm (Coan et al. 1989). Partially blocking NMDA receptors usinga moderate dose of AP5 permitted LTP to occur, however. In a similar vein,bath application of NMDA for 5 min prior to HFS also blocked the inductionof LTP (Izumi et al. 1992 a, b). These findings suggest that prior NMDAreceptor activation could induce a lasting metaplastic synaptic change, butsince the treatments (low magnesium or NMDA in the bathing solution) werealso present during the tetanus, they did not provide clear-cut examples ofmetaplasticity.

Fortunately, there is more direct evidence that activation of NMDA recep-tors can induce input-specific metaplasticity. First, it was observed by bothFujii et al. (1991) and Huang et al. (1992) that the block of LTP by priorconditioning stimulation was prevented when AP5 was present during thisprior stimulation. Second, repeated iontophoretic application of NMDA,which by itself did not cause a long-lasting change in synaptic strength, alsoinhibited subsequent LTP (Huang et al. 1992). These findings clearly indicatethat NMDA receptor activation can trigger an input-specific and long-term(60-90 min) suppression of LTP induction, a conclusion that has beenconfirmed by several recent studies (Fig. 5.9A-Q Wexler and Stanton 1993;Abraham 1996; Fujii et al. 1996).

Another consequence of NMDA receptor activation is facilitation of ho-mosynaptic LTD, as shown by Christie and Abraham (1992), using 5 Hzpriming and the associative LTD induction protocol (producing a form ofhomosynaptic LTD) in the lateral perforant path. The facilitation of LTDwas blocked when the NMDA receptor antagonist CPP was present duringthe 5 Hz priming stimulation, but LTD still occurred when CPP was adminis-tered after priming but before the associative stimulation paradigm. Interest-ingly, the induction of heterosynaptic LTP was not facilitated by primingstimulation, perhaps reflecting a difference in the underlying mechanisms ofinduction between the two types of LTD. In contrast to the inhibition of LTP,NMDA iontophoresis was not an adequate stimulus for facilitating subse-quent LTD (Wexler and Stanton 1993), suggesting that priming by synapticactivation may require co-activation of NMDA receptors and some otherreceptor subtype, possibly mGluRs.


Fig. 5.9 Examples of how prior activation of NMD A receptors or mGluRs canmodify subsequent plasticity. A. Pre-stimulation by 32 trains of theta-burst stimulation(TBS, solid line) to Schaffer collaterals in rat CA1 slices prevents the inhibition of LTPevoked by 4 trains of TBS (arrow). B. The induction of LTP recovers within 1.5h ofthe prior stimulation. C. The presence of the NMDA receptor antagonist AP5 duringpriming stimulation prevents the LTP-impairing consequences. D. lOmin applicationof the mGluR agonist ACPD (20 juM) facilitates the subsequent induction of LTPevoked by TBS. Reprinted with permission from Abraham and Tate (1997).

mGluR-mediated induction of input-specific metaplasticityIf the prior activation of NMDA receptors (by themselves or in concert withanother receptor subtype) inhibits LTP and facilitates homosynaptic LTD,what receptor system is responsible for the facilitation of LTP observed byChristie et al. (1995)? The strongest candidate appears to be one or more ofthe mGluR family. The first evidence for priming of LTP by mGluR activa-tion was presented by Bortolotto et al. (1994) who demonstrated in areaCA1 of the hippocampal slice that activation of mGluRs, by either bathadministration of the mGluR agonist ACPD or HFS in the presence of AP5,can facilitate the induction of persistent LTP, even if the activation occurslong before the actual LTP-inducing tetanization. In control slices, by con-trast, LTP persistence was typically blocked by the presence of a-methyl-4-carboxyphenylglycine (MCPG) during the LTP-inducing stimulation.Bortolotto et al. (1994) suggested that mGluRs act as a molecular switch thatfacilitates LTP for up to 7 h, but the switch can be turned off or reset by LFS.


The concept is attractive because it provides a mechanism by which LTPinduction is enhanced. However, the finding is controversial because of thefailure by other groups to replicate it (Selig et al. 1995; Thomas and O'Dell1995).

The idea that mGluR priming can facilitate LTP induction has remainedalive, in part, due to recent pharmacological studies. These studies suggestthat mGluR activation might serve to adjust the threshold of synapticmodification rather than simply acting as a molecular switch. For example,LTP induction in CA1 of hippocampai slices is facilitated 20min after alOmin application of the mGluR agonist ACPD (Fig. 5.9D; Cohen andAbraham 1996); after mGluR activation, LTP can be evoked reliably bystimulation that is normally near the threshold for LTP induction. ACPDapplication enhances LTP induction for l-3h, which is shorter than theminimum of 7 h of efficacy reported for the molecular switch (Bortolotto etal. 1994). The enhancement is not dependent on NMDA or AMPA receptorco-activation with the mGluRs, nor is it due to a persistent decrease inGABAergic inhibitory tone. More recent experiments have identified theGroup 1 mGluRs as being the critical receptor subtype involved in primingLTP in CA1 (Cohen et al. 1998). The involvement of Group 1 mGluRsimplicates activation of phospholipase C (PLC) as the signal transductionresponsible for LTP priming, a conclusion supported by the finding that aPLC inhibitor, U-73122, can block the priming effect by the Group 1 agonist,DHPG (Cohen et al. 1998). The above data collectively suggest that mGluRactivation might facilitate LTP induction and, thus, oppose the effects exertedby NMDA receptor activation.

5.4 Biological significance of metaplasticity

Metaplasticity provides a means by which synapses can integrate a responseacross temporally spaced episodes of synaptic activity. Thus, it is conceivablethat a memory trace can be encoded simply by the metaplastic state of a setof neurons. For example, sensory neurons inactive for a prolonged periodwould be more susceptible to LTP; increased susceptibility to LTP mightindicate a lack of recent sensory experiences in this modality. The susceptibil-ity to synaptic plasticity is, thus, a gauge for the recent activation history ofthe sensory system.

Both cell-wide and input-specific metaplasticity can similarly serve to gaugethe history of cellular activation. The question arises, then, as to whatdifferent functions input-specific and cell-wide metaplasticity might serve?Theoretical studies suggest that cell-wide metaplasticity provides a mecha-nism, based on patterned activity across time, to account for competitivesynaptic interactions (Bienenstock et al. 1982). While cell-wide metaplasticityaccounts for competitive synaptic interactions by maintaining cellular func-tion within a dynamic range, another role might be ascribed to input-specific


metaplasticity: to maintain synoptic function in a defined dynamic range. If afixed threshold of synaptic modification exists, then synaptic potentiation ordepression could positively feed back to produce polarized synaptic functionbecause strong synapses are more likely to be potentiated whereas weaksynapses are more likely to be depressed further. However, if the thresholdfor synaptic modification is independently determined at all excitablesynapses, then most synapses will be maintained in a range that permits largefluctuations in synaptic efficacy. As such, each synapse is maximally labileand able to respond with high gain to local changes in synaptic activation.

Most learning models require synaptic and cellular function to be main-tained within a dynamic range. Thus, biological systems are likely to requirea similar mechanism to encode memories; metaplasticity serves such a role.Indeed, manipulations that inappropriately slide the threshold of synapticmodification are also sufficient to impair learning and memory processes (e.g.Mayford et al. 1995). Certainly, experimental and theoretical studies areneeded to explore further the biological roles of metaplasticity. However, asthe characterization of metaplasticity is only in its infancy, it is reasonable toexpect that the biological interpretation of metaplasticity will lag behind themechanistic characterization of the phenomenon. As the phenomenology andmechanisms of metaplasticity are further elucidated, it might become possibleto determine the role of input-specific metaplasticity by selectively perturbingor facilitating the induction of metaplasticity in the behaving animal.

5.5 Neuromodulator-mediated metaplasticity

The cell-wide and input-specific metaplasticity described above could beconsidered elaborations of hetero- and homosynaptic plasticity. That is, theactivation of glutamatergic synapses led to a persistent change in the struc-ture or function of either those same synapses (input-specific metaplasticity)or of allied glutamatergic synapses terminating on the same cell (cell-widemetaplasticity) such that the ability to induce subsequent synaptic plasticitywas altered. Neuromodulation by many accounts, however, involves inputpathways employing various messenger molecules, such as acetylcholine,monoamines, or peptides. It can be asked therefore, whether activation ofthese neuromodulatory pathways can also induce metaplastic effects at nearbysynapses? Certainly this seems very likely, a priori, as these modulatorytransmitters have ready access to the intracellular biochemical machinery ofneurons via binding to G-protein-coupled receptors. The discussion belowwill examine the putative role of neuromodulators in metaplasticity.

5.5.1 Acetylcholine and metaplasticity

The importance of acetylcholine (ACh) in governing the excitability state ofneural circuits and the readiness of neurons to establish synaptic plasticity is


becoming increasingly well recognized. Further, it is widely believed that abreakdown of the cholinergic innervation of cortical areas is an importantmechanism underlying the cognitive and memory disorders characteristic ofthe early stages of Alzheimer's disease. The importance of this neuromodula-tory system for gating information storage processes is covered extensively inChapter 9. Virtually all of the studies in this area, however, are concernedwith the effects that ACh receptor activation exert on concurrently inducedsynaptic plasticity or learning. We now extend this issue by asking whetherthere are residual effects of ACh receptor activation that affect the subse-quent induction of synaptic plasticity, i.e. does ACh receptor binding inducemetaplasticity?

Given the similarities between muscarinic receptor-coupled second messen-ger pathways and the corresponding mGluR pathways, it is logical to predictthat ACh might be involved in at least the priming of LTP. In support of thisprediction, Christie et al. (1995) reported that atropine, a muscarinic recep-tor antagonist, blocked the priming-induced shift to the left of the LTPinduction function in the lateral perforant path of anesthetized rats. Atropinehad no effect on control, non-primed LTP. This block of the priming effect byatropine was in fact somewhat surprising, since the priming stimulation wasdelivered to a glutamatergic input (the lateral perforant path). However, theeffectiveness of atropine in blocking the priming of LTP indicated that AChwas nonetheless being released in this preparation, either through constitutiveactivity of cholinergic neurons, through polysynaptic activation of the cholin-ergic neurons by the priming stimulation, or by extrasynaptic diffusion ofglutarnate from its release sites to nearby cholinergic terminals.

Not only did atropine block the priming-induced facilitation of LTPinduced by 2-3 trains of TBS, it also prevented the inhibition of normallystrong LTP by priming stimulation. This latter finding is consistent with anearly report that priming stimulation of the medial septal nucleus (an impor-tant source of cholinergic afferents to the hippocampus) blocked subsequentinduction of LTP in area CA1 (Newlon et al. 1991), although no pharmaco-logical treatments were used to confirm that this was a cholinergic effect.Thus, while not firmly established, cholinergic afferents appear to be apotentially important neuromodulator capable of regulating plasticity thresh-olds across time. This may occur through the individual actions of thecholinergic afferents (Newlon et al. 1991), or through their acting in concertwith other receptor systems, such as mGluRs, which can produce synergisticor additive effects on downstream second messenger pathways (Brocher et al.1992; Wang and McCormick 1993; Salt and Eaton 1996).

5.5.2 Monoamines and metaplasticity

Monoamines have been widely reported to be responsible either directly forforms of synaptic plasticity, such as facilitation at Aplysia sensorimotor


synapses, or modulation of synaptic plasticity, such as LTP and LTD inmammalian forebrain neurons. In addition, monoamines have been ascribedintriguing roles in regulating the dynamics of local circuit interactions andproviding an organizing influence on the behavioral outputs of simple neuralsystems. Many of these effects have been documented in the precedingchapters in this book. Thus, similar to the situation for ACh, it is apparentthat if any of these actions of monoamines can survive long past theirphysical presence at the synapse, then there is strong reason to believe thatthey can serve a role in metaplasticity.

A recent study in Aplysia has directly addressed the question whetherserotonin can alter the ability of synapses made by inhibitory (L30) neuronsin the siphon withdrawal reflex pathway to show short-term plasticity (Fischeret al. 1997). In the initial experiments, tail shock was found to inhibit theexpression of the short-term plasticity processes of post-tetanic potentiationand augmentation, without affecting facilitation, a very short-lived plasticitymechanism occurring largely during the period of repetitive activation. Thiswas observed at both electrophysiological and behavioral levels. This effectwas attributed to the release of serotonin by the tail shock, since bathapplication of this monoamine was found to substitute for tail shock inmodulating the short-term plasticity. The metaplastic effect of serotoninlasted at least 20 min, but was not studied at longer intervals. While both tailshock and serotonin caused a reduction in the baseline level of inhibitorysynaptic efficacy, this effect did not appear to account for the modulation ofshort-term plasticity. Whether such heterosynaptic metaplasticity can beextended to modulation of long-term plasticity remains to be investigated.

In mammalian neurons also, the potential for monoamine-mediated meta-plasticity has been recognized for some time. Both dopamine and nor-epinephrine, acting at specific receptor subtypes positively coupled to adeny-lyl cyclase, have been shown to produce long-lasting increases in cell ex-citability (e.g. decreased spike frequency adaptation) and corresponding de-creases in the slow after-hyperpolarization (sAHP) in hippocampal pyramidalcells (Gribkoff and Ashe 1984; Heginbotham and Dunwiddie 1991; Dunwid-die et al. 1992). Interestingly, a long-lasting increase in pyramidal cellexcitability has also been observed following mGluR activation (Cohen andAbraham 1997). Since the sAHP has been suggested to be an importantregulator of LTP in these neurons (Sah and Bekkers 1996), it is sensible topredict that the reduction in the sAHP or associated changes in other K+

currents may underlie mGluR priming of LTP. Catecholamine signals mayprime LTP by a similar mechanism, as suggested early on by Dunwiddie et al.(1992). However, investigations of the role(s) played by monoamines inmetaplasticity have yet to be undertaken in mammalian neurons.

5.5.3 Stress hormones and metaplasticity

Like the monoamines and , stress hormones have been shown to play an


important modulatory role in synaptic plasticity when present during theinduction stimulus. Thus, for example, there is an inverted U-shaped functionrelating plasma corticosterone (CORT) titers and the induction of LTP orprimed-burst potentiation (Diamond et al. 1992; Kerr and Abraham 1994).Furthermore, stress leads to a facilitation of homosynaptic LTD induction, asdoes activation of the low-affinity glucocorticoid subtype of CORT receptor(Pavlides et al. 1995; Coussens et al. 1997). The overall effect of glucocorti-coid receptor activation may not be the simple one of a right- or leftwardshift of the LTP induction function, but it may involve a general expansion ofthe bounds of LTD induction, combined with a reduction in the capabilityfor LTP.

Because stress hormones may remain elevated in the blood supply for sometime following a stressful event, assessing whether there exists a modulationof synaptic plasticity that outlasts the physical presence of the stress hor-mone, in accord with the metaplasticity concept, becomes rather problemati-cal. One way around this dilemma is the use of an ex vivo preparation. Here,a stressful stimulus is applied to an animal, and then hippocampal slices areprepared for electrophysiological analysis of synaptic plasticity. Using thisparadigm, extracellular CORT should be removed by the bath perfusionsystem, leaving only the downstream effects of CORT receptor activation, ifany. It should be noted that synaptic plasticity is not normally induced for atleast 2h following placement of the slices in the tissue chamber, providingample wash-out time. This method was successfully employed by Kim et al.(1996), who found that a tail-shock stress (which raises serum CORT titersto a level sufficient to activate glucocorticoid receptors), did indeed facilitateLTD and inhibit LTP in a fashion very similar to that observed in wholeanimal experiments conducted during high levels of circulating stresshormones.

5.6 Present state and future directions in the field of metaplasticity

In this chapter we have provided both theoretical and experimental supportfor input-specific and cell-wide metaplasticity. Questions remain, though, asto whether input-specific and cell-wide metaplasticity are distinct or overlap-ping phenomena. How can future studies address the issue of metaplasticity?Because metaplasticity is often concomitantly induced with other forms ofsynaptic plasticity, what precautions should be taken when interpretingfindings involving synaptic plasticity?

Input-specific and cell-wide metaplasticity are either independent or over-lapping phenomena, but it will be difficult to test the relation between thetwo types of metaplasticity. As mentioned, most of the data on cell-widemetaplasticity have arisen from in vivo manipulations, while most of the dataon input-specific metaplasticity are based on in vitro manipulations. Thereare several obvious explanations for the discrepancies of the in vitro and in


vivo experimental findings. A failure to observe cell-wide metaplasticity invitro might be due to several non-exclusive factors. First, the cellular milieu iscompromised in vitro. For example, cell-wide metaplasticity might depend ongenetic machinery that is relatively ineffective in the slice environment.Second, cell-wide metaplasticity generally occurs over a relatively long timecourse (days), whereas most slice preparations lose viability after 8 h. Thus,cell-wide metaplasticity might not have time to become manifest in vitro.Third, stimulation protocols in vitro might activate a small subset of synaptictargets, whereas in vivo manipulations, such as dark-rearing, are likely toaffect extensively synaptic activity. The expression of cell-wide metaplasticitymay very well require a high degree of afferent cooperativity, or lack thereof.Many other hypotheses can be made to explain the dearth of observedcell-wide metaplasticity in vitro. Nonetheless, it has been observed (Muller etal. 1995; Holland and Wagner 1998), and the widespread observations ofinput-specific metaplasticity are encouraging and suggest that experimentscan be designed to tap mechanisms of cell-wide metaplasticity in vitro.Because of the limitations of the in vitro preparation, however, the degree towhich input-specific and cell-wide metaplasticity overlap remains to be seen.

To date, most of the in vitro studies have reported only homosynapticmetaplasticity, an idea not consistent with the BCM theory and a cell-widesliding threshold. However, recent studies suggest that prior activity can altersynaptic plasticity in a heterosynaptic manner. For example, Frey and Morris(1997) have shown that homosynaptic induction of long-lasting LTP can leadto heterosynaptic priming. Specifically, three trains of 100 pulses (100 Hz)separated by l0min intervals to one pathway can heterosynaptically primeother synapses such that a weak tetanization (11 pulses at 100 Hz), thatnormally would result in only a short-lived potentiation, now leads to along-lasting potentiation. This intriguing result suggests that strong stimula-tion can lead to a 'synaptic tag' at potentiated synapses, but that this tag canbe captured by sufficient activation of other inputs (Frey and Morris 1997).Thus, this metaplastic event may serve to aid memory storage during particu-larly salient events (e.g. 'flashbulb memories'). A recent paper by Hollandand Wagner (1998) demonstrates that a similar priming protocol can lead toa heterosynaptic facilitation of LTD and depotentiation. The authors suggestthat this enhancement might serve to prevent the storage of inappropriateinformation or, just as likely, there may be information coded in depressedsynapses. Collectively, these studies demonstrate several features of metaplas-ticity. First, metaplastic events can affect the duration of synaptic potentia-tion in addition to altering the direction and magnitude of activity-dependentsynaptic plasticity. Second, the same priming event may have a multitude ofmetaplastic consequences, such as simultaneously changing the duration ofsynaptic potentiation as well as the magnitude of LTD for a given pattern ofinduction. Finally, the discovery of heterosynaptic metaplastic events in vitrofurther validates the possibility for cell-wide changes as envisioned by theBCM theory.


Metaplasticity has been an elusive concept to assess due to, for example,the limitations of in vitro studies described above. Another reason metaplas-ticity might be difficult to address is that the phenomenon is probably anongoing event, serving to modify continually, and minutely, the modificationthreshold. How, then, will future studies address the issue of metaplasticity?The study of LTP and LTD has been a useful gauge of activity-dependentevents and will probably continue to be so. However, a multilevel analysis ofmetaplasticity is clearly needed. Combinations of molecular, electrophysio-logical, and pharmacological studies will be needed to address the mecha-nisms involved in metaplasticity. Furthermore, to overcome the limitations ofslice studies, increasingly more studies will need to be addressed in the wholeanimal. The advent of genetic manipulations should help pin down thegenetic machinery involved in metaplasticity and will aid in vivo studies. Thecombination of genetic manipulations and behavioral analysis will furtherserve to evaluate the biological significance of metaplasticity.

Although sufficient strides have been taken to establish firmly the conceptof metaplasticity, a complicated picture is emerging in the field. The multipleeffects of metaplasticity make it a difficult concept to evaluate and cloud thestraightforward interpretations of activity-dependent studies. Because meta-plastic effects are often induced concomitantly with synaptic plasticity,caution must be exercised when interpreting activity-dependent changes.For example, biochemical correlates of LTP might be involved in theinduction of LTP, the facilitation of depotentiation, or both. Thus, anystudy examining activity-dependent mechanisms will have the difficult task ofparsing out the differences between effects associated with synaptic plasticityor metaplasticity.

In sum, it clearly has been shown that not only can synapses have theirstrength altered for prolonged periods of time, but that the ability to exhibitthis plasticity can also be altered. Thus, in addition to considering howneuromodulation can alter synaptic responses, one must now consider thatthe prior cellular activity is also capable of altering responsiveness andplasticity.

Acknowledgement

Dr Abraham's research and work on this was review was supported by theNew Zealand Health Research Council. Dr Bear and Dr Philpot weresupported by the Howard Hughes Medical Institute.

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Changing the way we perceive things:sensory systems modulationALISON R. MERCER

6.1 Introduction

Imagine you are sitting in a crowded lecture theater chewing gum. You seepeople arriving and feel the vibration as someone sits down in the chairbeside you. A waft of cologne drifts into your nostrils and you recognize itimmediately. Now, rewind the tape. Play the same scene again in your mind,but this time imagine removing all of the information you received about thescene from your five primary senses. Without sight, sound, smell, touch, ortaste, would it matter if it were Arnold Schwarzenegger who sat down besideyou?

It is easy to take for granted the fundamental role that sensory systemsplay, not only in allowing us to perceive, but also to appreciate, the worldaround us. However, all animals face a similar dilemma: the amount ofinformation available to us far exceeds an amount our brains can analyse orretain. By necessity as well as by design, therefore, sensory systems are highlyselective information gatherers, and modulation of activity within sensorypathways plays an important role in filtering out redundant information,improving signal-to-noise ratios, and ensuring that, in the face of changingconditions, sensory circuits continue to extract information optimally. Theneuromodulatory mechanisms used to achieve such goals are commonlyshared across widely divergent species.

In vertebrates, perception of sensory events relies on transfer of informa-tion to the cerebral cortex of the brain, and all of the neurons that linksensory receptors at the periphery with the spinal cord, brainstem, thalamus,and cerebral cortex are potential targets for neuromodulation. Neuromodula-tors allow our perception of sensory inputs to be affected by levels of arousal,attention, and emotional stress, and they play a key role in mediating changesin sensory information processing as a result of experience.

While sensory signaling is generally thought of as rapid, being transmittedvia fast EPSPs and IPSPs, there is increasing evidence that sensory neurons, inaddition to being targets of neuromodulation, can themselves evoke slowerneuromodulatory actions as part of their normal transfer of information.Modulation by sensory neurons plays a role in preparing the targets ofsensory input for incoming information, and in adjusting information trans-fer over time.

6

Alison R. Mercer 199

6.2 Modulation of sensory systems begins in the periphery

Our windows on the world are provided by sensory receptors that convertphysical energy into the common currency of nerve signals, a process knownas sensory transduction. Far from being immutable, the sensory transductionprocess is extremely plastic, allowing receptors to function optimally undervery diverse conditions. Some of this plasticity is inherent in the receptorsthemselves. For example, intrinsic properties of the receptors are responsiblefor sensory adaptation, which decreases the amplitude of receptor potentialsin response to sustained stimulation. However, adaptation can be producedalso through the actions of modulatory neurons. Moreover, modulatoryevents can affect the sensitivity of receptors and alter their output in responseto changes in the state of the animal.

In a diverse range of vertebrate and invertebrate species, the biogenicmonoamine, serotonin (5-hydroxytryptamine, 5HT) has been strongly impli-cated in modulating the function of peripheral sensory organs. In some cases,the significance of serotonergic input has yet to be established, but in othercases, the functional implications of 5HT modulation of sensory organs areclear.

6.2.1 Modulation of taste transduction, a neuronal flavor enhancer

Chemical senses play an important role in determining the flavor and palata-bility of foods, and behavioral studies suggest that, at least in some species,taste thresholds and satiety are affected by peripheral 5HT (Montgomery andBurton 1986a,b; Alvarado et al. 1990; Yen and Fuller 1992). Taste budchemosensory responses in the mudpuppy, Necturus maculosus, are modifiedby 5HT released from cells located at the base of the bud (Fig. 6.1A). Eachtaste bud houses a cluster of chemoreceptors with processes that terminate ina specialized chemosensory membrane at the apical pore of the bud (Roper1989). At the base of the bud, receptor cells synapse with the afferent nerve,and also converge onto a small number of taste bud cells which, unlike thereceptors, are devoid of apical processes. Among them are basal cells thatcontain 5HT (Kim and Roper 1995), which is released when the cells aredepolarized (Welton and Roper 1992; Delay et al. 1993; Nagai et al. 1998).Exogenous application of 5HT, or repetitive stimulation of the basal cells,leads to hyperpolarization of the receptors, and increases both the receptormembrane input resistance and the amplitude of receptor potentials elicitedby chemical stimulation (Ewald and Roper 1994; Fig. 6.1B,C). These eventsare postulated to enhance the electrotonic propagation of receptor potentialsfrom the chemosensitive (apical) region of the receptor cell to the basal(synaptic) processes, effectively increasing the chemosensitivity of the tastereceptors (Ewald and Roper 1994). Recent studies reveal that 5HT modulatesa calcium current (ICa) in these cells. Interestingly, ICa is potentiated by 5HTin some cells, but inhibited in others (Delay et al. 1997). The functional

200 Sensory systems modulation

significance of this dual serotonergic modulation of ICa is unclear, but mayinfluence the animal's ability to discriminate certain taste stimuli.

6.2.2 Changing pain reception

The potential impact of peripheral modulation of sensory events is vividlyillustrated by considering the effects of turning up the gain on pain. 5HT isone of many substances released during inflammatory responses (recentlyreviewed by Sidall and Cousins 1995; Markenson 1996), and it activatesprimary afferent nociceptors directly through 5HT3 receptors (Richardson etal. 1985). Acting via 5HT2 receptors (Todorovic and Anderson 1990), 5HTcan potentiate pain induced by other mediators, such as bradykinin, which isreleased following tissue injury, while the actions of 5HT on 5HTla receptorscan produce hyperalgesia (Taiwo and Levine 1992). Hyperalgesia, or sensiti-zation, occurs if there is intense, repeated stimulation from tissue damage orinflammation (see Markenson 1996). One example is the pain caused bymicturition in the presence of a urinary tract infection (Dubner and Ruda1992), where a lowered threshold for activation of the primary afferentnociceptors leads to innocuous stimuli causing severe pain.

6.3 Behavioral changes can involve modulation of primarysensory neurons

The complexity of neural systems makes the task of relating events at acellular level with changes in behavior a challenging one. Nonetheless, a

Fig. 6.1 A. Schematic showing the proposed synaptic relations in Necturus tastebuds. Evidence suggests that chemoreceptors converge onto basal cells, some of whichcontain the biogenic monoamine, 5HT. The insert shows an enlargement of the basalregion of the taste bud. It has been postulated (Ewald and Roper 1994) that synapticinput from receptor cells (upper arrow), leads to release of 5HT from basal cells(middle arrow) which modulates the receptor cells, altering their output onto theafferent nerve (lower arrow). B,C. 5HT modulation of chemoreceptor sensitivity inNecturus taste buds. B. Receptor potentials elicited every 12s by focal application ofKC1 to the pore of the taste bud. KC1 stimuli were alternated with brief hyperpolarizingconstant current pulses to test the input resistance (downward deflections in thetrace). Exposure to 100/uM 5HT increased the amplitudes of receptor cell responsesand receptor cell input resistance. C. Recordings (superimposed) of KC1 responses andinput resistance in the basal process of a receptor cell at an expanded time-scale before(control) and during 5HT application. The dashed vertical line coincides with theonset of the receptor potential recorded in the apical end of the taste bud. (Reprintedfrom Ewald and Roper 1994 with kind permission from The Society for Neuroscience.)


number of studies provide convincing evidence that changes at a behaviorallevel can result, at least in part, from the modulation of primary sensoryneurons. This can occur through changes in the responsiveness of pr imarysensory neurons, such as changes in cell excitabil i ty, as well as throughalterations in the strength of synaptic outputs onto follower neurons. As aconsequence of modulatory events at this level, signals that are transmitted tothe central nervous system in response to a par t icular form of physicalstimulation can vary greatly depending upon the state of the animal.


6.3.1 Mechanoafferent excitability is dependent uponbehavioral state

Rapid sensory feedback from mechanoreceptors is important for the controlof movement. For this reason, one might suppose that such sensory inputwould be a reliable indicator of the physical stimulus. Yet, an individualmechanosensory neuron may be called upon to participate in very differenttypes of motor behavior requiring different kinds of input. For example,when an animal is standing still, a proprioceptor may report informationabout tonic limb position to maintain upright posture; yet when the animal ismoving, the same proprioceptor may be responsible for relaying phasicinformation needed for the animal to negotiate the terrain. Many studieshave now shown that the response properties of mechanosensory neurons canbe altered significantly by modulatory input (Pasztor 1989).

Neuromodulatory events can switch a sensory neuron into an altered state,allowing it to respond differently under a variety of circumstances. Forexample, the biogenic amine octopamine (OA), which plays an importantrole in the preparation and maintenance of flight in locusts (Orchard et al.1993), changes the response properties of a set of wing proprioceptors in thisinsect (Ramirez and Orchard 1990). Input to flight neurons from thesemechanoreceptive cells is important for the correct phasing of the flightmotor pattern, and for maintenance of the wing beat frequency. OA enhancesthe responsiveness of the wing stretch receptor to sinusoidal wing move-ments, causing it to fire more action potentials on each wing beat cycle. Thus,in preparation for flight, OA is released, thereby enabling the reflex feedbackpathway to participate effectively in this crucial behavior. Conversely, whenthe reflex activation of the sensory neuron is not needed, its excitability isreduced, perhaps preventing unwanted activation of flight neurons.

Another good example of modulation of proprioceptor responsivenesscomes from the crayfish muscle receptor organ (MRO). The MRO isanatomically and functionally equivalent to the vertebrate muscle spindle inthat it innervates a receptor muscle and participates in reflex responses. Thesereflexes control the extension of the animal's abdomen (or tail), which it usesboth for tonic posture and for escape locomotion (tail-flipping). The ex-citability of the receptor cell is altered by the biogenic amines, 5HT and OA,as well as by the neuropeptide proctolin (Pasztor 1989). Thus, the number ofaction potentials produced by this sensory neuron will depend not only uponthe stretch of the muscle, but also upon the concentration of neuromodula-tory substances present at the time.

The actions of a particular neuromodulatory substance are not necessarilythe same at all sites in the animal. For example, 5HT and OA increase theresponsiveness of the crayfish MRO to stretch, but proprioceptors in the ovalorgan of the crayfish, which are responsible for relaying information aboutgill movements, become less responsive as a result of the modulatory effectsof these amines (Fig. 6.2A,B). Proctolin, on the other hand, increases theresponsiveness of both types of proprioceptor (Pasztor 1989). The actions of

Fig. 6,2 Different sensory receptors are di f ferent ia l ly modulated in c r a y f i s h . A, Theoval organ responds with a brief burst of actions potentials in response to stretch of asensory strand on a structure near the gills. In the presence of serotonin or octopaminc,the response is decreased in magnitude, whereas it is enhanced in the presence of thepeptide proctolin. B. On the abdominal muscle receptor organ (MRO), the effects ofserotonin and octopamine arc d i f f e r e n t from their effects on the ova! organ. Likeproctolin, serotonin and octopamine increase the response of the MRO to stretch of aspecialized muscle in the abdomen of the animal , (Data adapted from Pasztor 1989.)C. The effect of serotonin on synaptic potentials evoked by primary sensory receptorscan be dependent upon the social status of the crayfish. For example, when anafferent nerve containing mechanoreceptors from the tai lfan is s t imulated, it evokes amonosynaptic FPSP in the lateral giant (I.G) neuron. In socially dominant animals,serotonin (5HT) increases the strength of this synapse, whereas in socially subordinatecrayfish, serotonin has an opposite modulatory effect, decreasing the strength of thesynapse, (Data adapted from Yeh et al. 1996. Crayfish drawing modified fromHuxley 1880.)

neuromodulatory substances can also vary between species (Pasztor andMacMillan 1990); therefore, generalizations about neuromodulators andtheir functions must be made with extreme caution.

Other studies have shown that 51 IT and OA play a role in determining theposture of the a n i m a l (Livingstone et al. 1980) and that there is a stronginteraction of serotonin with the social interactions of the an imal (Huber etal. 1997). Thus, d i f fe rent behavioral conditions can alter the way in which areceptor responds to a physical stimulus.



6.3.2 Presynaptic control of sensory input can gate reflexes

Not only can the responsiveness of sensory neurons be altered by neuromod-ulation, but their output can also be regulated: the flow of information intothe nervous system can be depressed or enhanced by modulatory influences.Presynaptic control over sensory input is very common. For example, there isan extensive literature about primary afferent depolarization (PAD), aGABA-mediated, chloride-dependent depolarization of sensory afferent termi-nals that decreases the effectiveness of incoming action potentials at evokingtransmitter release (Kennedy et al. 1974; Levy 1977; Nusbaum 1994). PAD isthought to gate sensory input during different behavioral states, such as sleep(Cairns et al. 1996), and in various types of behavior, such as locomotion(Cattaert et al. 1992; Burrows and Matheson 1994; Vinay et al. 1996). Inmany cases, the effect of the sensory input is dependent upon the phase of thelocomotor cycle with which it coincides, leading to a phenomenon calledreflex reversal (Pearson and Collins 1993; Pearson 1995).

In addition to GABAergic regulation of sensory terminals, other mecha-nisms provide a means for locomotory circuits to control the transmission ofmechanosensory information. For example, in the lamprey and in the Xeno-pus embryo, 5HT can decrease the synaptic efficacy of sensory neurons in thespinal cord (Sillar and Simmers 1994; El Manira et al. 1997). In Xenopus,5HT acts via a second messenger system to decrease T-type and highvoltage-activated calcium currents in Rohon-Beard sensory neurons, causinga decrease in synaptic output (Sun and Dale 1997). This 5HT-induced decrease in synaptic efficacy seems to be a mechanism designed toprevent overstimulation through sensory feedback, as 5HT also increases theintensity of the swimming behavior through its actions on interneurons (seeChapter 8).

The strength of sensory neuron synapses can be not only down-modulated, but also enhanced through the actions of neuromodulatoryinputs. Moreover, the sign of the effect can be dependent upon the behavioralstate of the animal (e.g. Fig. 6.2C). In crayfish that have been reared inisolation from other crayfish, 5HT enhances the effective strength of anelectrical synapse between mechanosensory afferents and their follower cell,the lateral giant (LG) interneuron. However, if two crayfish are placed in thesame holding tank, within half an hour, one will establish social dominanceover the other and this will alter the action of 5HT on the primary afferentsynapse of the subordinate. In subordinates, 5HT decreases the strength ofthe primary afferent to LG synapse, whereas in dominant or isolated animals,the same synapse is enhanced by this amine (Yeh et al. 1996). The differenteffects of 5HT at this synapse are thought to mediate a difference in thethreshold for tail-flipping behavior exhibited by dominant and subordinatecrayfish (Krasne et al. 1997). Thus, the strength of this sensory neuronsynapse is under neuromodulatory control, and that control is itself deter-mined by the state of the animal (see Chapter 10 for more about modulationof modulation).


6.3.3 Sensitization of Aplysia reflexes involves modulationof mechanosensory neurons

Enhancement of sensory neuron synapses and excitability plays an importantrole in behavioral sensitization of withdrawal reflexes in the marine mollusc,Aplysia californica. A gentle prod to the tail or siphon of Aplysia leads to adefensive withdrawal (Fig. 6.3A), the amplitude and duration of which isenhanced by prior presentation of a noxious stimulus, such as a shock to thetail (e.g. Fig. 6.3B). This behavioral sensitization is due, at least in part, tochanges in the responsiveness of the mechanoreceptor sensory neurons thatmediate the reflex response, and the effects of tail shock on these neurons aremimicked by 5HT (Brunelli et al. 1976; Walters et al. 1983; Abrams et al.1984). Like tail shock, 5HT leads to an alteration in a number of properties,including a broadening of action potentials in the sensory neurons, enhance-ment of cell excitability, and facilitation of transmitter release from thesensory neurons onto their follower cells (reviewed by Kandel and Schwarz1982; Carew and Sahley 1986; Byrne 1987; Hawkins et al. 1993; Fig. 6.3C).Facilitation of transmitter release occurs as a consequence of the increase incalcium influx that results from 5HT-induced spike broadening, and a cal-cium-independent process, perhaps involving transmitter mobilization or exo-cytosis, also appears to be involved (Gingrich and Byrne 1985,1987; Hochneret al. 1986a,b; Braha et al. 1990). Increasing the output from these sensoryneurons increases the magnitude of excitatory postsynaptic potentials in themotor neurons, thereby increasing the drive on the muscles responsible forproducing defensive withdrawal.

A great deal is known about the cellular mechanisms that underlie thesechanges. The effects of 5HT on spike duration and cell excitability are theresult of 5HT modulation of K+ conductances in the cells (Fig. 6.3D). Twoof the principal K+ currents involved are a voltage-dependent current thatresembles the delayed rectifier K+ current, IK,V (Baxter and Byrne 1989,1990), and a relatively voltage-independent K+ current, IK,S (Siegelbaum etal. 1982). Evidence suggests that 5HT-modulation of IK,V contributes signifi-cantly more to spike broadening than modulation of IK,S, but that IK,S

mediates most, if not all, of the changes in cell excitability (Byrne et al.1990). These modulatory actions involve at least two different receptors(Mercer et al. 1991; Li et al. 1995), one of which is coupled to adenylylcyclase and leads to increased production of adenosine cyclic monophosphate(cAMP) and activation of a protein kinase A (PKA) pathway (Bernier et al.1982; Abrams et al. 1984; Ocorr and Byrne 1985; Ocorr et al. 1986), andthe other of which is coupled to phospholipase C, which leads to diacylglyc-erol (DAG) formation and the activation of protein kinase C (PKC, Sacktorand Schwartz 1990; Sugita et al. 1992). In Aplysia sensory neurons, 5HT-in-duced increases in cell excitability are mediated almost entirely by PKA (Kleinet al. 1986; Baxter and Byrne 1990; Ghirardi et al. 1992), whereas both PKAand PKC contribute to spike broadening in these cells (Goldsmith andAbrams 1992; Sugita et al. 1992).

Fig. 6.3 Modulation of primary sensory neurons underl ies behavioral sensi t iza t ion inthe marine mollusc, Aplysia californica. A. Defensive-withdrawal of the siphon andgil l of A p l y s i a in response to a weak tact i le s t imulus (jet stream of water) to thesiphon. The parapodia and mantle shelf on the dorsal surface of the an ima l have beenretracted to show the siphon and g i l l . A1, Siphon and gill in a relaxed position. A2.GilI and siphon after reflex withdrawal in response to s t imulat ion. B. Time course ofsensitization after a single strong electrical shock to the tail. The siphon-withdrawalreflex was tested once every 0.5 h and the mean of each two consecutive responses isshown. Even at th is low rate of stimulation some habi tuat ion is apparent. However,after the third siphon s t imulus the experimental group received a single shock to thet a i l (arrow). After this sensi t izing s t i m u l u s the experimental animals had s i g n i f i c a n t l ylonger withdrawals than controls for up to 4h. Cl. 5HT is thought to he releasedfrom a facil i tatory interneuron (IN) that enhances the synapric connection betweenthe sensory neuron (SN) and its follower cell , the motor neuron (MN). C2-3. Stylizedrepresentations of control and facilitated responses, C2. Prior to s t imulat ion of thefacilitatory interneuron. An action potential in the SN leads to an EPSP in the MN.C3. After s t imulat ion of the facil i tatory interneuron. SN action potential is broader,ca lc ium i n f l u x ( /L.L) is increased, and EPSP a m p l i t u d e in the MN is enhanced. D.Current model of the m u l t i p l e processes that lead to short-term f a c i l i t a t i o n of Ap lys iasensory neurons. 51 IT released from a facilitatory In terneuron as a result of ta i l shock(sensitizing st imuli) binds to at least two distinct classes of receptors, leading to thetransient activation of two intracellular second messengers, cAMP and DAG. Actingvia their respective kinascs (PKA and PKC), these second messengers a f fec t mult iplec e l l u l a r processes, the combined effects of which lead to enhanced transmitter releasewhen the sensory neuron fires an action potential. (A reprinted wi th permission fromKandel 1976, WH Freeman and Company, San Francisco. B reprinted from Kandeland Schwartz 1982 with k i n d permission of The American Association for theAdvancement of Science. C,D reprinted from Byrne and Kandel 1996 with kindpermission from the Society for Neuroscience.)


Studies of Aplysia sensory neurons provided the first evidence forheterosynaptic facilitation, that is, enhancement of transmitter release by onepathway (in this case, the mechanoreceptor sensory neurons of Aplysia) as aresult of activity in another (modulatory) pathway (activated, in this case, bynoxious stimuli). Opportunities for relating responses observed at a behav-ioral level with events occurring at the cellular level make Aplysia particu-larly attractive as model system for exploring the cellular basis of behavior,and extensive analyses of simple forms of learning in Aplysia have providedimportant insights into learning-related synaptic modulation (Byrne et al.1993; Hawkins et al. 1993; Byrne and Kandel 1996; Carew 1996).

6.3.4 Insect eyes earn compound interest

5HT has also been implicated in modulating the responsiveness of sensoryneurons in the visual system. In particular, 5HT appears to switch insectphotoreceptors from a high-acuity, low-sensitivity day state to a low-acuity,high-sensitivity night state (reviewed by Weckstrom and Laughlin 1995). Thismodulation of sensory receptor sensitivities is likely to be important forinsects such as the locust, Schistocerca, which is active during the day, butmigrates at night. Stimulation with light gates an inward current in insectphotoreceptors that depolarizes the cells and activates voltage-sensitive K+

currents in the photoreceptor membrane. These outward K+ currents workagainst the light-gated conductance and have a significant influence on thesensitivity, signal-to-noise ratio, and frequency response of the receptors(Weckstrom et al. 1991).

Whole-cell K+-current profiles of photoreceptors from fast-flying diurnalinsects are dominated by large delayed-rectifier K + conductances (Fig. 6.4A),whereas in slow-flying species active at dusk or at night, fast, transient(A-type) K+ currents dominate (Fig. 6.4B). Perhaps not surprisingly, thephotoreceptors of Schistocerca express both transient and sustained K+

currents (Weckstrom 1994): sustained currents dominating during the day(Fig. 6.4C) and transient currents dominating at night (Fig. 6.4D) (Cuttle etal. 1995). 5HT modulation of these currents apparently assists in switchingthe eye from the day to the night state (Fig. 6.4E) (Cuttle et al. 1995; Heversand Hardie 1995), but why does 5HT target the K+ currents in these cells?

To ensure effective photon capture under low-light conditions, insectphotoreceptors, like vertebrate rods, must house an extensive array of pho-toreceptive membrane, but this creates a large capacitative load on the cells.In darkness, this is no problem. The dark-adapted phototransduction cascadeoperates relatively slowly and, therefore, the slow membrane time constant(approximately 4 ms) resulting from the large cell membrane capacitance haslittle adverse effect on photoreceptor performance. In darkness, mostvoltage-activated K+ channels in the membrane are closed and cell inputresistance is high. Under these conditions, the gain of the system is high,enhancing the likelihood that individual photon absorptions will give rise to

Fig. 6.4 Single-electrode, voltage-clamp recordings of voltage-gated K+ currents ininsect photoreceptors. Outward currents were elicited by step depolarizations over thephysiological response range. The non-inactivating delayed rectifier current, IKV,found in the blowfly, Calliphora vicina (A), typifies 'fast' photoreceptors found inrapidly flying diurnal species (Laughlin and Weckstrom 1993). The inactivating(A-type) currents recorded in the tipulid, Nephrotoma quadrifaria (B), are found in'slow' photoreceptors of slow flying, crepuscular species (Laughlin and Weckstrom1993). Photoreceptors of the locust, Schistocerca, switch diurnally between a daystate (C), similar to 'fast' cells, to a night state (D) similar to 'slow' cells, a change thatcan be induced by exogenous application of 5HT to day-state cells (E). (Reprintedfrom Cuttle et al. 1995 with kind permission from Springer.)

discrete photoreceptor responses. Fast, transient (A-type) K+ currents areparticularly prominent under these conditions and are believed to suppressany large voltage transients that may be generated by these highly sensitive,dark-adapted cells. However, this situation is not appropriate for normaldaylight conditions.

The photoreceptors of fast-flying diurnal species do not need to be sosensitive to light. What they require is excellent temporal resolving power inorder to detect the details of images that move rapidly across the visual fieldduring flight (Laughlin and Weckstrom 1993). In daylight conditions thephototransduction cascade operates much more rapidly and a slow mem-brane time constant could now place severe limits on the frequency responseof the cell. The activation of a sustained delayed rectifier K+ conductance,together with the light-gated current, lowers the membrane resistance of the



photoreceptor, reducing the receptor membrane time constant. In this way,the delayed-rectifier K + conductance serves to enhance the response dynamicsof the cells. Because the delayed rectifier current works against the light-gatedconductance, the sensitivity of the photoreceptor in bright light is reducedand the receptor potential is maintained in a range where sensitivity tochanges in light level is greatest. In bright daylight, the light-gated current isdominated by the delayed-rectifier conductance. Under these conditions, lightstimuli produce transient responses and high-frequency components are sparedfrom attenuation (Weckstrom et al. 1991; Juusola and Weckstrom 1993;Laughlin and Weckstrom 1993; Juusola et al. 1994). These mechanisms areextremely effective. The fastest known photoreceptor response is found in thelight-adapted eye of the blowfly (Laughlin and Weckstrom 1993).

In the presence of 5HT, A-type currents predominate, making the insecteye more adaptive to the night state (Cuttle et al. 1995; see Fig. 6.4). WhileK+-channel modulation typically involves up- or down-regulation of channelactivity (e.g. Siegelbaum et al. 1982), in insect photoreceptors, maximalamplitudes of fast, A-type and delayed rectifier-like currents appear to belargely unaffected by 5HT. Instead, exogenous applications of this amineinduce a reversible shift in the voltage dependence of the channels (Heversand Hardie 1995). In daylight, A-type currents would normally be completelyinactive over most of the photoreceptor's operating range. However, in thedark-adapted eye, 5HT is apparently responsible for shifting the operatingrange of the channel to more positive values, allowing transient, A-typechannels to become effective in opposing transient depolarizations, whilemaintaining the high membrane time constant.

6.4 Components of a sensory pathway can be modulatedindependently, or in a coordinated fashion

It is often the case that in response to changing conditions, not one, but manycomponents of a sensory pathway are altered in concert through the actionsof one or a number of neuromodulators. The coordinated actions of multipleneuromodulatory systems are well illustrated by modulatory events thatoccur, for example, in primary olfactory centers of the brain or in thethalamus, but nowhere are the well-orchestrated actions of a single neuro-modulator, in this case the catecholamine dopamine (DA), demonstratedmore clearly than in the vertebrate retina.

6.4.1 Adaptation of the vertebrate eye

One strategy adopted by many vertebrates to deal with the enormous rangeof light intensities is to shift from the use of one type of photoreceptor (rods)at low light levels to another (cones) at high light intensities (reviewed byWitkovsky and Dearry 1992). Vertebrates in which the pupillary aperture is

Fig. 6.5 Dopamine (DA)-induced retinomotor movements in the teleost retina. Lightonset, or a circadian subjective day signal, stimulates tyrosine hydroxylase, increasingDA synthesis and enhancing DA release. DA activation of non-synaptic D2 receptorson rod, cone, and RPE cells leads to a reduction in intracellular cAMP and light-adaptive cone contraction, rod elongation, and RPE pigment dispersion. (Reprintedfrom Witkovsky and Dearry 1992 with kind permission from Elsevier Science.)

relatively fixed, such as fish, amphibians, and birds, exhibit particularlystriking retinomotor movements in response to changing light conditions(Fig. 6.5). These morphological changes involve the contraction or elongationof the inner segment of the photoreceptors and redistribution of melaningranules in retinal pigment epithelial (RPE) cells (Dearry and Burnside 1986).These events are driven, at least in part, by DA (Dearry and Burnside 1986,1988; Witkovsky et al. 1988; Dearry et al. 1990). DA is released from asparsely distributed population of cells that form an extensive network ofprocesses across the retina. In some species the dopaminergic neurons areinterplexiform cells (IPCs), whereas in others, DA is released from a specialclass of amacrine cell (reviewed by Witkovsky and Dearry 1992; Fig. 6.6A).When the retina is stimulated by light, DA is released and binds to non-synaptic D2 receptors on cone, rod, and RPE cells, activating a pertussistoxin-sensitive G protein, which inhibits adenylyl cyclase activity in the cells



(Fig. 6.5). The resulting fall in intracellular calcium levels leads to light-adap-tive retinomotor movements: rod cells elongate and move out of the way,cone cells become shorter and fatter so that they collect more light, andpigment granules disperse into the long apical processes of the RPE cells,providing optical isolation of the cones and thereby improving the spatialresolution properties of the eye. In the dark, these movements are reversed:cones elongate, rods contract, and pigment granules aggregate into the basalends of RPE cell bodies. However, the induction of retinomotor movementsis just one of many ways that DA contributes to adaptation of the vertebrateeye to light (Dowling 1986, 1991; Djamgoz and Wagner 1992; Witkovskyand Dearry 1992). The two well-documented modulatory actions of DAdiscussed below do not involve direct modulation of the photoreceptors, butlead indirectly to changes in photoreceptor function.

Under daylight conditions, retinal circuitry ensures that retinal ganglioncells respond optimally to contrast in their receptive fields. This is notsurprising, as areas of contrast usually delineate the edges of objects and,therefore, are of particular interest to the animal. However, by reducing theresponses of retinal ganglion cells to regions of spatially uniform illumina-tion, retinal circuits reduce the redundancy in messages that are relayed to thebrain. This filtering takes place at the first synaptic layer of the retina andinvolves a process known as lateral inhibition. Lateral inhibition is mediatedby retinal horizontal cells (Fig. 6.6B), and the activity of these cells isregulated by DA.

Stimulation with light reduces L-glutamate release from the photoreceptorscausing the horizontal cells to hyperpolarize. In daylight, these inhibitorysignals spread laterally for long distances, via electrical synapses betweenhorizontal-cell processes (Fig. 6.7A). These signals generate a ring of inhibi-tion (the inhibitory or antagonistic surround) around the center region of thereceptive field that serves to reduce redundancy in the signals that are sent tothe brain (reviewed by Dowling 1986, 1991). Under conditions of low lightintensity, however, the inhibitory signals transmitted via the network ofhorizontal cells are no longer adaptive. To ensure that the retina continues toextract information optimally, therefore, retinal circuit properties must bealtered, and DA plays a central role in this process.

DA regulates the strength of lateral inhibition and center surround antago-nism as a function of adaptive state. After prolonged periods of darkness, theantagonist surround responses of many ganglion cells are reduced in strength,or even eliminated. DA rewires the retinal circuitry by uncoupling cells at gapjunctions. Electrical junctions between horizontal cells provide DA with oneof its principal targets (Teranishi et al. 1983; Piccolino et al. 1984; Lasaterand Dowling 1985; DeVries and Schwartz 1989). Activation of DA receptorson the horizontal cells switches on adenylyl cyclase (Van Buskirk andDowling 1981), triggering a rise in cAMP and the activation of cAMP-depen-dent PKA (Lasater 1987; De Vries and Schwartz 1989, 1992; McMahon1994). Phosphorylation of the gap-junctional channels by PKA alters their


conductance, reducing both the duration and the frequency of channelopenings (McMahon et al. 1989; McMahon and Brown 1994). As a result,the distance over which signals can spread laterally through the horizontal-cellsyncytium is reduced (Fig. 6.7B), and this in turn reduces the inhibitorysurrounds of ganglion cell receptive fields.

DA also reduces the responsiveness of horizontal cells to light (Hedden andDowling 1978; Mangel and Dowling 1985). Horizontal cell responses to lightresult from the reduction in transmitter release (L-glutamate) from the pho-toreceptors. However, DA enhances ionic conductance changes elicited byL-glutamate. In the presence of DA, therefore, the light-induced reduction oftransmitter release from the photoreceptors on horizontal cells is renderedless effective, and the amplitude of horizontal cell responses to light isreduced. The effect of DA on the glutamate-gated current in horizontal cellsis also mediated through a cAMP-dependent mechanism (Knapp and Dowl-ing 1987). However, in contrast to its effects on the gap-junctional channelsof horizontal cells, cAMP alters the gating kinetics of the glutamate-gatedchannels by increasing their open probability (Schmidt et al. 1990). Together,these modulatory actions of DA reduce lateral inhibition and surroundantagonism, enhancing the eye's function as a photodetector. Changing lightintensities, therefore, triggers an array of modulatory events in the vertebrateretina, which ensure that the information-gathering properties of the eye

Fig. 6.6 Synaptic connections of cells in the vertebrate retina. A. Electrical signalsgenerated by photoreceptors in response to light are passed to bipolar cells, thenconverted into action potentials in retinal ganglion cells for transmission to the brain.The visual signal is divided into ON and OFF channels at the photoreceptor tobipolar cell synapse and this is reflected in the two major classes of ganglion cells,ON-cells and OFF-cells. Each ganglion cell responds to light directed to a specificregion of the retina, known as the receptive field of the cell. Ganglion cell receptivefields are roughly circular and have a center with an antagonistic surround. ON-cellsincrease their firing rate when light is directed to the center of their receptive field, butlight applied to the surround suppresses the firing of these cells. The reverse is true ofOFF-cells. OFF cells are inhibited by light applied to the center of their receptive field,but excited by light directed at the surround. B. Lateral inhibition resulting from theinhibitory action of horizontal cells. Annular light hyperpolarizes the underlying cones(a). Postsynaptic horizontal cells (stippled) hyperpolarize (b). This signal spreadsthrough gap junctions (arrows) to neighboring horizontal cells, where it depolarizescones at the dark center of the annulus (c) via a sign-inverting synapse. Conedepolarization is communicated to bipolar cells via sign-preserving (d) or sign-reversingsynapses. Dopaminergic neurons, in this case interplexiform cells (IPCs), modulategap junctions between horizontal cells. Boxed insets represent cell voltage changes asa function of time after a flash of light. (A reprinted from Nakanishi 1995 with kindpermission of Elsevier Science. B reprinted from DeVries and Baylor 1993 with kindpermission of Cell Press.)


remain optimal, and DA, acting at multiple sites in the vertebrate retina,plays a pivotal role in this process.

6.4.2 (Controlling what the nose knowsThere are many interesting parallels between the organization of the verte-brate retina and the olfactory bulb. As in the retina, modulatory events in the

Fig. 6.7 The effects of changing light conditions on the electr ical coupling betweenhorizontal cells in white perch retina revealed by Inciter-yellow injection. A. Lucifer

yellow-injected cells in a light-sensitized retina. The dye was assumed to be injected

into the horizontal cell in the center of the micrograph showing the brightestfluorescence. The dye diffused into a large number of surrounding cells, indicating acnnsiderable amount of dye coupling. The cell was injected for 14 min with 20 nAhyperpolarizing current pulses. B. l.ucifer yellow-injected cells in a prolonged darkadapted retina. Dye diffused from the injected cell (center) into only a few surroundingcells, and these cells show only weak fluorescence. This cell was injected for 15 minwith 20 nA hyperpolarizing current pulses. Fluorescence micrograph calibration bar is50 um. (Reprinted from Tornqvist et al. 1988 with kind permission of the Society forNeuroscience.)

olfactory system occur at many levels, including that of the primary olfactoryreceptor neurons, For example, there is now evidence that the sensitivity ofprimary sensory neurons in the olfactory epithelium can he directly modu-lated through phosphorylation of cyclic-nucleotide-gated channels (Muller et



al. 1998), but the transmitter responsible for such a modulatory action hasnot yet been identified.

Modulatory events also occur at multiple sites within the olfactory bulb.Olfactory receptor neurons terminate in discrete spheres of olfactory-bulbneuropil, called glomeruli, and synapse with olfactory-bulb output neurons(mitral cells and tufted cells), and with periglomerular cells (Fig. 6.8A).Periglomerular cells are believed to mediate lateral inhibition betweenglomeruli (Mori 1987), and lateral inhibition is also mediated by a secondgroup of inhibitory interneurons, called granule cells, which make reciprocaldendrodendritic synapses with the mitral/tufted cells (Rall et al. 1966; Mori1987). Lateral inhibition is thought to sharpen peaks of activity in the mitralcell population and, as in the retina, to eliminate the transmission of redun-dant information (Mori 1987; Buonviso and Chaput 1990, Mori et al. 1992;Fig. 6.8B). The strength of lateral inhibition in the olfactory bulb is modu-lated by DA, and also by noradrenaline (NA) (see Trombley and Shepherd1993).

There is a subset of periglomerular neurons that contains DA in addition toGABA (Gall et al. 1987). The expression, in these neurons, of the rate-limit-ing enzyme involved in DA synthesis, tyrosine hydroxylase, can be reducedsignificantly by olfactory deprivation (Baker 1990; Wilson and Wood 1992).Olfactory deprivation not only leads to a dramatic reduction in the DAcontent of the olfactory bulb (Brunjes et al. 1985; Wilson and Wood 1992),but also enhances the responsiveness of mitral and tufted cells to odors(Guthrie et al. 1990). It has been suggested that DA depletion may releaseafferent input from both recurrent and lateral inhibition, thereby increasingthe number of mitral/tufted cells responding to odors at a given intensity.This facilitation occurs at the expense of a decrease in odor discrimination(Wilson and Sullivan 1995) and is reminiscent of the dark-adapted retina,where DA-induced reduction of lateral inhibition decreases the strength of theinhibitory surrounds of retinal ganglion cell center-surround receptive fields.

The vertebrate olfactory bulb also receives a dense projection from thelocus coeruleus, the site of the largest collection of NA-containing cells in thebrain (Foote et al. 1983). Activation of the locus coeruleus has recently beenshown to increase mitral cell responses to weak stimulation of the olfactoryepithelium (Jiang et al. 1996). However, the glomerular layer of the olfactorybulb, in which axons of olfactory receptor neurons synapse with mitral celldendrites, is completely devoid of NA fibers. Most noradrenergic processesterminate in the internal plexiform and granule cell layers of the bulb(McLean et al. 1989), and several lines of evidence suggest that NA-inducedincreases in mitral cell excitability result, at least in part, from disinhibitionof mitral cell activity through inhibition of synapses between mitral cells andgranule cells. Increased spontaneous mitral cell discharge elicited by exoge-nous application of NA to the turtle olfactory bulb, for example, can beoverridden by GABA, the inhibitory transmitter released by granule cells(Jahr and Nicoll 1982). In vitro studies suggest that these effects are

Fig. 6.8 Synaptic connections of cells in the vertebrate olfactory bulb. A. Informationis transmitted from olfactory receptor neurons to mitral and tufted cells in discretespheres of neuropil, called glomeruli (dashed circles). In each glomerulus, receptorneurons synapse not only with mitral/tufted cells, hut also with periglomerular (PG)cells, which mediate lateral inhibition between glomeruli. Mitral/tufted cells alsoform dendrodendritic synapses with granule cells, inhibitory interneurons that havebeen implicated in feedback and lateral inhibition. B. Lateral inhibition in theolfactory bulb. Odorant-induced impulses in a strongly-activated mitral cell (center)excite postsynaptic granule cells (stippled) through sign-preserving synapses. Theexcitatory responses spread to neighboring granule cells through gap junctions,producing inhibitory postsynapric potentials in adjacent mitral cells and a ring oflateral inhibition. As a result, weak inputs to the adjacent mitral cells fail to excite thecells and redundant information is filtered before the signals are transmitted to thebrain. Granule cell activity is modulated by efferent inputs to the olfactory bulb. (Areprinted from Nakanishi I995 with kind permission of Elsevier Science. B reprintedfrom DcVries and Baylor 1993 with kind permission of Cell Press.)


Fig. 6.9 A. Schematic drawing of a dorsal view of the 5HT-immunoreactive neuronthat arborizes- in the right antennal lobe of the moth, Manduca sexta. A s imi l a rneuron arborizes in the left antennal lobe. B. Laser scanning confocal micrograph of5HT-immunorcactiveprocesses labelled with Cy 3-conjugated antibody, in the antennallobe. Note the intense ramification in the glomeruli (e.g. arrowheads). Cal ibra t ionbar = 100 um. C,D. 5HT modulation of antennal- lobe neurons of Manduca sexta. C.The n u m h c r of action potentials elicited by ,1 constant current pulse (2 nA, 100ms) isincreased by 5HT, an effect reversed by washing in 5HT-free saline (Wash). 1).Modula t ion of K1 currents by 5HT. Outward current1, prior to 5HT application(Control) are s ign i f i can t ly greater than those recorded in the presence of 5HT (5HT ).The effects of 5HT are reversible (Wash) . Difference currents (Control-5HT) showthat 5HT modulates a tast (A-type) component (single-headed arrow) as well as amore slowly inact ivat ing K - cur ren t (double-headed arrow). (A reprinted from Kentet al. 1987 with kind permission of Wiley. B photomicrograph generously suppl ied byDr Xue Jun Sun, printed wi th kind permission also of Professors J. G. I i i ldebrand and[,. ]. Tolbert. C,l) repr in ted from Mercer et al. 1996a with k i n d permission ofSpringer . )


mediated, at least in part, via presynaptic a 2 receptors on mi t ra l celldendrites (Trombley and Shepherd 1992), and that the modulatory actions ofNA involve the i nh ib i t i on of a high-threshold calcium current in these cells(Tromblev 1992).


Modulation of olfactory information processing is also found in inverte-brates, where the behavioral implications of modulatory events aresometimes easier to deduce. For example, serotonergic neurons play a modu-latory role in primary olfactory centers of the sphinx moth, Manduca sexta.In Manduca, each antennal (olfactory) lobe of the brain is innervated by asingle 5HT-immunoreactive neuron (Fig. 6.9A), which projects to most, if notall, of the glomerular subunits of the antennal-lobe neuropil (Fig. 6.9B; Kentet al. 1987; Homberg et al. 1989; Sun et al. 1993; Oland et al. 1995).Morphological studies suggest that these neurons provide centrifugal feed-back to the antennal lobes from 'higher' centers of the brain (Homberg et al.1989; Sun et al. 1993). Exogenously applied 5HT increases cell excitability,leads to broadening of action potentials, and increases the input resistance ofantennal-lobe neurons (Kloppenburg and Hildebrand 1995; Mercer et al.1995, 1996a; Fig. 6.9C). Consistent with these effects, in vitro studies revealthat 5HT leads to a reduction in the amplitude of voltage-gated K+ currentsin the cells (Fig. 6.9D), including a fast activating A-type current (JA) and amore slowly activating current that resembles the delayed rectifier, IK v

(Mercer et al. 1995, 1996 a).The antennal lobes of male moths are specialized to detect and process

olfactory information about sex pheromonal cues released by conspecificfemales (Christensen and Hildebrand 1987; Hildebrand 1995, 1996), as wellas to initiate and control mate-oriented flight behavior (Willis and Arbas1991; Arbas et al. 1993). Each antennal lobe of the male contains aprominent, sexually dimorphic macroglomerular complex (MGC). The MGCis innervated by the axons of pheromone-specific receptors, and evidencesuggests that MGC output neurons play an important role in codingpheromonal information (Christensen and Hildebrand 1987; Hansson et al.1991). Recent studies reveal that excitatory responses of MGC projectionneurons elicited by essential components of female sex pheromone are en-hanced by 5HT, and that 5HT levels in the antennal lobes of M. sextaundergo significant diel fluctuations that coincide with reported changes inthe levels of odor-directed behavioral activity (Kloppenburg, Mercer, Hein-bockel, Ferns, and Hildebrand, unpublished data). Taken together, theseresults suggest that 5HT may be responsible, at least in part, for mediatingstate-dependent changes in olfactory function in the moth. As both thedetection and the discrimination of pheromones released by sexually recep-tive females is essential to the mating success of M. sexta, modulation of theresponsiveness of central olfactory neurons seems likely to have a significantimpact on the performance of this odor-dependent behavior.

6.5 The perception of sensory events can be modified bymodulation of central circuits

Modulation of activity at each and every level of a sensory pathway has thepotential to contribute in some way to changes in behavior. It is often


difficult, therefore, to define at a behavioral level the functional significanceof modulatory events observed at a cellular level, especially in the vertebratebrain. It has been clearly demonstrated, nonetheless, that modulation ofactivity within central circuits can have a profound impact on our perceptionof sensory inputs. This is well illustrated by considering two very interestingissues: first, why does an animal's natural response to particularly stressfulsituations, such as those involving defence or predation, include a diminishedresponsiveness to pain? Second, why, when we are asleep, do we become lessaware of sensory stimuli that seem so obvious to us when we are awake?

6.5.1 Descending pathways and pain control

Monoaminergic pathways descending from the brain to the spinal cordmodulate the transmission of ascending nociceptive signals, and thus alter theperception of pain (recently reviewed by Markenson 1996). These descendingmodulatory fibers have their origins in the frontal cortex, amygdala, andhypothalamus, and they project to the dorsal horn of the spinal cord.Electrical stimulation of specific brain regions along these pathways can havea profound influence on the perception of pain. As early as 1969, Reynoldsreported that painless surgery could be performed on rats by focal stimula-tion of the periaqueductal region of the midbrain. In humans also, stimula-tion of brain regions, such as the ventrobasal complex of the thalamus,suppresses activity in nociceptive pathways and reduces the severity of pain(Boivie and Meyerson 1982; Baskin et al. 1986). Monoaminergic neuronsfrom regions of the brainstem provide the major descending inputs to thedorsal horn responsible for inhibiting and modulating nociception (Fig. 6.10).These descending neurons release 5HT, or NA, and the actions of thesemodulatory agents are mediated via 5HT2 receptors and a 2-adrenergicreceptors, respectively (Crisp et al. 1991; Yeomans et al. 1992). Directapplication of either of these amines to the spinal cord produces analgesia,and analgesic actions of opiates such as morphine are mediated, at least inpart, through these descending monoaminergic projections (Yaksh 1979).

Local circuits in the dorsal horn play a critical role in processing nocicep-tive afferent input and in mediating the actions of descending pain-modulat-ing systems (Fig. 6.10). Descending serotonergic and noradrenergic neuronsnot only suppress the activity of spinothalamic tract neurons directly (Fig.6.10A), but also act via local inhibitory interneurons that contain the endoge-nous opioid peptide, enkephalin (Jessell and Kelly 1991). Release ofenkephalin and activation of opioid receptors on primary sensory afferentneurons in the dorsal horn decreases the duration of action potentials in theseneurons, reduces calcium entry into their terminals, and suppresses therelease of transmitter (glutamate, substance P) from the cells (Fig. 6.10B).Postsynaptic effects have also been described. The amplitude of afferent-evoked EPSPs in the dorsal horn projection neurons is reduced through theactivation of opioid receptors, and the cells are hyperpolarized by K +


conductance activation. As a result, the activity of nociceptive dorsal hornneurons is suppressed and input of sensory information to higher centers ofthe brain is inhibited.

6.5.2 Information gating and the thalamus

Selective control of sensory information flow to the cerebral cortex is a majorfunction of the thalamus. In mammals, nearly all sensory information passesthrough the thalamus before reaching the cerebral cortex, but transmission ofinformation varies depending on the animal's behavioral state. During wak-ing, for example, information transfer is enhanced, whereas slow-wave sleepor drowsiness reduces thalamic responsiveness. The responsiveness of thethalamus and patterns of activity generated in thalamocortical systems areunder the control of neurotransmitter systems in the brainstem, the hypotha-lamus, and the cerebral cortex, and a variety of neurotransmitters, includingacetylcholine (ACh), NA, 5HT, histamine (HA), and DA have been impli-cated in controlling the state of activity and excitability of thalamic andcortical neurons (for recent reviews see Steriade and McCarley 1990;McCormick 1992). The studies outlined in this section represent only a smallfraction of the work that is underway in this exciting area, but they revealthree fundamentally important principles: first, that response properties ofneurons are shaped by the complement of ion channels expressed by the cells;second, that the activity of these channels is susceptible to modulation; andthird, that modulation of sensory circuit components can have a profoundimpact on properties of the entire network.

Changes in thalamic responsiveness are associated with a shift from sleepto a state of wakefulness. Slow-wave sleep is characterized by the occurrenceof synchronized oscillations in thalamocortical systems. The mechanisms that

Fig. 6.10 Modulating the transmission of ascending nociceptive signals. A.Descending serotonergic and noradrenergic neurons contact the dendrites ofspinothalamic projection neurons and local enkephalin-containing inhibitoryinterneurons (ENKs) in the dorsal horn of the spinal cord. The descendingmonoaminergic neurons activate the local opioid interneurons and suppress theactivity of spinothalamic tract neurons. ENKs exert both pre- and postsynapticinhibitory actions at primary afferent synapses (see B). B. Diagram summarizing theactions of opiates on sensory and dorsal horn neurons. Opiates are postulated todecrease the duration of action potentials in the terminals of the primary sensoryneuron (i), probably by reducing Ca2+ influx. They also decrease the amplitude of thefast excitatory postsynaptic potentials recorded in dorsal horn projection neuronselicited by stimulation of the sensory neuron (ii), and they hyperpolarize the membraneof dorsal horn neurons by activating a K+ conductance in the cells (iii). (Reprintedwith permission from Kandel et al. 1991.)



underlie the generation, modulation, and function of these brain oscillationshave been reviewed recently by Steriade et al. (1993). During slow-wave sleepthe level of release of modulatory transmitters is low, which for thalamicrelay neurons favors the generation of rhythmic bursts of action potentials(Fig. 6.11A). The presence of these intrinsic oscillations facilitates the occur-rence of the slow circuit oscillations (delta waves and spindle waves) that arecharacteristic of slow-wave sleep. Owing to the frequency-limited and 'scram-bling' effects of this oscillatory mode of thalamocortical activity, as well asthe presence of prolonged and overpowering inhibitory processes, the transferof information from the thalamus to the cerebral cortex during slow-wavesleep is likely to be poor. During the shift to the awake and attentive state, atonic increase in the activity of ascending modulatory transmitter systemsabolishes slow rhythmic burst firing, induces fast rhythms, and allows thecortex to recover full sensory responsiveness. It is thought that under thesecircumstances, sensory information arriving from the periphery, or fromsubthalamic afferents, is more likely to be transmitted accurately to thecerebral cortex due to the increased frequency-following capabilities of thecells and the linearity of the transfer mode of action potential generation(reviewed by McCormick 1992).

How do ascending pathways modulate the activity of thalamic relayneurons to bring about changes in the firing pattern of these cells? Cat dorsallateral geniculate nucleus (LGN) relay neurons in vitro exhibit slow(0.5-4 Hz) rhythmic bursts of activity (Fig. 6.11B), and have provided anexperimentally tractable system for exploring the modulatory effects oftransmitters. High-frequency bursts of spikes in these cells result from theactivation, by a slowly depolarizing pacemaker potential, of a low-thresholdcalcium conductance, IT. The pacemaker potential is generated by a hyperpo-larization-activated cation current, Ih (McCormick and Pape 1990), an ionic

Fig. 6.11 Dorsal lateral geniculate nucleus (LGNd) relay neurons exhibit two distinctmodes of action potential generation. A. Intracellular recordings in vivo reveal thatduring periods of slow-wave sleep, LGNd relay neurons exhibit bursts of actionpotentials. In contrast, during waking or REM sleep, LGNd neurons fire in the singlespike or tonic mode of action potential generation. Transition from one mode offiring to the other is apparently accomplished by depolarization of the membrane by10-20mV. NA, 5HT, and ACh all cause slow depolarization of LGN relay neurons,promoting a change in the firing mode from one of rhythmic bursting to one of singlespike activity. B. Intracellular recordings from cat LGNd relay neurons in vitro revealspontaneous rhythmic burst firing. Depolarization with an intracellular injection ofcurrent abolishes this burst firing, which is replaced by single spike activity. LGNdneurons in vitro provide a useful system for exploring the actions of neuromodulatorson these cells, and the mechanisms through which they operate. (A reprinted fromHirsch et al. 1983 with kind permission of Elsevier Science; B from McCormick andPape 1990 with kind permission of Cambridge University Press.)


current carried both by Na+ and K+ ions that has a reversal potential ofaround —40 mV. Owing to the voltage-dependent properties of IT, anyneuromodulator that causes tonic depolarization of thalamic relay cells willinactivate IT and inhibit the generation of burst discharges. Indeed, thetransition from rhythmic bursting in slow-wave sleep to single spike activityduring waking (and REM sleep) is associated with substantial depolarizationof the membrane potential of LGN relay neurons (Fig. 6.11).


In vitro analysis has revealed two principal targets for the actions ofneuromodulators on these cells: (1) K+ conductances, in particular, a rela-tively linear K+ current that contributes substantially to the resting 'leak'conductance of the cell membrane (IKleak), and (2) the hyperpolarization-activated cation current, Ih. Several neuromodulatory systems affect theseconductances in similar ways. NA, HA, and ACh, for example, all cause slowdepolarization of LGN relay neurons through blockade of IKleak, promotinga change in the firing mode of thalamic neurons from rhythmic burstgeneration to single spike activity. Consistent with these findings, electricalstimulation of the brain in the region of the cholinergic nuclei that project tothe thalamus results in a marked increase in the responsiveness of LGN relayneurons to the activation of sensory receptive fields. Stimulation of the locuscoeruleus, which sends noradrenergic projections to the thalamus, also resultsin prolonged enhancement of responses of LGN cells to excitatory inputs.

Strong enhancement of Ih also results in the abolition of slow rhythmicburst discharge and enhancement of single spike activity. These changes inrelay cell activity appear to occur primarily as a result of an increase in theamount of Ih active at resting membrane potentials, which depolarizes thecells towards Eh (-40mV), decreasing the ability of thalamic neurons toundergo the large swings in membrane potential required for rhythmicoscillation. For example, spindle wave abolition during waking occurs, atleast in part, through the persistent activation of Ih in thalamocorticalneurons (Bal and McCormick 1996). Both NA and 5HT have been shown toabolish spindle wave generation through the enhancement of this current andthe abolition is reversed by local application of the Ih channel blocker cesium(Lee and McCormick 1996). A number of transmitter systems appear to haveoverlapping roles in the thalamus, but given that maintaining the thalamus inthe tonic firing mode appears to be important for most cognitive behavior,this is perhaps not surprising (McCormick 1992).

6.5.3 Modulation of cortical neurons

The activity of cortical neurons can also be altered by a range of putativeneuromodulatory agents (reviewed by McCormick 1992). While the func-tional significance of modulatory events at this level is not well understood,in the sensory cortex, as elsewhere, they are likely to provide a key toperformance flexibility. Noradrenergic neurons, for example, form prominentvaricosities through all layers of the sensory cortex (Freedman et al. 1975;Kosofsky et al. 1984), and there are numerous studies that document theeffects of NA on cortical neurons. Some reports are contradictory. Forexample, several studies provide evidence that NA enhances the signal-to-noise(S/N) ratio of central neurons (Foote et al. 1975; Waterhouse et al. 1980,1981, 1988, 1990), whereas other studies, using iontophoretic application ofNA (Videen et al. 1984; Manunta and Edeline 1997), locus coeruleusstimulation (Sato et al. 1989) and pharmacological stimulation of the nora-drenergic system (Edeline 1995; Manunta and Edeline 1997), fail to support


this finding. Recently, McLean and Waterhouse (1994) have shown that NAincreases the velocity tuning of neurons in the visual cortex of the cat. In therat auditory cortex, the frequency selectivity of neurons can also be increased,either by pharmacological activation of noradrenergic inputs (Edeline 1995)or by iontophoretic application of NA (Manunta and Edeline 1997). Moreselective output from the cortex would be expected to improve discriminationperformance, and indeed, behavioral studies, used in combination withpharmacological manipulation of noradrenergic systems, support the viewthat NA facilitates the performance of discrimination tasks (Arnsten et al.1988; Devauges and Sara 1990).

Acetylcholine (ACh) has also been strongly implicated in regulating thefunctional plasticity of cortical neurons (e.g. Weinberger et al. 1990;Richardson and DeLong 1991; Hasselmo and Bower 1993; Metherate andAshe 1993; Bakin and Weinberger 1996; Dykes 1997; Sarter and Bruno1997), and recent studies have begun to reveal the important role that AChplays in enabling the cortex to selectively improve the neural representationsof behaviorally relevant stimuli, while ignoring stimuli that are unimportant.ACh release can be evoked by electrical stimulation of neurons in the nucleusbasalis (NB), a cholinergic nucleus that sends projections to the entire cortex.NB neurons are activated as a function of the behavioral significance ofstimuli (see Richardson and DeLong 1991), and Kilgard and Merzenich(1998) have recently shown that NB activation in the adult rat, if paired withan auditory stimulus, leads to massive remodelling of the primary auditorycortex. This cortical plasticity resembles the receptive field remodelling thatoccurs in somatosensory and auditory cortices as a result of behavioraltraining (Merzenich et al. 1983a,b; Jenkins et al. 1990), which appears to beresponsible for improvements in a variety of behavioral skills, includingcompensatory adjustments following damage to sensory systems.

6.6 Experience can alter sensory processing throughmodulatory mechanisms

The potential for modulatory events to lead to long-term changes in thefunctioning of sensory circuits is inherent to most, if not all, sensory net-works. Repeated exposure of Aplysia sensory neurons to 5HT, for example,leads to long-term changes in the efficacy of connections between sensoryneurons and their follower cells. These long-term changes differ from short-term modulatory events in two fundamentally important ways: first, short-term events involve covalent modification of pre-existing proteins, whereaslong-term changes require gene expression and the synthesis of new proteins.Second, unlike short-term modulatory events, long-term changes involvestructural change (Bailey and Chen 1983, 1988a,b; Glanzman et al. 1990;Schacher et al. 1990; Bailey and Kandel 1993; Bailey et al. 1996). Long-termstrengthening of synaptic connections between Aplysia sensory neurons andtheir follower cells is associated with the growth of new synapses (Bailey and


Chen 1983, 1988a,b) and, at the behavioral level, these 5HT-induced changesin morphology are associated with long-term sensitization of reflex with-drawal responses.

Long-term structural changes, like short-term modulatory events, occur atall levels of the sensory nervous system. In the vertebrate retina, for example,covalent modification of junctional channels between horizontal cells (Lasater1987), which is responsible for rapid modulation of electrical coupling (seeSection 4.1), can be accompanied by longer-term changes that require synapseassembly and maintenance (McMahon and Mattson 1996; Pfeiffer-Linn andLasater 1996). In addition to its short-term modulatory actions on centralolfactory neurons (see Section 4.2), 5HT also apparently exerts longer-termmorphogenic effects in primary olfactory centers of the brain (Benton et al.1994; Moriizumi et al. 1994; Mercer et al. 1996b). Pharmacological deple-tion of 5HT in rats not only impairs olfactory performance (McLean et al.1993), but also causes shrinkage of the glomerular layer of the olfactory bulb(Moriizumi et al. 1994). Moreover, 5HT has been shown to enhance thegrowth in vitro of insect central olfactory neurons (Mercer et al. 1996b;Kirchhof and Mercer 1997a), and is a likely candidate to play a role inmediating the structural plasticity that is characteristic of the glomerularneuropil of the antennal (olfactory) lobes in some insect species (Winningtonet al. 1996; Sigg et al. 1997; Morgan et al. 1998). DA has been implicatedalso in these morphogenic events (Kirchhof and Mercer 1997b; Kokay andMercer 1997).

Modulatory mechanisms that lead to structural modifications within sen-sory circuits provide the basis for long-term changes in sensory informationprocessing as a result of experience. The idea that memories of sensoryexperiences could be stored through the modification of synaptic connec-tions, and that such events would occur in the same regions of the brain usedto process sensory information, was first suggested by Donald Hebb (1949).The interesting issue of neuromodulators and their role in memory formationand recall is discussed further in Chapter 9.

6.7 Sensory neurons can evoke modulatory effects

As we have now seen, modulatory influences can alter the processing ofsensory information in a multitude of ways. In each case, the transfer ofinformation by primary sensory neurons was assumed to be rapid. However,there is now ample evidence that primary sensory neurons, and in many casessecondary sensory neurons, can also evoke slower neuromodulatory actions.These modulatory actions can change the properties of postsynaptic follow-ers, and thereby alter the responses evoked by sensory input. This can occurfor a number of reasons: one is to allow sensory input to change the state ofthe system that it is projecting to, and another is to allow the sensory input tomaintain a set-point of activity in its target population.

One example of sensory neurons evoking long-lasting actions comes from a


sensory system known for its rapid transmission of information, the auditorysystem. Auditory afferents to the lateral superior olive in gerbils evokeprolonged depolarizations lasting many minutes (Kotak and Sanes 1995).The depolarizations appear to be due to the action of metabotropic glutamatereceptors. Thus, the same cells have fast actions, through ionotropic receptorsthat relay phasic auditory information, and also long-lasting actions, throughanother set of receptors, which are thought to play a role in organizing thedevelopment of the auditory system.

Whereas auditory afferents evoke fast and slow effects through theiractions on two different types of receptor, some primary sensory neuronsevoke neuromodulatory actions through the release of modulatory cotrans-mitters, such as neuropeptides and monoamines (Weiss et al. 1984; Cuello1987). In the stomatogastric system of crabs, gastropyloric receptor cells(GPR), which use ACh for fast neurotransmission, also contain 5HT and atleast one neuropeptide (Katz et al. 1989; Skiebe and Schneider 1994). Thefunction of the peptide is not known, but 5HT released from thesemechanoreceptive GPR cells evokes prolonged modulatory actions in themotor circuit that alter the properties of the postsynaptic neurons (Fig. 6.12;Katz and Harris-Warrick 1989). As a result, these primary receptor neuronsare able to change the nature of the motor pattern that is evoked, while at thesame time providing phasic sensory feedback (see Chapter 6 for moreinformation).

Sensory neurons can also release modulatory transmitters at peripheralsites, altering the responsiveness of other sensory neurons (Maggi 1995). Thishas been demonstrated for a stretch receptor in a sensory organ of thelobster, where the peptide proctolin, released from dendrites of one neuron inresponse to passive stretch, alters the excitability of other neurons in the samesensory structure (Pasztor et al. 1988). A similar form of sensory control wasdiscussed at the beginning of this chapter in reference to the release of 5HTby basal cells in response to sensory activation of Necturus taste buds(Welton and Roper 1992; Delay et al. 1993). The ability of one sensoryneuron to modulate the gain of another through the peripheral release ofmodulatory substances is a mechanism for local control over the responseproperties of the sensory epithelium and may be of general significance.

6.8 Summary

Modulatory events can have a significant impact on the functioning ofsensory circuits, and consequently also on our perceptions of the world.Neuromodulators enable us to adjust to changing environmental conditions,and ensure that our sensory systems continue to gather information opti-mally. Sensory pathways can be modulated at any level, even at the very firststage of sensory reception. Indeed, sensory neurons themselves can evoke

Fig. 6.12 A primary sensory neuron can evoke neuromodulatory effects. Thegastropyloric receptor (GPR) cell responds to stretch of a muscle in the stomatogastricsystem of crabs, and it evokes modulatory effects on neurons in the pyloric centralpattern generator. The top trace is an extracellular recording from a motor nerveshowing action potentials of different amplitude from the three pyloric neurons, LP,PY, and PD. Upon muscle stretch (bottom trace), GPR fires action potentials, asshown in the extracellular recording (GPR). An intracellular recording in the pyloricneuron, LP, shows a prolonged change in LP activity in response to GPR firing. Themodulatory effects of GPR allow the motor pattern to be altered regardless of thetemporal relationship between GPR activity and that of the pyloric neurons.(Previously unpublished recording courtesy of P. Katz.)

modulatory effects which, in turn, alter the function of central circuits, orprovide sensory inputs with local control over their own sensitivity. Bytargeting the conductances that shape the response properties of sensoryneurons, or by changing the weighting of connections between cells, neuro-modulators can alter the functioning of entire neural networks. The impact ofsuch events can be profound and, in many cases, is reflected in changes at abehavioral level. While most modulatory events are short-lived, modulationof sensory circuits can also produce long-term changes in sensory informationprocessing as a result of experience. There can be little doubt, therefore, thatperformance flexibility provided by sensory systems modulation contributessignificantly to the success and survival of all species.



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Flexibility of muscle control by modulationof muscle propertiesSCOTT L HOOPER, VLADIMIR BREZINA, ELIZABETH C. CROPPER, ANDKLAUDIUSZ R. WEISS

7.1 Introduction

A primary function of nervous systems is to produce behavior; a fundamentalgoal of neuroscience is to understand how they do so. Nervous systems donot produce behavior in isolation, but instead depend on the organs theyinnervate to implement their commands. It is therefore impossible to under-stand how nervous systems produce behavior without understanding howeffectors respond to their input.

This process would be straightforward if muscles responded to neuronalinput in a simple linear manner. However, neuronal input triggers a series ofintramuscular electrophysiological and biochemical processes that, as a con-sequence of their own collaborative interactions, and according to their ownintrinsic dynamics, result in muscle contraction. The relationship betweenneuronal activity and muscle response is therefore often complex. In particu-lar, muscle properties frequently limit the ability of muscles to accuratelyreproduce the dynamics of neuronal activity, and this limitation could placesevere constraints on the range of motor activity that nervous systems caninduce.

Muscle modulation can overcome some of these difficulties, and it is thusnot surprising that it is widespread (it is almost ubiquitous in invertebrates).In some of the many systems where it has been studied, a considerableamount is known about its behavioral, electrophysiological, and biochemicaleffects. However, a general conceptual framework of the role and conse-quences of modulation in neuron to muscle communication, and in motorpattern expression, has been slower to emerge.

Therefore, in this chapter we attempt to put muscle modulation in contextby identifying two broadly defined functional advantages that muscle modu-lation could provide, and considering the functional implications of extrinsicand intrinsic neuromodulation. In each case we first discuss the issue at handin general terms, and then provide specific neuromuscular systems thatillustrate the point well. We next describe a particularly well-understoodexample of muscle modulation (the ARC system of Aplysia), and end bylisting several questions whose resolution is necessary to achieve a full

7

242 Flexibility of muscle control

understanding of the role of muscle modulation in motor pattern production.Please note that we are not reviewing all systems in which muscle modulationoccurs (such a review would be a book in itself), nor do we believe that theconceptual framework we provide is the final word; our goal instead is tobegin the conversation by providing a framework against which others canreact. It is also important to note that many of the issues raised below are notlimited to neuromuscular systems, but will apply to any system in which fastinputs drive slowly responding effectors (e.g. second messenger systems;DeKoninck and Schulman 1998).

7.2 Why modulate muscles?

Central to the concept of neuromodulation is the idea that it is functionallyadvantageous to alter an entity's properties. In motor pattern-generatingnetworks, the possible advantages (e.g. constructing multiple functional net-works out of a single set of neurons and synaptic connections; see Chapter 8)are clear; the functional advantages of muscle modulation are not as obvious.Consideration of modulation's effects on muscles, and the kind of musclesobserved to be modulated, suggests two reasons for muscle modulation. First,muscle modulation often gates muscle responsiveness to, or increases muscleindependence of, neural input. These actions alter the coupling betweenneural activity and motor output, and this increase in nervous system flexibil-ity may be one reason for muscle modulation. Second, muscle modulationoften occurs in muscles whose contraction and relaxation dynamics are slowrelative to at least some of the motor patterns that they produce, whichsuggests that modulation may exist to better match effector response toneural input.

7.2.1 Gating and independence from neural control

Control of muscle contraction seems straightforward—to contract a muscle,one causes its motor neuron to fire action potentials; to relax a muscle, onestops the motor neuron from firing. However, motor neurons are not alwaysmere follower neurons. Instead, in a variety of vertebrate preparations motorneurons synapse onto other motor neurons (Ginnel 1966; Auerbach andBennett 1969; Matsuura 1971; Cullheim et al. 1977; Fulton et al. 1980;Shapovalov and Shiriaev 1984; Perrins and Roberts 1995.3,6) and/or ontospinal interneurons (Eccles et al. 1954), and hence may help shape motoroutput patterns. In at least one vertebrate (Xenopus), motor neuron to motorneuron synapses provide a large proportion of on-cycle excitation duringswimming (Perrins and Roberts 1995a), and motor neurons may even be partof the swimming central pattern generator (Perrins and Roberts 1995c). Ininvertebrates, motor neurons clearly can be members of central patterngenerators (see Chapter 8). This participation of motor neurons in shaping or

S. L Hooper, V. Brezina, E. C. Cropper, and K. Weiss 243

generating motor patterns would seem to pose potential difficulties for motorsystem function. For instance, there might be situations in which the patternof motor neuron activity required for proper function of the motor neuron'sneural network (the neuron's central responsibility) and the pattern of motorneuron activity required to produce a given motor output (the neuron'speripheral responsibility) might conflict.

This problem can be circumvented by appropriate nervous system design.However, in some cases it may be easier to use modulation to alter muscleresponsiveness to neural input. For instance, modulation could allow a motorneuron to fire in any central activity pattern without unwanted motor outputby making the motor neuron's muscle unresponsive to neural input. Moremoderately, modulators could reduce a muscle's dependence on input byputting the muscle into an active state in which, although neural inputtriggers muscle contractions, contraction duration and amplitude are primar-ily determined by the muscle itself. Muscle modulation could also induceendogenous myogenic activity, and thus muscle contraction could continueeven if the motor neuron were silent. Below, we give two examples thatillustrate these processes. We provide another example (Hirudo heart) inSection 7.3.

Mytilus anterior byssal retractor (ABR) muscle and othercatch muscles

The ABR muscle of the mussel, Mytilus, induces defensive clamping to thesubstrate; the adductor muscles of bivalve molluscs cause defensive shellclosing. Both muscles show catch, in which brief nerve stimulation or AChapplication induces contractions that outlast the triggering input by an houror more (Winton 1937; Hanson and Lowy 1960). The same input applied inthe presence of serotonin or dopamine induces rapidly (1 min) relaxingcontractions, and serotonin application rapidly relaxes muscles in whichcatch has been induced (Twarog 1954). As such, serotonin gates the ability ofthese muscles to show catch. Theoretically, the serotonin-induced increase inrelaxation rate would allow these muscles to follow phasic neural input, andthus participate in phasic motor patterns. However, available evidence sug-gests that these muscles are never phasically active, and repetitive motorpatterns are instead performed using dedicated phasic muscles present at thesame joint (Marsh et al. 1992).

The process described here raises the question of what the animal does if itis threatened immediately after catch is released, since serotonin levels arelikely to be relatively high, and hence catch impossible, at this time. Anintriguing speculation is that in this behavioral state the neural response tothreats changes so that now muscle contraction is maintained by a differentneural activity pattern, sustained motor neuron firing.

Palaemon pyloric dilator muscleFMRFamide-like peptides gate the ability of the pyloric dilator muscle of theshrimp (Palaemon) stomatogastric system to follow neural input and to

Fig. 7.1 FMRFamide can induce spontaneous endogenous rhythmicity or gate muscleresponsiveness to neural input in the pyloric dilator muscle of the shrimp. Undercontrol conditions (left column) the muscle is not endogenously rhythmic (A), andmotor nerve stimulation induces only very small contractions (B, C). Early afterFMRFamide application (middle column), the muscle is endogenously rhythmic (A),and neural input can reset the rhythm (B). Arrows indicate the expected time of peakcontraction if the motor neuron is not stimulated. Rhythmic input (unless within anarrow cycle period range) disrupts muscle activity (C). Later in the FMRFamideapplication (right column), endogenous activity ceases (A), but the ability of neuralinput to trigger large muscle contractions remains (B, C). Scale bars are 1 s. Modifiedfrom Meyrand and Marder (1991).

express myogenicity. Under control conditions (Fig. 7.1, left) the muscleshows no myogenic rhythm (panel A), and only very small contractions inresponse to either single burst (panel B) or rhythmic (panel C) motor nervestimulation. Such small contractions are unlikely to cause useful movements.Upon application of FMRFamide-like peptides, the muscle undergoes atransition to an endogenously rhythmic state (Fig. 7.1A, middle). In this state,a single burst of motor neuron action potentials can reset the muscle'srhythm (Fig. 7.IB, middle), but rhythmic stimulation at periods differentfrom the muscle's natural period disrupt it (Fig. 7.1C, middle). After a periodof time in FMRFamide, the muscle reaches a state in which it is no longerendogenously rhythmic (Fig. 7.1A, right), but single or rhythmic nervestimulation induces large contractions (Fig. 7.1B,C, right) (Meyrand andMarder 1991).


S. L. Hooper, V. Brezina, E. C. Cropper, and K. Weiss 245

These results suggest that FMRFamide-like peptides may act as a gatethroughout the entire continuum of muscle responsiveness noted above. First,without modulation the muscle does not respond to neural input, and thus itsmotor neuron would be free to fire in any central pattern that was required(in this system motor neurons are part of the central pattern generator).Second, in the active but not endogenously rhythmic state (Fig. 7.1, right),muscle contractions result from intrinsic all-or-nothing regenerative muscledepolarizations. As such, in this state the motor neuron's only role may be totrigger the contractions, and hence the motor neuron's intraburst spikepattern could change to fit its role in central processing without alteringmuscle contraction amplitude or duration. Finally, the induction of endoge-nous myogenicity could allow rhythmic pyloric dilator muscle activity tocontinue during times in which it was required by the central circuitry thatthe pyloric dilator neurons be silent (Meyrand and Moulins 1988).

7.2.2 Compensation for slow muscle temporal filtering

It might be presumed that muscles would have evolved so that they canfaithfully follow the entire range of neural input they receive as behaviorchanges. However, the response of even the fastest muscle fiber (vertebratefast twitch fiber) is at least 40 times longer than the neural input that triggersit, and hence muscle tension cannot accurately follow rapidly changing neuralinput (Partridge 1966). This problem increases for muscles with slowerresponse dynamics and is most acute in the slow graded muscles often presentin lower vertebrates and invertebrates. These fibers do not spike, but insteadshow simple excitatory potentials, and small unitary contractions, in responseto a motor neuron spike; they very often also have slow relaxation kinetics.As a consequence of these properties, muscles composed of these fiberscontract and relax very slowly (tens to hundreds of times slower than twitchmuscles).

It would seem that such slow muscles would be unable to follow rapidlychanging neural input, and they have often been presumed appropriate onlyfor very slow or tonic motor patterns (e.g., posture). However, these musclescan be involved in relatively rapid movements in lower vertebrates(Hetherington and Lombard 1983; Carrier 1989), and are the effectors inmany relatively rapid invertebrate rhythmic motor patterns including thecrustacean pyloric motor pattern (Morris and Hooper 1997a), molluscanfeeding (Cropper et al. 1990), leech swimming (Mason and Kristan 1982),and crustacean ventilation (Mercier and Wilkens 1984; Josephson and Stokes1987). Modulation of muscle properties is important for changing the tempo-ral properties of these slow muscles to allow them to follow fast changes ininput. In the absence of such modulation, this 'mismatch' of rapidly changingneural activity and slowly responding effector can dramatically alter theeffector's ability to reproduce the input's temporal characteristics.

Fig. 7.2 Slow effectors display temporal summation when driven by relatively rapidinputs. The figure shows the output of a simple slow muscle model in which eachspike in the motor neuron bursts (filled rectangles above time axis) induces a smallunitary contraction that relaxes as a single exponential. When the motor neuron'scycle period is long, the muscle can relax almost totally between neuron bursts (A); ascycle period shortens, the muscle's contractions show increasing temporal summation,and at steady state consist of phasic contractions riding on a sustained baselinecontracture (B). See text for explanation of dashed contraction in B. Both simulationswere performed at a constant burst spike frequency and duty cycle.

Figure 7.2 demonstrates the effects of a mismatch in temporal propertiesfor a rhythmic system.1 This figure shows the output of a simple slow musclemodel in which each motor neuron spike induces a small unitary contraction,and the muscle relaxes with single exponential time constant. At slow cycleperiods, the muscle relaxes almost completely between bursts (Fig. 7.2A).However, as the period decreases an increasing baseline (tonic) contracturedevelops (Fig. 7.2B). This contracture limits the muscle's output range.

The concerns raised in this section are not limited to rhythmic systems, but will occur wheneverslowly responding effectors are driven by rapidly changing input; a rhythmic input was chosensolely because it is the easiest to describe, and because many of the best understood experimentalsystems in which modulation occurs are rhythmic.



Consider, for instance, a desired output with the same cycle period, dutycycle, and phasic contraction amplitude as before, but with a lower toniccontracture (Fig. 7.2B, dashed trace). The slow muscle model cannot producethis contraction because the temporal summation of the phasic contractionsproduces the tonic contracture; any attempt to reduce the contracture byreducing motor neuron firing will also reduce the muscle's phasic contractionamplitude.

In many motor patterns a tonic contracture would be inappropriate, and itwould seem advantageous to be able to express a wide range of motoroutputs. The presence of slow muscles in systems innervated by rapidlychanging neural inputs is therefore surprising; the widespread occurrence ofmodulation in such systems may exist in part to ameliorate the effects of thismismatch between input and muscle dynamics. In particular, increases inmuscle relaxation rate would increase the ability of muscles to follow rapidlychanging neural inputs, and hence the cycle period range over which themuscle would not necessarily produce a tonic contracture. Note that withperiods longer than this, contractions containing any combination of tonicand phasic components can still be produced by having the motor neuron firecontinuously (to maintain the tonic contracture) with phasic variations inspike frequency (to produce the overriding phasic contractions). Thus, modu-lation would also increase the range of motor outputs the muscle can express.

Panulirus pyloric musclesAn example of a temporal mismatch between muscles and the pattern ofneuronal activity that drives them is seen in the stomatogastric system oflobsters and crabs. The neural pattern produced by the pyloric network ofthe stomatogastric ganglion consists of rhythmic bursts of motor neuronspikes at cycle periods between 0.5 and 2.0 s. However, most pyloric musclesare slow muscles and, in response to physiological nerve stimulation, showlarge interburst temporal summation that transform rhythmic inputs intocontractions with large tonic components (Fig. 7.3) (Ellis et al. 1996; Morrisand Hooper 1996, 1997a,b, 1998; Koehnle et al. 1997). If pyloric functiondepends on rhythmically alternating muscle contractions (as might be ex-pected from a rhythmic neural pattern), this temporal filtering would becontrary to function.

This difficulty may be partially overcome by muscle modulation. Amineand peptide modulators can decrease pyloric muscle contraction amplitudeand increase muscle relaxation rate (Lingle 1980, 1981; Jorge-Rivera andMarder 1996; Jorge-Rivera 1997), which would increase phasic motor re-sponse. In the blue crab, terminals of one of the pyloric motor neuronscontain dense core vesicles in addition to clear vesicles, suggesting that thisneuron releases a modulatory cotransmitter onto its muscle in addition to itsfast neurotransmitter (Patel and Govind 1997). The pyloric network is alsomodulated centrally to produce a wide variety of neural output patterns (seeChapter 8). This raises a general problem in neural coding. Consider amodulator that decreases the pyloric cycle period from 2 to 0.5 s. The effect

Fig. 7.3 The dorsal dilator muscle of the lobster stomatogastric system showsdramatic temporal summation when its motor nerve is stimulated with physiologicallyrelevant parameters. A shows the muscle's response to 2 s cycle period stimulation, Bthe response to 1 s stimulation, and C to 0.5 s stimulation; in all cases the sameintraburst spike frequency (60 Hz) and duty cycle (0.25) were used. At the fastest cycleperiod, the muscle transforms a rhythmic input into an almost completely tonicoutput. Modified from Morris and Hooper (1998).

of this change on the pattern of muscle contractions will depend on themuscle state—if the muscles are unmodulated, the pattern will becomealmost completely tonic; if a modulator has sufficiently increased the musclerelaxation rate, the pattern instead will remain phasic, and simply cycle fourtimes as fast. Similarly, the functional effects of sensory feedback loops



(indeed, of any change in motor neuron activity) would be different in eachmuscle modulatory state.

This dependence of the functional effect of central activity on muscle statewould seem to tremendously complicate motor pattern generation and con-trol because it implies that to achieve any given motor pattern change, thecenter must keep track of, and compensate for, the muscle's modulatorystate. In the pyloric system, one possibility is that motor function is notparticularly finely controlled (within broad ranges, any motor pattern func-tions well enough), but this is difficult to reconcile with the large amount ofperipheral and central neuromodulation this system receives (Harris-Warricket al. 1992). An alternative possibility is that muscle modulation is coordi-nated with simultaneous central modulation so that each muscle modulatorystate is associated with only one or a few neural activity patterns.

Vertebrate slow twitch muscle fibers—a possibility?There is evidence of neuromodulation in vertebrate skeletal muscle. Verte-brate skeletal muscle consist of two fiber types, fast (twitch duration80-100 ms) and slow (duration 300-400 ms). Fast fibers are divided into twogroups, fatigable (tension rapidly declines (~ 1 min) in response to repeatedtetanic stimulation) and fatigue-resistant (tension declines over tens of min-utes); slow fibers are very fatigue resistant (hours). Each motor unit consistsof a single fiber type; slow units generate the smallest twitches, fast fatigue-resistant the next largest, and fast fatigable the largest (Burke et al. 1974).Motor units are recruited in order of twitch size; slow units are recruitedfirst, then fast fatigue-resistant, and then fast fatigable (Henneman et al.1965; Desmedt and Godaux 1977). Consequently, only slow units are activein low force movements (posture maintenance, walking), whereas all unitsare activated in high force movements (sprinting).

As a consequence of their rapid fatigue, the fast fiber types provideprogressively less force as movement continues, and thus some relativelyrapid motor patterns (sustained running) depend almost completely on slowfiber activity. Physiologically relevant concentrations of epinephrine decreaseslow muscle twitch duration (Fig. 7.4, top) and increase slow muscle relax-ation rate (Fig. 7.4, bottom) (Bowman and Zaimis 1958; Bowman and Nott1969), and plasma epinephrine concentrations dramatically increase duringrunning and similar strenuous activity, increasing up to tenfold at maximalexertion (Loucks and Horvath 1984; Mazzeo 1991).

A variety of changes in muscle properties occur during bouts of continuousactivity (Clamann 1990), and it is therefore difficult to predict the functionalrole of this modulation. Although slow fibers relax more slowly than fastfibers, their relaxation rate is fast enough that the intercontraction temporalsummation shown in Fig. 7.2 will not occur during most rhythmic move-ments. It is thus doubtful that epinephrine's modulation exists to preventslow fiber summation between bursts. However, decreased twitch durationand increased relaxation rate would be expected to increase the ability of

Fig. 7.4 Epinephrine reduces twitch duration, and increases twitch relaxation rate, inthe primarily slow twitch fiber soleus muscle of the cat. The top panel shows twomuscle twitches obtained by supramaximal nerve stimulation; injection of epinephrineinto the circulation dramatically shortens twitch duration. The bottom panel showsthe same traces with the epinephrine trace shifted horizontally to show the increase intwitch relaxation rate. Modified from Bowman and Zaimis (1958).

slow units to accurately reproduce rapid changes within bursts (Partridge1966). It is thus possible that one role of epinephrine's modulation of slowfibers may be to 'tune' their contraction and relaxation characteristics tomaximize mechanical or energetic efficiency during sustained, rapid motorpattern production.

Mammalian heartThe first observation of muscle modulation was the discovery that vagalnerve stimulation released soluble substances that altered frog heart contrac-tions (Loewi 1921). At the time this was described as evidence of chemical


Fig. 7.5 Summary of vertebrate heart modulatory pathways. Parasympathetic activitydecreases heart rate, primarily by affecting the sinoatrial (SA) and atrioventricular(AV) nodes; it has little direct effect on cardiac contractility (Rhoades and Tanner1995). Sympathetic activity increases heart rate through effects on the SA and AVnodes, and increases heart muscle relaxation rate and contractility through directeffects on the muscle. Modified from Rhoades and Tanner (1995).

neurotransmission, but in modern parlance it would be called neuromodula-tion. In the ensuing 70 years, vertebrate (particularly mammalian) hearts andtheir modulation have been extensively studied (for textbook treatments seeBerne and Levy 1977; Guyton and Hall 1996). This work illustrates thepossibly deleterious effects of a temporal mismatch between a rhythmicdriver (the heart pacemaker) and the temporal characteristics of its effector(the heart muscle's relaxation rate) particularly well, and how muscle modu-lation can overcome these effects to maintain proper function.

Mammalian heart rate is controlled by the autonomic nervous system. Itcan be increased by enhancing sympathetic activity and diminishing parasym-pathetic activity, and decreased by enhancing parasympathetic and diminish-ing sympathetic activity (Fig. 7.5). In humans, the intrinsic, unmodulatedheart rate is about 105 beats per minute; heart rate increases above thisintrinsic rate arise from sympathetic activity. Such increases are easily ob-served and behaviorally important; sympathectomized animals cannot per-form strenuous tasks (Cannon 1932). Under these conditions, changes inmyocardial contractile properties are likely to be particularly important.

Sympathetic activity releases catecholamines, which exert multiple effectson the heart to enhance cardiac function. One such effect is increased heartrate ( positive chronotropy). However, increasing heart rate alone does notnecessarily increase cardiac output. Cardiac output is stroke volume (thevolume of blood pumped per heart beat) multiplied by heart rate. Cardiacoutput thus will not increase with heart rate if stroke volume decreases (or, atleast, will increase less than if stroke volume remained constant). In part,stroke volume is determined by how much blood flows into the ventriclesduring diastole. If heart rate increases without other compensatory mecha-



nisms being present, blood will flow into the ventricles for a shorter timeperiod and consequently they will fill to a lesser degree. Thus, withoutcompensation, heart rate increases could compromise ventricular filling, andcardiac output not only might not increase, but could even decrease.

Catecholamines have two additional effects on ventricular myocardiumthat circumvent this difficulty (Katz 1988). One effect is to increase myocar-dial relaxation rate (positive lusitropy). Ventricular filling occurs in twophases—early diastole (when the ventricles are relaxing but the atria have notbegun to contract), and late diastole (when the atria contract). Filling duringearly diastole is determined by the atrio-ventricular pressure gradient, whichincreases as ventricular relaxation rate increases; increasing ventricular relax-ation rate would thus increase early diastole filling. At rest the myocardiumrelaxes completely before diastole ends, and increased early diastole fillingwould have relatively little effect on total ventricular filling. However, whenheart rate increases, the myocardium can no longer fully relax during dias-tole, and catecholamine-induced positive lusitropy would therefore helpmaintain early diastole filling and adequate ventricular filling.

Although positive lusitropy can increase ventricular filling when heart rateis increased, this effect alone does not necessarily mean that the heart willpump blood as well as it did at rest. To understand this, it is important tonote that the ventricles pump only a fraction of the blood that fills them (theejection fraction), and this fraction can decrease when positive lusitropyoccurs. To compensate for this decrease, and hence ensure a maximalincrease in cardiac output, catecholamines also exert a positive inotropiceffect (contractility is increased and heart beats are strengthened) on themyocardium that offsets any decrease in ejection fraction produced by thepositive lusitropic effects.

In summary, catecholamines increase mammalian heart rate (positivechronotropy). Without compensatory changes, these increases would allowinsufficient time for ventricular filling. However, catecholamines also en-hance ventricular relaxation rate (positive lusitropy), which allows adequateventricular filling despite the reduced interbeat interval. To maintain ejectionfraction, catecholamines also enhance myocardial contractility (positiveinotropy), and hence ensure that increased heart rate is associated withincreased blood pumping.

Locust leg and flight musclesIn addition to producing single motor patterns at different cycle periods,muscles produce multiple types of behavior, i.e. function as multipurposedevices, and situations may occur in which different types of behavior cannotbe generated efficiently by the same muscle. For example, muscle temporalproperties could interfere with muscles participating in both tonic and phasicmotor patterns. One solution to this problem would be mechanisms that altermuscle contractile properties so as to match contraction characteristics to


specific behavioral demands. An excellent example of how this problem canbe solved is the tibiae extensor leg muscle of the locust (Evans 1981; Evansand Siegler 1982).

Locust legs function both in maintaining posture and in locomotion. Thedemands put on the leg muscles differ significantly in the two types ofbehaviors. When the leg maintains posture, the muscle functions properlywhen it sustains a tonic contraction. In contrast, during locomotory behaviorthe muscle must generate rapid phasic contractions. The analysis of theinnervation and modulation of the locust leg provides a clear example of howthese two types of demands can be reconciled elegantly through the actions ofmodulatory neurotransmitters.

In addition to its conventional motor neuronal innervation, the tibiaeextensor muscle is also innervated by an octopaminergic neuron namedDUMETi. Unlike conventional motor neurons, the DUMETi neuron does notproduce muscle contractions. However, octopamine increases the relaxationrate of SETi motor neuron-evoked twitch contractions (Fig. 7.6A), and thiseffect is mimicked by stimulation of the DUMETi neuron (Fig. 7.6B).

Evidence for the functional relevance of the octopaminergic modulationhas been obtained in experiments in which the SETi motor neuron wasstimulated rhythmically in a manner mimicking its activity in a walkinganimal (Fig. 7.7A). Under these conditions, when the DUMETi neuron is notstimulated and exogenous octopamine is not applied, muscle tension relaxesslowly and consequently does not return to rest (dashed line), a situation thatwould lead to ineffective walking. However, when exogenous octopamine isapplied (or the DUMETi neuron is fired, not shown), muscle tension relaxesalmost completely each cycle. Thus, the octopaminergic modulation allowsmuscle contractions to more closely follow the neuronal activity pattern.

What effect would the octopaminergic modulation have on the otherbehavior—posture—that the tibiae extensor muscle produces? In thisbehavior the muscle must produce a sustained tonic contraction, butoctopaminergic modulation, presumably due to its increase in relaxation rate,reduces the tonic level of such contractions (Fig. 7.7B). Thus, in the presenceof octopamine a transient decrease in motor neuron firing would be morelikely to cause a relaxation of muscle contraction, and hence a loss ofposture. Therefore, for the system to operate properly, octopaminergic modu-lation should occur when the animal is locomoting but not when it isstationary. Recordings of DUMETi neuron activity indicate that this is indeedthe case—the neuron fires as the animal becomes active, but not when it isstationary.

Precisely analogous results have been obtained in the bilaterally pairedpleuroaxillary muscles of the locust. These muscles' anatomical placementand the firing times of their motor neurons during flight are such that themuscles would enhance lift production if they phasically contracted in re-sponse to their neuronal input (Elson and Pfliiger 1986). However, in theabsence of modulation, recordings from isolated muscles show that when the

Fig. 7.6 Octopamine decreases the duration, and increases the relaxation rate, oflocust tibiae extensor muscle twitches induced by SETi motor neuron stimulation. A.The top traces show the muscle's response to tonic SETi neuron firing at the markedinterspike frequencies; the bottom traces the response to the same input in thepresence of octopamine. Modified from Evans and Siegler (1982). B. Stimulation ofthe octopaminergic DUMETi modulatory neuron (bar) increases the amplitude andrelaxation rate of tibiae extensor twitches induced by tonic stimulation of the SETimotor neuron. Modified from Evans (1981).

muscles are stimulated at flight frequencies, considerable intertwitch summa-tion occurs, and hence they develop a sustained baseline similar to thatshown in Figs 7.2 and 7.3; it has therefore been suggested that these musclesprimarily develop tonic tension during flight (Pfau 1977; Pfau and Nachtigall1981).

The muscles are also believed to be involved in steering because, inresponse to an imposed roll, the muscle on the downward side receives moremotor neuron spikes per wingbeat cycle (which, if the muscle accuratelyresponded to this change, would generate more lift), whereas the muscle onthe upward side receives fewer spikes per cycle (which would generate lesslift) (Elson and Pfluger 1986; Wolf 1990). For this hypothesis to work, themuscles would need to accurately follow these neural input changes, other-


Fig. 7.7 Octopamine application increases the ability of the tibiae extensor muscle tofollow rhythmic SETi motor neuron activity mimicking that observed during walking.A. Under control conditions (i) the muscle relaxes slowly, and a baseline contracture,that would presumably be contrary to function, develops in response to rhythmicSETi neuron stimulation. In the presence of octopamine (ii) relaxation rate is increased,and the muscle is able to relax almost completely during each SETi neuron interburstinterval. B. Octopamine would reduce the ability of the tibiae extensor muscle tomaintain a sustained contraction. Tibiae extensor muscle contraction helps maintainposture when the animal is stationary, and octopamine reduces the tension the muscledevelops in response to tetanic SETi motor neuron stimulation. As such, DUMETineuron firing would presumably be contrary to function when the animal is stationary,and in fact the neuron is silent when the animal is not locomoting. Modified fromEvans and Siegler (1982).

wise the animal would be slow to respond at the beginning of a roll, andwould overcorrect at its end. However, recordings of muscle tension when



the appropriate stimulation is applied to its motor nerve show that (in theabsence of modulation) the muscle responds only slowly to these changes(Stevenson and Meuser 1997).

The role these muscles play in flight or steering has thus been difficult toidentify. However, Stevenson and Meuser (1997) have recently shown thatthese muscles also receive input from an identified octopaminergic dorsalunpaired median neuron (DUM3,4,5a). Stimulation of this neuron, or oc-topamine application, increases muscle twitch amplitude and relaxation rate.Under these conditions the muscles contract much more phasically whenactivated at flight frequencies (and may be completely phasic under thecombined influence of the octopaminergic modulation and a GABAergicinhibition the muscles also receive (Duch and Pfluger 1995)), and thus couldincrease lift generation as required during flight. Furthermore, in the presenceof octopamine, muscle tension accurately tracks transient changes in motorneuron firing. Wing lift could therefore be changed rapidly throughout a roll,and thus these observations also increase the muscles' suitability as steeringmuscles. Unfortunately, the activity of the modulatory neuron during flight isunknown. Nonetheless, these results clearly demonstrate the ability of musclemodulation to match effector dynamics to input temporal parameters, and toincrease muscle function and motor output range.

7.3 Hierarchies of control: extrinsic versus intrinsic modulation

In most of the examples considered so far, the modulation has been extrinsic—the modulators have been released from neurons other than the muscle'smotor neuron(s). However, muscle modulation can also be intrinsic, in whichthe motor neuron(s) themselves release modulators (Cropper et al. 19870).The mode of modulator release has important consequences for the func-tional effects of muscle modulation. As already noted, one possible advantageof muscle modulation is to increase motor output range. This increase takeson different forms depending on whether the modulators are extrinsic orintrinsic, and on the number of intrinsic pathways.

In the case of intrinsic modulation, modulator release is typically a func-tion of motor neuron activity. As a result, intrinsic modulation does not givethe muscle access to the full range of motor activity that would be possible ifmodulator release and motor neuron activity were decoupled. That is, if themuscle is receiving neural input with an activity pattern that induces therelease of X uM of modulator, it cannot express the motor output that thatneural activity pattern would induce in the presence of any other modulatorconcentration because motor neuron activity determines modulator concen-tration, and thus no other concentration can be achieved.

This limitation can be partially overcome by having multiple motor neu-rons, each with its own modulatory complement, innervate the muscle, inwhich case varying the firing of the various motor neurons will alter the


muscle's modulatory milieu. In the best known case of intrinsic neuromodu-lation (the ARC system), multiple motor neurons are in fact present (Cohenet al. 1978). However, modulation and motor neuron firing are still coupled,and hence this method does not provide complete independence of motorneuron activity and modulation.

In contrast, extrinsic modulation provides complete independence in thatany motor neuron activity pattern, and any modulator concentration, cansimultaneously exist. Extrinsic modulation is extremely widespread, and isgenerally present even in systems with intrinsic modulation. Extrinsicmodulation also provides a mechanism to overcome the problem of musclemodulation changing neural coding in that it allows simultaneous modula-tion of central networks and muscle, and hence simultaneous matching ofneuronal activity with changing muscle state.

Hirudo heartFMRFamide-like peptides are both extrinsic and intrinsic modulators of theleech heart (Li and Calabrese 1987). Each heart segment is innervated by acholinergic motor neuron, the HE neuron (Fig. 7.8A), which is driven by theheartbeat central pattern generator and fires rhythmic bursts of action poten-tials (Calabrese and Peterson 1983; Maranto and Calabrese 1984a,b), TheHE motor neurons induce Excitatory Junctional Potentials (EJPs) in heartmuscle cells, and these EJPs entrain a myogenic rhythm (Maranto andCalabrese 1984b; Calabrese and Maranto 1986). FMRFamide and relatedpeptides are present in HE motor neuron cell bodies and terminals (intrinsicmodulation), and are also present in a second class of neurons that innervatethe heart, the HA neurons (Kuhlman et al. 1985; Li and Calabrese 1987).The HA neurons are not motor neurons since their firing does not inducemuscle fiber EJPs, and they cannot entrain the heart rhythm (Calabrese andMaranto 1984), and thus are extrinsic modulatory neurons.

FMRFamide application to dissociated heart cells activates a persistentNa+-selective inward current and increases voltage-dependent Ca2+ and K+

currents (Thompson and Calabrese 1992). The increases in inward currentsmay play an important role in amplifying HE neuron-induced heart celldepolarization, and hence in inducing contraction. FMRFamide applicationor HA neuron activity dramatically increases heart tension (Fig. 7.8B), andcan induce myogenic rhythms in hearts pharmacologically isolated from HEneuron input (Li and Calabrese 1987). The inability to block the FMRFamidereceptor means it is impossible to prove that, as in Palaemon, FMRFamideor similar modulation is required for heart contraction. However, the ampli-fying effects of the currents which FMRFamide affects, and FMRFamide'sability to induce myogenicity, suggest that this could be the case, and thusthat FMRFamide could gate heart activity.

The presence of intrinsic and extrinsic modulation by the same neuropep-tide means that heart muscle state can be 'positively', but not 'negatively',decoupled from HE neuron activity. That is, modulator concentration cannot

Fig. 7.8 FMRFamide-like neuromodulation of the leech heart. A. A schematicshowing the innervation of the heart by the HE motor and HA modulatory neurons.Both neurons contain FMRFamide and related peptides. B. HA neuron activity (bars)dramatically increases heart tension. Modified from Calabrese and Maranto (1984).

be less than that associated with HE neuron activity, but HA neuron activitycan increase modulator concentration beyond this level. Recent work (R.Calabrese, personal communication) suggests that HA neuron activity is theprimary determinant of heart contraction amplitude. It is thus possible that,



as was also likely in Palaemon, HE neuron input plays a timing role andthat, once triggered, contraction amplitude is primarily determined by heartmodulatory state. However, changes in HE neuron activity would be ex-pected to change modulator concentration, and thus the extent to which thispartial decoupling of the periphery from the center actually exists woulddepend on the precise relationship between modulator release and HE neuronactivity.

7.4 Bringing it all together: the ARC neuromuscularsystem of Aplysia

As our last example, we shall discuss the accessory radula closer (ARC)neuromuscular system of Aplysia. The ARC system is relatively simple,experimentally tractable, and in systematic studies over the past 20 years hasprovided a body of data that illustrates many of the themes of this chapter inparticularly clear form. In addition, it provides insight into the role ofmultiple modulatory input to the same structure.

The ARC system participates in rhythmic consummatory feeding behaviorsuch as biting, swallowing, and rejection of unsuitable food (Kupfermann1974). As with many other molluscs, Aplysia grasps food, in this caseseaweed, by extending from its mouth a structure called the radula. Themovements of the radula are produced by a complex muscular structurecalled the buccal mass. In an ingestive cycle, the radula protracts, closes onthe food, retracts, and opens to release the food into the esophagus. Inrejection, the relationship between the opening and closing of the radula andits forward and backward movement is altered so that the radula is closedduring protraction rather than during retraction, pushing material out ratherthan pulling it in (Weiss et al. 1986; Morton and Chiel 1993).

To generate integrated, functional behavior each muscle cannot operateindependently, but instead must contract in a certain functional relationship—with the appropriate relative amplitude, waveform, and phase—to thecontractions of its antagonist muscle as well as those of other muscle pairs(Fig. 7.9). If these relationships are not achieved, the behavior will bedysfunctional, i.e. the animal will be unable to feed. Biting, swallowing, andrejection, which use the same muscles for quite different sequences of move-ments, require that different relationships be achieved. Furthermore, theparameters of these types of behavior are not fixed, but vary considerably inresponse to behavioral demands. Most notably, when a hungry animal beginsto feed, a progressive increase in feeding movement strength and frequency,characteristic of food-induced arousal, occurs (Fig. 7.10A; Susswein et al.1978). Feeding movement strength and frequency also vary according to thequality of the food being ingested (Hurwitz and Susswein 1992). The func-tional relationships between muscle contractions must be maintained throughall these modifications of behavior as well. These requirements can be

Fig. 7.9 The ARC neuromuscular system and its modulation in its func t iona lcontext. See text for details.

summarized as follows: out of all the possible sizes and shapes of all of thecontractions of all of the muscles, only a small subset produce functionalbehavior, and the hounds of this subset shift as output parameters change, oras the animal switches behavior. Furthermore, somewhere within the houndsthere is, presumably, some opt imal set of contractions that produces the mostefficient behavior.

Let us look more specifically at the constraints operating in one representa-tive antagonistic muscle pair—the ARC (or 1.5) muscle, a powerful musclethat closes the tadula (Cohen et al. 1978), and a weaker antagonist, such asthe recently described radula opener muscle complex 17-110 (Evans et al.1996). The problems inherent in the interaction of such a muscle pair areschematically presented in Fig. 7.10B. The top panels show the ind iv idua lcontractions of the two muscles, driven by alternating bursts of motor neuronfiring. The bottom panels show the net movement, assumed to be given, inthis simple conceptual illustration, by the sum of the ind iv idua l contractions.Functional behavior—alternating opening and closing of the radula -re-quires transitions across the dashed zero line.

Let us see what happens at the beginning of the meal as the animalbecomes aroused, as in Fig. 7.10A. The problems, as well as their solution,are entirely analogous to those described earlier (Fig. 7.2) for a single muscle.


Fig. 7.10 Food-induced arousal and the problems it poses for the integration of antagonistic muscle contractions. A. Top, increase instrength (measured on an arbitrary l-to-4 scale) of successive biting responses as the animal begins to feed. Modified from Weiss et al.(1982). Bottom, decrease in successive interbite intervals. Modified from Susswein et al. (1978). B. Schematic representation of theindividual contractions of the antagonistic radula closer (ARC) and opener muscles (top), and their sum, the net open/close movement ofthe radula (bottom), under various conditions as discussed in the text. Modified from Weiss et al. (1993).


Initially, the contractions are small and the behavior cycles slowly (column 1in Fig. 7.10B). Each muscle relaxes fully before its antagonist contracts, andfunctional opening and closing of the radula occurs. As the behavior speedsup, however, the muscles no longer have time to relax fully, and build up apermanent baseline contraction (column 2). As the ARC is the strongermuscle, this keeps the radula permanently closed. Functional behavior iscompletely disrupted. Essentially, the muscles are too slow for the speed atwhich the nervous system is now attempting to drive the behavior.

The problem becomes even worse as ARC contractions grow larger as wellas more frequent (column 3). Radula opening could be restored by strength-ening the opener muscle to match the ARC (column 4), but this would leavethe two muscles in permanent co-contracture, an energetically unfavorablesituation. A much better solution is to speed up the muscle kinetics, especiallythe relaxation kinetics of the stronger ARC muscle (column 5), to match theincreased frequency of the neural commands. This restores fully functionalopening and closing of the radula. The behavior now unfolds in all respectsessentially as before (compare columns 1 and 5), but on a faster time-scale.

Such kinetic matching is a very important part of the solution actuallyimplemented in the ARC muscle (see below). However, adjustment of justrelaxation rate may not always be sufficient. The relaxation rate of the ARCmuscle can be accelerated (presumably for biochemical or biomechanicalreasons) only perhaps fivefold. Beyond this, it is necessary to adjust othercontraction parameters. Reducing the size of contractions, for instance, helpsthem relax sooner to any given level. More generally, then, what is needed issimultaneous, independent control over multiple contraction parameters,such as size and relaxation rate, to dynamically match peripheral perfor-mance to central commands as the behavior changes.

In the ARC system, such control is provided by a complex peripheralneuromodulatory network (Fig. 7.9). The ARC muscle is innervated by twomotor neurons, B15 and B16, that release ACh as their classical transmitterto contract the muscle (Cohen et al. 1978). Both neurons also release severalfamilies of peptide cotransmitters that shape the ACh-induced contractions.B15 releases the small cardioactive peptides (SCPs) and the buccalins (BUCs);B16 releases the myomodulins (MMs) and the BUCs (Lloyd et al. 1984;Cropper et al. 1987a,b; 1988). There are two SCPs, nine MMs, and perhapsas many as 19 BUCs, but the forms within each family, which are probablyobligatorily co-released in a relatively constant mixture, may be functionallyredundant (Brezina et al. 1995). These are all intrinsic modulators, originat-ing within the motor neurons themselves. In addition, serotonin (5-HT) isreleased from the extrinsic, purely modulatory metacerebral cells (MCCs)(Weiss et al. 1978), and FMRFamide and five related peptides, the FRFs, arealso present in the ARC system (Cropper et al. 1994).

The actions of all these modulators on ARC muscle contractions (Fig.7.11) can be analysed as some combination of three primary effects: potentia-tion and depression of contraction size and acceleration of relaxation rate

Fig. 7.11 Typical actions of the various modulator classes in the ARC neuromuscularsystem. These are contractions of the ARC muscle (more precisely, muscle lengthunder isotonic, lightly loaded conditions) elicited by intracellularly driven bursts ofspikes (stim.) in motor neuron B15 (BUC) or B16 (all others), before (c, control) andafter application of 10-7 or 10-6 M of each modulator (in five separate experiments).Note the major effects: potentiation of amplitude and acceleration of relaxation ratewith 5-HT and SCP (SCPB was used); potentiation of amplitude at low, and depressionat high, MM (MMA) concentrations, with acceleration of relaxation rate at allconcentrations; pure depression, with no effect on relaxation rate, with FRF and BUC(FRFD, BUCA). Data kindly provided by Dr. I. V. Orekhova.

(Brezina et al. 1995). 5-HT and the SCPs are strong potentiators and weakdepressors (see below), giving large net increases in contraction size. TheMMs both strongly potentiate and strongly depress, the former predominat-ing at low and the latter at high concentrations. At the same time as theyalter contraction size, all these modulators (5-HT, SCPs, and MMs) acceler-ate muscle relaxation rate. The BUCs, FRFs, and FMRFamide are puredepressors, with no effect on relaxation rate.

A considerable amount is known about the underlying cellular mechanismsin this system. Except for the BUCs, all of the modulators act directly on theARC muscle itself. They potentiate contractions by enhancing, via thecAMP/PKA pathway, a Ca2+ current that supplies Ca2+ for contraction(Brezina et al. 1994 a), and depress contractions by activating an opposing,hyperpolarizing K current (Brezina et al. 1994b) (Figs 7.12, 7.13A). Strongdepressors such as the MMs and FRFs activate large K+ currents, weakdepressors such as the SCPs and 5-HT small K+ currents. The acceleration ofthe relaxation rate is thought to be mediated by cAMP/PKA-dependentphosphorylation of the giant muscle protein twitchin (Probst et al. 1994).The BUCs and to some extent the FRFs, FMRFamide, and even MMs depresscontractions by a different, indirect mechanism, namely by presynapticallyinhibiting ACh release from the motor neuron terminals onto the muscle(Cropper et al. 1988).

Let us now return to the functional significance of the modulation. B15



and B16 release significant amounts of peptide cotransmitters when they firein behaviorally relevant patterns, and progressively greater amounts whentheir firing intensifies as it does during food-induced arousal (Vilim et al.1996a,b). The potentiating action of the released SCPs and MMs, as well asof the extrinsic modulator 5-HT (see below), probably accounts for much ofthe increase in the contraction size seen in arousal. At the same time as theyincrease contraction size, however, the SCPs and MMs (and 5-HT) acceleratemuscle relaxation rate. Furthermore, together with the potentiating peptides,both neurons co-release the BUCs (Vilim et al. 1996a), which depresscontraction amplitude but do not affect relaxation rate, thus emphasizing thenet effect on relaxation rate. As the behavior speeds up during arousal, theseactions progressively intensify, dynamically optimizing the muscle propertiesalong the lines proposed above.

Through intrinsic modulation, the same motor neuron that commands amuscle to contract simultaneously optimizes the muscle's properties for thatcontraction. This is an elegant design with the minimum of elements. By thesame token, however, because everything follows automatically from thesame motor neuron firing pattern, the different modulatory effects are alwayscoupled to each other, as well as to the basic contraction due to the classicaltransmitter, and cannot be varied independently as may be required, forinstance, in different types of behavior that use the muscle in different ways.To do this, additional independent sources of modulation are required

Fig. 7.12 Schematic summary of the electrophysiological mechanisms by whichmodulators acting directly on the ARC muscle potentiate and depress its contractions.These are quasi-steady-state current-voltage (I-V) relations of various components ofion current in the ARC muscle. They are useful in summarizing the physiologicalsituation because the ARC is a slowly contracting, non-spiking muscle, in which thedegree of contraction is directly determined by the membrane voltage. The musclenormally rests just above the K equilibrium potential (EK). As it is depolarized byincreasing concentrations of ACh released from the motor neurons, it follows atrajectory similar to the curve marked IK (dominated by K currents). Contractionbegins above about -40mV, where an underlying Ca current (ICa) that is essentialfor contraction begins to activate. The potentiating modulators—5-HT, SCPs, andMMs—enhance ICa, and so potentiate contractions. (Right inset: SCPB enhances ICa

activated by voltage-clamp step from —90 to 0 mV). The directly acting depressingmodulators—5-HT, SCPs, MMs, FRFs, and FMRFamide—activate an outward,hyperpolarizing K current, which counteracts the ACh-induced depolarization,decreases activation of ICa, and so depresses contractions. Contractions may even beabolished altogether if, as with the MMs and FRFs, the K current is large enough tohyperpolarize the muscle below the contraction threshold of —40 mV. (Left inset:MMA activates K current at a steady holding potential of —30 mV.) Modified fromBrezina et al. (1994b).


(Brezina and Weiss 1997). These additional sources may be extrinsic modula-tory inputs or simply a second intrinsic modulatory motor neuron.

The power of two motor neurons releasing different peptides to produce avariety of contraction types was analysed using the ARC system (Brezina etal. 1996). For simplicity, this analysis was performed using just the twofamilies of potentiating peptides, the SCPs and MMs. At any concentration,either peptide alone, acting through the network of cellular mechanisms inthe muscle (Fig. 7.13A), couples the two functionally important effects of

Fig. 7.13 Combinatorial modulation by SCPs and MMs of the size and relaxationrate of ARC muscle contractions. A. The network of effects through which the SCPsand MMs act. Note the unequal convergence on the K current, which makes the MMsmuch stronger depressors than the SCPs. B. Plot of the contraction size:relaxation rateratio. Increasing concentrations of pure SCP and MM were applied in experimentslike those in Fig. 7.11. At any concentration, each modulator alone couples the twocontraction parameters in a fixed, but different, ratio. Ratios not on either curve (e.g.point X) cannot be achieved. C. Combinations of the modulators uncouple the twoparameters to allow access to a much wider range of ratios. These are the relaxationphases of contractions like those in Fig. 7.11. Modified from Brezina et al. (1996).

contraction size and relaxation rate in a fixed ratio. Other ratios that may berequired cannot be achieved. Accelerating the relaxation rate with SCP alone,for instance, inevitably also potentiates the contractions, while doing so withMM depresses them (Fig. 7.13B). Other contraction shapes, such as contrac-tions with much faster relaxation rate but unaltered size (point X), are notpossible. However, because the SCPs and MMs couple the two effects in adifferent ratio, intermediate ratios can be reached with combinations of bothSCP and MM. Different SCP:MM combinations are likely to be releasedwhen the two motor neurons fire differentially, as they do in different typesof behavior (Cropper et al. 1990). As a result, the two actions are effectivelyuncoupled; by varying the SCP:MM combination, it is possible to control thecontraction size and relaxation rate independently (Fig. 7.13C), so as toachieve, for instance, contractions with a much faster relaxation rate butunaltered size (Fig. 7.13C, last panel).



Extrinsic modulation, of course, can be completely independent of motorneuron activity. In the ARC system, the purely modulatory MCC neuron(Fig. 7.9) begins firing as soon as food is detected. This is well before the firstbite and before the ARC motor neurons fire, and thus before any intrinsicmodulators can be released. Therefore, the extrinsic modulation sets themuscle properties in an anticipatory fashion (Kupfermann and Weiss 1982).

It is worth reiterating that much of the modulation in the ARC system, aselsewhere, must be peripheral-due to the slow intrinsic properties of theARC muscle, there is no adjustment in motor neuron firing that the centralcircuitry can make to produce contractions that are large and brief. However,for optimal performance of the neuromuscular system, as the muscle ismodulated, the motor neuron firing pattern should change suitably. Thisrelates to the issue of neural coding discussed earlier in this chapter. Hereextrinsic modulation can play an important role. The MCC neuron, forexample, not only modulates the ARC muscle peripherally but at the sametime centrally alters the activity of the ARC motor neurons and higher-ordercircuits (Fig. 7.9) (Weiss et al. 1978; Kupfermann et al. 1989).

Modulatory processes very much like those operating in the ARC musclealso modulate its antagonist, the radula opener muscle (Scott et al. 1997),and appear to be ubiquitous throughout the feeding neuromuscular appara-tus of Aplysia. Most, if not all, feeding motor neurons contain intrinsicpeptide cotransmitters (Table 7.1), and modulatory mechanisms similar tothose reviewed here, though often in somewhat different combinations, havebeen described at their neuromuscular junctions and target muscles (e.g.Church et al. 1993; Fox and Lloyd 1997). The MCC neuron provideswidespread extrinsic modulation. In this way not just a single muscle ormuscle pair, but the whole feeding apparatus, is coordinated to producefunctional behavior.

7.5 Outstanding unresolved issues

In assembling these examples, several areas became apparent that are oftenignored in studies of muscle modulation, but whose investigation is necessaryto fully understand the role of muscle modulation in creating behavior.

First, detailed studies sufficient to predict the movements expected from agiven set of muscle contractions are seldom available. Particularly in inverte-brates, muscles often function in extremely complex physical plants in whichthe motion induced by any given muscle contraction is likely to depend onthe contractile state of other muscles or the arrangement of physical plantelements (ossicles, supporting tissue, etc.). Thus, at present it is generallyimpossible to predict the movement that will be produced by a given set ofmuscle contractions, and hence impossible to predict the behavioral conse-quences of modulator-induced changes in those contractions. Such studies areextremely tedious and preparation specific. However, it will be impossible to


Table 7.1 Peripheral modulation like that studied in the ARC muscle probablyoccurs in most, if not all, of the neuromuscular circuits generating feeding-relatedmovements in Aplysia. Summary of identified buccal motor neurons active duringbuccal motor programs, noting their classical fast transmitter (glu, glutamate), theircomplement of modulatory peptide cotransmitters (+, unidentified peptide; in allcases additional non-methionine-containing peptides may be present), the musclesinnervated, and the principal movements caused. Every motor neuron containsmodulatory peptides, in most cases some subset of the same peptides that modulatethe ARC (US) muscle. Modified from Church and Lloyd (1994)

Neuron

BlB2B3B4B6B7

B8A

B9B10Bll

B13

B15

B16B38

B39B43B44B45B47

B48

Conventionaltransmitter

Probably gluAChProbably gluAChProbably gluACh

ACh

AChAChACh

ACh

ACh

AChProbably glu

AChAChAChAChACh

ACh

Peptidetransmitter

SCPsSCPsFMRF, +FMRFSCPsFMRF, MMs,

SCPsMMs

SCPsSCPsMMs, SCPs

CCK-like

BUCs, SCPs

BUCs, MMsSCPs

FMRF, +SCPsMMsMMsMMs

MMs

Musclesinnervated

OesophagusOesophagusiI3m, aiI3p, m, 17i, c I3p, m, 16

iI6i,cI4, 16

i,c I3p, m, 16i,c I3p, miI4, 16

116

i!4, 15

iI5iI3a

i, cI3ailli,cI6illiI3a inhibitory

18

Evokedmovement

Gut peristalsisGut peristalsisJaw closureSmall, ill-definedJaw closure

Small, ill definedRadula closure

and retractionJaw closureJaw closureRadula backward

rotationRadula forward

rotationRadula backward

rotation andclosure

Radula closureAnterior jaw

closureJaw closureJaw shorteningSmall, ill definedJaw shorteningInhibition of

anterior jawclosure

Radulaprotractionand opening

truly understand the role modulation plays in generating behavior until theyare performed.

Second, detailed studies of muscle response to varying neural input (themuscle neural code), particularly in systems with well-described neural out-puts, are seldom available. Part of this may stem from a belief that a simpletransform always exists between neural activity and motor output, andconsequently that descriptions of neural activity are sufficient to understandbehavior. Also, once again such studies are tedious and preparation specific.


A recent attempt to derive a general method to predict EJP amplitude andsummation from neural spike data is a step towards resolving this difficulty(Sen et al. 1996), as is descriptive work relating muscle contraction character-istics (phasic amplitude, percentage phasic, etc.) to neural input parameters(spike frequency, duty cycle, etc.) (Ellis et al. 1996; Morris and Hooper1996, 1997a, 1998; Koehnle et al. 1997). Regardless, muscle modulationgenerally occurs in muscles with complex contraction properties, and it willbe impossible to understand how muscle modulation alters muscle contrac-tion without a more complete understanding of how these muscles respond tomotor neuron input.

Third, muscle modulation complicates neural control of muscle contractionin that it makes the effect of a given change in neural output dependent onmuscle state. A priori., this would seem to imply that central and peripheralmodulation should be coordinated so that central function changes appropri-ately as muscle state changes. However, we have very little information as towhen the various muscle modulatory systems are activated, and whether theyand central modulatory systems are co-activated as part of a generalizedbehavioral state change. How central activity is altered coordinately withmuscle modulation so that muscle activity is continually correctly controlledis not well understood, and is a fundamental difficulty in understanding hownervous systems produce action.

Fourth, studies of muscle modulation are generally qualitative, not quanti-tative. That is, although they show that modulation of the muscle hasoccurred, measurements of even the most basic contraction characteristics(rise time, relaxation rate) are generally lacking. Consequently, it is generallyimpossible to build even extremely simplified heuristic models with which toinvestigate the possible functional consequences of the modulation theydescribe. In a sense, it is the equivalent of describing an ion current as beinghyperpolarization activated, but not providing the voltage and time constantsnecessary to model it. The ability to numerically model neurons and neuralnetworks has tremendously deepened our understanding of nervous systemfunction; until we can do the same with the effectors that carry out thenervous system's commands, we can never hope to truly understand theneural basis of behavior.

Acknowledgements

The authors thank J. B. Thuma for figure preparation and proofreading. S. L.Hooper acknowledges support from the NIH, NIMH, and HFSP; V. Brezina,E. C. Cropper, and K. R. Weiss acknowledge support from the NIMH.

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Making circuits dance: neuromodulation ofmotor systems

OLE KIEHN AND PAUL S. KATZ

8.1 Introduction

To an observer, a dance can seem like an effortless extension of the music:body gliding across the floor, legs rhythmically moving to the music, armssuddenly lifted. Yet such a graceful series of movements belies complexproblems of coordination that underlie not just the dance, but most move-ments that any animal makes. How can a limited network of interconnectedneurons produce a seemingly infinite combination of movements?

The production of movements by animals must be highly flexible in orderto allow the animal to perform in a constantly changing environment. In thesimplest case, an animal must be able to increase or decrease the velocity ofits movement. Often this involves a substantial change in the phase relation-ships between the firing of motor neurons. Thus, when a horse changes itsgait from a walk to a pace or to a gallop, the motor neurons that innervatemuscles in the four legs are activated in completely different patterns (Fig.8.1). Clearly the motor networks underlying this flexibility must have mecha-nisms to allow different outputs to be generated at different times.

Although the actual cellular mechanisms underlying gait transitions andproduction of different movements by spinal cord and brainstem circuits inmammals simply are not known at this point, we do have a good idea howsimilar changes in motor patterns are produced for rhythmic behaviors inother types of organisms. In particular, work on invertebrate motor systems,such as the stomatogastric nervous system in crustaceans, indicates thatneuromodulatory actions of inputs to motor circuits contribute greatly to-wards producing the flexibility observed in motor behavior.

As we will see, neuromodulatory inputs can reshape the motor output byaltering cellular properties and the synaptic connectivity of neurons in motorcircuits. Neuromodulatory substances each have a suite of effects on neuronsin motor circuits, resulting in a coordinated response from the motor net-work. Since different neuromodulatory substances have different sets ofeffects, they can each cause a different type of motor behavior to be selected.Thus, neuromodulators have important roles in motor control in that theycan reconfigure a single motor network to produce many different types of

8

Fig. 8.1 Locomotor pattern of horse during walk, pace, and gallop. The dark barsindicate the stance phase when the legs are on the ground, while the white barsindicate the swing phase when legs are off the ground. In walking there is a sequentialmovement of legs first on one side then on the other side: left hind (LH), left front(LF), right hind (RH), and right front (RF). In pacing, legs on the same side of thebody move together (LH and LF) and out of phase with those on the opposite side ofthe body (RH and RF). In the gallop, one hindlimb lands first (LH), followed by theother hindlimb and the front leg from that side (RH, LF), and finally, the diagonalfront leg lands (RF). In gallop there is a period of time when none of the limbs are onthe ground before the pattern repeats. (Adapted from Pearson 1976.)

behavior. Recent results from mammalian and other vertebrate preparationssuggest that similar mechanisms are also at work in those circuits.

There are three basic types of movement. Voluntary movements, such asplaying the violin or throwing a ball, are purposeful and target-directed andrequire a complex interplay between lower and higher brain structures.Reflexive movements, such as the knee jerk reflex in humans or escaperesponses in fishes, are responses to external stimuli that are fast, involun-tary, and often involve a simple set of muscles. Rhythmic movements, likewalking, swimming, or chewing, are automatic and involve repetitive activa-

276 Neuromodulation of motor systems

Ole Kiehn and Paul S. Katz 277

tion of large groups of muscles, in a complex alternating pattern. Complexmovements such as dancing probably involve a combination of all three basictypes of movement. In this chapter, we will focus on rhythmic movementsbecause more is known about the roles that neuromodulation plays in theproduction of this class of movements. Many of the generalizations that wewill draw from this research are probably applicable not only to other typesof movements, but to non-motor circuits as well.

8.2 The elements of neuromodulation in motor systems: alterationsof cellular and synaptic properties

Rhythmic movements require that muscles contract and relax in a complexpattern. This can be seen in the sequential activation of flexor and extensormuscles controlling different joints in a walking animal or in the travellingwave of muscle contraction on each side of the body in a swimming fish.Localized neuronal networks in the central nervous system control the timingof these coordinated muscle activities. These networks, called central patterngenerators (CPGs), are capable of producing rhythmic movements even whenisolated from sensory input (Delcomyn 1980).

The output of a particular CPG, (i.e. its motor pattern) depends on twothings: the synaptic interconnections in the network and the intrinsic mem-brane properties of the component neurons. The synaptic interconnectivity orwiring diagram determines possible avenues of fast information transferbetween cells. The cellular properties of the component neurons determinehow these synaptic signals are processed before being conveyed to other cellsin the network.

It is now clear from studies over the last 10-15 years, in both invertebrateand vertebrate CPGs, that neuromodulators can change both the strength ofsynaptic connectivity within the network and the intrinsic membrane proper-ties of the component neurons. As we will see later in this chapter, themodulatory state of the system will determine a number of aspects of motorcontrol. Let us first examine what types of elementary effects modulatoryinputs have on motor circuits. These effects are the building blocks ofmodulatory control. Many of these mechanisms were discussed in Chapter 3,but we will review them here in the context of motor circuit design.

8.2.1 Rewiring circuits

We may often think of the nervous system as a hard-wired device whoseconnectivity is changed only during the developmental period or as a result oflearning. However, work on CPGs has shown that the strength of connec-tions between neurons is not fixed, but can vary continuously undermoment-to-moment neuromodulatory control. Synaptic strength can be in-


creased or decreased by neuromodulators acting either presynaptically toalter the amount of transmitter released or postsynaptically to alter theresponse of the follower neuron to the transmitter. In some cases, even thesign of a synapse can be inverted from excitatory to inhibitory due toneuromodulatory actions. Thus, the wiring diagram for a circuit is merely anoutline of potential connections and does not uniquely determine the flow ofinformation at all times.

Modulation of chemical transmissionOne well-documented example of changes in synaptic strength comes fromwork on the pyloric motor CPG in the lobster stomatogastric ganglion. Here,transmitter release occurs both in response to spike activity and in a gradedfashion as a result of subthreshold voltage-fluctuations (Hartline andGraubard 1992). The non-spiking, graded transmission among pyloric neu-rons is strongly altered by biogenic amines: dopamine, serotonin, and oc-topamine. For example, dopamine can extinguish the inhibitory connectionbetween a particular pair of identified neurons (Fig. 8.2A; Johnson andHarris-Warrick 1990). In contrast, octopamine enhances the transmission atthe same synapse (Fig. 8.2A). So the effect of neuromodulation can be afunctional disconnection of cells or a strengthening of the communicationbetween cells. The monoamines each have different actions at differentsynapses within the pyloric circuit. Some of the effects are due to presynapticchanges in the release of neurotransmitter and some are due to postsynapticchanges in the response of the receptors or in the input resistance of the cell(Cleland and Selverston 1997; Johnson and Harris-Warrick 1997). Thus, thewiring diagram of synaptic connections is strongly dependent upon whichneuromodulator is present (Johnson et al. 1995; Fig. 8.3A).

Neuromodulatory alteration of synaptic strength is likely to be importantfor producing flexibility in vertebrate locomotion due to the actions onglycinergic synapses of two neuromodulatory substances, serotonin and nora-drenaline. Glycinergic transmission in the spinal cord mediates reciprocalinhibition between neuronal pools, driving antagonist muscles in almost allvertebrate CPGs (see Kiehn et al. 1997). For example, in the CPG forswimming in Xenopus tadpoles, the glycinergic interneurons cross the spinalcord and ensure that the two sides of the body alternate during swimming.Serotonin and noradrenaline both act presynaptically to alter release ofglycine, but they have opposite effects: serotonin suppresses glycinergicneurotransmission, whereas noradrenaline enhances it (McDearmid et al.1997; Fig. 8.4). The functional consequence of the serotonergic modulation isa prolongation of burst duration (due to delayed burst termination) with littleeffect on the swimming frequency. In contrast, noradrenaline reduces theswimming frequency with little change in burst duration. It is likely that theseeffects of serotonin and noradrenaline on glycinergic transmission are com-mon to other vertebrate CPGs, where the two transmitters have effects on the

Fig. 8.2 Neuromodulation can change the strength and sign of graded synaptictransmission. All records are from isolated pairs of neurons in the stomatogastricnervous system of lobsters. Spike-evoked transmission is blocked with tetrodotoxin(TTX, 0.1 uM) leaving only graded synaptic transmission. A. Under controlconditions, depolarization of the presynaptic neuron (the pyloric dilator neuron; PD)hyperpolarizes the postsynaptic neuron (the lateral pyloric neuron; LP). Dopamine(100 uM) abolishes the inhibitory connection between PD and LP while octopamine(10 uM) enhances it. Neuromodulation is therefore functionally disconnecting cellsor strengthening their ties. B. The connection between LP and PY is a mixed chemicaland electrical synapse. The diode symbol represents a rectifying electrical synapse.Because the electrical synapse dominates under control conditions, depolarization ofthe presynaptic cell (LP) also causes the postsynaptic cell (PY) to depolarize. Whendopamine (100 uM) is added to the bath, the strength of the electrical synapse isreduced and the strength of the inhibitory chemical component is enhanced. PY nowhyperpolarizes upon LP depolarization. Dopamine, therefore, induces a sign reversalof the synapse. Lines with solid balls represent inhibitory synapses. (Adapted fromJohnson and Harris-Warrick 1990 and Johnson et al. 1993.)

motor patterns similar to those seen in tadpoles (see Sillar et al. 1997 forreferences).

Modulation of electrical couplingAnother way that neuromodulators can change CPG network activity is bychanging electrical coupling between neurons. Electrical coupling betweencells is present in many motor circuits where it tends to synchronize activityin connected cells. The influence that connected cells impose on each other isdependent upon the electrical coupling conductance (i.e. the ease with whichcurrent flows through the gap junctions). Neuromodulators can increase ordecrease the strength of the electrical coupling between cells. In its simplest



form this will synchronize the activity among cells or disconnect cells whichwere previously operating as an ensemble.

Some cells have both chemical and electrical synapses that can be differen-tially modulated. In one case in the stomatogastric system, two cells areconnected with a rectifying electrical synapse and a chemical inhibitorysynapse (Fig. 8.2B). Dopamine can invert the sign of the connection, convert-ing a functionally excitatory synapse into an inhibitory one (Johnson et al.1993). In the unmodulated state, the inhibitory component of this mixedsynapse is weak or absent and the electrical synapse dominates, making theconnection between the two neurons functionally excitatory. In the presenceof dopamine, the strength of the electrical synapse is reduced and the strengthof the inhibitory chemical component is enhanced. Dopamine, therefore,induces a sign reversal of the synapse, functionally rewiring the connectionbetween the two neurons.

Changing the coupling conductance can also have complex effects, whichdepend on the state of the intrinsic membrane properties of the neurons (seebelow). This important insight comes from work with mathematical simula-

Fig. 8.3 Rewiring of the pyloric CPG in the stomatogastric ganglion and modulationof cellular properties causes different functional circuits to arise and different motoroutputs to be produced. A. Neuromodulators can rewire a circuit by changing thesynaptic strength. The left diagram shows the anatomically defined set of connectionsbetween neurons in the pyloric CPG of the stomatogastric ganglion of spiny lobsters.These connections were determined by pairwise recording and stimulation of isolatedcell pairs. Dopamine, serotonin, and octopamine each have different effects on thesynaptic connections. A thicker line represents an enhancement of the synapse; adotted line represents a weakening of the synapse. (Adapted from Johnson et al.1995.) B. Neuromodulators can regulate bursting and steady state excitability. Theneurons were synaptically isolated from one another by killing presynaptic neuronsand/or pharmacologically blocking synapses. Under these conditions, some neuronsare silent (the anterior burster, AB, and the pyloric neuron, PY) and others aretonically active (the pyloric dilator, PD, and the lateral pyloric neuron, LP). The directactions of dopamine, serotonin, and octopamine were then observed. Each of thethree amines caused the AB neuron to display rhythmic membrane potentialoscillations topped by action potentials. The bursting induced in each case differed inamplitude and frequency. The membrane potentials of the remaining neurons weredifferentially altered by application of the amines. For example, dopamine caused thePD cell to hyperpolarize, but caused the PY cell to depolarize, whereas serotonin hadthe opposite effect. (Adapted from Harris-Warrick and Flamm 1986.) C. Differentfunctional circuits arise out of the various modulatory actions. As a result of theabove changes in synaptic strength and excitability, different sets of neurons participatein the circuit in the presence of each of the neuromodulators. D. Different motorpatterns are produced by the different functional circuits. Each reorganized circuitproduces a different motor pattern. The bars represent the proportions of the cycleduring which each of the neurons is firing action potentials.


tions of neurons, which have been used to examine the effect of electricallycoupling an oscillatory neuron to a second neuron that is either silent (andrelatively hyperpolarized) or depolarized (Kepler et al. 1990). Running thesimulation on a computer showed that in this simple two-neuron network,the shape of the waveform of the oscillating neuron, the strength of thecoupling conductance, and the membrane potential of the passive followerneuron will determine the frequency of oscillation for the two cells. Thus,when an oscillatory neuron with a dominating hyperpolarizing waveformwas connected to a silent passive neuron and the coupling conductance was

Fig. 8.4 Neuromodulators can change reciprocal inhibition in opposite directions. A.Schematic of the spinal locomotor network in the Xenopus tadpole. The excitatory(E) interneurons provide excitatory drive onto motor neurons (Mn), other excitatoryinterneurons and commissural interneurons (C). The C interneurons use glycine astransmitter and are responsible for the alternation between the two sides of the cordduring swimming. B. Intracellular recordings from a motor neuron. The rhythmicinhibition mediated by glycinergic IPSPs (straight arrow, upper trace) is reversed bychloride injection (straight arrow, lower trace). The arrowheads point to sodiumaction potentials. C. Serotonin (2 uM) decreases while noradrenaline (NA; 8 uM)increases the glycinergic transmission from C interneurons onto motor neurons. TheIPSPs have been reversed by chloride injection into the cells. D. These antagonisticactions of serotonin (2 uM) and noradrenalin (3 uM) on the reciprocal glycinergicinhibition translate into opposite changes in swimming frequency and motor neuronalburst durations. (Adapted from McDearmid et al. 1997.)

progressively increased, the bursting frequency decreased. In contrast, whenan oscillatory neuron with a dominating depolarizing waveform was coupledto a silent neuron, it sped up until it reached a maximal frequency, after


Fig. 8.5 Alteration of electrical coupling can change bursting behavior. The AB andPD cells of the stomatogastric ganglion are electrically coupled. AB is a conditionalburster and PD oscillates purely as a result of its electrical connection to AB (Al).However, the presence of PD as a passive follower of AB has an important effect onbursting in AB. When AB is hyperpolarized, its cycle period increases, but its burstduration remains a constant proportion of the overall cycle period (A2). When PD iskilled by photoinactivation, AB can continue to oscillate (Bl). However, now whenAB is hyperpolarized and slows down its cycle period, the duration of each burstremains constant (B2). Thus, decoupling PD from AB changed AB from a constantduty cycle oscillator into a constant duration oscillator. (Adapted from Marder et al.1993.)

which it started to decrease its frequency again as the coupling strengthcontinued to increase. These effects were reversed when the passive cells weredepolarized.

The effect of electrical coupling in controlling the oscillations produced bya real network was demonstrated in the stomatogastric nervous system (Fig.8.5). Under certain conditions (see below) the membrane potential of theanterior burster (AB) cell will oscillate on its own without any synaptic input.We will see later that these oscillations are important for producing rhythmicbehavior. The AB is electrically coupled to another stomatogastric neuron,the pyloric dilator (PD). PD is not rhythmically active on its own, but will firebursts of action potentials due to its electrical coupling with the rhythmicallyactive AB cell. However, by virtue of its coupling, PD exerts control over the



oscillatory pattern of activity expressed by AB (Marder et al. 1993). If AB ishyperpolarized by current injection through a microelectrode, it will oscillatemore slowly (Fig. 8.5A1-A2). As the period of oscillation lengthens, theburst duration of AB lengthens as well, so that AB remains depolarized for aconstant proportion of the overall cycle period. However, if the electricalcoupling to PD is removed (in this case by killing PD, Fig. 8.5B1), lengthen-ing the oscillation period does not lengthen the burst duration. Instead, ABdisplays constant burst duration regardless of cycle period (Fig. 8.5B2). Thus,the electrical coupling to PD acts as a mechanism to ensure that AB displays aconstant duty cycle regardless of the oscillation period. The mechanismunderlying this effect is not related to the specific conductances of PD, butinstead can be reproduced with a general model of an oscillator and anelectrically coupled passive cell (Marder et al. 1993).

To summarize, the chemical and electrical synapses between neurons in acircuit are under the control of neuromodulation. Neuromodulatory sub-stances can alter the strength of coupling as well as the functional sign of theconnection. Since different neuromodulatory substances can have oppositeeffects on the same synapses, the network can be functionally rewired on amoment-to-moment basis, allowing it to produce different motor outputs.Therefore, the functional connectivity between the neurons in a circuit at anyone moment is defined by which neuromodulators are present at that time.

8.2.2 Changing neuronal personalities

Another way that neuromodulation can functionally rewire a network is toalter how neurons integrate their synaptic inputs. Neurons are endowed witha variety of ionic conductances, including voltage-dependent potassium,sodium, and calcium conductances. The particular combination of conduc-tances, their time- and voltage-dependence, and the density of channels in themembrane are unique features of individual neurons, or subpopulations ofneurons. As a result of such individual differences, neurons are often distin-guishable from one another in their firing behavior and their electricalresponses to synaptic inputs: that is, they have 'individual personalities'.Neuromodulators can alter the biophysical parameters of one or several ofthese conductances, thereby changing the overall balance of conductancesexpressed by a neuron. This may profoundly alter the cell's firing behaviorand thereby alter the cell's personality. As a consequence of the manyneuromodulators present and their different effects on ionic conductances,the same cell can display multiple personalities. Such changes in cellularbehavior have major repercussions for motor pattern generation.

Modulation of resting conductances can determine neuronalparticipation in a networkNeuromodulation of the resting membrane potential is one mechanism foraltering the participation of a neuron in a network (Fig. 8.3B). For example,


depolarization of the resting potential could aid in the recruitment of a cellinto a motor network by fast synaptic inputs. Such a depolarization canoccur merely by decreasing a resting potassium conductance, which wouldcause the membrane potential to move closer to spike threshold. In contrast,increasing a resting potassium conductance might hyperpolarize a cell andcause it to drop out of the network. Additionally, such changes in restingconductances will have consequences for the activation state of voltage-dependent conductances that determine the cell's firing pattern. Thus, simplychanging the resting potential of sets of neurons can select a functional circuitfrom an anatomically defined network (Fig. 8.3C) and allow different behav-ior to be produced (Fig. 8.3D).

Modulation of conductances involved in phase-transitionsReciprocal inhibition between neurons is a common design used for rhythmicpattern generation (for a recent review see Cropper and Weiss 1996). There-fore, ionic conductances, which change the time that it takes neurons toescape from inhibition, are essential for the function of the CPGs becausethey help initiate phase-transitions between inhibition and excitation. Threeionic conductances, which are widely distributed throughout the animalkingdom, have attracted the special attention of researchers. These conduc-tances produce currents known as IT (a transient low-threshold calciumcurrent), Ih (a hyperpolarization-activated inward cation current), and IA (atransient potassium current). Perhaps because these conductances are soimportant for determining the pattern of activity in a network, they arecommon targets for neuromodulation.

The transient low-threshold calcium current, IT, has certain properties thatare important for phase transitions and enhancement of bursting activity.First, this current has an activation threshold around or slightly depolarizedto the resting membrane potential. Second, it inactivates rapidly upon depo-larization. Thus, if the membrane potential is maintained at a depolarizedlevel, IT is inactivated after a short period of time. Finally, the inactivation isremoved by hyperpolarization (see Huguenard 1996 for a review). Therefore,inhibitory synaptic input will remove the inactivation by hyperpolarizing thecell. Upon release of the hyperpolarization, IT will cause a short-lastingrebound excitation before inactivating again. Changing the maximum con-ductance of IT will therefore change the rate of alternation between phases ina rhythmic behavior. This is exactly what happens in the lamprey spinal cordwhere metabotropic GABAB receptor activation depresses a low-thresholdcalcium current, similar to IT, in interneurons involved in producing theswimming motor pattern (Matsushima et al. 1993). This depression results indelayed spike onset, leading to a longer hyperpolarized phase and thereforeto a slower alternation between antagonistic muscles. The end result is that

the fish swims more slowly. Ih has a number of properties which make it important for allowingneurons to escape from inhibition (see Pape 1996 for a review). First, the


conductance underlying the current is strongly activated by hyperpolariza-tion, such as occurs during synaptic inhibition. Second, the current is inwardand thus would tend to depolarize the cell and counteract the hyperpolariza-tion that activated the conductance. Third, when the membrane potential ishyperpolarized, the current tends to remain on because it is slowly inactivat-ing, or in some cases does not inactivate at all. Finally, the kinetics ofactivation and deactivation are slow. So when the membrane potential ishyperpolarized, the current activates slowly, causing the membrane potentialto slowly 'sag' back towards the resting membrane potential. But moreimportantly, when the hyperpolarization is released it is also slow to deacti-vate, so Ih contributes to the formation of a depolarizing overshoot. Thisbehavior has two important consequences for the integrative properties of thecell. First, the depolarizing sag limits the effect of sustained inhibitory inputsand helps the cell escape from inhibition. Second, the depolarizing overshootcan trigger a burst of action potentials. Thus, if Ih is enhanced by neuromod-ulation, for example by shifting its voltage dependence for activation to moredepolarized levels or by accelerating its rate of activation (Pape 1996), thetime required for the phase transition will decrease. This is exactly whathappens to the lateral pyloric (LP) neuron from the stomatogastric ganglion,where dopamine enhances Ih (Harris-Warrick et al. 1995).

The third current which regulates the rebound from inhibition is thetransient potassium current, IA. This outward potassium current is usuallyinactivated at resting membrane potential. Hyperpolarization removes theresting inactivation of IA and a subsequent depolarization will cause atransient activation of the conductance. Activation of IA will counteract therebound activation—brought about, for example, by Ih or IT—and delay itsonset. Therefore, a neuromodulatory enhancement of IA will tend to delayphase transitions, whereas a reduction of IA will accelerate such transitions.Once again, this occurs in the stomatogastric ganglion where dopaminecauses a phase advance of LP, in part, by reducing the contribution of IA

(Harris-Warrick et al. 1995).Often, multiple conductances are regulated simultaneously by a neuro-

modulator to produce a particular change in the behavior of a neuron. Forexample, as just mentioned above, dopamine simultaneously enhances Ih andreduces IA in the LP neuron. This combined change reinforces the action ofdopamine because both modulatory effects will tend to accelerate the re-bound of the neuron from inhibition. The relative contribution of each of thedifferent conductances towards producing a particular response is difficult todetermine because each conductance has voltage and time dependencies.Thus, merely blocking a single conductance will indirectly alter the currentcarried by other conductances. One method that has been successfully used toevaluate the roles of the different conductances in the production of complexneuronal activity is the conductance clamp or dynamic clamp (Sharp et al.1993). Using this technique, which allows artificial conductances to beinserted into real neurons, it was determined that most of the effect of


dopamine on the LP neuron was due to a reduction of IA and that theenhancement of Ih was relatively less important in causing the observedphase advance (Harris-Warrick et al. 1995).

The role of Ih and IA in controlling the phasing of LP was independentlytested using 'hybrid networks' of simulated neurons and real neurons (Fig.8.6; Le Masson et al. 1995). A real-time numerical simulation of the LPneuron was created on a computer. The ionic conductances of this artificialLP neuron had the same properties as the real LP neuron. Then the real LPneuron in the pyloric network was killed by photoinactivation (Miller andSelverston 1979) and the artificial LP neuron was substituted in its place.Microelectrodes in the other pyloric neurons (AB, PD, and PY) were used tomonitor when computer generated synaptic potentials should be evoked inthe model neuron and for injecting synaptic currents into these followerneurons of LP when the model LP neuron was generating a rhythmic output(Fig. 8.6B). The output of the hybrid network—measured as the membranepotential fluctuations in the real neurons and the artificial LP neuron—wasremarkably similar to the control output from the intact network (Fig.8.6C,D). Besides confirming that the known conductances in the LP neuroncan account for its pattern of activity, the hybrid network also allowedresearchers to alter conductances in the LP neuron at will to see how thataffected the overall network activity. It was found that when the maximalconductance of IA was set low and the maximal conductance of Ih was sethigh (a situation comparable to dopamine modulation observed in real LPneurons; Harris-Warrick et al. 1995), then the model LP neuron fired earlierin the cycle than when IA was high and Ih was low (Fig. 8.6E,F).

In short, IT, I/h, and IA are important for phase-transitions in rhythmicallyactive networks. These currents operate at voltages near the threshold forspike activity, making them well suited to interact with rhythmic inhibition.Neuromodulation of their biophysical parameters can dampen or boostthe postsynaptic effect of the rhythmic inhibition without interfering withpresynaptic mechanisms.

Modulation of conductances that determine spike rateThe rate at which a neuron fires is not purely a function of how muchexcitatory synaptic input it receives. The firing rate of a neuron is determinedby a number of factors including the density of sodium channels and theiractivation and inactivation kinetics. However, these types of parameters arerarely affected by neuromodulation. Instead, neuromodulation tends to alterconductances that determine the period between spikes. This can causechanges not only in steady state firing, but also in spike frequency adapta-tion.

A variety of different ionic conductances play roles in determining firingrate. Some that have been implicated in spike frequency adaptation in anumber of systems are conductances producing calcium-activated potassiumcurrents (IK-Ca)- The effect of IK-ca is often seen as a slow after-

Fig. 8.6 The use of hybrid circuits to examine the roles of conductances in theproduction of rhythmic motor patterns. A. A representation of the pyloric CPG circuitof spiny lobsters. B. The lateral pyloric (LP) neuron was killed by photoinactivationand replaced by a computer-generated simulation of LP. The synapses that LPreceived from other neurons were simulated by recording from presynaptic neuronsand injecting simulated synaptic currents in response to presynaptic membranedepolarization into the model LP neuron. The synaptic actions of LP onto postsynapticfollowers (PD, LP, and PY) were mimicked by injecting appropriate currents throughthe microelectrodes in follower neurons. C. The output of the pyloric CPG undercontrol conditions. The top three traces are simultaneous intracellular recordings fromthree of the pyloric cell types (PD, LP, and PY). The bottom bars represent the timesduring which each of the cells fired action potentials. Note that there is a three-phasepattern. D. The output of the hybrid network. The model LP neuron trace is thesimulated membrane potential generated by the computer in real time. The phaserelationships and appearance of the model cell and the real cells are similar to thecontrol network. E. In a different preparation, the parameters of the model LP neuronwere altered so that the maximal conductance of IA was set high and the maximalconductance of Ih was set low. This resulted in a phase delay of the model LP neuronwith respect to the other two cells. F. In the same preparation, when the parameters ofthe model LP neuron were altered so that the maximal conductance of IA was set lowand the maximal conductance of Ih was set high (a condition that is comparable todopamine modulation), the LP neuron showed a phase advance and fired more actionpotentials. (Adapted from Le Masson et al. 1995.)

hyperpolarization following an action potential. A decrease in IK-Ca willdecrease spike frequency adaptation and increase neuronal excitability as isseen in lamprey motor neurons and premotor interneurons in response to


Fig. 8.7 Modulation of spike adaptation in lamprey neurons alters lamprey swimmingbehavior. A. Lamprey spinal neurons exhibit a slow after-hyperpolarization (sAHP)following action potentials. The sAHP is mediated by a calcium-activated potassiumcurrent (IK-Ca). Serotonin reduces IK_Ca and thus decreases the sAHP. B. Directlyblocking the sAHP with apamin causes an increase in excitability of spinal neurons byreducing spike frequency adaptation. C. Oscillations in spinal neurons are producedin the presence of TTX by addition of NMDA to the bathing medium (top). Furtheraddition of the channel-blocker apamin increases burst duration and cycle period byprolonging the depolarizing phase of the bursts. D. Blocking IK-Ca also increases burstduration and cycle period during swimming. In the presence of NMDA, alternatingbursts of action potentials typical of fictive swimming can be recorded from the left(L) and right (R) ventral roots of the lamprey spinal cord. Increasing the level of freeserotonin level by blocking the serotonin uptake with citalopram (1 uM) caused amarked slowing of the NMDA-induced swimming frequency. There is also aprolongation of burst duration and an increase in burst intensity. (Data from Wallenand Grillner 1987; Wallen et al. 1989a. Adapted from Grillner and Matsushima 1991and El Manira et al. 1994.)

either serotonin or apamin, a blocker of IK-Ca (Wallen et al. 1989a,b; Fig.8.7A,B). This decreased conductance causes an increase in the intensity ofmotor neuron burst discharges during swimming induced by excitatoryamino acid receptor agonists, like NMDA. The period of oscillation for theswimming also increases because a reduction of IK-Ca will prolong theplateau phase of the NMDA-induced membrane potential oscillations inpremotor interneurons (Fig. 8.7C, see below). When applied during an


NMDA-induced swim motor program, serotonin or enhancement of endoge-nous serotonin release by serotonin reuptake blockers will increase burstduration and period in much the same manner as that produced by blockadeof IK-Ca (Fig. 8.7D).

Modulation of conductances underlying neuronal bistabilityActivation or inactivation of bistable properties by neuromodulators is animportant mechanism for controlling motor circuits. Bistability refers to thecondition whereby a neuron has two relatively stable membrane potentials:one below threshold for firing action potentials and one above threshold.Brief depolarizing currents, such as a barrage of synaptic input, can cause theneuron's membrane potential to jump to the depolarized state, where it willcontinue to fire action potentials for a prolonged period of time. Thisdepolarized membrane potential is termed a plateau potential (Hartline et al.1988; Llinas 1988). The plateau can be terminated either spontaneouslybecause of a time-dependent change in the balance of ionic conductances (e.g.a slow activation of IK-Ca)

or by brief inhibitory synaptic inputs. In someneurons the threshold for activating the plateau potential is above thethreshold for action potential generation. This allows the cell to display atruly bistable firing pattern because the neuron can switch back and forthbetween two stable modes of firing (Kiehn 1991; Kiehn and Ekin 1998).

In general, if a neuron can produce plateau potentials, then its integrativecapacity is greatly transformed. Strong synaptic inputs will rapidly activate ordeactivate the plateau, while weaker inputs will be ineffective or need longerduration. By enhancing the responses to brief synaptic inputs, both inintensity and duration, plateau properties provide an important postsynapticamplification mechanism. In rhythmic systems, plateau properties allow anentire phase of activity to be switched on as a result of a brief excitatoryinput, or in response to a rebound from inhibition.

Plateau potentials have been found in neurons throughout the animalkingdom. In most cases, the ability of a neuron to produce plateau potentialsis controlled by neuromodulatory substances (Figs 8.8 and 8.9). Typically,neuromodulators induce plateau potentials by enhancing inward currents (Ih,ICa) and/or decreasing outward currents such as calcium-activated potassiumcurrents (IK-Ca) or other resting potassium currents (Fig. 8.9A; Kiehn 1991;Kiehn and Harris-Warrick 1992b; Zhang and Harris-Warrick 1995). Con-versely, neuromodulatory inputs can inactivate the ability of a neuron toproduce plateau potentials (Cazalets et al. 1990). By acting on conductancesthat induce or remove the ability of neurons to produce plateau potentials,neuromodulation can drastically transform the processing performed by acircuit (see Fig. 8.13).

Modulation of conductances underlying conditional burstingRhythmic motor patterns in many networks arise in part due to the activityof bursting pacemaker neurons. These neurons produce rhythmic bursts of

Fig. 8.8 Transmitter-induction of motor neuronal plateau properties across species.A. Turtle spinal motor neuron. In the presence of serotonin (10 uM) a shortdepolarizing current pulse initiates a prolonged plateau potential in a turtle motorneuron. The plateau potential is terminated by a brief hyperpolarizing current pulse.The fast sodium spikes are blocked with TTX (1 uM). (Adapted from Hounsgaardand Kiehn 1989.) B. Cat spinal motor neuron. Induction of plateau potentials in catspinal motor neurons after intravenous injection of the noradrenergic precursorL-DOPA (100mg/kg). The plateau potential was elicited by short-lasting depolarizingpulse and fast action potentials were inactivated by long-lasting precedingdepolarization. A short lasting hyperpolarizing pulse terminated the plateau. (Adaptedfrom Conway et al. 1988.) C. Insect respiratory motor neuron. In the presence ofoctopamine a short-lasting depolarizing current injection elicits a prolonged plateau ina locust respiratory motor neuron, which is terminated by steady hyperpolarization.(Adapted from Ramirez and Pearson 1991b.)

Fig. 8.9 Co-transmitters acting at different receptors can participate inneurotransmission and a neuromodulatory induction of plateau potentials. A.Schematic diagram of the synapse from a gastropyloric receptor (GPR) to the dorsalgastric (DG) motor neuron in the stomatogastric ganglion of crabs. Acetylcholinereleased from GPR acts at nicotinic receptors. Serotonin also released from GPRacting at one or more receptors alters a number of different conductances. It enhancesan Ih and a calcium conductance (ICa). The latter causes an increased influx ofcalcium, which secondarily activates another inward current, a non-specific cationcurrent (ICAN) and an outward conductance (Io)- Serotonin decreases Io. B.Stimulation of GPR at 10 Hz for 2s evokes a prolonged plateau potential in DG. Abrief pulse of current injected into DG prior to GPR stimulation elicited a single spike.C. In the presence of nicotinic and muscarinic acetylcholine receptor antagonists, GPRstimulation caused a smaller depolarization of DG that was insufficient to evoke aplateau potential. Immediately after GPR stimulation, a brief current pulse triggered aplateau potential. The same current pulse delivered before GPR or 9s after wassubthreshold for evoking even an action potential. D. A puff of serotonin deliveredfrom a pipette will also induce plateau properties in DG. Here the plateau wasterminated prematurely with a brief hyperpolarizing current pulse. (From Kiehn andHarris-Warrick 1992a.)

action potentials not as a result of synaptic input, but rather as a consequenceof their intrinsic ionic conductances (see Chapter 4). In only a few motorsystems have the bursting properties been shown to be constitutive (Smith etal. 1991). Rather, bursting pacemaker activity in individual neurons isusually conditional upon the presence of neuromodulatory substances. Per-haps the best example of a conditional burster neuron in a CPG is theanterior burster (AB) cell, in the crustacean stomatogastric ganglion. WhenAB is synaptically isolated from all other CPG neurons in the stomatogastric


ganglion, it continues to burst. The bursting in AB disappears, however,when it is isolated from extrinsic neuromodulatory inputs (Fig. 8.3B, toptrace, control).

Not only is the bursting in AB conditional upon the presence of neuromod-ulatory substances, but the character of bursting is dependent upon whichneuromodulator is present. The bursting activity in a completely isolated ABcan be restored through application of any one of a number of neuromodula-tory substances to the bathing medium or by stimulating modulatory neuronsthat release these transmitters (Harris-Warrick and Marder 1991; Marder1993; Marder and Calabrese 1996). Due to differences in the conductancesaltered by each modulatory substance, AB bursts in a slightly differentfashion in terms of cycle frequency, burst duration, and burst amplitude(Harris-Warrick and Flamm 1986; Fig. 8.3B, top traces). Since AB is theprime pacemaker for the entire CPG, this translates into specific changes inthe overall pyloric network activity. The multiple mechanisms for burstinduction, therefore, allow the system to change the frequency and amplitudeof its motor output simply by changing the relative activity of neuromodula-tory inputs.

Conditional bursting properties are also seen in a variety of spinal cordinterneurons and motor neurons (Wallen and Grillner 1987; see Grillner andMatsushima 1991 for a review). For example, in lamprey neurons, bursting isdependent upon activation of glutamate receptors by NMD A (Fig. 8.7C,D).Such membrane potential oscillations are seen in many other vertebrateneurons and arise from the NMDA-induced negative slope conductanceregion (NSR) in the current-voltage relationship brought about by a voltage-dependent block of the NMDA-receptor channel by Mg2 + . NMDA-inducedmembrane potential oscillations are also found in rhythmically active in-terneurons in the lumbar spinal cord of neonatal rats (Hochman et al. 1994;Kiehn et al. 1996 b) and in spinal swim-related neurons in amphibians (Sillarand Simmers 1994; reviewed in Sillar et al. 1997). In amphibians, theNMDA-mediated voltage oscillations require the presence of serotonin (Sillarand Simmers 1994; Scrymgeour-Wedderburn et al. 1997), suggesting thatserotonin in these species is needed for the non-linearity in the current-volt-age relationship.

Due to the large numbers of cells in spinal vertebrate networks, it is noteasy to test whether conditional NMDA-mediated bursting plays a significantrole for the rhythm-generation itself. Nevertheless, it is certain that thenon-linearity in membrane properties which NMDA and possibly othertransmitters induce in spinal interneurons will work as an amplifier ofrhythmic activity. During rhythmic network activity, this can be demon-strated by injecting steady current into cells which possess burstingproperties, and observing the amplitude changes of the intracellular voltageexcursions. When such cells are hyperpolarized, and the membrane potentialmoves out of the NSR, the amplitude of the rhythmic voltage excursiondecreases dramatically (Fig. 8.10) and the effect of the 'pure' synaptic activitycan be seen. At more depolarized levels the bursting properties will kick in

Fig. 8.10 Bursting properties enhance synaptic inputs. A. Muscarine-induced (20 uM)rhythmic locomotor-like activity recorded in spinal interneuron and a ventral root inthe neonatal rat. At zero current injection into the cell the voltage fluctuations wereabout 30 mV in amplitude. The amplitude of the fluctuations were reduced to about10 mV with a —17.5 pA constant hyperpolarization, while further hyperpolarizationwith a similar sized constant current injection (from —17.5 to —35 pA) caused aproportionally smaller reduction in the peak to through amplitude. This behaviorindicates a strong amplification of the synaptic drive in a certain voltage region. B. Involtage clamp the cell displays a clear negative slope region in the I-V relationship,indicative of bursting properties. When comparing membrane potentials in A and B itis seen that when the membrane moves into the negative slope region the strongamplification of the peak to trough amplitude happens (compare 'a', 'b', and 'c')(Adapted from Kiehn et al. 1996b).

again and amplify the depolarizing phase. Thus, the bursting properties willfacilitate excitatory information flow in the circuit and aid in the generationof rhythmic network activity. In amphibians, the NMDA-mediated voltageoscillations are very slow compared to the swimming frequency. They will,therefore, not contribute to the generation of the cycle-by-cycle motor output.Instead, the NMDA-mediated oscillations may be recruited when slow changesin the motor output are needed (Scrymgeour-Wedderburn et al. 1997).

8.2.3 Changes in cellular and synaptic properties producesecondary effects

As we have illustrated, neuromodulatory inputs to a motor network canchange the strength of chemical and electrical synapses as well as the intrinsicelectrical properties of neurons in that network. This ultimately changes theoutput of the network and hence the behavior that is produced. It isimportant to note that each neuromodulatory substance can have a differenteffect on each member of a motor network either by acting on a different



receptor on each target or by having the receptors coupled to differenteffectors. As we will see, the differential actions of neuromodulators onneurons in motor circuits underlie some forms of behavioral plasticity such asmotor pattern selection.

Even if two target cells have the same receptor and effector systems, theaction of a neuromodulator could result in different behavioral outputs dueto distinctions in the non-modulated intrinsic ionic conductances expressedby the two neurons. For example, if Neuron A expressed a large calcium-activated potassium conductance (in this case a non-modulated channel) andNeuron B expressed a large calcium-activated cation current (also a non-modulated channel), then a neuromodulatory enhancement of a calciumconductance in both cells would cause an inhibition of activity in Neuron A,but an enhancement of activity in Neuron B. Thus, the overall action of aneuromodulator cannot be predicted without knowing the response of eachmember of the network.

The functional action of a neuromodulator becomes even more complexwhen embedded within a network of interconnected neurons. A change in theconductances of a single neuron can reverberate through a network and causechanges in the activity of other neurons. For example, changing the kineticsof a single potassium conductance in the AB cell of the stomatogastricganglion will cause that cell to change its bursting frequency. That willchange the firing rate of every other cell in the circuit due to the synapticinteractions of the network.

Similarly, a modulatory change to one CPG circuit can reverberate to othercircuits with which it is loosely coupled. For example, in the crab stomato-gastric ganglion, one neuron in the gastric mill CPG receives inhibition fromone neuron in the pyloric CPG. The two CPGs appear to be autonomouswith the natural period of gastric mill CPG at 10s being much slower thanthat of the pyloric CPG (about 0.5-2 s). However, computer simulations ofthe circuit suggested that even with this small amount of synaptic input to thegastric mill CPG, changes in the frequency of pyloric motor pattern inducedby modulatory substances ought to change the period of oscillation of theslower gastric mill CPG (Marder et al. 1998; Nadim et al. 1998). Physiologi-cal experiments subsequently provided evidence to support this hypothesis.Thus, a modulatory effect in one CPG circuit can even alter the production ofmotor patterns in other circuits.

8.3 Choreographing motor patterns: the effects of neuromodulatorson the output of motor circuits

Through their actions on synaptic and membrane properties, neuromodula-tory substances can alter the expression of motor patterns (Fig. 8.11). Byendowing neurons with the properties that are needed to form a functionalCPG circuit, neuromodulatory substances can initiate motor patterns. Simi-

Fig. 8.11 Network functions of neuromodulators. A. Unmodulated networks. B.Neuromodulators can ini t ia te and maintain motor activity. C. Neuromodulators canchange the ongoing motor activity. D-E. Neuromodulators can reorganize motorpatterns by: switching of neurons between networks (D) or causing fusion of motornetworks (E).

lar ly , by changing those properties, modulatory substances can alter anongoing motor pattern. Recent work has shown tha t these same types ofeffects can reorganize ent ire networks.



8.3.1 Neuromodulators can activate motor patterns

As a rule, the initiation of rhythmic movements requires non-rhythmic inputfrom a source external to the CPG network itself. Often the initiationinvolves fast synaptic excitation, which brings the network into its oscillatingmode. A good example is the escape swimming elicited in tadpoles inresponse to short-lasting skin stimulation (Roberts 1990). Primary sensoryneurons process the sensory message and excite secondary sensory neurons,which depolarize CPG neurons in the spinal cord. This short-lasting depolar-ization is enough to start the network activity, which is then maintained byintrinsic network mechanisms.

In contrast to this type of initiation, where the transmitter activates analready functional circuit, neuromodulators can initiate motor patterns bytransforming a group of interconnected neurons into a functional centralpattern generator (Fig. 8.11A,B). An example of this occurs when the sea slugTritonia diomedea executes rhythmic swimming behavior to escape frompredators. The pathway for initiation of this response involves activation of aset of serotonergic neurons (Fig. 8.12). These cells increase the strength ofsynapses made by another neuron in the network and reduce spike frequencyadaptation in that other neuron, allowing the motor system to function for aperiod of time as a rhythmic pattern generator (Katz et al. 1994; Katz andFrost 1995a,b, 1997). Application of a serotonin antagonist that blocks thesemodulatory actions also blocks the ability of the animal to produce the swimbehavior (McClellan et al. 1994; Katz and Frost 1995a). Furthermore,application of exogenous serotonin will elicit either the swim motor programwhen applied to the isolated nervous system or the swim behavior itself wheninjected into the whole animal (McClellan et al. 1994).

Neuromodulators, such as 5-HT, noradrenaline, and dopamine, can alsoinitiate locomotor activity in cats, rats, and rabbits (see Cazalets 1995 andKiehn et al. 1997 for recent reviews). It has been debated, however, whetherthese amines normally function to activate the CPG networks (see Grillner1981 and Pearson 1993). A crucial argument has been that pharmacologicaldepletion of spinal monoamines does not prevent the glutamate-mediatedinitiation of locomotion by stimulation of the locomotor region in themidbrain. It is possible, however, that parallel pathways exist to initiate thelocomotor activity and it seems premature to exclude a role of the amines inthe initiating process. The case is further complicated by the fact thatglutamate, acting via the NMDA-receptor, induces bursting properties inspinal interneurons, as discussed previously. Although the necessity of thesebursting properties for rhythm-generation has not been established, theyprovide an example of rhythmogenic membrane properties that might beactivated in conjunction with initiation of motor patterns in vertebrates.

Neuromodulators can also play a role in initiation of rhythmic motoroutput by changing the threshold for conventional synaptic inputs to evoke amotor pattern. This is the case in the locomotor systems of the leech and thelocust. In the leech, 5-HT increases the probability that a stimulus will cause

Fig. 8.12 Neuromodulation is involved in in i t ia t ion of the T r i t o n i a swim motorprogram. A. The network of neurons under ly ing the swim motor program in Tr i tonia .Sensory neurons converge on the dorsal ramp interneuron (DRI) which synapses onthe dorsal swim in t e rneu rons (DSIs). The DSIs have synap t i c actions on the otherCPG neurons: cerebral neuron 2 (C2) and the ven t r a l swim interneurons (VSIs). The

CPG neurons synapse on the ef ferent f l e x i o n neurons, ventral flexion neuron (VPN),and dorsal f lex ion neurons (DFN-A,B), which relay the pattern of a c t i v i t y to themuscles. The DSIs also evoke neuromodulatory actions on C2. B. Example of a swimmotor program. Simul taneous intracellular recordings from DRI, DSI, and C2. At thearrow, a per ipheral nerve was stimulated for 0.5s evoking the swim motor program.Bursts in DSI and C2 alternate with hursts in the VSIs (not shown). C. An example ofneuromodula t ion int r ins ic to the C P G . DSI st imulat ion evokes monosynaptic EPSPs( n e u r o t r a n s m i s s i o n ) and causes an increase in the excitabil i ty of C2 (neuromodulation).Without the increased exci tabi l i ty , C2 would not be capable of f i r i n g at the ratesobserved dur ing the swim motor program. 1). DSI st imulat ion presynaptically enhancestransmitter release from C2 so that EPSPs evoked by C2 onto its motor neuronfollower (DFN-A) are larger fo l lowing DSI s t imula t ion . (P. Katz, from previously-unpublished recordings; see also Katz and Frost 1995a, 1997.)

the animal to swim. Some of this effect is mediated by a 5-HT-inducedincrease in excitability of neurons that gate the input to the CPG (Kleinhausand Angstadt 1995). In the flight system of the locust, octopamine appears tofacilitate the ini t ia t ion of f l i g h t by inducing burst ing and plateau properties inCPG neurons (Ramirez and Pearson 1991 a,b).



8.3.2 Neuromodulators can alter ongoing motor activity

The most well-recognized, and ubiquitous, role for neuromodulators inmotor control is to alter ongoing motor activity (Fig. 8.11C). For rhythmicmotor acts, there are three ways that a neuromodulator can alter an ongoingmotor pattern: (1) it can increase or decrease the repetition rate of themovements (i.e. the cycle frequency), (2) it can change muscle force bychanging the duration and intensity of the motor neuron bursts, or (3) it canchange phase relationships between muscles.

In the previous sections, we mentioned several mechanisms which wouldchange the cycle frequency of the movement. These include changes inbursting properties, resting membrane currents, one or several of the sub-threshold currents (/h, 7T, and /A) and reduction of /K.Ca. Modulation ofsynaptic inhibition in the network can also result in a change of cyclefrequency. For example, we saw that noradrenaline decreases the speed oftadpole swimming by enhancing glycinergic transmission (Fig. 8.4D). Modu-lation of reciprocal inhibition between CPG neurons has also been suggestedas one of the mechanisms underlying peptidergic regulation of the heartbeatfrequency in medicinal leeches (Calabrese et al. 1995).

Some of the modulatory building blocks that we have discussed can alterthe firing rate of CPG interneurons. This will change the synaptic drive tomotor neurons, altering the intensity of motor neuron firing, and therebychanging the force produced by the muscles. Furthermore, the intensity ofmotor neuron bursts can also be altered by directly modulating the propertiesof the motor neurons themselves or by modulating the strength of thesynapses to the motor neurons (see below).

The phase relationships between motor neurons determine the actualnature of the behavior; a change in phasing underlies the gait that the animaluses. Phase relationships can vary greatly, as in the difference between a walkand a gallop, or they can vary more subtly as they do during different speedswithin a gait. At the moment it is not known to what extent neuromodula-tors are involved in such changes in the intact animal. Some simulationssuggest that modulatory actions are not necessary for gait changes (Collinsand Richmond 1994), but numerous studies in both invertebrates and verte-brates have shown that neuromodulators can change the phase relations andrelative timing of motor neuron firing and the resulting muscle activity in anongoing rhythmic motor act (for example, Fig. 8.3D). The mechanisms forthese ubiquitous changes are only starting to be unravelled but they involvemany of the building blocks that we have already discussed, e.g. the sub-threshold currents (Ih, IT, and IA).

8.3.3 Neuromodulators can reconfigure networks

Perhaps the most dramatic role of neuromodulation in motor control is theability of neuromodulators to reorganize or reconfigure CPG networks


(Dickinson and Moulins 1992; Marder and Weimann 1992). This type ofneuromodulation is most thoroughly studied in the stomatogastric nervoussystem, and the main conclusion from this work is that although the networkof synapses between neurons is anatomically defined, the functional circuitsthat exist at any one time are due to the actions of neuromodulators. Thus,by changing cellular and synaptic properties, neuromodulators choreographcircuits from an ensemble of interacting neurons capable of dancing with avariety of partners.

In the simplest case of reconfiguration, silent neurons can be recruited intoa motor pattern, or previously active neurons can be removed from participa-tion. This results in different functional circuits producing fundamentallydifferent motor patterns (Fig. 8.3C,D).

A neuron (or neurons) can also switch allegiance between functionalcircuits (Fig. 8.11D). For example, the VD cell in lobsters is often active withthe pyloric rhythm (Fig. 8.13A,B), but when the CPG controlling the cardiacsac (CS) portion of the foregut is active, VD ceases to fire with the pyloriccircuit and is instead recruited into the much slower cardiac sac circuit (Fig.8.13D,E; Hooper and Moulins 1989). The reconfiguration can be evokedreliably by stimulating a particular sensory nerve and the ionic mechanismsunderlying this switch have been elucidated in some detail. When VDparticipates in the pyloric motor pattern, it exhibits plateau properties thatallow it to produce strong bursts of action potentials upon rebound from therhythmic synaptic inhibition it receives from pyloric neurons (Fig. 8.13C). Inresponse to stimulation of the sensory nerve, which activates the cardiac sacrhythm, VD loses its ability to generate plateau potentials and will not fireaction potentials in response to pyloric synaptic input (Fig. 8.13F). Thiscauses VD to suspend its participation in the pyloric motor pattern. At thesame time, strong synaptic excitation from cardiac sac neurons providesslower rhythmic input that now drives the cell. It is almost as if stimulationof the sensory input acts like the clutch of an automobile engine: it candisable the ability of VD to generate plateau properties and thereby disengagethe input from the pyloric motor pattern; this allows VD to then be engagedand controlled by the slower excitatory inputs of the cardiac sac rhythm.

Neuromodulators also reconfigure entire motor networks, causing neuronscomprising separate functional circuits to merge or fuse into one newfunctional circuit (Fig. 8.HE). This has been shown in the lobster, where theneuropeptide Red Pigment Concentrating Hormone (RPCH) causes a fusionof two CPG circuits into one (Dickinson et al. 1990). Before RPCH applica-tion, two motor patterns coexist, being generated by separate CPG circuitswith different inherent cycle frequencies. However, in the presence of RPCH,the neurons composing the two circuits unite and fire in a conjoint pattern,with an intermediate frequency. One mechanism for the fusion seems to bean RPHC-induced increase in the strength of synapses from one circuit (thecardiac sac CPG) driving inputs onto the other circuit (the gastric mill CPG).In another example from the same system, activity of the pyloric suppressor

Fig. 8.13 Neurons can change their allegiance and switch from one functional circuitto another due to neuromodulatory actions. A. Under conditions where the cardiacsac (CS) CPG is inactive, the ventral dilator (VD) neuron participates in the pyloriccircuit. B. The top two traces are simultaneous intracellular recordings showing theactivity of VD and the pyloric dilator (PD) cells during typical pyloric activity. Thebottom two lines are representations of the spiking activity of VD and PD. Note thatthe two cells fire in a constant phase relationship when the CS circuit is not active. C.Under control conditions, VD expresses plateau properties. In response to a briefpulse of injected current, it remains depolarized and fires action potentials. D. Whenthe CS circuit is active, VD changes its firing pattern and joins the CS circuit. E.Simultaneous recordings from PD and VD when both the pyloric and CS circuits areactive show that VD now fires long bursts of action potentials in phase with theslower CS motor pattern and is mostly silent during the faster pyloric motor pattern.PD in contrast is only slightly affected during CS bursts, but continues to express thefaster pyloric motor pattern. Note that the time-scales in B and E are different. F. TheCS motor pattern can be reliably elicited by stimulating a sensory nerve. Followingstimulation of this nerve, VD loses its ability to produce plateau potentials in responseto current injection. The loss of plateau properties is one of the factors that causes VDto cease its participation in the pyloric circuit. (Adapted from Hooper and Moulins1989.)

(PS) neuron in lobsters can take elements from three different CPG circuitsand cause them to fire in one common motor pattern (Meyrand et al. 1991).In this way, muscles that at times act independently can be drawn togetherinto a more complex pattern of activity (Fig. 8.14).

At the moment, little is known about these types of network reorganiza-tions in CPGs other than those in the stomatogastric system. Reconfigurationin the larger neuronal networks that control rhythmic activity in vertebratesis difficult to evaluate because the CPG networks are poorly defined and it is



Fig. 8.14 Entire networks can reorganize due to the actions of modulatory neurons,A. When the pyloric suppressor (PS) neuron is si lent , there are three separate CPGcircuits in thc stomatogastric nervous system: the esophageal CPG, the pyloric CPG,and the gastric m i l l CPG. When separated from each other, these three circuitsproduce motor rhythms with different frequencies, with the gastric m i l l r h y t h m beingthe slowest and the pyloric rhythm the fastest. B. When PS is active, components of allthree CPGs fuse into a single funct ional circuit with PS now producing a motorpattern r u n n i n g at a frequency which was not present in any of the motor rhythmsbefore. Some neurons, such as pyloric neuron l.P and the gastric neuron GM, ceasebeing active and do not contribute to the production of the motor pattern, C.Simultaneous i n t r a c e l l u l a r recordings from LG, VD, LP, and PS, and an ex t race l lu la rrecording of a nerve showing sp ik ing act ivi ty from the GM neurons. On the lef t sideof the figure, PS is silent. GM and I.G are par t ic ipat ing in the ongoing gastric millmotor pattern wi th a cycle period of about 10s (one cycle is out l ined by the box.).The VD and I.P are par t ic ipat ing in the faster pylor ic motor pattern with a cycleperiod of about 2s. There is no monitor of the slow esophageal r h y t h m . When PS isdepolarized (at the arrow head), it begins to fire bursts of action potentials. Thisimmediately changes the activity of the other cells in the network. I.P and GM stopf i r i n g action potentials, whi le LG and VD switch their f i r ing pattern so they are f i r i n ghursts of action potentials with a period of about 8s (see box on right). (Adaptedfrom Meyrand et al. 1991.)

impossible to he sure that one has recorded from all possible members of afunctional circuit. In one of the best-defined vertebrate CPG networks, the


Fig. 8.15 Dual patterns of hindlimb locomotor activity induced by serotonin anddopamine in the neonatal rat. Serotonin (40 uM) induces a regular fast activity whiledopamine (0.2 mM) induces a slow irregular activity. IL is a flexor muscle in the limb.Rectus femoris (RF) and vastus laterali (VL) shift from flexor-like activity in serotoninto extensor-like activity in dopamine. Semitendinosus (ST) shifts from its usualextensor activity (out of phase with IL) in serotonin to flexor-like activity in dopamine.Finally, biceps femoris (BF) displays, in addition to its extensor bursts, flexor bursts indopamine. (Adapted from Kiehn and Kjaerulff 1996.)

spinal CPG networks in tadpoles, sensory stimulation can switch rhythmicstruggling into rhythmic swimming: two distinct motor patterns. Soffe (1993,1996) suggested that the switch from struggling to swimming in the tadpole,'involves recruitment of neurons within classes already participating in swim-ming rather than otherwise inactive ones', and that 'the expression of one orthe other pattern is controlled simply by the level of excitation within this(same) circuit'. This led the author to propose that neuromodulatory reorga-nization of the network is not needed to obtain such changes in behavior. Incontrast, work in the isolated rat spinal cord led Cowley and Schmidt (1994)and Kiehn and Kjaerulff (1996) to propose that the distinct rhythmic hindlimbmotor patterns elicited by acetylcholine, 5-HT, and dopamine can be ex-plained by specific transmitter-induced reorganization of the spinal CPGnetworks. The two patterns induced by 5-HT and dopamine, for example,are distinct in terms of flexor or extensor activity in certain muscles (Kiehnand Kjaerulff 1996; Fig. 8.15). This suggests that if the spinal rhythmgenerating network that controls a single limb is composed of a mosaic offlexor and extensor 'unit-burst-generators' with independent control of mus-cles or parts of muscle (Grillner 1981), the switch from extensor to flexoractivity may be explained by assuming that the activity of neurons in suchunit-burst-generators is affected differentially by 5-HT and dopamine. Analternative explanation is that 5-HT and dopamine directly recruit or expelspecific subgroups of motor neurons, either by postsynaptic effects or by


controlling the transmission from the unit-burst-generator to the motorneurons.

8.3.4 Neuromodulation can alter the ability of a CPG to driveits follower motor neurons

Neuromodulation can change the effectiveness of CPG circuits at drivingmotor neurons by directly altering the coupling between the CPG and itsfollower motor neurons. For example, neuromodulatory substances havebeen shown to alter the strength of the synaptic drive from the CPG to motorneurons in the respiratory system of vertebrates. Here activation ofmetabotropic glutamate receptors (mGluRs) or serotonin receptors reducesthe inspiratory drive in phrenic motor neurons through a presynaptic mecha-nism (Lindsay and Feldman 1993; Dong et al. 1996). Paradoxically, bothreceptors also increase the excitability of phrenic motor neurons, possibly byreducing K+ currents, at the same time that they decrease synaptic input tothese neurons. How this contrary presynaptic and postsynaptic modulation isadjusted during normal ventilation is not yet understood. It is likely thateither one of the two modulatory effects will dominate at a given time,possibly due to changes in concentrations of modulatory substances. Forexample, low concentrations of mGluR agonists result in a decreased inspira-tory output from phrenic motor neurons, while high concentrations have thereverse effect.

Neuromodulatory actions can also increase the coupling of a CPG to itsfollowers. In the mollusc Tritonia, the coupling of the escape swim CPG toits efferent followers increases when the CPG is activated due to the actionsof serotonergic neurons within the CPG (Fig. 8.12D; Katz et al. 1994). Thismay enable the CPG to better drive its followers during the production of thebehavior.

Charles Sherrington referred to motor neurons as the final common path ofa motor system: all signals must eventually be translated into motor neuronfiring in order for a movement to be produced. However, the motor neuronsare not merely passive followers of their inputs. The membrane properties ofthe motor neuron will shape the inputs that it receives and these propertiesare under neuromodulatory control. For example, serotonin and nora-drenaline can induce the expression of plateau potentials in spinal motorneurons of cats and turtles (Fig. 8.8, Conway et al. 1988;Hounsgaard and Kiehn 1989; see Kiehn 1991 for a review). Motor neuronplateau potentials may be partly responsible for the sustained motor neuronfiring during postural activity in intact rats and humans (Kiehn et al. 1996 a;Kiehn and Eken, 1997). It is also likely that they help shape the final motoroutput during walking (Brownstone et al. 1994). Thus, when plateau poten-tials are enabled in motor neurons, they behave as active followers on theoutput side of the spinal cord. They can actively interpret their synaptic inputand shape the motor output. In at least one system, there is also evidence thatmodulation of motor neuron properties causes them to be recruited into the


CPG, thereby allowing the output neurons to affect the generation of thebehavior (Mangan et al. 1994).

8.4 Integrating neuromodulation into neuronal circuits

Much of the work on neuromodulation in motor systems involves applicationof exogenous substances to evoke neuromodulatory effects. However, to fullyunderstand how neuromodulation is integrated into motor circuits, we mustrecord from and stimulate the neurons that release neuromodulatory sub-stances. By recording the activity of neuromodulatory neurons during theproduction of motor activity, we can determine when the neuromodulation isactivated with respect to the behavior that it affects. It is also important tostimulate neuromodulatory neurons because the natural release of transmittermay differ from the effects elicited by exogenous application of the sub-stances due to interactions with cotransmitters or due to temporal and spatialconstraints on release from the neuron.

8.4.1 Properties of neuromodulatory neurons

Many of the neurons that evoke neuromodulatory effects also have classicalsynaptic actions either through the actions of cotransmitters or due to asingle substance acting at different receptors. In this way, they can participatein rapid information transfer as well as slower neuromodulatory effects. Forexample, muscle-receptor cells in the crab stomatogastric nervous system,called GPR cells, release serotonin to induce plateau potentials in a postsy-naptic neuron, while they co-release acetylcholine which acts at nicotinicacetylcholine receptors to evoke fast EPSPs that trigger the plateau potentials(Fig. 8.9; Katz and Harris-Warrick 1989). In contrast, the dorsal swiminterneurons (DSIs) in the Tritonia swim CPG use serotonin for both neuro-transmission and neuromodulation through actions at pharmacologicallydistinct serotonin receptors (Fig. 8.12C,D; Katz and Frost 1995a). Similarly,fast and slow actions of neurons are seen in vertebrate motor systems whereglutamate acts as both a neurotransmitter and a neuromodulator throughdifferent postsynaptic receptors.

Neuromodulatory neurons can also have diverse neuromodulatory actionson different postsynaptic followers. For example, by acting at pharmacologi-cally distinct receptors, serotonin released by the GPR cells induces plateauproperties in DG, but produces a slow inhibition of another cell type, and aslow excitation of yet a third cell type (Katz and Harris-Warrick 1990b;Zhang and Harris-Warrick 1994). Segregation of receptors on postsynapticneurons also allows a single presynaptic cell to have a neuromodulatoryeffect on one cell type, but only fast synaptic actions on other cell types.

Recordings from neuromodulatory cells have shown that some neuromod-


ulators may be released tonically while others apparently are released sporad-ically or even rhythmically. For example, the giant serotonin neuron inmolluscs plays a modulatory role in the generation of feeding behavior(Pentreath et al. 1982). Recent recordings of these neurons in freely behavingsnails indicate that they fire tonically at a low rate to produce their modula-tory actions (Yeoman et al. 1994). In contrast, the serotonergic brainstemcells, which project to motor and premotor neurons in vertebrate spinal cord(Jacobs and Fornal 1993), fire rhythmic bursts of action potentials duringrepetitive activity, like locomotion. Such rhythmic activity is also observed insome modulatory neurons in the lobster stomatogastric system (Meyrand etal. 1994; Fig. 8.14C), and the serotonergic neurons in the Tritonia escapeswim CPG (Katz et al. 1994; Fig. 8.12B).

8.4.2 Sources of neuromodulation

There are a variety of sources of neuromodulation for CPGs. These can bedivided into two categories: extrinsic neuromodulation (originating fromother parts of the nervous system) or intrinsic neuromodulation (originatingfrom within the CPG itself; see Katz 1995; Katz and Frost 1996 for recentreviews). These two types of neuromodulation have different sets of con-straints associated with them (Fig. 8.16). For example, extrinsic neuromodu-lation is, in essence, optional to the CPG. That is, the circuit can exist in amodulated or an unmodulated state or different modulatory inputs can beactive at different times. In contrast, intrinsic neuromodulation is as much apart of the circuit as the neurotransmission. The activity of any particularextrinsic input is determined by activity elsewhere in the nervous system,whereas the activity of an intrinsic modulatory neuron is determined by theactivity of the circuit of which it is a part.

Extrinsic neuromodulationExtrinsic neuromodulation originates from sources outside the circuits theyaffect. That is to say that the synaptic input from these neurons is notrequired for the cycle-by-cycle production of the rhythmic behavior, yet theneurons have some effect on the motor pattern. Such extrinsic sources caninclude 'higher-order' modulatory neurons, neurohormones, or primary sen-sory afferents.

The concept of higher-order modulatory neurons is exemplified by theserotonergic, dopaminergic, and noradrenergic cell groups within the verte-brate brainstem. These cells are few in numbers, but they project fibers in adivergent fashion to almost every area of the brain and spinal cord, and thushave very global actions. For example, individual 5-HT-containing cellsinnervate both cervical and lumbar parts of the cord, acting on both motorneurons and pre-motor interneurons in those areas (Kuypers and Huisman1982). In this way, extrinsic modulation can control multiple motor circuitssimultaneously (e.g. circuits generating forelimb and hindlimb movements),

Fig. 8.16 Neuromodula tory effects can be evoked by neurons either extrinsic orinrr insic to a CPG. The sources of extrinsie neuromodulation are higher-ordermodulatory neurons, hormones or pr imary sensory affereuts, which are each distinctfrom the CPG circuit itself (a,b,c). Extrinsic neuroniodulation is usually optional tothe system. With extrinsic neu romodu la t ion , a single c i r c u i t can be affected bydifferent modulatory inputs. For example, neurons a and b both affect the left CVGcircuit. Extrinsic neuromodulatory i n p u t s can act as coordinating elements, affectingmult iple circuits (such as neuron b). Intr insic neuromodulation arises from within thecircuit that is affected (neurons d and e) and is therefore not optional to the c i rcu i t ,but instead varies wi th the degree of network ac t iv i ty . Neurons that arc intr insic toone c i r cu i t may be ext r ins ic to other circuits (such as neuron d).

and can provide a coordinated modulatory i npu t to many neurons andconnections in the same motor CPG.

Neurohormones can have neuromodulatory actions on motor systems. Forexample, a cholecystokinin (CCK)-like neuropept ide plays a role in activatingfeeding behavior in lobsters (Turrigiano and Selverston 1990). The concen-tration of the CCK-like peptide increases in the hemolymph or blood af terfeeding and the increase correlates with an increase in rhythmic motoractivity in the gastric mil l musculature. Injection of CCK into the hemolymphdirectly causes a similar increase in gastric mill activity while CCK antago-nists block the effect. Together, this suggests that a CCK-like neurnpeptide inthe blood indeed activates the gastric m i l l CPG. Interest ingly, a CCK-likepeptide is also present in higher-order neurons that project to the stomatogas-tric ganglion (Turrigiano and Selverston 1991), suggesting that the peptideexerts its effects from mul t ip le sources, possible using different regulatoryprocesses and time-scales.

Another newly recognized source of extrinsic modulat ion is pr imary sen-sory neurons (see Chapter 6). For example, the GPR cells of the stomatogas-trie system are proprioceptive cells that respond to stretch of part icularmuscles (Katz and Haris-Warrick 1989, 1990a,b), much l ike the vertebratemuscle spindle. GPR participates in r e f l ex loops with some neurons in the



stomatogastric ganglion, and also has long-lasting neuromodulatory effects,altering the production of motor patterns. This role for primary sensoryneurons means that afferent input is not limited to acting on a cycle-by-cyclebasis to correct the motor output, but rather the motor pattern can be shapedin more complex ways as a result of the sensory feedback that the circuitreceives. Neuropeptides and amines are present in vertebrate sensory neuronsand there is increasing evidence for their participation in modulatory actions.

Intrinsic neuromodulationNeuromodulation can also arise intrinsic to a motor circuit and affect otherneurons in the same CPG (Katz 1995; Katz and Frost 1996). The arrange-ment allows a degree of local modulatory control and ensures thatmodulation occurs only when the particular circuit is active. Intrinsic neuro-modulation has recently been described in a few CPGs. For example, thedorsal swim interneurons (DSIs) were identified as members of the CPGunderlying escape swimming in Tritonia; because of their fast synapticactions they participate in the cycle-by-cycle generation of the rhythmicswimming behavior (Getting 1989). However, these same neurons also dy-namically increase the strength of synapses made by another neuron in thenetwork, as well as increase that cell's excitability (Katz et al. 1994; Fig.8.12C). Thus, the properties of cells in the CPG change while the behavior isbeing generated due to the modulatory actions of another cell embedded inthe CPG. The presence of neuromodulation intrinsic to the CPG may beimportant for monitoring the activity of the CPG and thus causing use-depen-dent alterations in the behavior.

Such use-dependent changes in a motor system are seen with anotherexample of intrinsic neuromodulation from work on tadpoles. Here it hasbeen shown that ATP released from spinal neurons during sensory-evokedswimming episodes increases the excitability of the spinal CPG network byreducing voltage-activated K+ currents in spinal neurons (Dale and Gilday1996). After it is released, ATP is metabolized into adenosine by extracellularectonucleotidases. Adenosine acts at a set of receptors distinct from ATPreceptors to cause a reduction in voltage-activated Ca2+ currents, therebylower the excitability of the rhythmic network (Fig. 8.17). Thus, the twoneuromodulators have opposing actions on the network activity. Dale andGilday (1996) have proposed that a gradually changing balance betweenextracellular concentrations of ATP and ADP during a swim episode mayplay a role in the termination of the behavior. At the onset of swimming, therelative concentration of ATP will be high, whereas the concentration of ADPwill be low. That causes the network excitability to start off high. As theswimming progresses, the adenosine concentration would increase as moreATP is converted to adenosine. This leads to a gradual increase in K+

currents and decrease in Ca2+ currents and thereby decreases networkexcitability. Eventually, the system will stop producing rhythmic motoractivity due to the build-up of ADP. Thus, accumulation of a neuromodulator

Fig. 8.17 Intrinsic neuromodulation can serve as a mechanism for terminatingrhythmic motor activity. A. The proposed scheme for adenosine effects on theswimming rhythm. Activity increases the external ATP level as it is released fromneurons during swimming episodes. Initially, ATP increases the excitability of thespinal CPG network by reducing voltage-activated K+ conductances in spinal neurons.With a delay, adenosine is produced from ATP, and adenosine reduces voltage-activated Ca2+ conductances and thereby lowers the excitability of the rhythmicnetwork. In the beginning of the swimming episode the ATP level will be high and theadenosine level low. That gives a high network excitability. As the swimmingcontinues, the adenosine concentration increases as more ATP is converted toadenosine, leading to a gradual increase in K+ conductance and decrease in Ca2 +

conductance and thereby a decreased network excitability. Eventually, the system willstop producing rhythmic motor activity. The effects on K+ conductances and Ca2 +

conductances are studied in acutely isolated neurons from the spinal cord. B-C.Sensory-evoked swimming activity (recorded as ventral root activity, VR) in Xenopustadpole is inhibited by bath application of adenosine (B: 100 uM) and increased by anadenosine receptor antagonist (C: 8-phenyltheophylline, 2 uM). (Adapted from Daleand Gilday 1996.)

produced by a motor network can play a role in self-termination of motorbehavior.



8.4.3 Convergence of modulation

One of the consistent themes which emerges from studying neuromodulationin motor systems is that there is often a convergence of modulatory inputsonto a motor network. For example, in the respiratory system, acetylcholine,5-HT, catecholamines, and at least five endogenous peptides, some of whichare colocalized with the amines, modulate ventilation (Bianchi et al. 1995).The many functions of all this modulatory input are still being explored, butit is clear that it provides flexibility to the system. Since each modulatoryinput has a different suite of effects, activation of a particular input or set ofinputs will select the motor pattern to be produced by the network.

How are all of these inputs coordinated? What prevents simultaneouslyactive inputs from conflicting with each other? Researchers are just beginningto unravel these questions. For example, it has been shown that the GPR cellsactivate another modulatory input to the stomatogastric ganglion of crabs(Blitz and Nusbaum 1996). In this way the effect of GPR cells is combinedwith the supporting modulatory actions of another input neuron. It is easy toimagine that modulatory inputs can suppress other conflicting inputs viapresynaptic inhibition (Nusbaum 1994).

8.5 Long-term alteration of motor patterns

The outputs of CPGs are adjusted constantly to regulate the degree of musclecontraction caused by their activity. For example, in limbed animals sensorysignals enhance the load support during the stance phase and prevent theswing phase until the leg is unloaded. This proprioceptive feedback ismediated by muscle and joint receptors and causes an on-the-fly correction ofthe centrally programed motor pattern. There is now evidence that these fastproprioceptive adjustment mechanisms are plastic and that they can adjust tolong-term changes in the sensory signaling. For example, in spinalized catswhere locomotion on a treadmill is evoked by L-DOPA injection, cutting thelateral-gastrocnemius/soleus nerve results in long-term up-regulation of theload-compensating effects from group I afferents in the synergistic medial-gastrocnemius nerve, allowing the cat to slowly recover its normal steppingbehavior (Whelan and Pearson 1997). The mechanism for this long-termchange in the proprioceptive feedback is unknown, but it clearly involvesadjustment of synaptic strengths, perhaps mediated by neuromodulatorsreleased locally. In fact, recent evidence suggests that the lamprey spinal corddisplays a substance P and activity-dependent LTP-like synaptic plasticity(Parker and Grillner 1998).

Neuromodulatory inputs may play a role in promoting long-term plasticityof CPG circuits. In spinalized cats, daily intraperitoneal or intrathecal injec-tions of the a-2 adrenergic receptor agonist, clonidine, enhanced the recoveryof locomotion when combined with training on a treadmill (Chau et al.


1998). Other systems are also providing evidence that CPGs can exhibitdifferent forms of learning. Non-associative types of learning such as habitua-tion and sensitization have been described for the Tritonia escape swim CPG(Brown et al 1996; Frost et al. 1996, 1998). Operant conditioning of CPGoutputs have also been reported in the respiratory CPG for the snail Lymnea(Lukowiak et al. 1996) and the feeding CPG in the sea hare Aplysia(Nargeot et al. 1997). These studies show that synapses and neuronalproperties with CPG circuits are labile in response to experience. There isevidence in each of these examples of a role for neuromodulatory actionscausing the learned changes in circuit operation.

8.6 Concluding remarks

In this chapter we have described how neuromodulation in motor systemscan change the connections between neurons and the way neurons fire andreact to synaptic inputs. In this sense, neuromodulators can program thecircuit and the response of neurons. Thus, neuromodulators can change theinformation content of a given neuronal network, which in the case of motorcircuits are the movements they produce.

Although neuromodulation creates a lot of flexibility for the nervoussystem, it makes life difficult for neurophysiologists trying to determine thecellular basis for behavior. For example, it means that while it is oftenrelatively easy to localize the CPG to a certain region in the central nervoussystem, the CPG structure itself is evasive; rather than being an anatomicaldefined network with fixed members and stereotyped cellular response pat-terns, it seems to be a 'loose organization of neurons', with changeablemembrane properties (Harris-Warrick 1988). The structure and the output ofthe CPG are therefore state-dependent features determined by the nature ofthe modulatory inputs at a given time.

However, there are limits to the flexibility produced by neuromodulation.A circuit cannot be reprogramed to produce any possible output; it isrestricted by its own anatomical connections and the biophysical constraintsof its channels and synapses.

Why is neuromodulation necessary to produce network flexibility? Part ofthe answer to this question comes when we consider the divergent andconvergent nature of neuromodulation. Neuromodulatory inputs can influ-ence all important parameters of the movement simultaneously by affectingmultiple sites in one or several networks. Such changes are mediated by adiversity of effects on synaptic connections and component neurons. If thesame type of adjustments were to happen through fast synaptic transmission,which carries only two signs, it would require a much more elaboratehigher-order control system to obtain the same changes in network informa-tion content. Furthermore, since modulation is usually slow and long-lasting,the timing of modulatory effects becomes less critical than if it occurred via


fast synaptic transmission. This allows neuromodulators to cause smoothphase-transitions between different forms of motor behavior. Finally, throughthe induction of active properties such as plateau potentials or rhythmicbursting, neuromodulation reduces the need for ongoing synaptic inputs.These are effects which cannot be replicated by fast synaptic transmission. Ittherefore appears that neuromodulation is better suited to make motorcircuits dance than is conventional synaptic transmission.

Acknowledgements

Ole Kiehn's work is supported by the Novo Foundation and the DanishMRC. Paul Katz's work is supported by a grant from the National Institutesof Health. We would like to thank Ole Kjaerulff and Bruce Johnson forreading a previous version of this chapter.

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Wallen, P., Buchanan, J. T., Grillner, S., Hill, R. H., Christenson, J., and Hokfelt, T.(1989a). Effects of 5-hydroxytryptamine on the afterhyperpolarization, spike fre-quency regulation and oscillatory membrane properties in lamprey spinal cordneurons. Journal of Neurophysiology, 61, 759-68.

Wallen, P., Christenson, J., Brodin, L., Hill, R., Lansner, A., and Grillner, S. (1989b).Mechanisms underlying the serotonergic modulation of the spinal circuitry forlocomotion in lamprey. Progress in Brain Research, 80, 321-7.

Whelan, P. J. and Pearson, K. G. (1997). Plasticity in reflex pathways controllingstepping in the cat. Journal of Neurophysiology, 78, 1643-50.

Yeoman, M. S., Pieneman, A. W., Ferguson, G. P., Ter Maat, A., and Benjamin, P. R.(1994). Modulatory role for the serotonergic cerebral giant cells in the feedingsystem of the snail, Lymnaea. I. Fine wire recording in the intact animal andpharmacology. Journal of Neurophysiology, 72, 1357-71.

Zhang, B. and Harris-Warrick, R. M. (1994). Multiple receptors mediate the modula-tory effects of serotonergic neurons in a small neural network. Journal of Experi-mental Biology, 190, 55-77.

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Neuromodulation and memory functionMICHAEL E. HASSELMO AND CHRISTIANE LINSTER

9.1 Introduction

Neuromodulation plays an important role in a variety of memory processes.Several modulators appear to regulate the storage of new information incortical networks. This raises the fundamental question: Why is it necessaryto modulate learning? Why not just maintain learning dynamics continu-ously? We provide examples of memory processes in which modulation isnecessary in order to alter dynamics for different aspects of learning andmemory. Activation of muscarinic acetylcholine receptors appears to setappropriate dynamics for encoding of new information in cortical networks,whereas removal of modulation may set appropriate dynamics for consolida-tion (transfer of information from hippocampus back to neocortex). Acetyl-choline and norepinephrine seem to act together to enhance responsiveness toexternal stimuli, while maintaining an appropriately sparse representation.Finally, activation of GABAB receptors is likely to be important for rapidchanges in retrieval dynamics which enhance convergence to specific storedrepresentations.

9.1.1 Learning, memory, and modulation

Experimental research suggests that numerous neuromodulators play a rolein the cellular physiology of learning and memory. This research covers awide range of different species, different neuromodulators and differentbehavioral tasks. However, what most people mean when they refer to'memory' concerns only a portion of this broad field of research (i.e. episodicmemory function). We will briefly review a wide range of research in thisintroduction, but will then focus on research concerning episodic memoryfunction in mammalian species.

Considerable detailed work has been performed on invertebrate speciesincluding Aplysia californica (Hawkins et al. 1993) and Hermissenda crassi-cornis (Alkon et al. 1986). Research in these species utilizes simple learningparadigms. Kandel and associates have studied cellular and molecular mecha-nisms underlying non-associative learning in the gill-and-siphon-withdrawalreflex of Aplysia. In this animal, touch to the siphon causes withdrawal ofthe gill. This reflex can be enhanced (sensitized) if the siphon touch is

9

Michael E. Hasselmo and Christiane Linster 319

preceded by electrical shock to the tail (see Chapter 6). These researchersproposed that short- and long-term facilitation of synaptic transmission bythe neuromodulator serotonin enhances the amplitude and duration of gillwithdrawal, providing a mechanism for sensitization in this paradigm.Features of the molecular machinery described in invertebrates have provenuseful for analysis of memory function in mammalian species, but the specificpresynaptic facilitation of transmission by the neuromodulator serotonindoes not seem to have a clear homology with what is found in mammalianspecies.

The neural circuits involved in certain types of classical conditioningparadigms in mammalian species have also been studied extensively(Thompson 1986), and neuromodulators have been demonstrated to influ-ence these classical conditioning paradigms. For example, studies in rabbitshave used the eyeblink conditioning paradigm, in which a puff of air to theeye (unconditioned stimulus) causes an eyeblink (unconditioned response).Coupling the air puff with a tone (conditioned stimulus) eventually results inan eyeblink to the tone (conditioned response). Learning of this conditionedresponse is slowed after blockade of neuromodulatory effects at muscarinicacetylcholine receptors by the drug scopolamine (Solomon et al. 1983, 1993;Myers et al. 1996).

Work in mammalian species has also addressed the neural basis of operantconditioning with the corresponding emphasis on reward mechanisms. Ex-tensive work on the pathways implicated in reinforcement learning suggestsan important role for the dopaminergic pathway arising in the ventraltegmental area (Stellar et al. 1983). Recent modeling of this neuromodulatorypathway proposes that dopamine release depends upon a match betweenexpectation of reward and actual reward (Montague et al. 1996; Schultz etal. 1997).

With regard to human memory function, psychological data suggest thatmemory can be separated into a number of different subdivisions. Onedivision concerns the difference between memories available to consciousrecollection (explicit memory) and memories which alter behavior in tasksbut are not accessible to conscious recollection (implicit memory) (Schacteret al. 1993). The neuromodulatory influences on these types of memoryappear to be quite distinct. For example, blockade of muscarinic acetyl-choline receptors by the drug scopolamine impairs explicit memory for listsof words but does not impair implicit memory (for example, for sequences ofmovements) (Nissen et al. 1987). Another division concerns the distinctionbetween emotionally salient information and emotionally neutral informa-tion. The amygdala has been implicated in storage of associations betweensensory stimuli and the autonomic responses which can be interpreted asphysiological evidence for emotional states (LeDoux 1995). Recent work hasdemonstrated that noradrenergic modulation may be particularly importantfor this function, as memory for emotional stimuli is impaired by thenoradrenergic receptor blocker propranolol in humans (Cahill et al. 1994)

320 Neuromodulation and memory function

and this impairment is obtained with local infusion of propranolol to theamygdala in animals (McGaugh and Cahill 1997).

Human explicit memory function can also be classified according to theduration of the delay between encoding and retrieval, allowing division into(1) short-term memory, (2) intermediate-term memory, and (3) long-termmemory. Retention of information for a short period of time, without anyintervening distraction, appears to involve the prefrontal cortex. There isconsiderable overlap between what is referred to as working memory andshort-term memory. The prefrontal cortex appears relevant for rememberinga telephone number or a simple stimulus. Modulatory effects of dopaminehave been proposed to gate the entry of information into working memory(Williams and Goldman-Rakic 1995; Goldman-Rakic 1996), and dopaminer-gic drugs have been shown to influence human spatial working memory(Luciana and Collins 1997).

Memory of a stimulus for a longer period, with intervening distraction,appears to require structures of the ventromedial temporal lobe, including thehippocampus and entorhinal cortex (Eichenbaum et al. 1992; Cohen andEichenbaum 1993). Lesions of the hippocampal formation impair delayedrecall of lists of words or paired associates in humans (Graf et al. 1984).Highly familiar semantic information or memories of events from the distantpast appear to be spared after hippocampal lesions, but specific aspects ofsemantic memory (i.e. specific words) can be impaired by lesions of specificneocortical subregions, suggesting that long-term memory is stored in neocor-tical structures.

The type of memory stored in the medial temporal lobe has been describedas 'intermediate-term' memory. In humans, this type of memory has beendemonstrated to be sensitive to drugs affecting muscarinic acetylcholinereceptors (Hasselmo 1995), /3-adrenergic receptors (Mewaldt and Ghoneim1979), and GABAB receptors (reviewed in Tang and Hasselmo 1994). Theroles that neuromodulation plays in the storage of intermediate-term memorywill be the focus of this chapter.

9.1.2 Hebbian learning in neural network models andlong-term potentiation

Due to the complexities of cortical circuits, neural network simulations mayprove essential to understanding the role of neuromodulators in corticalfunction. Many of the effects of neuromodulators such as acetylcholine andnorepinephrine are diffuse and subtle within cortical networks. Their effectson a single cell level are more subtle than the net effect of small changes incellular parameters on the dynamics of the full network. Simulations ofcortical networks provide a means for analysing the functional significance ofspecific neuromodulatory effects in the context of particular behavior. Localdrug infusion has provided details about certain structures in which neuro-modulatory effects can influence behavior (see McGaugh 1989). Neural


network models can aid in making the further step of showing how thefunction of neural circuits in these regions might be altered by neuro-modulation.

Any review of how neuromodulation influences learning and memory mustaddress the effect of neuromodulators on long-term potentiation (LTP). Theimportance of Hebbian LTP has been demonstrated in both models andexperiments. Simulations of mammalian episodic memory function com-monly store information by modifying the strength of connections betweenindividual neurons in the model system (Anderson 1983; Hertz et al. 1991;Hasselmo 1995; Hasselmo and Wyble 1996; Fransen and Lansner 1998).Changes in the strength of synaptic connections have also been used to modelbehavior in conditioning tasks (Myers et al. 1996). For effective memoryfunction in these models, it is important that the changes in synaptic strengthfollow the Hebb rule: a synapse is strengthened only when there is both pre-and postsynaptic activity at that synapse (Fig. 9.1). This means that strongactivity at one synapse will strengthen that synapse and not neighboringsynapses (Fig. 9.IB). But if two synapses cooperate to cause strong postsy-naptic activity, then they are both strengthened (Fig. 9.1C). This allowsstorage of associations between the activity of one population of neurons andthe activity of another population of neurons (see Fig. 9.5). The use ofcomputational modeling techniques has demonstrated that this dependenceupon both pre- and postsynaptic activity is very important for changes insynaptic strength to effectively store information.

The importance of the Hebb rule in theoretical work led to specificexperiments focused on demonstrating that the physiological phenomena ofLTP had Hebbian properties (i.e. that it could reflect modification of excita-tory synapses dependent upon combined pre- and postsynaptic activity)(McNaughton et al. 1978; Levy and Steward 1979; Wigstrom et al. 1986).In these experiments, presynaptic activity is obtained with stimulating elec-trodes placed among the fibers in a particular pathway (for example, stratumradiatum of hippocampal region CA1). Postsynaptic activity is obtained witha separate extracellular electrode activating a different pathway, or an intra-cellular electrode injecting current into the postsynaptic neuron (forexample, a pyramidal cell in stratum pyramidale of region CA1). Theseexperiments have demonstrated that weak presynaptic stimulation does notchange the size of synaptic potentials unless it is presented at the same time asa separate strong stimulus or postsynaptic current injection.

Pharmacological studies have shown a correlation between LTP and mem-ory function in behavioral tasks. The Hebbian properties of LTP have beenproposed to result from the physiological properties of the NMDA receptor:to activate the NMDA receptor, presynaptic release of glutamate mustcoincide with sufficient postsynaptic depolarization to remove the Mg2 +

blockage of the channel pore. The ability to induce LTP has been correlatedwith the ability to store memory; the NMDA receptor antagonist APVimpedes induction of LTP in slices and also impairs memory function in the

Fig. 9.1 Hebb learning rule for synaptic enhancement. Synapses that effectivelyactivate the postsynaptic neuron are strengthened. A. Neurons a and b form excitatorysynaptic inputs to neuron c. The firing patterns of a and b and the resulting EPSPs inc are shown on the right. Activation of either synapse in a pattern that does notstrongly activate the postsynaptic cell causes no change in the strength of eithersynapse. B. Neuron a fires rapidly for a time, strongly depolarizing c. Following this,the strength of the connection from a to c is enhanced, but the strength of theconnection from b to c is unaffected. C. Both a and b contribute to stronglydepolarizing c. This results in an enhancement of both synapses.

Morris water maze (Morris et al. 1986). In these behavioral experiments, ratswere placed in a circular water tank and learned to find a platform which layjust out of sight beneath the water's surface. The rats entered the tank atdifferent locations but learned that the platform was always in the samequadrant. Control rats learned to find the platform rapidly, and when it wasremoved would spend most of their time swimming in the quadrant of themissing platform. Rats treated with infusion of an NMDA receptor antago-nist near the hippocampal formation were slower to learn the platformlocation, and did not selectively swim in the quadrant of the missing plat-form. This evidence suggests that NMDA-dependent changes in synapticstrength within the hippocampus could underlie the rats' ability to learn and



remember the location of the hidden platform in this task. This researchshows an ideal interaction of modeling and experiment. Simulations ofnetworks showed the importance of Hebbian synaptic modification formemory storage. This led to physiological work focusing on understandingbiological mechanisms for Hebbian synaptic modification. Here we reviewphysiological data showing that neuromodulators influence LTP, and discussmodeling work addressing the question of why neuromodulation should actto alter the level of LTP within cortical networks.

9.1.3 Why should neuromodulation turn learning off and on?

A number of studies suggest that neuromodulation functions as a learning'switch', with increased levels of the modulator resulting in increased storageof new information. This viewpoint is inherent in much of the research on therole of neuromodulators in LTP. Modulators such as acetylcholine andnorepinephrine have been demonstrated to enhance LTP in cortical struc-tures, and to play an important role in behavioral memory tasks. But thisraises a fundamental question. Why is it necessary to modulate learning?Why not just leave the network in a learning state continuously?

The answer to this question lies in the fact that modulators do more thanjust turn learning on and off. What they provide is a global signal to ensurethat LTP and long term depression (LTD) correlate with a particular dynami-cal state of the network. This only becomes apparent when we considereffects on LTP and LTD in the context of modulatory effects on other aspectsof neuronal physiology. The notion of a modulatory switch suggests thenecessity for not modifying synapses under certain dynamical conditions. It isnot necessary, or even feasible, to store every episodic event. Instead, organ-isms must focus on forming an effective representation of the externalenvironment, and only updating that representation when it is necessary forgenerating appropriate behaviors in specific situations.

9.2 Modulatory effects on LTP and other cellular parameters

9.2.1 Modulation of LTP

Postulating an effect of neuromodulation on memory function, many learningand memory researchers have focused on neuromodulation of LTP. Here,neuromodulators are defined as substances which alter the processing charac-teristics of neural circuits without providing rapid transmission of informa-tion. Thus, the synaptic currents produced by AMPA glutamate receptors andGABAA receptors are considered to be involved primarily in the rapidtransmission of information through cortical networks, whereas slower ac-tions of metabotropic glutamate receptors and GABAB receptors are consid-ered neuromodulatory; they do not rapidly transmit information through

Fig. 9.2 Examples of modulatory systems implicated in learning and memory. A.Cholinergic modulation of cortical structures arises from nuclei of the basal fore-brain,inc luding the media l septum (MS) which innervates the h ippocampal format ion , thediagonal band of Broca (DB) which innervates hippocampus, olfactory bulb , andpiriform cortex, and the nucleus basalis of Mcyner t (nBM) which innervatesneocortical s tructures. B. Noradrenergic modulation of cortical structures arises fromthe locus coeruleus (LC). Individual neurons in this structure project to disparateregions of the bra in , C. Fast transmission of information between local corticalcircuits is accomplished by the neurotransmitter effects of glutamatc; however,glutamate also has slower metabotropic effects on neurons which can be seen usmodulatory. Fast inhibitory effects in local cortical c i rcui ts are mediated by GABAact ivat ion of (GABAA receptors. GABA also has slower modulatory effects at GABAA,receptors.

cortical networks, hut they do alter the dynamical properties of corticalnetworks (Hasselmo 1995). This def in i t ion also applies to many of theclassical neuromodulatory substances, i nc lud ing acetylcholine, nore-pinephrine, dopamine, serotonin, and neuropeptides. Here we w i l l focus onwork exploring the role of the modulators acetylcholine and norepinephrinein memory funct ion. The anatomical pathways involved in these transmittersystems are summarized in Fig. 9.2.

Neuromodulators have been shown to enhance LTP within a var ie ty ofcortical structures. Physiological experiments in brain slice preparations havedemonstrated enhancement of LTP by cholinergic agonists at a number ofdifferent synaptic pathways, including the perforant path inpu t to the denate


Fig. 9.3 Enhancement of long-term potentiation by activation of cholinergicreceptors. A. Intracellular recordings of synaptic potentials elicited by stimulation ofthe association fiber layer (layer Ib) of piriform cortex in control solution. Averagedpotentials are shown before (Pre) and after (Post) repetitive stimulation at 5 Hz for10s. There is little change in size of synaptic potentials after this stimulation paradigmin control solution. B. Recordings of synaptic potentials performed with the cholinergicagonist carbachol (20 uM) continuously present during all phases of the experiment.Potentials show a considerable increase after repetitive stimulation (Post), in contrastto the potential recorded before stimulation (Pre). The cholinergic agonist enhanceslong-term potentiation. C. The NMDA antagonist 2-amino-5-phosphonovaleric acid(APV) blocks long-term potentiation. Potentials show little difference before (Pre) andafter (Post) repetitive stimulation in the presence of 20 uM carbachol and 50 uMAPV. (Adapted from Hasselmo and Barkai 1995.)

gyrus (Burgard and Sarvey 1990), the Schaffer collateral input to region CA1(Blitzer et al. 1990; Huerta and Lisman 1993, Huerta and Lisman 1995),excitatory synaptic connections in primary visual cortex (Brocher et al.1992), and association fiber connections in the piriform cortex (Hasselmoand Barkai 1995). Norepinephrine has been shown to enhance LTP ofpopulation spikes in the dentate gyrus in vivo (Neuman and Harley 1983;Harley 1991) and of both population spikes and EPSPs in vitro (Stanton andSarvey 1985, 1987; Hopkins and Johnston 1988).

An example of the cholinergic enhancement of LTP is demonstrated in Fig.9.3, showing intracellularly recorded synaptic potentials elicited by associa-tion fiber stimulation before and after 5Hz trains of stimulation. In thepresence of the cholinergic agonist carbachol, the LTP of these potentials isconsiderably greater than LTP obtained in control solution. LTP is notobtained in solution with carbachol and the NMDA receptor blocker 2-amino-5-phosophonovaleric acid (APV).

There are many other ways in which LTP can be enhanced by neuromodu-lation. For example, in slice studies of region CA1, it has been shown thatcholinergic modulation induces spontaneous oscillatory activity, and LTP ismost strongly enhanced by stimulation in phase with this activity (Huertaand Lisman 1993, 1995; see also Chapter 4). Synaptic enhancement has alsobeen induced by long-term application of cholinergic agonists at low concen-trations without stimulation (Auerbach and Segal 1996).

Drugs that block neuromodulatory effects of acetylcholine and nore-



pinephrine on LTP appear to impair memory function: muscarinic receptorantagonists such as scopolamine block the cholinergic enhancement of LTP(Burgard and Sarvey 1990; Huerta and Lisman 1993) and these antagonistsalso impair learning of new information in both humans (Ghoneim andMewaldt 1977) and animals (Aigner et al. 1991; see Hasselmo 1995 forreview). Noradrenergic receptor antagonists also impair storage in a range oftasks (McGaugh 1989). For example, the B-adrenergic antagonist propra-nolol impairs storage of emotional information in a human memory experi-ment (Cahill et al. 1994). These results demonstrate that modulators couldcontribute to encoding of new information through enhancement of LTP, butthey do not prove that the effect on LTP is the only action of thesemodulators relevant to memory function. Other cellular effects of thesemodulators might be just as important for enhancing memory function.

Neuromodulation by neurons intrinsic to cortical circuitry could also affectLTP (Fig. 9.2C). Pyramidal cells utilize glutamate as a neurotransmitter,whereas inhibitory interneurons release GABA. However, both of thesesubstances act at metabotropic receptors which have modulatory actions onLTP. For example, activation of GABAB receptors on inhibitory synapticterminals enhances LTP (Mott and Lewis 1991; Olpe et al. 1993; Davies andCollingride 1996). In these experiments, activation of GABAB autoreceptorssuppresses the release of GABA with a time course which specifically en-hances LTP induced by pulse priming stimulation or theta-pattern stimula-tion, but not LTP induced by stimulation that does not have this specific timecourse. Thus, GABA B receptors may underlie the stronger capacity of theta-patterned stimulation for induction of LTP (Larson and Lynch 1986). Activa-tion of metabotropic glutamate receptors has also been shown to enhanceLTP (Riedel and Reymann 1996; Manahan-Vaughan 1997). While theseeffects on LTP are important, the other cellular effects of metabotropicglutamate and GABAB receptor activation may also be important formemory function.

9.2.2 Modulatory suppression of excitatory synaptic transmissionThe connection between modulatory effects on LTP and memory seemsrelatively straightforward, even without the use of neural network models.Modulators which enhance LTP could simply turn on encoding of newinformation. However, it is important to emphasize that modulators thataffect LTP always influence other cellular parameters. In particular, many ofthe substances that enhance LTP, such as acetylcholine (Blitzer et al. 1990;Burgard and Sarvey 1990; Huerta and Lisman 1993; Hasselmo and Barkai1995), also suppress excitatory synaptic transmission (Hounsgaard 1978;Brocher et al. 1992; Hasselmo and Bower 1992; Hasselmo and Cekic 1996).This has been shown both in slice preparations (Hounsgaard 1978; Valentinoand Dingledine 1981; Williams and Constanti 1988; Brocher et al. 1992;Hasselmo and Schnell 1994) and in vivo (Rovira et al. 1983; Herreras et al.1988).

Fig. 9.4 Cholinergic suppression of synaptic transmission. Intracellular recordings ofsynaptic potentials elicited by stimulation of afferent fibers (layer Ia) or intrinsic fibers(layer Ib) in piriform cortex (Hasselmo and Bower 1992) in control solution, andduring perfusion of the cholinergic agonist carbachol (100/iM). The presence ofcarbachol reduces the size of intrinsic fiber synaptic potentials due to activation ofpresynaptic muscarinic receptors which suppress the release of glutamate. Thus,synaptic potentials undergo a short-term suppression due to activation of acetylcholinereceptors at the same time as activation of acetylcholine receptors causes increasedlong-term potentiation (see Fig. 9.3). This suppression does not appear in Fig. 9.3because the entire experiment in Fig. 9.3B was performed in carbachol.

Figure 9.4 shows an example of the suppression of excitatory synaptictransmission by the cholinergic agonist carbachol in brain slice preparationsof the piriform cortex (Hasselmo and Bower 1992). This suppression hasbeen shown to be selective for intrinsic and association fibers in piriformcortex (that is, synaptic connections between neurons within the piriformcortex), whereas afferent fibers entering the piriform cortex from the olfac-tory bulb do not show cholinergic suppression (Fig. 9.4). Thus, the modula-tion selectively shuts down the spread of activity within a cortical region, butnot the input to that region.

Norepinephrine also has effects on both LTP and synaptic transmission.For example, /3-adrenergic receptor activation enhances LTP and often en-hances synaptic transmission directly (Neuman and Harley 1983; Lacailleand Harley 1985; Stanton and Sarvey 1985, 1987; Hopkins and Johnston1988; Harley 1991). However, in addition to B-adrenergic receptors, nore-pinephrine also activates a-adrenergic receptors which suppress some corticalexcitatory synaptic potentials (Scanziani et al. 1994; Hasselmo et al. 1997).Once again, these modulatory actions are specific for particular pathways;the LTP enhancement seen at the medial perforant path does not appear to be



accompanied by a change in basal synaptic transmission, whereas noradren-ergic modulation seems to simultaneously enhance LTD at the lateral per-forant path (Babstock and Harley 1993).

The actions of GABA and glutamate at metabotropic receptors also showdual effects on LTP modulation and modulation of excitatory synaptictransmission. As noted above, the presynaptic inhibition of GABA release byGABAB receptors seems to enhance induction of LTP with theta-patternedstimulation (Mott and Lewis 1991; Olpe et al. 1993; Davies and Collingridge1996). In addition, activation of GABAB receptors strongly suppresses excita-tory glutamatergic synaptic transmission in cortical structures (Ault andNadler 1982; Colbert and Levy 1992; Tang and Hasselmo 1994). Similarly,besides modulating LTP (Riedel and Reymann 1996; Manahan-Vaughan1997), mGluR receptors also suppress excitatory synaptic transmission incertain pathways (Koerner and Cotman 1981; Hasselmo and Bower 1991;Dietrich et al. 1997). As described below, this suppression of transmissionmay be important for regulating the spread of neural activity within corticalnetworks during learning (Hasselmo 1995).

9.2.3 Modulation of other cellular properties

The dynamics of network activity is strongly influenced by other cellulareffects of neurornodulators. Modulators such as acetylcholine and nore-pinephrine have been shown to enhance neuronal firing rates by reducingpotassium currents underlying spike frequency adaptation (Tseng and Haberly1989; Schwindt et al. 1992; Barkai and Hasselmo 1994). These modulatorsalso depolarize cortical interneurons (Pitler and Alger 1992; Gellman andAghajanian 1993; Patil et al. 1997), and suppress GABA release (Pitler andAlger 1992). In addition, acetylcholine causes a depolarization of pyramidalcell membrane potential (Cole and Nicoll 1984).

In computational models these effects can be used to mediate simplestorage of associations (Berner and Woody 1991), and they might alsoenhance the rate of learning by increasing magnitude or duration of thepostsynaptic activity in the network (Barkai et al. 1994; Fransen and Lansner1995, 1998; Hasselmo and Barkai 1995). The postsynaptic effects of thesemodulators may provide an important counterbalance to the suppression ofexcitatory transmission. In this manner the total spiking activity within anetwork could be kept the same, or even enhanced, by a modulator, but therelative influence of external afferent input versus intrinsic retrieval in drivingthis activity could be radically altered. The effects of neurornodulators on arange of cellular properties may ensure that at the same time that LTP andLTD are increased (to enhance the rate of encoding), the dynamics of corticalcircuits are altered to ensure that the proper patterns of activity are encoded.


9.3 Modulation determines strength of external information relativeto internal prediction

One of the problems with most learning rule-based neural models of memoryfunction is the fact that learning and recall may interfere in undesirable ways.Unless care is taken to prevent this, the presentation of a new pattern duringlearning elicits an erroneous response from the network. This spuriousactivity perturbs (or even prevents) learning. A possible solution to thisproblem will be addressed in this section.

9.3.1 Retrieval can interfere with learning

As noted above, the focus on modulation of LTP raises the question: Whyshould learning be turned off and on? Why not just maintain high levels ofsynaptic modification at all times? One constraint concerns the informationcapacity of the network—if every episode is being stored, then the networksmay reach their capacity. But experiments have not demonstrated the specificcapacity of long-term memory, so it is not clear how severe this limitationmay be. On the other hand, a wide range of theoretical work has demon-strated that learning should be performed only when necessary. This has beentermed the stability-plasticity dilemma (Grossberg 1976). Animals require astable representation of the environment that most effectively guides behaviorin a number of different situations. They must be sufficiently plastic to adaptto new environmental conditions (for instance, a change in the distribution offood resources), but must be sufficiently stable that they do not changebehavioral strategies on the basis of every experience (for example, a singleday when the food distribution is radically different).

Many computational models start with greater plasticity of synaptic con-nections which gradually reduces over time, perhaps corresponding to acritical period of development followed by the lesser adaptability of adultanimals. However, even adult animals have the capacity to change represen-tations of their environment in response to salient alterations of the structureof input. This requirement led to development of models in which themagnitude of learning depends on a constant comparison of internal predic-tions with input from the external environment. When the prediction matchesinput, then learning does not occur. When internal retrieval does not matchexternal input, then learning is enhanced and representations are changed.Many abstract algorithms use a learning rule driven by the magnitude oferror—the difference between internal prediction and external input. Thisincludes the Widrow-Hoff learning rule (see Hertz et al. 1991), the back-propagation of error rule (backprop) (Rumelhart et al. 1986), and theRescorla- Wagner model of conditioning (Rescorla and Wagner 1972). Otheralgorithms change a broader range of network dynamics on the basis of the


magnitude of match between internal predictions and external input(Carpenter and Grossberg 1987).

Neuromodulators provide a means by which the magnitude of learningcould be altered dependent upon the level of match. Internal processing bycortical networks could generate predictions that could be compared directlywith the external input to the network. If there is a mismatch between theinternal prediction and the external input, increased levels of mismatch couldresult in an increase in neuromodulatory input, enhancing the modification ofnetwork representations via enhancement of synaptic modification.

In addition to the enhancement of synaptic modification during storage, allof these types of algorithms put an unusual requirement on networks.Namely, the output of the network is not allowed to guide behavior whenthere is a strong mismatch. In this manner, an animal with an erroneousprediction does not act on that erroneous prediction. For example, if a ratnever encounters a cat in a particular location, it ultimately develops arepresentation allowing it to consistently predict the absence of a cat in thatlocation. But when it suddenly encounters the odor of a cat in that location,it does not act on its previous learning. Instead, it acts on the single exampleof the current input. This allows the rat to survive the mismatch event.Without this change in dynamics, the network will never live to be modified!

9.3.2 Suppression of retrieval during mismatch prevents interference

This raises the question of how the output of the network is suppressedduring a mismatch event (for learning of the new information), whereas thesame output of the same network can guide behavior consistently in theabsence of a mismatch. This is where other effects of neuromodulatorsbecome very important. In addition to changing the strength of synapticmodification, these neuromodulators might also change the relative influenceof internal predictions and input from the external environment. Under mostconditions, internal predictions dominate and guide behavior, but when thereis a sufficient mismatch, external input could be allowed to dominate, andthe internal predictions would be suppressed.

An effective means for modulators to suppress internal predictions is tosuppress excitatory synaptic transmission at the very synapses being strength-ened. This provides a functional justification for a paradoxical effect of someneuromodulatory substances. As described above (Figs 9.3 and 9.4), at thesame time that it enhances LTP, acetylcholine strongly suppresses excitatoryintrinsic fiber synaptic transmission (Hasselmo and Bower 1992; Hasselmo etal. 1995). In considering the role of neuromodulators in learning and mem-ory, it is important to focus on the full range of modulatory effects at acellular level. Along with enhancing LTP, both acetylcholine and nore-pinephrine influence a range of cellular parameters. These effects could serveto further enhance the influence of external input relative to internal predic-


Fig. 9.5 Modelling the learning of a single word pair in a paired associate learningtask. This example is highly simplified, but represents mechanisms which could takeplace in region CA3 of the hippocampal formation. Each circle represents a populationof pyramidal cells, with lines representing intrinsic excitatory cortical synapses betweenthese populations of neurons. Storage of the association between these words dependson Hebbian synaptic modification of the synapses. Left: during learning, externalinput activates a population of neurons representing the environmental context(features of the specific behavioral environment at that specific time), a population ofneurons representing the word 'leather' in this specific context, and a population ofneurons representing the word 'holster' in this context. Active neurons in each regionare represented by filled circles. Middle: Hebbian synaptic modification results instrengthening of connections between active neurons in both regions, as shown bythickening of lines. Right: during recall, external input activates the population ofneurons representing context and the population of neurons representing the word'leather'. Activity spreads across previously modified synapses to activate thepreviously associated population of neurons (the population representing the word'holster'). Modulatory enhancement of synaptic modification will strengthen memoryretrieval in a network of this type.

tion during learning. Any perspective on the role of neuromodulation re-quires awareness of this full range of cellular effects.

We have implemented a neural network of cortical memory functionillustrating the interplay between these different effects on the cellular andsynaptic levels onto global network dynamics (Figs 9.5 and 9.6). Duringlearning, the overall effects of cholinergic modulation are to enhance pyrami-dal cell activity, increasing learning performance while simultaneouslysuppressing synaptic transmission at intrinsic association fibers, preventingpreviously stored pattern from interfering with the learning process. Afterlearning, cholinergic modulation is suppressed and sets the stage forrecall. Acetylcholine (ACh) therefore ensures that learning and recall do notinterfere. As an illustration, Fig. 9.6 shows how this suppression of synaptictransmission prevents predictions or retrieval on the basis of previous repre-sentations from interfering with the formation of new representations in

Fig. 9.6 Illustration of how internal retrieval can interfere with learning of newrepresentations. Consider learning of a second overlapping word pair after learning ofthe first word pair shown in Fig. 9.5. A. Without suppression of synaptic transmissionby ACh, retrieval interferes with learning. Left: during learning of the second wordpair ('leather-boot'), activity spreads across the previously modified synapse toactivate the other population of neurons. Lateral inhibition reduces activity of thepopulation of neurons representing the word 'boot'. Middle: this allows Hebbiansynaptic modification to strengthen an undesired connection between the secondcontext (Context C) and the first word. This undesired connection is shown with adashed line. Right: during retrieval, presentation of the word 'leather' in the secondcontext (Context C) evokes the word from the first word pair. Proactive interferenceis strong. B. With suppression of intrinsic synaptic transmission by ACh, retrieval ofthe first word pair is prevented. This allows the input of the word 'boot' to activate aseparate population of neurons. Middle: in this case, Hebbian synaptic modificationonly strengthens the desired connections within the network. Right: during retrieval,presentation of the word 'leather' in the second behavioral context (Context C) cannow evoke the word 'boot'. Proactive interference is greatly reduced.

memory models (Hasselmo et al. 1992; Hasselmo and Bower 1993; Has-selmo 1995).


Michael E. Hasselmo and Christians Linster 333

9.4 Extrinsic versus feedback regulation of modulation

The previous section describes how neuromodulation could play an impor-tant role in controlling the level of external input, dependent upon the matchor mismatch between external input and internal prediction. If neuromodula-tors play this role, then there should be some consideration of the mechanismfor control cf neuromodulation.

Neuromodulators could be regulated by mechanisms extrinsic to the localmismatch. For example, levels of modulators change quite dramaticallyduring different stages of the sleep cycle (Aston-Jones and Bloom 1981;Chrobak and Buzsaki 1994). Acetylcholine and norepinephrine are both athigh levels during waking behavior, but acetylcholine drops to much lowerlevels during slow-wave sleep (Marrosu et al. 1995; Jimenez-Capdeville andDykes 1996). Loss of cholinergic modulation during slow-wave sleep wouldremove the cholinergic suppression of feedback connections from hippocam-pus to neocortex (Hasselmo et al. 1996), allowing a strong influence ofhippocampus on neocortex which would be ideal for consolidation. Duringparadoxical sleep (REM sleep), acetylcholine levels come up to waking levels,but modulators such as norepinephrine drop to much lower levels.

These changes in levels of modulation could depend on circadian rhythmsand interactions between brainstem nuclei independent of the actual informa-tion processing occurring at any given point in time. However, changes inmodulation dependent on the match between external input and internalprediction requires some mechanism for feedback regulation of neuromodu-lation. Feedback regulation of neuromodulation would allow local levels ofactivity to determine the amount of neuromodulation within the system. Thishas been suggested for both invertebrate (Katz and Frost 1996) and mam-malian preparations (Hasselmo 1995; Linster and Hasselmo 1997).

How could feedback regulation of neuromodulation occur? Many nucleifrom which neuromodulators arise are quite a distance from the corticalstructures receiving neuromodulatory innervation. However, connectionssuitable for feedback regulation are commonly present and physiological datasuggest that stimulating cortical structures can change the level of activity instructures providing neuromodulatory input. For example, stimulation of thefrontal cortex influences activity in the locus coeruleus, which providesnoradrenergic innervation of cortical structures (Sara and Herveminvielle1995; Sara et al. 1996). Similarly, cortical regions may influence the level ofacetylcholine released in them via regulation of inhibitory influences oncholinergic cells of the basal forebrain (Dudchenko and Sarter 1991; Fadel etal. 1996; Givens and Sarter 1997). Furthermore, levels of acetylcholinerelease in different neocortical regions may be regulated separately (Jimenez-Capdeville and Dykes 1996). The hippocampus is involved in a similarfeedback situation; stimulation of the output of the hippocampus influencesspiking activity in the medial septum, which provides cholinergic innervationof the hippocampal formation (McLennan and Miller 1974).

It is also possible that the levels of local activity influence the amount of


modulator release from axon terminals without requiring activity to spreadall the way down to subcortical nuclei and back. For example, local activa-tion of glutamate receptors influences levels of noradrenergic release(Montague et al. 1994). Additionally, the neuromodulatory effects of GABAat GABAB receptors and glutamate at metabotropic glutamate receptorsprovide a means by which levels of fast transmitters can change the modula-tory state of a cortical circuit directly.

Feedback regulation of neuromodulatory input may play a role in ensuringthat neuronal activity is not excessively distributed within a region, therebydecreasing the amount of overlap between different stored patterns. Forexample, storage of new sensory input will be greatly enhanced if the patternsof neuronal activity are sparse and do not overlap. In neural network models,storage of non-overlapping patterns of activity is much more effective thanstorage of highly overlapping patterns. Thus, in addition to suppressingretrieval during enhancement of LTP, modulators might increase the sparse-ness of the stored representations.

Since many of our associative memory models and experimental data thusfar have investigated neuromodulatory effects in olfactory cortex, we haveused a computational model of the olfactory bulb to analyse how modulationof inhibition in the olfactory bulb (Linster and Gervals 1996) can preventsuch overlap and thus help to 'ortbogonalize' sensory input patterns presy-naptic to the pyramidal cells of olfactory cortex. Activity-dependent feedbackregulation of modulatory substances leads to optimal levels of inhibition inthe olfactory bulb network over the entire input space (Linster and Hasselmo1997). In addition, the amount of overlap between pairs of output patterns isconsiderably decreased by an activity-dependent modulation of inhibition.

Based on a variety of physiological data, modulatory input in this modelacts simultaneously on lateral inhibition in the glomerular layer and onfeedback inhibition in the granule cell layer of the olfactory bulb. Themodulation of inhibition in the glomerular layer ensures a constant averagenumber of active mitral cells, irrespective of the complexity of the inputpatterns, while modulation of granule cell inhibition ensures a constantaverage spiking probability for mitral cells. We do not specify the nature ofthe neuromodulator in this model, as at the physiological level both ACh andnoradrenaline (NA) mediate the effects implemented in the model (Jahr andNicoll 1982; Ravel et al. 1990; Elaagouby et al. 1991; Trombley andShepherd 1991). At the behavioral level, however, the relative roles for NAand ACh in olfactory learning seem to differ, suggesting the existence of twomodulatory pathways mediating the same effects at a cellular level, but indifferent behavioral situations (see Ravel et al. 1990; Wilson et al. 1994).

Additional mechanisms for ensuring sparse representations may also existin the olfactory cortex (piriform cortex). The modulatory effects of nore-pinephrine and acetylcholine in this structure are similar, causing suppressionof excitatory intrinsic synaptic transmission (Hasselmo and Bower 1992;Hasselmo et al. 1997). In computational models of the piriform cortex, this

Michael E. Hasselmo and Christians Linster 335

suppression of excitatory synaptic transmission has been shown to enhancethe 'signal-to-noise' ratio of cortical activity, increasing the response ofneurons receiving direct afferent input while decreasing background activity(Hasselmo et al. 1997). This effect may be further enhanced by the strongmodulatory effects of acetylcholine and norepinephrine on cortical interneu-rons, causing a strong depolarization (Pitler and Alger 1992; Gellman andAghajanian 1993) coupled with suppression of synaptic transmission (Dozeet al. 1991; Pitler and Alger 1992). This corresponds to the enhancement ofexternal input relative to internal prediction, but can also be seen as ensuringa sparser representation for the storage of new information. Thus, thesemodulatory effects of norepinephrine and acetylcholine may act to improvestorage by making different memories more distinct (less overlapping). This isconsistent with behavioral evidence on the role of acetylcholine in behavioraltasks (Metherate and Ashe 1991; Sarter and Bruno 1997).

9.5 Fast versus slow modulation—muscarinic versus GABABreceptor effects

We have presented a functional rationale for changing dynamics and modula-tory state between learning and retrieval. But this raises the issue of the timecourse of such changes. On an intuitive level, our thought processes involve aconstant interaction of external input and internal retrieval or prediction,except in extreme cases where we are thinking internally about somethingcompletely unrelated to the external input, in which case we lose the externalinput. Understanding the role of neuromodulation in mediating this type ofswitch requires understanding how rapidly the levels of neuromodulatorscould change function within a region. If modulatory changes underliedynamics of learning and retrieval, then the time course of these modulatorychanges should match the time course of behavioral changes.

9.5.1 Muscarinic receptor effects may underlie slower state changes

Available evidence suggests that the effects mediated by muscarinic choliner-gic receptors change over a relatively slow time course. For example,stimulation of the cholinergic innervation in brain slice preparations of thehippocampus causes a slow depolarization of pyramidal cells which increasesover a period of seconds and persists for 10 to 20s (Cole and Nicoll 1984).Recent experimental work in this laboratory (Hasselmo and Fehlau, unpub-lished work) has explored the possible time course of changes in presynapticmuscarinic modulation of synaptic transmission, demonstrating a similarslow time course (see Fig. 9.7). These effects appear to be due to thedynamics of intracellular second messengers, because immediate infusion ofthe muscarinic cholinergic antagonist atropine after acetylcholine does notspeed the recovery of synaptic potentials in the slice preparations. The time


Fig. 9.7 Difference in time course of modulatory effects of GABA and acetylcholineon synaptic transmission. Height of synaptic potentials is plotted as a percentage ofcontrol response in a brain slice preparation of the hippocampus. After a briefpressure pulse injection of acetylcholine, suppression of synaptic potentials increasesfor a few seconds and decreases over 10-20 s. After pressure pulse injection of GABA,suppression of synaptic potentials increases over a few hundred milliseconds anddecreases over a period of about 1 second.

course of these changes is appropriate for changing the dynamics of corticalfunction across several seconds.

These slow muscarinic effects could underlie changes between differentdynamical states which persist for many seconds. For example, muscariniceffects may contribute to setting dynamics for the presence of theta rhythm inelectroencephalograms (EEGs) from the hippocampus (Bland 1986; Stewartand Fox 1990; Bland and Colom 1993). Theta activity consists of high-amplitude oscillations in the EEG of 3-10 Hz which are observed in thehippocampus and associated structures when a rat is actively running throughits environment and when it is in REM sleep (stages when levels of acetyl-choline released in the cortex are high) (Marrosu et al. 1995). In contrast,theta is reduced during periods of inactivity in an awake rat, and duringslow-wave sleep (times when acetylcholine levels are lower).

Decreases in muscarinic effects could set appropriate dynamics for consoli-dation during slow-wave sleep. The removal of cholinergic modulation dur-ing slow-wave sleep should remove cholinergic suppression of feedbackexcitation, allowing information stored in the hippocampus during explo-ration of the environment to strongly drive cortical activity, and therebyproviding appropriate dynamics for consolidation of stored information(Chrobak and Buzsaki 1994; Hasselmo and Wyble 1996, 1997; Hasselmo etal. 1996). Note that this use of the term consolidation refers to the transfer ofinformation from higher order structures such as the hippocampus back toother neocortical areas. Some experimental evidence supports this mechanism


of consolidation. Although here 'consolidation' refers to dynamics withinspecific physiological models (Hasselmo et al. 1996), the term may also beused to describe effects of post-training injection of drugs to study neuromod-ulation (McGaugh 1989). Depending upon the substance, these post-traininginjections are reported to either enhance or impair consolidation, but it is notclear what cellular mechanisms underlie the sensitivity to post-training injec-tions. It is possible that the high doses of drugs used in post-training injectionstudies perturb normal consolidation dynamics during quiet waking, orinfluence subsequent sleep cycles. Network modeling may allow these post-training injection data to be related to specific cellular processes.

9.5.2 GABAB receptor effects may change within theta cycles

More rapid changes in the dynamics of cortical networks could be induced byactivation of GABAB receptors. Levels of GABA change quite rapidly withincortical structures. In particular, within the hippocampal formation, activityof inhibitory interneurons has been demonstrated to show phasic changesrelative to the theta rhythm in hippocampal EEGs (Buzsaki and Eidelberg1983; Fox et al. 1986; Skaggs et al, 1996). This would allow a large changein levels of GABA within hippocampal circuits within the time course of asingle theta rhythm, approximately 100ms. This means that the dynamics ofhippocampal circuits could change from early to late phases of the thetacycle.

The question still remains whether the cellular effects of GABA modulationchange sufficiently rapidly. Activation of GABAA receptors is certainly suffi-ciently rapid, though this effect has not commonly been described as neuro-modulatory. Activation of GABAB receptors has effects more commonlydescribed as neuromodulatory, including second messenger mediated sup-pression of glutamatergic and GABAergic synaptic transmission (Ault andNadler 1982; Colbert and Levy 1992; Tang and Hasselmo 1994), as well assecond messenger-mediated alterations in postsynaptic potassium currents(Andrade et al. 1986; Connors et al. 1988). The time course of postsynapticpotassium currents is slower than that of GABAA mediated changes inchloride conductance, but has a decay constant of about 100ms, which isconsiderably more rapid than the muscarinic depolarization (Connors et al.1988; Patil and Hasselmo 1998). Recent experiments (see Fig. 9.7) suggestthat the presynaptic modulation of glutamatergic transmission mediated byGABAB receptors is also much more rapid than the cholinergic modulationof transmission, with decreases over a period of a few hundred milliseconds(Isaacson et al. 1993; Hasselmo and Fehlau, unpublished data).

Thus, modulatory effects due to GABAB receptor activation may besufficiently rapid to allow changes in network dynamics at different phases ofthe theta rhythm. This possibility is supported by previous work showingpotential modulatory differences during different phases of the theta rhythm.In particular, the excitability of hippocampal neurons changes, as reflected in

Fig. 9.8 Possible role of modulation by GABAB receptors in allowing separate recallof overlapping sequences within the hippocampal formation. We propose thatmodulation is strongest early in the theta phase (due to extensive activity ofhippocampal interneurons) and decreases in later phases of the theta cycle. Early inthe theta cycle, GABAB modulation suppresses intrinsic transmission, allowing afferentinput to dominate, and allowing only partial spread of activity along many differentassociative links. As the theta cycle continues, intrinsic transmission gets stronger,enhancing the strength of internal predictions. Competition between active sequencesresults in fewer sequences being played out at greater lengths, until the networkconverges to retrieval of a single sequence, strongly driven by the spread of activityalong intrinsic connections.


the different magnitude of the population spike evoked by stimulation atdifferent phases of the theta cycle (Rudell et al. 1980; Buzsaki et al. 1981;Rudell and Fox 1984). This effect is presumed to result from changes in thelevel of postsynaptic inhibition on hippocampal pyramidal cells (Fox 1989).However, changes in levels of presynaptic modulation of glutamatergictransmitter release could also contribute to these phasic changes in themagnitude of evoked synaptic potentials. Research in our laboratory suggeststhat in addition to changes in population spike size, the EPSP shows changesin height which could reflect modulation of synaptic transmission (Wyble etal. 1997).

What would be the significance of such rapid changes in modulatory state?These could be important for providing phasic changes in retrieval dynamics,from a phase in which afferent input dominates (due to GABAB suppressionof intrinsic transmission) to a phase where internal predictions are moredominant (Fig. 9.8). This would allow the network to sample a wide numberof alternate solutions to a particular input pattern, and then converge to themost plausible of these solutions. In network simulations of hippocampal


region CA3, we show that changes in modulation allow separate and distinctretrieval of multiple overlapping stored sequences (Sohal and Hasselmo1997a,b; Wallenstein and Hasselmo 1997). These changes in modulationcould also underlie the phenomenon of theta phase precession, observed forplace cell responses. Place cells are neurons which respond most stronglywhen a rat is in a particular location in its environment. These cells appear tofire late in the theta cycle when a rat enters a location, and progressivelyearlier in the theta cycle as a rat moves through its location (O'Keefe andRecce 1993; Skaggs et al. 1996). In a detailed biophysical simulation ofhippocampal region CA3, we have demonstrated that this phase precessioncould result from progressively longer sequences playing out as GABAB

suppression of transmission decreases across the course of a theta cycle(Wallenstein and Hasselmo 1997).

Effects at nicotinic receptors could also contribute to these phasic changesin dynamics, with a time course which is potentially more rapid than effectsat muscarinic receptors. Cholinergic neurons in the medial septum appear tobe more active at a particular phase of theta (Stewart and Fox 1990). Thisphasic firing may not strongly influence muscarinic receptor effects giventheir slow time course, but could result in phasic changes in the enhancementof glutamatergic synaptic transmission by activation of nicotinic receptors(Gray et al. 1996). Cholinergic and GABAergic neurons of the medial septumset the theta firing of interneurons in hippocampus by alternately excitingand inhibiting these neurons (Stewart and Fox 1990). This would requirecholinergic and GABAergic neurons in the septum to fire out of phase, butwould result in GABA and ACh levels in the hippocampus that are at theirhighest levels simultaneously. In this case, activation of GABAB receptorswould suppress intrinsic transmission, whereas activation of nicotinic recep-tors could enhance transmission by the afferent fibers. This enhancement hasbeen shown at the mossy fiber of region CA3 bringing input from the dentategyrus (Gray et al. 1996). The enhancement might also appear in the portionof region CA1 receiving direct input from entorhinal cortex, where highlevels of nicotinic receptor binding have been demonstrated (Rubboli et al.1994; Court and Clementi 1995).

This work suggests that different modulatory states at the start and end ofeach theta cycle correspond to an initial sampling of many hypotheses,concluding with strong activation of a single hypothesis which most stronglymatches the external constraints. If one were to choose the ideal time forstoring new representations, this would correspond to once on each thetacycle during the late phase (when the final sequence has been chosen). Thismight explain the fact that LTP can be most effectively induced by theta-patterned stimulation (Larson and Lynch 1986), and is strongest at thepositive phase of the theta cycle (Huerta and Lisman 1993). Thus, rapidneuromodulatory changes within the course of a theta cycle could mediateboth cycles of retrieval dynamics, as well as determining the appropriateinformation for storage.


9.6 Local versus global

We have discussed how the temporal dynamics of neuromodulatory effectsdetermine the role of neuromodulation in learning and memory. The questionremains of how the spatial distribution of neuromodulatory influences playsa role in the function of these neuromodulatory effects. Clearly, there arebroad differences in the distribution of neuromodulatory effects. Singleneurons in the locus coeruleus or ventral tegmental area distribute axoncollaterals to broad areas of cortex, suggesting that these neuromodulatoryinputs simultaneously set the dynamics of numerous subregions and evendifferent modalities (Moore and Bloom 1979). In contrast, cholinergic inner-vation appears to be somewhat more local, with each cholinergic neuron inthe basal forebrain distributing axon collaterals over an area with a radius ofonly about 1 mm (Price and Stern 1983). Activation of GABAB receptors andmetabotropic glutamate receptors has the potential for both highly local andrelatively distributed modulatory effects.

These differences in the anatomical distribution of synapses from a singlemodulatory neuron could reflect important functional differences betweenthe different modulatory systems involved in learning and memory. The levelof noradrenergic modulation may be set by environmental conditions whichrequire a general global change in sensitivity to external stimuli. For example,in a novel environment, an animal may go into a state of fear in which thesensitivity of response to all modalities of stimulation are enhanced to speedits reaction time and escape from danger. These same properties of modula-tion would enhance the learning of a wide range of stimuli. In contrast, thelocal distribution of cholinergic innervation could reflect a more local modu-lation on a column-by-column basis. This could allow selective sensitivity tomodalities or categories which are relevant to a specific behavior. Forexample, an animal may be in a familiar environment, so that its noradrener-gic tone would be low, but it might encounter an unfamiliar odor. In thiscontext, cholinergic modulation might be enhanced only in those corticalsubregions important for evaluation of the novel odor. Thus, one couldimagine a system in which some cortical regions were dominated by internalpredictions, with little response to external stimuli. All columns or subregionswhich matched this internal prediction would remain in a low modulatorystate. However, if a specific column or subregion had external input whichdid not match this prediction, these could individually go into a state ofhigher cholinergic modulation—suppressing the internal influence from othercortical regions and enhancing the sensitivity to external input. A network ofthis type would allow learning in a more selective manner—focusing on thoseaspects of stimuli not matching the current expectation.

9.7 Conclusion

We have provided an overview of some modulatory effects important for


learning and memory in mammalian cortical structures. In particular, wehave emphasized looking beyond just the modulatory effect on LTP, toconsider how modulation changes the dynamics of cortical regions, setting adynamical state appropriate for the storage of new information. Furtherresearch on the role of modulation in learning and memory should continueto focus on the full range of effects of modulatory substances on cellularparameters.

Acknowledgements

Supported by NSF grant IBN 9723947 and NIMH grant R29 MH52732.Data in this chapter are from projects performed along with Dr Edi Barkai,Brad Wyble, and Brian Fehlau.

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10

Metamodulation: the control and modulationof neuromodulationPAUL S. KATZ AND DONALD H. EDWARDS

10.1 Introduction

As we have seen throughout this book, neuromodulatory processes bestowflexibility on neuronal systems. By changing cellular and synaptic properties,neuromodulation alters the flow of information carried by fast synapticinteractions. It enables circuits of neurons to produce more than one mode ofbehavior or to have more than one set of response properties. This type offlexibility must be controlled so that those circuits act appropriately toproduce adaptive behavior. How is this flexibility controlled? What activatesneuromodulation? Is neuromodulation itself under modulatory control?

It seems logical from an engineering standpoint that neuromodulationought to be well regulated. After all, neuromodulatory inputs can orchestrateentire patterns of behavior. It is important that the modulation be evoked atthe correct time and with the correct intensity to produce the desired effect.Furthermore, because modulatory neurons often act as coordinating units,having divergent actions on many circuits, it may be simpler to regulate themodulation than to regulate each target of the modulation individually. Thismight have evolutionary implications in that differences in modulatory sys-tems could underlie species differences in behavior with the fundamentalcircuitry remaining very similar. It also appears to make neuromodulation aprime target of drug action. Some parasites even have evolved mechanisms totake advantage of modulatory systems to control behavior.

Ultimately, it is important to address the role that the control of neuro-modulation plays in the production of behavior at the level of neuronalcircuits, individual neurons, and synapses. At present, there are ample cellularand molecular data documenting mechanisms that could underlie control ofneuromodulation, but there are very few studies that relate those mechanismsto the control of behavior. The task of the future is to relate the cellular andmolecular mechanisms to behavioral changes to provide a comprehensivepicture of the control of neuromodulation.

10.2 Modulation of neuromodulation: second-orderneuromodulation

This book has been concerned primarily with neuromodulatory actions that

Hj*. 10.1 Metamodulation. The modulatory e f fec t s of one neuron can be themselvessubject to neuromodulation by a second neuron. In this example, neuron t- evokes fastEPSPs in neuron d, an example of fast neutrotransmission. In wha t can he termedfirst-order neuromodutation, a c t i v i t y in neuron b increases the strength of theconnection from c to d, For second-order or meta neuromodutation, a c t i v i t y inneuron J docs not itself evoke a s y n a p t i c porential in neuron J and does not directlyincrease the strength of the connection from <: to d, but instead increases the potencyof the modulation by neuron b. The shaded regions show the extent and rime-courseof [he modulatory actions.

directly affect cellular and synaptic properties. However, neuromodulatoryactions can also change other neuromodulatory effects, i.e. modulation ofmodulation (Fig. 10.1). These two levels of modulatory control can hetermed pr imary or first-order neuromodulation (direct modulatory effects oncel lu lar and synaptic properties) and second-order neuromodulation or meta-madulation (modulatory effects on first-order neuromodulat ion) respectively.Most of the mechanisms that under l ie second-order neuromoduta t ion are thesame as those tor first-order modulat ion. Thus, metamodulation can resultfrom alteration of the properties of f i rs t-order neuromodulatory neurons orfrom modulation of the effects of those neurons.

10.2.1 Direct modulation of first-order inodulatory neuronsThe properties of any neuron can he affected by neuromodulat ion. Therefore,the most direct mechanism for second-order modulation is for a modulatoryneuron to he a target of another modularory neuron (Fig. 10.2A). This serialorganization appears to occur in the retina, where dopaminergic inrerplexi-torm cells ( f i rs t -order modulatory neurons) are directly contacted by c e n t r i f u -gal peptidergic axons arising from the base of the olfactory bulb (second-ordermodulatory neurons) (Zucker and Dowling 1987). Application of the pep-tides contained in the olfactory bu lb appears to directly ac t iva te the dopammeneurons and thus e l ic i t the effects of dopamine ( U m i n o ami Dowling 1991).Although the mechanisms of action of the peptides are unknown, presumablythey act at merabotropic receptors causing some change in the res t ingconductances of the dopaminergic neurons, thereby causing those cells tobecome active.

350 The control and modulation of neuromodulation

Fig, 10.2 Organization of second-order nenromodulation. A. Serial organization iswhere a second-order modulatory neuron (a) directly modulates the properties of afirst-order modulatory neuron (b), B-J)). Convergent organization is when a second-order modnlarory neuron modulates the effectiveness of the first-order modulatoryneuron. This can occur through a modulation of the presynaptic release properties ofthe neuron (B), the postsynaptic receptive properties of the neuron receiving theprimary modulation (C), or through an action that occurs within the synaptic cleftitself to modulate the effectiveness of neuron b (D).

Another example of one modulatory neuron act ivat ing another occurs inthe stomatogastric nervous system of crabs. Among the many modulatoryinputs to the stomatogastric ganglion are the serotonergic GPR cells and thepeptidergic MCN1 cells. Both cell types directly evoke neuromodulatoryactions on neurons in the stomatogastric ganglion (Kmz and Harns-Warrick1989, 1990a; Nusbaum et al. 1992; Coleman and Nusbaum 1994), Inaddition, GPR causes a prolonged activation of MCN1 (Blitz and Nusbaum1996). Thus, activation of one modulatory neuron recruits a second modula-tory input to the circuit.

Similar modulation of firing properties occurs among the diffuse modula-tory systems of the vertebrate brain. For example, serotonin alters rhe firingproperties of noradrenergic neurons of the locus coeruleus (Haddjeri et al.1997). By the same token, stimulation of neurons in the locus coeruleus altersthe firing of dopaminergic ventral regmental neurons through a mechanismthat involves u\ adrenoreceptors (Grenhoff et al. 1993).

Such a serial arrangement of neurumodulation is also seen in male sexual

Paul S. Katz and Donald H. Edwards 351


behavior. Testosterone functions as a prohormone that is converted toestrogens in the preoptic area of the hypothalamus. The estrogens are thenable to promote mating behavior in castrated male rodents (Davidson 1969;Sodersten 1973; Sodersten et al. 1986). The estrogens may act throughanother neuromodulator, dopamine (DA), since neurons in the preoptic areaare dopaminergic. Destruction of these neurons eliminates sexual perfor-mance which can be briefly restored by application of dopamine agonists(Hansen et al. 1982). Moreover, copulatory behavior is enhanced by DAagonists and is reduced by DA antagonists (Ahlenius and Larsson 1984;Napoli-Farris et al. 1984).

10.2.2 Modulation of the effectiveness of first-ordermodulatory neurons

Besides acting directly on first-order modulatory neurons in a serial organiza-tion, second-order neuromodulation can change the effectiveness of a first-order modulatory neuron in a convergent organization (Fig. 10.2B). Forexample, in insects, the biogenic amines serotonin and octopamine potentiatethe effects of cardioacceleratory peptides (CAPs) (Prier et al. 1994). TheCAPs act in a dose-dependent fashion to accelerate the heart rate.Octopamine and serotonin applied at concentrations similar to those foundin the haemolymph of the animal during preparation for flight potentiate theeffects of the CAPs nearly twofold. When applied alone at these sameconcentrations, these amines are subthreshold or near-threshold for causing adirect effect. Thus one neurohormone can modulate the effectiveness ofanother neuromodulator. A similar effect of one neuromodulatory substanceon another is seen in the stomatogastric system of spiny lobsters where priorexposure of the isolated nervous system to the peptide proctolin potentiatesthe ability of a second neuropeptide, red pigment concentrating hormone(RPCH), to elicit the production of a motor program (Dickinson et al. 1997).

There are many mechanisms that might produce such modulation of theeffectiveness of a modulatory neuron. Some mechanisms involve actions onthe output of first-order modulatory neuron, some involve changes to theresponse of postsynaptic targets of those modulatory neurons, and someoccur in the synapse itself (Fig. 10.2B).

Regulation of modulatory transmitter contentIt has been demonstrated that artificially increasing the transmitter content ofa neuron increases its synaptic effectiveness (Poulain et al. 1986). Thus, oneway for the output of a modulatory neuron to be regulated is throughmodulation of transmitter synthesis. The activity of tyrosine hydroxylase, therate-limiting enzyme for catecholamine synthesis, is acutely regulated byphosphorylation (Zigmond et al. 1989). A number of different neurotrans-


mitters, including neuropeptides, can up- or down-regulate tyrosine hydroxyl-ase activity, thereby altering the catecholamine content of neurons (Zigmond1998). Although there are no direct demonstrations that this mechanism isused to alter the output of a neuron, it seems that the potential exists for it tobe a pathway for neuromodulation. Monoamine synthesis is known to bealtered through physical exercise (Meeusen and De Meirleir 1995; Meeusenet al. 1996; Chaouloff 1997), but this may be due to changes in theavailability of chemical precursors rather than a neuronal modulation of thesynthetic enzymes.

One neuron can also have its release process altered by other neuronsthrough the use of 'borrowed transmitters', a novel mechanism wherebyneurons take up and release a substance that they do not synthesize (Fig.10.3). The expression of specialized uptake systems in neurons that do notsynthesize modulatory substances thereby allows the activity of one neuronto alter the transmitter phenotype of another neuron transiently, essentiallyturning it into a modulatory neuron. For example, a subclass of bipolar cellsin the retina is immunoreactive for serotonin and releases serotonin in acalcium-dependent fashion upon depolarization, but does not contain theenzymes necessary to synthesize serotonin (Schutte 1994). These cells appearto be taking up serotonin from a class of retinal amacrine cells that dosynthesize and release serotonin. Thus, through their activity, these amacrinecells modulate the output of the bipolar cells by lending them a neurotrans-mitter. A similar use of borrowed transmitters occurs during the developmentof somatosensory cortex; glutamatergic thalamic afferents which do not havethe synthetic enzymes for serotonin transiently express the serotonin trans-porter (Bruning and Liangos 1997) and take up serotonin (Lebrand et al.1996). It is thought that these cells must borrow serotonin from raphe axonsthat also innervate the same structures and are probably using it for somephase of the developmental process. Other examples of borrowed transmit-ters have been reported in a variety of systems (Feuerstein et al. 1986;Vanhatalo and Soinila 1994, 1995; Alsonso et al. 1995; Musolf et al. 1997;Beltz et al. 1998) and neurons can be made to release a false transmitterunder experimental conditions (Dan et al. 1994). Thus, this novel mechanismfor altering the output of a neuron may prove to be more common thanpreviously realized.

Regulation of modulator releaseOne modulatory substance can enhance or suppress the release of a classicalneurotransmitter (Chesselet 1984; Vizi 1984; Powis and Bunn 1995) and, insome cases, another neuromodulatory substance. For example, serotoninenhances dopamine release from ventral tegmental neurons (Brodie andBunney 1996) and in the striatum (Ichikawa and Meltzer 1995). Nora-drenaline potentiates serotonin release in the hippocampus (Feuerstein et al.1985a) and adenosine and glutamate enhance monoamine release in severalsystems (Feuerstein et al. 1985b; Barraco and Stefano 1990; Ohta et al.


Fig. 10.3 Borrowed transmitters. The pathway for synthesis of a neurot ransmit ter isshown. After its release, a neurotransmitter may diffuse to neighboring synapses. Ifthose synapses contain the appropriate transporters, tha t t ransmitter can he taken up.If the appropriate vesicular transporters are also present, then the 'borrowedtransmitter' can be loaded into vesicles and released.

1994). This second-order neuromodulatory effect can be taken a level furtherto tertiary modulation. For example, in the hippocampus, dopamine activatesD-2 receptors on noradrenergic neurons which then enhance the release ofserotonin from serotonergic neurons (Matsumoto et al. 1996). Similarly,serotonin can indirectly i nh ib i t the release of acetylcholine in the hippocam-pus by acting on substance-P-containing neurons (Feuerstein et al. 1996). Inthis way, one neuron can change the magnitude of a modulatory effectevoked by a second neuron.

Autoreceptors on the presynaptic terminal provide a mechanism for self-regulation of release of modulatory transmitters (Starke et al. 1989). How-ever, the same receptors can also he the target of neurotransmitter releasedfrom nearby neurons, in which case they have been referred to as hetero-


receptors. Activation of heteroreceptors thus allows one neuron to directlymodulate the output of another neuron.

Autoreceptors can also be the targets of other ligands which do not directlymodulate release of the modulatory substance, but instead modulate theregulation of that release. Recently, an endogenous peptide, 5-HT-moduline,has been identified that non-competitively blocks serotonin 5-HT1B autore-ceptors (Massot et al. 1996; Seguin et al. 1997). The presence of this peptidealters the output of serotonin from serotonergic neurons by preventing theserotonin from activating autoreceptors.

Regulation of postsynaptic responsivenessBesides increasing the effective output of a modulatory neuron, second-orderneuromodulation can change the responsiveness of that neuron's target. Forexample, testosterone in male hamsters promotes the ability of vasopressin torelease flank marking (Albers et al. 1988) apparently by increasing thesensitivity of hypothalamic neurons to vasopressin (Albers and Bamshad1998).

The postsynaptic effect of a modulatory neuron can be altered through achange in the responsiveness of the postsynaptic receptors (Bohm et al.1997). There are a number of examples of allosteric actions of substances atreceptors. For example, a substance called oleamide, recently isolated be-cause of its ability to induce sleep, was shown to allosterically alter thesignaling through serotonin receptors (Thomas et al. 1997).

The effectiveness of a metabotropic receptor is dependent upon its couplingto a G-protein (Fig. 10.4). One mechanism that limits the effectiveness ofmetabotropic receptors is called heterologous desensitization, whereby themetabotropic receptor is phosphorylated by protein kinase A or proteinkinase C (Fig. 10.4B) (Chuang et al. 1996). This form of 'desensitization'differs from homologous desensitization which is caused by prolonged expo-sure of the receptor to its agonist (Fig. 10.4C). Homologous desensitizationof metabotropic receptors is mediated by a unique class of serine/threonineprotein kinases known as G-protein receptor kinases (GRKs), that phospho-rylate the receptor only when the agonist is bound (Ferguson et al. 1996a).This phosphorylation event prevents the receptor from interacting with theG-protein, thus effectively inactivating it. The GRKs themselves are targets ofprotein kinase A and protein kinase C which can thereby alter the efficacy ofhomologous desensitization and provide yet another mechanism for second-order neuromodulation (Fig. 10.4D).

Heterologous desensitization of the cannabinoid receptor has recently beendemonstrated (Garcia et al. 1998). The CB1 cannabinoid receptor modulatespotassium and calcium currents through activation of a G-protein. Phospho-rylation of the CB1 receptor by protein kinase C prevents the receptor fromactivating the G-protein and thereby prevents the modulation of the ionchannels. In contrast, somatostatin, which activates a different receptor, canstill modulate the same potassium channels. The function of this example of

Fig. 10.4 Modulation of the effectiveness of metabotropic receptors, A. When ametabotropic receptor is activated by a l igand, it binds to a G-protein (consisting ofa, B, and y subunits), allowing GTP to displace GDP on the a subun i t . B.Heterologous desensitization occurs when a second metabotropic receptor (receptor2)activates a kinase that phosphorylates the f i rs t receptor, thereby preventing thereceptor from associating with its G-protein. C. Homologous desensitization occurs inresponse to prolonged exposure of the receptor to its own agonist. A G-proteinreceptor kinase (GRK) phosphorylates the receptor and increases its association withan intracel lular protein, arrestin. This again prevents the receptor from activating itsG-protein and can also increase the rate at which the receptors are internalized. D.Homologous desensitization can by enhanced through metabotropic receptoractivation of kinascs which phosphorylate GRK, enhancing its kinase activity.

metamodulation is nor known, but it was suggested that such a mechanismmight be viewed as a potential 'antidote' to the effects of mari juana, anexogenous agonist tor the CBl receptor (Garcia et al. 1998).

Regulation of the overall number of receptors available to transduce thefirst-order modulatory action w i l l also alter the effectiveness of the first-ordermodulatory action (Bohm et al. 1997). Endocytosis of rnetabotropic recep-tors plays a role in longer-term desensitization. For homologous desensitiza-tion, GRK phosphorylation of the receptor in the presence of a cytoplasmicprotein called arrestin leads to coupling with another protein, dynamin, andinternalization via clathrin-coated vesicles (Lohse et al. 1990; Ferguson et al.1996a ,b ; Goodman et al. 1996; Zhang et al. 1996). A down-regulation ofdopamine and opiate receptors in this fashion has been implicated as playinga role in drug addiction (Nestler and Aghajanian 1997), The levels of arrestincan be altered by protein kinase A activity (Chuang et al. 1996), providing amechanism for the regulation of metabotropic receptor levels by other



metabotropic receptors.The identity of the G-protein to which a receptor is coupled determines its

action within a neuron. Neuromodulatory actions can directly alter thiscoupling. For example, phosphorylation of the B2-adrenergic receptor causesthat metabotropic receptor to associate with a different type of G-protein andthus changes the nature of the signal produced by the receptor (Daaka et al.1997).

Not only can the number of receptors and their coupling to G-proteins beregulated, but the effectiveness of the G-proteins and the second messengersystems is also under regulatory control. A recently discovered family ofproteins known as 'regulators of G-protein signaling' (RGSs) may play a rolein determining the time course of G-protein actions (Neer 1997; Saitoh et al.1997; Arshavsky and Pugh 1998). The second messenger system itself can bealtered, for example, by altering the expression or the activity of enzymaticcomponents; chronic morphine exposure has been hypothesized to up-regulate adenylyl cyclase in the locus coeruleus through a pathway involvingcyclic AMP response element binding protein (CREB) (Lane-Ladd et al.1997) and this has been implicated in neuronal adaptation to chronic drugexposure (Nestler and Aghajanian 1997). Thus, many levels of the responseto a neuromodulatory substance can be altered by second-order neuro-modulation.

Intrasynaptic modulatory actionsSecond-order neuromodulation can also alter the effective concentration of aneuromodulatory substance by changing the availability of the modulatorysubstance after it has been released. One way for this to occur is to alter thekinetics of reuptake for that substance. Recent evidence suggests that sero-tonin and dopamine transporters can be modulated by phosphorylation(Wolf and Kuhn 1990; Tian et al. 1994) and nitric oxide has been shown toregulate transmitter reuptake (Pogun and Kuhar 1994). Furthermore, there isevidence that there may be endogenous ligands that directly suppress sero-tonin reuptake by binding to the transporter itself (Barbaccia et al. 1983).

Extracellular enzymes that break down modulatory substances also play arole in limiting their effectiveness (Bohm et al. 1997). Regulation of pepti-dases can alter the duration or intensity of neuropeptide actions (Turner andBarnes 1994). An interesting example of this occurs in the parabrachialnucleus where substance P (Sub-P) presynaptically inhibits the release ofglutamate. Application of calcitonin gene-related peptide (CGRP) enhancesthe effect of Sub-P by acting as a substrate for the peptidase that wouldotherwise inactivate the Sub-P (Fig. 10.5) (Saleh et al. 1996). Thus, competi-tion for the peptidase allows one neuropeptide to increase the effectiveness ofanother.

Regulation of gene expressionUltimately, the output of a modulatory neuron and the effects that it evokeson its targets are determined by the genes expressed in these neurons. Gene


Fig. 10.5 Competition for peptidases can alter modulatory actions. A. Glutamate(Glut) and Substance P (Sub-P) arc co-released from terminals in the parabrachial

nucleus. Under basal conditions, an efficient endopepridase prevents the Sub-P fromreaching presynaptic NK I receptors (NK ] rs) and sufficient glutamate is released toactivate postsynaptic glutamate receptors (Glu-rs). B. Under conditions with highlevels of CGRP release from afferent terminals, CGRP overwhelms the peptidase,allowing Sub-P to avoid degradation and activate NKl-rs. These receptors in turndecrease release and thus cause a smaller glutamate-evoked response. (Adapted fromSateh et al. 1996.)

expression can he altered through a variety of different pathways, some ofwhich are linked directly to the modulatory actions of metabotropic receptors(Collins et al. 1998), intracellular calcium (Bito et at. 1997; Ginty 1997),growth factor receptors (Riccio et al. 1997), or direct genomic actions ofsteroid hormones (McEwen 1991; Spindler 1997). Just about all properties ofneurons are subject to regulation through alteration of gene expression.Changing the number or proportions of channels in the membrane, forexample, will change the integrative and firing properties of a cell and


thereby change how that cell communicates with other neurons.

10.2.3 Interactions between first-order modulatory systemsTwo or more first-order modulatory systems often converge on the sametarget. In such cases the different inputs can act as functional antagonists andoppose the action of the other, or they can act synergistically. This can alsoact such that the effect of one is in a sense orthogonal to the effect of theother.

Functional antagonism between modulatory inputs.Functional antagonism between modulatory systems can adjust the state ofthe neuronal circuits between two extremes. Perhaps the best-recognizedexample of functional antagonism between modulatory inputs is the innerva-tion of targets by sympathetic and parasympathetic neurons. For instance,noradrenergic and cholinergic neurons both innervate the heart where theyevoke neuromodulatory actions: noradrenaline speeds up the heart whereasacetylcholine slows it down (Levy 1984) (see Chapter 7). A similar functionalantagonism exists in arthropods between the effects of serotonin and oc-topamine; in the lobster, serotonin acts at a number of different sites in thenervous system to enhance the activation of flexor muscles, whereas oc-topamine opposes the actions of serotonin and enhances extensors (Kravitz1990). This may have a role in controlling the production of dominant andsubordinate behavior in these animals as well as in crayfish. Serotonin andoctopamine also appear to have opposite effects on locomotion in moths,where their actions have been tied to circadian rhythms (Linn et al. 1992).

The opposing actions of modulators are sometimes not used to shift thestate of a system between two extremes, but instead are involved in finecontrol of a circuit. For example, in the buccal system of Aplysia, there aremotor neurons that release two or more peptides in addition to acetylcholine.Some of the peptides enhance the contractions evoked by the acetylcholine,whereas others reduce the size of the contractions (Weiss et al. 1992). Themixture of enhancing and reducing actions may be important for limiting thesize of the evoked contractions (see Chapter 7).

Functional synergism between modulatory inputsIndependent neuromodulatory inputs can converge on a target to producesynergistic actions. This is often the case when two modulatory inputs bothactivate the same second messenger system. For example, serotonin and SCPB

both activate the cAMP pathway in the ARC muscle of Aplysia (Lloyd et al.1984). This may partially underlie the ability of the giant serotonergic neuronMCC in Aplysia to enhance the contractions produced by the motor neuronsin this system (see Chapter 7).

A compelling example of synergy between neuromodulators is found in thesuprachiasmatic nucleus, which controls circadian rhythms in mammals.Three neuropeptides, vasoactive intestinal peptide (VIP), peptide histidine


isoleucine, and gastrin releasing peptide, have been found to shift the circa-dian activity rhythms of rats in the same manner as light. Moreover, all threeintroduced together are far more effective than any of the three pairs ofsubstances, or of any of the substances alone (Albers et al. 1991). The natureof this interaction at the cellular level is unknown.

Orthogonal modulatory systemsIn some cases, multiple modulatory inputs to a system are neither antagonis-tic nor synergistic. Instead, they act orthogonal to one another, neitherenhancing nor decreasing each other's effectiveness. For example, at least 15different modulatory inputs have been found in the stomatogastric ganglion(STG) of lobsters (Harris-Warrick and Marder 1991; Harris-Warrick et al.1992). These inputs each have a unique set of modulatory effects on thecentral pattern generator circuits in the STG. Octopamine and dopamine, forexample, each alter motor patterns produced by the pyloric CPG through asuite of actions on each of the cells and synapses. When applied together, thetwo substances have effects that are simply additive. This may be attributedto the substances acting at different receptors which activate separate secondmessenger pathways.

10.3 Time-scales of action in the control of neuromodulation

Neuromodulation has certain properties that distinguish it from neurotrans-mission (see Chapter 1). One of these properties is that neuromodulatoryeffects tend to act over a longer period of time than fast synaptic transmission(seconds or longer as opposed to milliseconds). As a result of having a longertime-course, neuromodulation is in a good position to alter the flow informa-tion passing through the faster pathways. Thus, in the time-period where aneuromodulatory event may change the strength of a synapse, that synapsemay be activated repeatedly (Fig. 10.1). Similarly, neuromodulatory neuronsthemselves can be acted upon by even slower modulatory inputs that mightlast hours or days (Fig. 10.6A). However, the control is not always slowcontrol over fast; fast actions of neurotransmitters can gate slower neuro-modulatory actions (Fig. 10.6B,C). This can result in prolonging the effectfrom a fast-acting synapse.

10.3.1 Very slow control over slow neuromodulation

The slow control over neuromodulation can take a number of forms. Forexample, there are cyclic changes in the nervous system such as circadian,menstrual, and circannual rhythms. Animals also undergo changes in theirlife that are not periodic, but evince long-lasting changes in informationprocessing such as changes in social status.


Fig. 10.6 Fast and slow metamodulation. A, Second-order modulatory neurons thathave long-lasting effects on first-order modulatory neurons tan alter the strength ofthe modulat ion for a prolonged period of time. The gradual shading represents therime-course of action of each modulatory neuron on its target. Neuron a increases thestrength of the modulation evoked by neuron b for a period of rime after it isactivated. B. Hast presynaptic facil i tat ion can have long-lasting effects if it enhancesthe long-lasting actions of a modulatory neuron ( b ) . U n l i k e the slow control, ifneurons a and b are not s i m u l t a n e o u s l y active, neuron a w i l l have no effect onneuron b, C, S imi l a r ly , fast presynaptic inhibi t ion can have effects that out last itssynapt ic ac t ions if it decreases transmitter release f rom a slow modu la to ry neuron.

Cyclic changes to modulationCyclical changes in the effectiveness or act ivat ion of neuromodulatory pa th -ways result from circadian and other rhythms. For example, the effectivenessof octopamine as a neuromodulator in moths is dependent upon the phase ofthe circadian rhythm at which it is applied (Linn and Roelofs 1992). Seasonaland annual cycles also change the effect iveness of modulatory systems. Thus,the effects of testosterone on mating behavior and inter-male aggression inmale mammals depends on the time of year (i.e. whether the animal is in thereproductive season) (Delville et al. 1996; Higley et al. 1996). Testosteronepromotes male sexual behavior and inter-male aggression du r ing the repro-ductive season, but has li t t le effect outside the season. Testosterone releaseand its effects are also governed by dai ly rhythms, so that it has its effectsd u r i n g the mating season only during the right time of day, which wi l l varywith the species.


The effect of social interactionsSocial status is another behavioral state variable that exerts control overneuromodulation. Unlike the periodicity of reproductive cycles or dailyrhythms, social status is the result of inter-animal interactions that depend onunpredictable factors that include the size and experience of possible rivals.Like other animals, mice establish dominance relationships, and these canexert strong effects on their reproductive competence through actions onlevels of gonadal hormones and hormone receptors in the brain. Bothtestosterone levels and testosterone receptor levels are significantly lower insubordinate mice than in dominants (Raab and Haedenkamp 1981). Simi-larly, socially subjugated hamsters exhibit a 50% decrease in vasopressinlevels in the anterior hypothalamus, an area involved in regulation of aggres-sive behavior (Delville et al. 1998).

The reproductive axis of male fish is also strongly affected by changes insocial status. Both the body markings and behavior of male cichlid fishchange in response to transitions in social status, and neurons in the preopticarea of the hypothalamus that contain gonadotropin-releasing hormone(GnRH) change size (Francis et al. 1993). Dominant status is gained byacquiring and successfully defending a territory, which enables the animal toattract and defend mates. Upon acquisition of a territory, the size of theGnRH neurons increases. Presumably, this increase potentiates the neuroen-docrine reproductive axis, and promotes successful reproduction. Loss of aterritory causes the cells to shrink, although more slowly than they grew,suggesting that the dominant phenotype is the preferred state.

A similar effect of social status occurs in crayfish, where the modulatoryactions of serotonin on escape behavior depend on the social status and thesocial history of the animal (Yeh et al. 1996, 1997) (Fig. 10.7). Reflexiveescape is elicited by an attack on the rear of the animal that excites massivelyconvergent sensory input to the lateral giant (LG) interneuron, a commandneuron for the escape behavior. Serotonin modulates the response of the LG,and with it the excitability of escape. In socially isolated animals, serotoninproduces persistent facilitation of the LG's response. When placed together,the animals fight and establish a dominance hierarchy where one animalbecomes subordinate to the other. Gradually, over a 12-day period followingsuch a social transition, the effect of serotonin changes: instead of enhancingthe response of the LG to sensory input, it diminishes that response. Theeffect of serotonin on the new dominant animal changes too, from a persis-tent facilitation to a facilitation that is removed with the serotonin (notshown in figure). These changes can be reversed by re-isolation of the animal.In a similar fashion, transition from a subordinate to a dominant statuscauses the effect of serotonin to reverse over the same 12-day period follow-ing the social promotion. Interestingly, social demotion of a dominant animalto subordinate status does not lead to a change in the facilitatory effect ofserotonin on LG, even after 40 days, suggesting that, as in the cichlid fish, thedominant physiological phenotype is preferred.


Fig. 10.7 Changes in social status alter the neuromodulatory effect of serotonin. Inisolated animals serotonin increases the size of the EPSP from primary afferents to thelateral giant (LG) neuron by about 63% (filled square). The inset shows the EPSPrecorded in the LG neuron in response to electrical stimulation of an afferent nerve. Inthe presence of serotonin (5HT), the EPSP is larger than under control conditions.Two crayfish were then paired. They immediately fight and within minutes establish adominance hierarchy. The dominant animal stands higher than the subordinateanimal. Over the course of the next 12 days, the effect of 5HT changes, particularly inthe subordinate (circles). After 12 days of pairing, 5HT now decreases the size of theevoked EPSP in LG by about 38%, whereas in dominants (triangles), 5HT continuesto increase the EPSP by 22%. After re-isolating the crayfish for about 8 days, the effectof 5HT converges for both the dominant and subordinate to be about a 56% increaseover control. (Data taken from Yeh et al. 1997.)

These changes have been shown to result from changes in the populationsof serotonin receptors on the LG or its input synapses, indicating thatchanges in social status affect the distribution of serotonin receptors in theabdominal nervous system, far from where status is likely to be perceived bythe animal. The signal of status that provokes the change in receptors isunknown, but is likely to include serotonin itself, which, when injected, canpromote both aggression and transitions to social dominance (Huber et al.1997).

Fast control over slow neuromodulationFast synaptic actions can also play a role in controlling the slower neuromod-ulatory effects (Fig. 10.6B,C). Recently, it was shown that neuronal nicotinicreceptors can gate the output of aminergic neurons, allowing the modulationonly to be effective when the synapses were presynaptically facilitated (Li etal. 1998). Presynaptic inhibition may decrease release from a modulatory


neuron, thereby attenuating its effect for a brief time. Such presynapticcontrol over modulatory neurons is seen in the stomatogastric system ofcrabs (Nusbaum et al. 1992; Nusbaum 1994).

The slow time-scale of neuromodulation extends the time over whichfast-acting synapses exert their effects. For example, if neuron a causespresynaptic facilitation that lasts only milliseconds but acts on neuron b,which evokes a neuromodulatory effect that lasts 5s, then the effect ofneuron a will be seen for those 5 s (Fig. 10.6B). The behavioral relevance ofthis type of control is less well understood than slow control of neuro-modulation.

10.4 Activation of modulatory systems

Understanding the pathways involved in the control of neuromodulationrequires determining what activates neuromodulatory neurons. However, inmost cases, this task is about as ill-defined as asking what activates neuronsin general, because most, if not all, neurons are likely to evoke neuromodula-tory actions of one sort or another. For example, since most neurotransmit-ters act at metabotropic as well as at ionotropic receptors, many neuronsevoke neuromodulatory actions simultaneously with their rapid synapticactions. Furthermore, even ionotropic receptors may cause activation ofG-proteins (Wang et al. 1997), thus modulatory actions can occur even if no'metabotropic' receptors are present. Moreover, a large percentage of theneurons utilize cotransmitters such as neuropeptides that evoke neuromodu-latory actions. Neuromodulatory effects have been observed to be evoked byneurons at all levels within the nervous system, from primary sensoryneurons (Chiel et al. 1990; Katz and Harris-Warrick 1990b) to interneurons(Katz and Frost 1996) to motor neurons (Cropper et al. 1987). Thus,whenever these neurons are activated by sensory stimulation, or by inputsfrom other neurons, or through their own intrinsic activity, they evokeneuromodulatory effects.

In many systems, however, there are classes of neurons that appear to useneuromodulatory actions as their primary means of communication. In thevertebrate brain, these include the diffuse modulatory centers of the raphenuclei, the locus coeruleus, and the substantia nigra. In these cases and inothers where the action of the neuron is primarily modulatory, it is worthasking if there are any general rules about their activation. In some cases itappears that neuromodulatory centers are activated in a tonic fashion,providing a modulatory background upon which fast transmission acts. Inother cases, modulatory neurons are activated in a very phasic manner andthe timing of their effects is important for the information that they transmit.

10.4.1 Tonic and slowly varying modulatory influencesThe raphe nuclei have a principally modulatory function, being composed ofpredominantly serotonergic neurons that have a diffuse projection pattern to


Fig. 10.8 Thc f i r ing rate of scrotonergic neurons in the raphe nuclei of cats isdependent upon the behavioral state of the animal, A. During active waking, there is ahigh tonic discharge rate. B. The rare of tonic f i r i n g decreases dur ing quiet waking. C.During slow-wave sleep the serotonin neurons fire slowly and i r regular ly . D. Theserotonin neurons are not active at all during REM sleep. E, F. The activity ofserotonin neurons (51 IT unit) can be correlated with changes in motor behavior andalertness. Dur ing grooming, the 5HT uni t fires dur ing periods of repetitive movements(6). During orientation to arousing s t imul i , the 5HT units typically stop firing actionpotentials (F). (Modified from Jacobs and fornal 1993 and Jacobs 1994.)

all other areas of the brain and spinal cord. Their activity varies cyclicallywith the animal's circadian rhythm. Raphe neurons tend to fire tonically atlow rates (less than 5Hz), presumably due to their own intrinsic membraneproperties. This pattern changes depending upon the sleep/wake state of theanimal: the neurons fa l l silent dur ing REM sleep and are at t he i r highestbasal rate during active waking (Fig. 10.8A-D) (Jacobs and Fornal I993) .

The basal rate of firing for serotonergic raphe neurons varies nor only as afunction of the arcadian rhythm, it also depends upon the type of activitytha t the a n i m a l is engaged in. Spike rate appears to increase when the animalsproduce a variety of repetitive movements such as grooming (Fig. 10.8E) or


walking on a treadmill. Activity can be momentarily decreased during orien-tation responses to arousing stimuli such as a door opening or closing (Fig.10.8F). It should be noted that not all raphe neurons are active at the sametime. For example, midbrain dorsal raphe neurons appear to be activatedunder different conditions than medullary caudal raphe neurons (Veasey etal. 1997). The general effect of the raphe neurons is to suppress sensory inputand enhance motor activity (Jacobs and Fornal 1993). Thus, the conclusionfrom this work is that these neurons act as general gain-setters for motoractivity and that the precise temporal firing pattern is not very important.Instead, the tonic firing of these neurons sets a modulatory level that can bevaried up or down depending upon external inputs.

Serotonergic neurons in invertebrates have also been found to play asimilar gain-setting function (Ma et al. 1992). In gastropod molluscs, forexample, the giant serotonergic metacerebral cell is tonically active, butincreases its firing during feeding episodes and thereby enhances a number ofparameters of the feeding behavior (Weiss et al. 1986; Yeoman et al. 1994).Thus, these neurons change their activity in response to the behavioral stateof the animal and this results in a potentiation of particular types of motorbehavior. Once again, the precise firing pattern of these neurons is notimportant. All that matters is the level of tonic spiking activity for setting amodulatory baseline upon which fast processes could operate.

The accumulation of neuromodulatory substances due to their tonic releasecan act as an integrator which triggers a change in behavior. For example,during wakefulness there is tonic release of ATP which is converted extracel-lularly to adenosine. The accumulation of adenosine eventually alters theactivity of cholinergic neurons and induces a sleep state (Porkka-Heiskanenet al. 1997).

10.4.2 Phasic activation of modulatory neurons

Some neuromodulatory substances are released in response to single behav-ioral events or stimuli. For example, testosterone levels increase in male miceafter being introduced to novel females (Bronson and Desjardins 1982), andestrus is induced in female prairie voles by the effect of male urine on thevomeronasal organ (Wysocki 1979; Dluzen et al. 1981). The exact timing ofthe release of these substances is probably not important for their effects onthe behavior that they influence.

Modulatory neurons can also be precisely activated and their timing maybe crucial for their participation in the behavior that they mediate. Forexample, dopamine neurons in the ventral tegmental area are involved inmotivational processes underlying learning and memory (Schultz 1997;Schultz et al. 1997). These neurons are activated by a variety of stimulirelated to the animal's learning state (Fig. 10.9). Unexpected (or ratherunpredicted) presentation of food or other rewards will activate these neu-rons (Fig. 10.9A), whereas they are not activated if the same food stimulus is


Fig. 10.9 The firing rate of dopamine neurons in the ventral tegmental area is relatedto the prediction of stimuli. The top traces are peristimulus histograms of firing rate.The raster diagrams show the spiking of a dopamine neuron in relationship to thepresence or absence of a reward or a conditioned stimulus. A. An increase indopamine neuron firing rate is recorded in response to an unpredicted reward. B. Anincrease is recorded in response to a predictive conditioned stimulus, but no change infiring is seen when the predicted reward occurs. C. The firing rate increases inresponse to a conditioned stimulus, but when a predicted reward does not occur, thereis a decrease in the firing rate. (Modified from Mirenowicz and Schultz 1996.)

presented in a predictable fashion. Instead, they fire more in response to aconditioned stimulus that will predict the occurrence of the food (Fig. 10.9B).Omission of an expected reward stimulus will actually decrease the firing of


the neurons (Fig. 10.9C) (Mirenowicz and Schultz 1996). Thus, the temporalrelationship with respect to anticipation or perception of physical stimuli isimportant for the activation of these dopaminergic neurons. This pattern ofactivity has been hypothesized to play a role in providing an error signal toneurons making decisions and predictions about the environment.

10.5 Exogenous influences on neuromodulation

Neuromodulation can be acted upon and changed by things outside thenervous system. For example, we have seen that social interactions can alterneuromodulatory effectiveness. Since neuromodulatory pathways often or-chestrate entire patterns of behavior, they are often targets of exogenousinfluences. Substances introduced into the body either as drugs or as a resultof parasites that directly modify neuromodulatory processes can change thebehavior of the organism in a coordinated fashion. Neuromodulatory actionsare often the locus of such exogenous influences because they can be changedwithout destroying the basic mechanism of fast information processing. Theflexibility that neuromodulation imparts to a nervous system is therefore asubstrate for further plasticity.

10.5.1 Co-opting of modulatory systems to control behavior: drugs

The fact that neuromodulatory systems are involved in coordinating entirepatterns of behavior means that they are good targets for drugs that modifybehavior. Most psychoactive drugs alter some aspect of neuromodulationrather than neurotransmission. For example, the serotonergic system is thetarget of hallucinogens such as LSD (Breier 1995; Abraham et al. 1996). It isalso the target of antidepressants such as fluoxetine, i.e. Prozac (Wong et al.1995). Similarly, the dopamine modulatory system is the target of neurolepticdrugs and amphetamines (Gjedde et al. 1995; Hietala and Syvalahti 1996).Very few psychoactive drugs affect fast synaptic pathways, although oneprominent example is benzodiazepines such as Valium that alter the affinityof GABA for its ionotropic receptor (Izquierdo and Medina 1991;Macdonald and Olsen 1994).

10.5.2 Co-opting of modulatory systems to control behavior:parasites

We are all aware of how infectious agents can cause a change in their host'sbehavior to help the pathogen in its own life cycle. For example, cold virusescause us to cough and thus increase the likelihood of spreading the virus. Inmost cases, the alteration of host behavior is due to a physiological responseoutside the brain, such as inflammation of mucus membranes. However,


certain parasites have evolved methods of also co-opting modulatory systemsto use them to directly control the behavior of their hosts by secretingsubstances that can pass through the blood-brain barrier (Adamo 1997).

An interesting example of parasitic modulation of behavior comes fromwork on small, freshwater crustaceans called amphipods. Amphipods serve asintermediate hosts to a polymorphid cystacanth parasite, followed by ducksand muskrats as the definitive hosts. The parasite appears to alter thebehavior of the amphipods, making them more likely to be fed upon by thedefinitive hosts of the parasite and thereby enabling the parasite to continueits life cycle. The amphipods normally dive deeper into the water and moveaway from light when disturbed. However, individuals infected with thelarval stage of the parasite exhibit altered behavior when disturbed: they skimthe water surface and then cling to floating objects. Non-parasitized individu-als could be made to exhibit this behavior by injecting them with serotonin(Helluy and Holmes 1990). Moreover, it was found that the ventral nervecords of infected individuals showed an increase in the number of serotonin-immunoreactive boutons (Maynard et al. 1996). Thus, it seems that thelarval stage of the parasite somehow alters the serotonin modulatory systemof the amphipods to change the behavior of its host.

Parasites may alter behavior through changes of the modulatory systems inother animals as well. For example, serotonin enhances egg-laying in thesnail, Biomphalaria glabrata. Infection of the snail by the human blood fluke,Schistosoma mansoni, leads to a decrease in serum serotonin concentrationand a cessation of egg-laying activity in the snail host (Manger et al. 1996).Recent results indicate that mosquitoes infected with the parasite that causesmalaria change their behavior and are more likely to feed multiple times, thusincreasing the spread of the parasite from host to host (Koella and Packer1996). The feeding behavior of mosquitoes is altered by peptidergic modula-tion (Brown et al. 1994), and it has been suggested that change in thebehavior of mosquitoes hosting the parasite might be altered due to a directaction on the nervous system (Koella and Packer 1996). Changes in modula-tory transmitters were also seen in mammals exposed to certain parasites(Abdel Ghafar et al. 1996). Thus, various parasitic organisms have'discovered' that the behavior of their host can be controlled throughmanipulation of the host's modulatory systems.

10.5.3 Defects in modulatory systems cause behavioral deficits

Diseases of the nervous system often involve defects in neuromodulation andresult in an alteration of an entire pattern of behavior or a class of behaviorpatterns. For example, Parkinson's disease is a defect in the dopamine systemand alters the ability of the sufferer to generate voluntary movements (Gupta1993). Defects in the serotonin system can lead to several different conditionsincluding depression, obsessive/compulsive disorder, and eating disorders(Griebel 1995; Handley 1995). The appearance of particular behavioral


Fig, 10.10 Species differences in receptor dis t r ibut ion can under l ie differences inmating behavior. A. Prairie voles exhibi t a preference for spending t ime with the i rmates. However, if infused with an oxytocin (OT) antagonist, the females show nopreference for their mate over a stranger and will also spend more time alone.(Modified from Insel et al. 1995.) B. Montane voles do nut show pair-bondingbehavior. The distribution of oxytocin and vasopressin receptors d i f f e r s for the twospecies. Oxyrocin receptors are more prominent in the prelimbic cortex (PI.) and thenucleus accumbens (NAcc) of prairie voles compared to montane voles. The brainareas are involved in the dopamine reward pathway. Vasopressin receptors are moreintensely expressed in the diagonal band (DB) in pra i r ie voles than in montane voles.(Modified from Young et al. 1998.)

symptoms in response to these types of lesions in modulatory systems atteststo their importance in orchestrating whole ranges of behavior.

10,5,4 Evolutionary changes to neuromodulation

Since neuromodulatory inputs provide flexibili ty to circuits, it seems that


evolutionary changes in the modulation of homologous circuits might be asimple way to permanently alter the range of behavior produced by thosecircuits or to constrain the output of a system (Katz 1991). There arenumerous examples of species differences in the localization of amines andpeptides as well as their receptors. This variability might be the substrateunderlying the evolution of behavioral differences in organisms with similarnervous systems.

For example, there is good evidence that phylogenetic differences in local-ization of metabotropic receptors in closely related species are responsible fordifferences in sexually-related social behavior (Winslow et al. 1993a,b; Inselet al. 1994, 1995). Prairie voles are a monogamous species, whereas theclosely related montane vole is not monogamous. After mating, prairie volesprefer to spend time with their mates rather than being alone or with volesthat they are not familiar with (Fig. 10.10A). In contrast, after mating,montane voles prefer to be alone (Williams et al. 1992; Young et al. 1998).A number of lines of evidence suggest that oxytocin release in females andvasopressin release in males causes the pair-bonding in prairie voles. Onesuch piece of evidence is that females infused with an oxytocin receptorantagonist do not display a mate preference (Fig. 10.10A). The brainanatomies of the two vole species are remarkably similar, but differ substan-tially in the localization of oxytocin and vasopressin receptors (Insel andShapiro 1992; Insel et al. 1994; Young et al. 1996, 1997a, 1998) (Fig.10.10B). Thus, highly complex behavior can be altered by natural selectionthrough a simple change in the expression pattern of modulatory receptors.Recent evidence suggests that this may be accomplished through a deletionmutation in the promotor sequence of the gene coding for these receptors(Young et al. 1997b).

Another example of behavioral differences between closely related speciesthat appears to result from a change in the modulation of a circuit is theemergence of the adult swimming behavior in two frog species. Unlikeembryos of the African clawed frog, Xenopus laevis, embryos from the froggenus Rana display the mature form of swimming by the time of hatching. InRana temporaria, serotonergic neurons from the raphe nuclei project alongthe ventral portion of the spinal cord in embryos at this stage of development(Woolston et al. 1994), whereas in Xenopus embryos at a similar stage, thisinnervation is lacking (van Mier et al. 1986). Conversely, at the time ofhatching, the Rana embryos lack a dorsal projection of serotonin neurons inthe spinal cord, and thus the sensitivity of skin sensory pathways whichinitiate locomotion is not altered by serotonin. In contrast, the dorsal cord inXenopus is already innervated by serotonin at hatching and serotonin modu-lates sensory pathways in that species (Sillar and Simmers 1994). Thus, thedifferences in developmental timing of extrinsic inputs to similar circuitsresults in species differences in the production of behavior without any needto change the basic motor circuitry itself.


10.6 Conclusions

The importance of neuromodulation in the production of behavior by ner-vous systems is underscored by the multiple mechanism that regulate it. Inmany cases, the first-order modulation is itself subject to neuromodulation ofone form or another, a situation which we have called metamodulation.Thus, not only is classical neurotransmission subject to alteration, but themodulation of that transmission and the modulation of cellular propertiescan also be altered through some of the same types of mechanisms. Meta-modulation also involves mechanisms that are not found in first-order modu-lation, such as heterologous desensitization. The time-scales of such meta-modulation are extremely varied, ranging from moment-to-moment controlof modulatory axons through presynaptic inhibition to seasonal changes inthe effect neuromodulatory substances. The causes of metamodulation areequally varied, ranging from competition between modulatory neurons tosocial competition between individuals.

The complexity of processing resulting from metamodulation may be badnews for electrophysiologists because it means that the state of the animalmay alter not only the neuronal properties and synaptic strengths, but alsothe modulation of those characteristics. Thus, researchers interested in relat-ing synaptic and modulatory actions to the production of behavior or theprocessing of sensory information must pay more attention to the state ofthose cells and synapses under natural conditions. The good news is thatbeing cognizant of such mechanisms may get us closer to an understanding ofhow nervous systems actually process information so as to produce the highlyflexible patterns of behavior that animals display.

Although great strides have been made in our understanding of neuronalprocessing, we are still a long way from understanding the neuronal basis forvery complex state-dependent behavior. Perhaps the next breakthroughs willinvolve parting with current dogma about how nervous systems processinformation; non-traditional modes of communication including neuromodu-lation and metamodulation are sure to be increasingly important as we try tograsp the complexities of the brain. Indeed, as we have discussed, a knowl-edge of these modes of communication is essential for an understanding ofsuch crucial issues as drug abuse and mental illness. Relating such mecha-nisms to the normal functioning of the brain is our ultimate challenge.

Acknowledgements

We would like to thank Shih-Rung Yeh, Michael Horner, Franklin B. Krasne,and Edward A. Kravitz for many thoughtful discussions of these issues. PaulKatz's work is supported by a grant from the National Institutes of Health.Donald Edwards' work is supported by the National Science Foundation.


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Index

Bold numbers denote references to figures

acetylcholine 40enhancement of LTP 325innervation of cortex 324modulation of

cardiac muscle 250, 251cortical neurons 225

muscarinic receptors 65, 66muscarinic modulation

of bursting 294of excitatory synapses 327of spike frequency adaptation 124of backpropagating action potentials 141

nicotinic receptors 6-7, 57, 59, 60-3desensitization of 91gating of aminergic neurons 363involvement in memory storage 339

role inlearning 319metaplasticity 185-6presynaptic facilitation 133

see also nucleus basalisacross-fiber coding, see coding mechanismsaction potential threshold 123; see also spike

frequency adaptationA-current, see potassium conductancesadaptation, see spike frequency adaptationadenylate cyclase 4

coupling to G protein 86adenylyl cyclase, see adenylate cyclaseadenosine, see purinergic transmissionADP-ribosyltransferase 69-70adrenaline, see epinephrineadrenergic receptors, see norepinephrineafter-hyperpolarization 90, 92, 124, 289

role in metaplasticity 171—2AHP, see after-hyperpolarizationAKAP 99, 100AMPA/kainate receptors, see glutamateamines, see dopamine, norepinephrine,

octopamine, serotoninamphipods 369analgesia 219anandamide 41, 49Aplysia

ARC neuromuscular system 259-67, 260,261, 263, 265, 266, 268, 359

bursting in R15 neuron 126-7, 129effect of PKA in 90insertion of calcium channels in bag cells

113long term sensitization in 225-6

metaplasticity in 187modulation of transmitter release in 93—6nitric oxide signaling in 70operant conditioning in 311peptide release in 49, 50presynaptic facilitation in gill and siphon

circuit 132-3, 141-2, 205-7, 206arachidonic acid, see phospholipase-A2arrestin 356ARC neuromuscular system, see AplysiaArt of the Fugue viATP 38, 40; see also purinergic transmissionauditory system

effect of nucleus basalis stimulation on 225potassium channel modulation in 109slow actions of afferents in 227

augmentation, see homosynaptic plasticityautoreceptors 11, 12, 55-6, 354

modulation of 355

backpropagation of action potentials 138,139, 140, 141

BCM theory, see Bienenstock, Cooper, andMunro theory

BDNF, see growth factorsbehavioral state 364-6, 365

effect on sensory receptors 202-3social status 204, 362, 363

biochemical integration 17, 18, 19-24Bienenstock, Cooper, and Munro theory

162-7, 163mechanisms of sliding threshold in 167-78

bistability, see plateau potentialsborrowed transmitters 353, 354blowfly photoreceptors 208brain-derived neurotrophic factor, see growth

factorsbucculin, 262-4bursting 125-130

effect of electrical coupling on 283, 284homeostatic regulation of 145, 146in thalamus, 222-4, 223modulation of 281, 290, 292-4

calciumas a second messenger 87-9buffers 177role in

anandamide synthesis 49bursting 125-6, 222, 223

384 Index

homeostatic plasticity 148information processing 19—21nitric oxide synthesis 51, 52sliding threshold for LTP 167-78, 168transmitter release 45

spatial signaling 20, 21calcium activated potassium conductances, see

potassium conductancescalcium conductances

role in thalamic oscillations 222, 223role in rhythmic motor patterns 285-6

calmodulin 89CAM-kinase, see protein kinasescAMP, see cyclic AMPcannabinoid receptor 355-6cardiac, see heartcatecholamines, see dopamine, epinephrine,

norepinephrine, octopaminecentral pattern generator, definition of 277channels, see ion channelscholinergic, see acetylcholinecircadian rhythm 18-19, 22, 359-60

effects onGABA responses 64modulatory actions 333, 361serotonergic neurons 365

circuit, see networkclassical conditioning 319; see also learningcoding mechanisms

labeled line coding 32population coding 32frequency coding 32-3rate coding 32-3temporal coding 33-5

compartmentalization of second messengeractions 96-105

computer simulations 53, 54, 329-332,334-5, 338-9; see also hybridnetworks

conductance clamp, see dynamic clampconsensus sequence 87

for protein kinases 100correlations role in information coding 36cortex

activity-dependent regulation of quantalamplitudes 150

backpropagation of action potentials in139, 140

intrinsic and modulatory circuitry 324homeostatic regulation of conductances

144-5modulation of

firing properties in 224-5synaptic depression in 137

neurotrophin regulation of dendriticoutgrowth in 143

PKA modulation in 90cotransmission 47-9, 215, 260, 262-7, 263,

265, 266, 268, 305, 364CPG, see central pattern generatorcrayfish

effect of social status in 204, 362, 363modulation of mechanoreceptors in 202,

203CREB 87, 357cronotropy 251-2cyclic AMP 87

response element-binding protein, see CREBsee also protein kinase A; see also adenylate

cyclasecyclic nucleotide-gated channels

in retinal bipolar cell 5phosphorylation of 214-15

cytoskeleton 96, 97, 98, 99, 100, 103, 104

DAG, see phospholipase-CDale's Principle 29dark adaptation 207, 209-13, 214dendrites, conductances on 138-40dendritic spines 176

role in calcium regulation 175-77dendro-dentritic synapses 9, 44desensitization, see ionotropic receptors;

metabotropic receptorsdiacylglycerol, see phospholipase-Cdiagonal band of Broca 324, 370dopamine

ionotropic receptors 60modulation of

muscle catch 243stomatogastric system 279, 281, 286-7retinomotor movements in retina 210

reversal of synaptic sign 279, 280role in

retina 210-13, 350olfactory bulb 215presynaptic facilitation 133sexual behavior 352working memory 320

see also substantia nigraDrosophila

period and timeless genes 18-19, 22phototransduction 103-5, 104

drug addiction 356, 357drugs, psychoactive 368dye coupling, see gap junctionsdynamic clamp 286-7dynamin 111, 112, 356dystroglycan 97

electrical coupling, modulation of 279,279-84

electrotonic synapses, see gap junctions

Index 385

enkephalin 40, 221epinephrine modulation of twitch muscle 249,

250error signal 367, 368estrogen, see steroid hormonesevolution 370—1exocytosis, modulation of 94-5

false transmitter 353feedback regulation of neuromodulation

333-5feeding behavior, see ARC neuromuscular

system, stomatogastric ganglionFGF, see growth factorsFMRFamide 40

activation of ionotropic receptors 60cleavage of 57modulation of muscle properties 243—5,

257-9, 258, 263frequency coding, see coding mechanismsfunctional circuits 281, 300

GABA 40role in promoting LTP 171, 172, 326

GABAA receptorsdesensitization of 61, 62depolarizing effects of 63, 64insertion in hippocampal neurons 113

GABAB receptors 63, 326involvement in memory retrieval 338, 339modulatory actions of 337

gain-setting by modulatory neurons 366gamma amino butyric acid, see GABAgap junctions 3

between horizontal cells 211, 213, 214between mitral cells 216modulation of 279-84

gatingof backpropagation 139of modulatory actions 360, 361, 363-4of motor output to muscles 242-5of thalamic input to cortex 129

gene expression 357-9regulation by PYK2 111

glial cells 14glutamate 40

AMPA/Kainate receptorsclustering of 98homeostatic regulation of 149, 150

metabotropic receptorsin auditory pathways 227role in metaplasticity 183-4

NMDA receptors 60clustering 170developmental decrease in duration of

EPSCs 169

role in bursting 127, 289, 293role in metaplasticity 167-70, 182structure 59see also long term potentiation

receptor interacting protein, see GRIPglycine 40

mediated inhibition in spinal cord 278, 282G proteins 4

mechanism of action 86G protein-coupled receptors, see metabotropic

receptorsG protein receptor kinases 355, 356graded transmission, see neurotransmission,

non-spikingGrb2 adapter protein 108, 110, 111, 112GRIP 98-9GRK, see G protein receptor kinasegrowth factors 4, 41

fast actions of 67-8, 134, 135long term effects of 142-3, 143receptors for, see tyrosine kinase receptors

guanylate cyclasereceptor 68, 69soluble 68-9

guanylyl cyclase, see guanylate cyclaseHamlet vih-current

role in bursting 126, 223, 224role in rhythmic motor patterns 285-7

Hebbian synaptic plasticity 138, 140, 320-3,322, 331, 332

see also long term potentiation;metaplasticity

heteroreceptors 12, 355Hirudo, see leechheart

leech 257-9, 258mammalian 250-2, 251

heterologous desensitization 355-7, 356heteroreceptors 12heterosynaptic plasticity 9, 10-11, 207

see also presynaptichippocampus

backpropagation of action potentials in 141dopamine modulation of synaptic transmis-

sion in 134insertion of GABAA receptors in 113insulin receptors in 113PKA modulation in 90, 92, 93, 99-100metamodulation in 353-4modulation of spike frequency adaptation in

124role in memory retrieval 338-9synaptic depression in 133-4spillover of neurotransmitter in 55see also long term potentiation

Hodgkin and Huxley model 122

386 Index

homeostatic plasticity 143-151homosynaptic plasticity 9, 11, 12, 45-6, 47-8

see also Hebbian synaptic plasticity; synap-tic depression; synaptic facilitation

horizontal cells 211-12, 213, 2145-HT, see serotonin5-HT-moduline 355hybrid networks 287, 2885-hydroxytryptamine, see serotoninhypothalamus 362

Ih, see h-currentimmediate early genes 108InaD protein 104, 105information

content in non-spiking transmission 37—8processing 15-16, 30-9transfer during bursting 129-30

inositol trisphophate, see phospholipase-Cinsulin, see growth factorsintrinsic modulation 256-67, 307, 308-10,

309ion channels

ligand gated, see ionotropic receptorsmodulation of 90, 92see also cyclic nucleotide-gated channels

ionotropic receptors 58-63anchoring of 96-8comparison with metabotropic receptors

3-6, 4, 85coupling to G-proteins 364definition of 3-4, 58, 84desensitization of 61, 62, 90, 91mediating presynaptic facilitation 7modulation of 89-90permeability 61structure of 59

IP3, see phospholipase-CIP3 receptor 88IRS-1 protein 107, 108

K+ channel, see potassium channelkainate/AMPA receptors, see glutamatekinases, see protein kinases

labeled line, see coding mechanismslamprey

bursting in 289, 293serotonergic modulation of synaptic depres-

sion in 136serotonergic modulation of spike frequency

adaptation 289lateral inhibition

by olfactory bulb periglomerular cells 215,216

by retinal horizontal cells 211, 213in learning networks 332

learningassociative 319, 329-32, 331, 366motor 310non-associative 131-3, 205, 206, 207,

225-6, 311, 318-19olfactory 334role of dopamine 366, 377rules 329see also classical conditioning; operant con-

ditioningleech

heart 257-259swimming, initiation by serotonin 297-8

ligand gated ion channels, see ionotropicreceptors

locus coeruleus 13, 29projection to cortex 324projection to olfactory bulb 215see also norepinephrine

locustinitiation of flight by octopamine 298leg and flight muscles 252-6, 254, 255photoreceptors 207-9

long term depression 149effect of prior activity on 180in cortex 166see also Bienenstock, Cooper, and Munro

theorylong term memory, see memorylong term potentiation

definition of 12effect of

GABAergic inhibition on 172neuromodulation on 324-6priming stimulus on 161prior activity on 179-81, 183theta oscillations on 132

homeostatic control of 148-9in cortex 166information content in 32in hippocampus 132, 161, 170, 172, 173-5,

179, 183, 186, 321, 324-6in spinal cord 310metaplasticity of 160-90NMDA receptor-dependent 182, 321-3,

325see also Bienenstock, Cooper, and Munro

theory; Hebbian synaptic plasticityLTD, see long term depressionLTP, see long term potentiationlusitropy 252

malaria 369MAP kinase 108-9MAP kinase-kinase 108

Index 387

Manduca sextaolfactory processing in 217, 218peptide synthesis in 44post-tetanic potentiation in 46, 48

marijuana 356maxi-K channel 102, 103mechanoreceptive neurons, modulation of 202medial septum 324memory

CAM kinase involvement in 89explicit 319implicit 319in motor systems 310-11long term formation in Aplysia 142, 225-6retrieval 332, 338storage 331time course 320working 320

metabotropic receptors 63—6comparison with ionotropic receptors 3-6,

4, 85coupling to G protein 357definition of 3-4, 84desensitization 355-7, 355glutamate 4-6in retina 4-6, 5pathways mediated by 86structure of 65

metamodulation 350, 349-372metaplasticity 160-90

definition of 160see also Hebbian synaptic plasticity

mitogen-activating protein kinase, see MAPkinase

modeling, see computer simulationsmodulation, see neuromodulationmonogamy 370, 371motor learning 310-11motor neurons 257-67

as members of CPGs 242, 304-5plateau potentials in 291, 292, 304release of peptides from 49, 257, 260,

262-7, 260, 261, 263, 266, 268synaptic drive to 298, 304

motor patterninitiation 295, 297-8termination 308-9modulation 296selection 295

movements, types of 276MRO, see muscle receptor organmuscarinic, see acetylcholinemuscle receptor organ 202, 203muscle

cardiac 250-52, 251catch 243relaxation rate 245-56, 246, 248, 250, 261,

262-7, 263, 265, 266skeletal 249, 250

myogenic contractions 243-5, 244, 251-2,257-9

myomodulin 262-7Mytilus anterior byssal retractor muscle 243

Na+ channel, see sodium channelnegative slope conductance 293, 294neonatal rat, modulation of bursting in 294,

303nerve growth factor, see growth factorsN-ethylmaleimide sensitive factor 95network reconfiguration 300-4neuromodulation

by motor neurons 257, 260, 262-7, 260,261, 263, 266, 268

by sensory neurons 226-7, 228, 292, 301,307-8, 364

combinatorial effects 266definition of 1-3, 2, 24, 323first-order 350in metaplasticity 160, 162intrinsic vs. extrinsic 256, 306—9, 307of electrotonic connections 279-84, 282of neuromodulation 350, 349-372of release 353-5of synaptic transmission 278, 279of transmitter synthesis 353role in information processing 15-16second order, see metamodulationsurvey of attitudes on vii-viii

neuromodulatory neurons 226-7, 257-8,253, 259-60, 305-6, 364

neuropeptides 40activation of ionotropic receptors 60dendritic release of 44

inactivation of 57, 357, 358in the ARC system of Aplysia 262—9modulation of

motor networks 300, 307muscle properties 243-5, 244, 257-9peptide action 352retinal dopamine neurons 350sensory transduction 202, 203serotonin autoreceptors 355

potentiation of effects by amines 352synthesis and release of 42, 43, 44, 48-9,

50see also FMRFamide, neurotransmitters,

opioids, peptide hormonesneuropeptide receptor distribution 370, 371neurotransmission

definition of 1modulation of 278, 279non-spiking 20, 23, 37-9, 38, 279non-vesicular release 49, 51, 52

388 Index

neurotransmitterdiffusion in synaptic cleft 52-6, 53-4kinetics of binding to receptors 53receptors, see ionotropic receptors;

metabotropic receptorsspillover 55

neurotransmitters 40-1release of 93-6synthesis of 42, 43table of identified 40table of putative 41types of 40-2

neurotrophins, see growth factorsNGF, see growth factorsnicotinic acetylcholine receptors,

see acetylcholinenitric oxide 8, 41

diffusion and degradation 57-8production of EPSPs 70receptors 68-70; see also guanylate cyclase

receptorregulation of serotonin and dopamine trans-

porters 357synthesis and release 49, 51, 52see also volume transmission

NMDA receptors, see glutamate receptorsnociception, see pain perceptionnon-spiking transmission, see

neurotransmissionnon-synaptic, see volume transmissionnon-vesicular release, see neurotransmissionnoradrenaline, see norepinephrinenorepinephrine 40

enhancement of LTP 324-6innervation of cortex 224-5, 324modulation of

cardiac muscle 251, 252cortex 224-5, 328cortical excitatory synapses 327glycine inhibition 278, 282pain pathways 219plateau potentials 291serotonin release 353spike frequency adaptation 124ventral tegmental dopamine neurons 351

receptor coupling to G-protein 357role in

memory storage 319-20olfactory bulb 215

see also adrenergic receptors; locus coeruleusNSF, see N-ethylmaleimide sensitive factornucleus basalis 225; see also acetylcholine

octopamine 40modulation of

lobster posture 359locust muscles 253-6, 254, 255mechanoreceptors 202peptide actions 352plateau potentials 291

oleamide 41, 355olfaction

frequency modulation coding in 36olfactory bulb

comparison to retina 213-15long-term effects of serotonin on 226model of memory storage 334synaptic organization of 215, 216

operant conditioning 311, 319; see alsolearning

opioids 219, 221oscillations 17

myogenic 243-5, 244see also bursting

oxytocin 370, 371

pacemaker firing, see tonic firingPAD, see primary afferent depolarizationpain perception 200, 218-220, 221Palaemon pyloric dilator muscle 243-5, 244Panulirus pyloric muscles 247-9, 248parasites 368-9parasympathetic innervation of heart 251,

252, 359Parkinson's disease 16, 42, 369PDZ domains 97, 98, 100

in nitric oxide synthase 51, 52in InaD protein 104, 105

peptidase 57, 357, 358peptide hormones 44, 307; see also neuro-

peptidesperiaqueductal region 219pheromones in Manduca 218phosphatases 102phospholipase-A2 86phospholipase-C 85, 87, 106, 110, 205

in Drosophila phototransduction 104, 105phosphorylation, see protein kinasesphosphotidylinositol, see phospholipase-C;

see also phospholipase-A2kinase-3 107, 108

photoreceptors, see visual systemPI, see phospholipase-C; see also

phospholipase-A2piriform cortex 334—5PKC, see protein kinases; see also

phospholipase-Cplasticity, see homosynaptic plasticity;

heterosynaptic plasticity; Hebbiansynaptic plasticity

plateau potentials 290, 291, 292, 300PLC, see phospholipase-Cpopulation coding, see coding mechanisms

Index 389

post-inhibitory rebound, see reboundexcitation

postsynaptic density proteins 178post-tetanic potentiation, see homosynaptic

plasticitypotassium channel

close association with kinases andphosphatases 102, 103

clustering 100M-current 123modulation by tyrosine kinase pathways

109-11modulation of inactivation 101role in bursting 125-6

potassium conductancesA-current 209, 222, 223, 224

role in rhythmic motor patterns 285-7calcium activated 90, 102, 103, 125,

288-90modulation by serotonin 207-9, 208, 217,

218presynaptic

facilitation 8-9, 62-3, 131-3inhibition 8-9, 133, 134

of sensory afferents 204modulation 49

primary afferent depolarization 204prohormones, see neuropeptide synthesisprotein kinases 84-6

calcium/calmodulin dependent (CAMkinase) 88-9

regulation by RC3 175role in metaplasticity 173, 174

G protein receptor kinase 355, 356protein kinase A 87, 92, 99

anchoring protein 99modulation of

calcium entry 93gap junctions 211-2metabotropic receptor desensitization

355-7role in presynaptic facilitation of trans-

mitter release 133, 205, 206protein kinase C 85, 87

cytoskeletal linkage 103, 104modulation of

metabotropic receptor desensitization355-7

potassium channels 101, 102, 103role in presynaptic facilitation of trans-

mitter release 205, 206role in long term memory storage 142see also tyrosine kinase

proto-oncogenes, see tyrosine kinase receptorspurinergic

modulation ofamine release 353-4excitability in Xenopus 308, 309synaptic depression 137

receptors 57transmission 14, 40

raphe nuclei 13, 29, 364-6, 371; see alsoserotonin

rapsyn 96, 97Ras proteins 107, 108rat, see neonatal ratrate coding, see coding mechanismsRC3, see protein kinases calcium/calmodulin

dependentrebound excitation 145, 146, 285receptor guanylyl cyclase, see guanylate

cyclasereceptor internalization 356receptor tyrosine kinase, see tyrosine kinasereceptors, see ionotropic receptors;

metabotropic receptorsregulators of G protein signaling 357respiratory system 310retina

comparison with olfactory bulb 213-15dark adaptation in 209-13metabotropic signaling in 4-6synaptic organization of 5, 213

retrograde messenger 12RGS proteins 357rhythmic movements

responses of muscles in 243-9, 244, 248ryanodine receptor 88; see also calcium

sag current, see h currentSchistosoma 369schizophrenia 16Schwarzenegger, Arnold 198SCP, see small cardioactive peptidesecond messengers 83-9

compartmentalization of 96-105spatial signaling 21

sensitization, see learning, non-associativesensory adaptation 199sensory feedback, long-term changes in 310sensory transduction 199serotonin 40

as a borrowed transmitter 353co-opting by parasites 369long term effects of 225-6modulation of

bursting 127, 129, 293calcium conductances 199-200dopamine release 353glycine inhibition 278, 282locus coeruleus neurons 351muscle catch 243pain pathways 219peptide actions 352plateau potentials 291, 292

390 Index

sensory transaction 199-200, 202, 203spike frequency adaptation 289synaptic depression 136transmitter release 132-3, 205-7, 206visual transduction in insects 207-9

released from sensory neurons 227, 228role in

crayfish social status 203, 204, 362, 363lobster posture 359olfactory lobe of Manduca 217, 218

species differences in 371see also raphe nuclei

serotonin receptors, modulation of 355sexual behavior 361, 366

rats 351-2voles 370, 371

SH2 domain, see src-homology domainsimulations, see computer simulationsskeletal muscle 249, 250sleep 220, 221-4

effects on acetylcholine and norepinephrinelevels 333

effects on cholinergic neurons 366effects on raphe neurons 365role of oleamide in 355

sliding threshold, see Bienenstock, Cooper,and Munro theory

small cardioactive peptide 49, 262-7, 359SNAP-25 95social behavior, see behavioral statesodium channel, down regulation 111spaced training 142species differences 370, 371spike frequency adaptation 33-4, 92, 123,

124, 287-90, 289, 297spinal cord

pain pathways 219spines, see dendritic spinessrc-homology domain 66-7, 107, 108steroid hormones 14-15, 20, 188, 351-2,

355, 361stochastic resonance 36stomatogastric ganglion

bursting in 126, 128-9, 130, 283, 292-3electrical coupling in 283, 284gastro-pyloric coupling 295, 302homeostatic regulation of properties in 144,

145, 146metamodulation in 350, 352modulation of 281

A-current in 286-7, 288h-current in 286-7, 288synaptic transmission in 278, 279

multiplicity of modulatory actions in 130,360

network reconfiguration in 300-4, 301,302

neuromodulatory actions of sensoryneurons in 227, 228, 292

plateau potentials in 292

presynaptic inhibition of modulatoryneurons 363-4

use of hybrid networks in 287, 288stomatogastric neuromuscular system 243-5,

244, 247-9, 248stress hormones 187-8substance-P 40

in parabrachial nucleus 358internalization of receptors 111role in long term potentiation 310

substantia nigra 13, 29sympathetic innervation of heart 251, 252,

359synapse, sign reversal of 279synapsin 89synaptic

depression 136, 137see also homosynaptic plasticity

facilitation, see homosynaptic plasticitylocations 9transmission, see neurotransmission

synaptobrevin 95synaptotagmin 95syntaxin 95

tadpole, see Xenopustaste transduction

modulation by serotonin 199, 201temporal coding, see coding mechanismstemporal filtering 245-7, 246testosterone, see steroid hormonesthalamus

bursting in 126, 129, 131role in gating sensory information to cortex

220-4theta oscillations 132, 336-9

see also burstingtime-scale

of modulatory actions 335-7, 336, 360-64,361

of synaptic action 6-7, 245-7, 246of signaling 20-21

tonic firing 125transduction, see sensory transductiontransient receptor potential channel, see TRP

channeltransmission, see neurotransmissiontransmitter, see neurotransmittertransporters 353, 357Tritonia

initiation of the swimming motor programin 297

neuromodulation intrinsic to circuits in 308serotonergic enhancement of transmitter re-

lease in 133, 298TRP channel 104, 105tyrosine hydroxylase regulation 353; see also

dopamine, norepinephrine

Index 391

tyrosine kinaseautophosphorylation 107PYK2 109, 110receptor 3-4, 66-8, 67, 85, 8

internalization 112signaling cascades of 106-13

twitch muscle 249, 250

norepinephrine effect on 351visual system

insect photoreceptors 207-9, 208see also retina

volume transmission 8, 10, 56

Walsh inhibitor 90, 92

uptake of neurotransmitter, see transporters

vasopressin 40, 371cleavage of 57

ventral tegmental areafiring properties of 366-8, 367

Xenopusdevelopment of swimming 371modulation of glycinergic inhibition in 278,

282purinergic modulation of excitability in 308,

309switching motor programs in 303

Documents

Beyond Neurotransmission - P. Katz (Oxford, 1999) WW