Levels in the Cognitive and Biological Sciences Dissertation

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UNIVERSITY OF CINCINNATI

Date: October 17, 2006

I, Gregory S. Johnson,

hereby submit this work as part of the requirements for the degree of:

Doctor of Philosophy (PhD)

in:

Philosophy

It is entitled :

On the Relationship between Psychology and Neurobiology: Levels in the Cognitive and

Biological Sciences

This work and its defense approved by:

Chair: Professor Thomas Polger

Professor Robert Richardson

Professor John Bickle

Professor Jenefer Robinson


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On the Relationship between Psychology and Neurobiology:Levels in the Cognitive and Biological Sciences

A dissertation submitted to the

Division of Research and Advanced Studiesof the University of Cincinnati

in partial fulfillment of therequirements for the degree of

DOCTORATE OF PHILOSOPHY (Ph.D.)

in the Department of Philosophyof the College of Arts and Sciences

2007

by

Gregory S. Johnson

B.A., Georgetown University, 1995

Committee Chair: Thomas W. Polger


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UMI Number: 3264438

3264438

2007

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3

Abstract

In this dissertation I offer an account of the relationship between psychology and neurobiology. Ido this in terms of two types of levels, levels of organization and levels of explanation. A

hierarchy of levels of organization orders the entities and activities that are found in nature.

Alternatively, the different ways of describing those things that we find in nature are placed at

levels of explanation . The thesis of my dissertation is that these two types of levels need to be

used together in order to understand the relationship between psychology and neurobiology.

Neurobiological entities are located at the appropriate levels of organization. The descriptions

offered in cognitive psychology of the capacities that humans have are located at a level of

explanation above the neurobiological levels of organization.

Selecting the correct levels of organization entails identifying the types of entities and the

types of activities that are able to carry out psychological capacities. Based upon this

requirement the appropriate levels of organization are the level where neurons and their activities

occur and the level where macromolecules and their activities are found. The activities at these

two levels of organization carry out the psychological capacities that are described by cognitive

psychology at a higher level of explanation.

In the first part of the dissertation (chaps.12) I develop and defend a hierarchy of levels

of organization that is based upon Wimsatts account of levels of organization. In the second part

of the dissertation (chaps. 34) I use Marrs account of levels of explanation as the basis for my

analysis of levels of explanation. I argue that the type of description that is offered in cognitive

psychology is the type that belongs at Marrs highest level of explanation. In the final part of the

dissertation (chaps. 56) I combine these two different hierarchies, levels of organization and


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levels of explanation, into a two-dimensional framework. This entails locating the lowest level of

explanation at one, or in this case two, of the levels of organization. Therefore, the hierarchy of

levels of explanation is composed of different kinds of descriptions of the entities and activitiesthat are found at the neuronal and macromolecular levels of organization.


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Acknowledgments

This dissertation, and my graduate studies more generally, have been greatly aided by thegenerous help of my advisor, Tom Polger, to whom I would like to extend sincere thanks for all

of his efforts. Thanks are also due to the other members of my dissertation committee, John

Bickle, Bob Richardson, and Jenefer Robinson. I would also like to thank the other faculty and

staff of the University of Cincinnati philosophy department for providing a helpful and enjoyable

environment while I was a graduate student. I am also grateful for the financial support provided

by the Charles Phelps Taft Research Center for one year while I worked on this dissertation.


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Contents

List of Figures and Tables 9

Introduction 11

1 Levels of Organization 161.1 Wimsatts account of levels of organization 161.2 Interaction versus composition 201.3 Levels of organization 24

1.3.1 The cell network level of organization 241.3.2 The sub-cellular level of organization 331.3.1 The chemical level of organization 421.3.4 Higher levels 43

1.4 Objections 47

2 A Critique of Churchland 562.1 Churchlands analysis of levels 562.2 Churchlands hierarchy of levels of organization 62

2.2.1 The cell network level of organization 692.3 Synopsis of Churchlands ten levels 88

2.3.1 Brain areas 89

3 Levels of Explanation 943.1 Marrs account of levels of explanation 953.2 An example from Marr 99

3.2.1 The computational theory 1013.2.2 Representation and algorithm 1043.2.3 Neural implementation 105

3.3 Marrs middle level 1073.3.1 Classical computational models 1083.3.2 Connectionist models 1123.3.3 Biologically realistic models 1133.3.4 Marrs middle level 117

4 Models of Cognitive Appraisals and the Level of theComputational Theory 121

4.1 Background for the models 1224.1.1 Appraisal theories 1224.1.2 Constraints 124


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4.1.3 Initial evidence for the appraisal process 1264.2 Models of the appraisal capacity 132

4.2.1 Roseman 1324.2.2 Methodologies 1364.2.3 Scherer 141

4.3 Process models of the appraisals 1464.3.1 A review of Marrs middle level 1464.3.2 A process model of the appraisals 1494.3.3 Critique 156

5 A Two Dimensional Model of Levels 1615.1 Levels of explanation and levels of organization 162

5.1.1 The hierarchy of levels of explanation 1665.2 Levels of organization 170

5.2.1 Determining the appropriate levels of organization 1705.2.2 The organism level of organization 1725.2.3 Brain areas 1735.2.4 The cell network level of organization 1755.2.5 The sub-cellular level of organization 1775.2.6 The chemical level of organization 178

6 Critiques of Lycan and Craver 1856.1 Lycan 186

6.1.1 Lycans commitment to homunclular functionalism 1876.1.2 Lycans commitment to the continuity of levels of nature 1886.1.3 A critique of Lycans account 1896.1.4 Kim 200

6.2 Craver 2026.2.1 Cravers account of mechanistic levels 2026.2.2 The mechanistic level 2036.2.3 Spatial memory 2066.2.4 Decomposition 212

7 Concluding Remarks 216

References 219


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List of Figures and Tables

Figure 1.1 Wimsatts levels of organization 17

Figure 1.2 The cell network level of organization 26

Figure 1.3 Modulation of single cell responses 28

Figure 1.4 Neural circuit in the visual cortex 29

Figure 1.5 Spiny stellate cell 32

Figure 1.6 Monocularly deprived axons 35

Figure 1.7 Intracellular cascade 36

Figure 1.8 Removal of synapses 39

Figure 1.9 Calmodulin and calmodulin-dependent protein kinase II 41

Figure 1.10 Thymine and adenine 42Figure 2.1 Brain areas for song production in canaries 92

Figure 3.1 Motion used for identifying shapes 102

Figure 3.2 The aperture problem 103

Figure 3.3 Time derivative of the zero-crossing 105

Figure 3.4 Neural implementation of edge detection 106

Figure 3.5 Neural implementation of motion detection 106

Figure 3.6 ACT-R program 110

Figure 3.7 Connectionist network 113

Figure 3.8 A node in a connectionist network 113

Figure 3.9 Compartmental model of a pyramidal cell 114

Figure 3.10 Compartmental model represented as electrical circuits 114

Figure 3.11 Model of neurons in the piriform cortex 116

Figure 4.1 Skin conductance levels from Speisman et al (1964) 129

Figure 4.2 Skin conductance levels from Lazarus and Alfert (1964) 131

Figure 4.3 Rosemans model of cognitive appraisals 132

Figure 4.4 Scherers process model of the cognitive appraisals 153

Figure 4.5 Rosemans (2001) model of the cognitive appraisals 159

Figure 4.6 Scherers model of the cognitive appraisals 160

Figure 5.1 Levels of organization and levels of explanation 164



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Figure 5.3 Microstimulated feeding motion 177

Figure 5.4 Entities interacting at three levels of organization 182

Figure 6.1 Lycans levels of nature 192


Figure 6.3 Lycans decomposition of a face recognizer 195

Figure 6.4 Levels of a key 199

Figure 6.5 Cravers mechanistic levels 207

Figure 6.6 The relationship between mechanistic levels 213

Figure 6.7 The molecular process for long-term potentiation 214

Table 1.1 Levels of organization based upon composition 21

Table 1.2 Churchlands hierarchies of levels of organization 57Table 2.2 Synopsis of Churchlands ten levels of organization 88

Table 4.1 Marrs levels of explanation and the psychological sciences 121

Table 4.2 Scherers stimulus evaluation checks 142


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Introduction

This dissertation provides an account of the relationship between psychology and neurobiology. Iconcentrate on cognitive psychology and those capacities that are recognized as psychological

capacities: memory, language use and comprehension, emotion, vision, and so on. Given these

psychological capacities, which can beand often aredescribed in the language of cognitive

psychology, the issue is how to explain the relationship between these types of descriptions and

the neurobiology that carries out the capacities.

My answer is provided using levels as the framework. Therefore, one task is to establish

the idea that more than one type of level is required in order to accurately describe the

relationship between psychology and neurobiology. The two required types of levels are levels of

organization and levels of explanation. Only employing one type of level, which gives us a

single hierarchy of levels, is not sufficient for providing the correct picture of this relationship.

Before saying more about my account I will briefly describe different ways in which

levels are used. As Churchland and Sejnowki (1988) point out, the three main ways of talking

about levels are as levels of organization, levels of explanation, and levels of processing. Only

levels of organization and levels of explanation concern this project, but I will briefly lay out all

three so that we are clear on the different ways of using the term levels .

The term levels is probably most commonly used to refer to levels of organization. When

identifying a level of organization one is generally trying to identify a particular playing field

(i.e., a level) and the different entities that occupy it. Having a relatively clear idea of what

entities are at a particular level of organization, and not at some other level, then suggests what

sort of composition and causal relations might exist between different entities. It is expected that


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entities at one level of organization will causally interact only with entities at the same level of

organization, and not with entities at higher or lower levels of organization. With regard to

composition, it is expected that entities at a lower level will compose the entities at higher levels.For example, humans are at one level of organization and they causally interact with other

humans, other animals, and artifacts of the appropriate size. At a lower level are the organs that

compose humans, which causally interact with each other, but not with other humans.

A second way that levels are sometimes used is as levels of explanation (this same use is

sometimes referred to as levels of description or levels of analysis). Churchland and Sejnowski

say of this type of levels, Levels of analysis concern the conceptual division of a phenomenon

in terms of different classes of questions that can be asked about it (1988:741). The basic idea is

that these types of levels provide a way of ordering different kinds of descriptions of the same

phenomenon.

And third, although levels of processing do not concern this project, I will discuss what is

meant by the term in order to distinguish it from the other ways of talking about levels. Levels of

processing are a series of points or stages within a complex, but fairly linear procedure or

process. Levels are demarcated by either or both: (1) their temporal placement within the

processso levels will line up with respect to the order in which they occur in the process; or (2)

levels are demarcated by their relative simplicity or complexity with respect to the final stage of

the processso simple levels precede more complex ones and the phenomena at the more

complex levels are (in some sense) built up from the phenomena at the simpler levels. A unique

feature of levels of processing is that, unlike levels of organization (or levels of explanation),

there are causal interactions between the different levels of processing.


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issue of reductionism or of eliminativism, although what is done here may have an application to

those problems.

Outline of the project

In the first chapter I review Wimsatts account of levels of organization. He suggests that levels

of organization can be characterized in terms of entities interacting in regular and predictable

ways with each other. Adopting his analysis I construct a hierarchy of the levels of organization

that fall within the scope of the brain. In chapter two I look at a hierarchy of levels of

organization that is offered by Churchland (1986). Critiquing her account also provides the

opportunity to further explain some of aspects of the hierarchy that I offered in chapter one.

In the third chapter I lay out Marrs account of levels of explanation, and discuss the

three levels that he suggests are required in order to completely explain an information

processing task. In this chapter I also look at some other types of explanations (symbolic

modeling, connectionist modeling, and biologically realistic modeling) that, broadly speaking

fall within the scope of his middle level of explanation. Then in chapter four I examine some

models that have been offered in cognitive psychology to explain the early part of the emotion

process. The purpose of looking at these models is to demonstrate that the format of these types

of explanations is what Marr characterized as his highest level of explanation. Recognizing that

these models are the type of description that is offered at a particular level of explanation allows

us to place psychological descriptions of capacitiesor at least one example of suchinto a

hierarchy of levels of explanation.

In chapter five I offer the account in which levels of organization and levels of

explanation are combined to form the two dimensional model. This model illustrates that


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psychological descriptions of capacities are a certain, abstract way of describing the activity that

occurs among neurons (at one level of organization), and among macromolecules (at another

level of organization). In the final chapter I contrast my account with the accounts offered byWilliam Lycan (1981, 1987) and by Carl Craver (2002). This is an opportunity to demonstrate

some of the problems that arise when one attempts to explain psychological capacities with only

a single hierarchy of levels.


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Chapter 1 16

1. Levels of Organization

In this chapter I offer an account of the different levels of organization that fall within the scopeof the brain. I begin by reviewing Wimsatt s (1976) analysis of levels of organization. Using this

as the starting point, I develop a hierarchy of levels by applying Wimsatt s analysis to several

examples of different types of activities that are found in the brain. The hierarchy of levels of

organization that is developed here is one important part of the account of the relationship

between psychology and neurobiology that I will lay out in chapter five.

1.1 Wimsatts account of levels of organization

Wimsatt begins by suggesting that the best way in which to understand levels of organization is

by using size (1976: 237 8). Larger entities are at higher levels of organization and smaller

entities are at lower levels of organization. Even if size alone cannot be used as the sole variable

that determines what levels of organization are, it is a good indicator of the level of organization

at which an entity belongs. As Wimsatt points out in a footnote, one reason why size is a useful

guide is because forces act differently on entities of different sizes, or only act upon entities of a

certain size. He explains this by saying, Different forces can have different ranges either

because their force laws vary with different powers of the radius or because in our world some

with the same exponent in their force laws are cancelled out at close ranges (electrostatic forces),

while others (gravitation) are not (1976: 237, n12).


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Chapter 1 17

If the entities in the world are delineated on the basis of size, we find that entities appear

to be found at (roughly) certain sizes (1976: 240 1, figure 1.1). 1 But more important than size

alone as an indicator of levels of organization is size as an indicator of a regularity and predictability of interactions (1976: 238) among the entities at each size. If the entities at certain

sizes do have regular and predictable interactions then this regularity and predictability of

interactions suggests that size is a relevant variable for establishing an ordered set of levels.

Figure 1.1. Wimsatt s diagram of different possible plots for size versus regularity and

predictability of interactions. The suggestion, which is made in the top plot, is that the

regularity and predictability of interactions (on the y-axis) will be high for some sizes and

low for others. The slightly less regular plot on the bottom ( Our World? ) suggests that the

regularity and predictability of interactions are quite high for smaller sizes (i.e., the first few

peaks) and becomes progressively flatter as size increases, although still retaining dipsand rises. From Wimsatt (1976: 240).

1 His groups of entities, in increasing size, are: the atomic, the molecular, the macro-molecular, theunicellular, smaller metazoan, larger metazoan, and the socio-cultural ecological.


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Chapter 1 18

However, we do not know initially that the interactions of the entities are going to be

equally regular and predictable for each of the groups of entities of a particular size, or even that

size is the reason that there is any regularity or predictability at all. In order to determine whythese groups indicate that there will be regular and predictable interactions, Wimsatt suggests

that there have to be certain conditions in place that generate the regular and predictable

interactions. For example, natural selection, or the pressure from natural selection, is one of these

conditions. Given change over time on an evolutionary time scale, what counts as an entity will

change. At one point single cells were the most highly evolved biological entity, at a later

point multicellular organisms were, and at a still later point metazoan organisms were. In this

case there is a condition, pressure from natural selection, that causes organisms to find loci of

predictability and regularity, that is, places where their existence is relatively stable with respect

to finding food and not being food themselves. 2 This locus of predictability and regularity e.g.,

the space occupied by metazoan organisms can then be taken to constitute a level of

organization. On the other hand, errant changes in size that make it more difficult for an

organism or a group of organisms to find food or avoid predators would make those organisms

interactions less predictable and regular. In addition to the conditions created by natural

selection, other conditions generate other loci of predictability and regularity. As Wimsatt says,

Atomic nuclei and molecules constitute two other levels of organization and foci of regularity.

They are so because they are the most probable states of matter under certain ranges of

conditions (1976: 239).

At this point in his argument Wimsatt is motivating the idea that there are conditions in

the world which have a tendency (a high probability) of generating regularity. These places

2 As Wimsatt notes, this is an oversimplification (1976: 238).


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Chapter 1 19

where regularity and predictability are found can then be characterized as levels of organization.

So, when a level of organization is understood as a local maximum of predictability and

regularity what is being said is that entities have congregated at some particular size because itis there that they have a predictable and regular environment.

With this much laid out, Wimsatt proposes to shift the perspective from considering

levels of organization as abstract spaces where regularity and predictability are found, to

considering levels of organization as a feature of the entities that fill up that space. Now the idea

is that a level of organization is a result of entities interacting in stable ways with each other. The

gain, in addition to being parsimonious, is that it makes causation (i.e., these interactions) a

feature that defines levels of organization rather than a consequence of it (1976: 239 40). That

is, the interactions give rise to a level of organization and not the other way around; a level of

organization is not a place where interactions are able to occur. To make the shift from thinking

of levels as some place in an abstract space to a feature of entities interacting Wimsatt introduces

the idea that:

organisms are an important feature of the environment of many of the other organisms thatthey interact with. The presence or absence of an organism may have a strong effect on the

predictability and regularity of the environment for another organism, and thus, of howclose the latter is to a level of organization the dependence of what constitutes stablestates on what else is around is found at all levels of organization (1976: 239).

The point that Wimsatt is introducing is that entities causally interacting (and the extent that they

are dependent on their interactions) gives rise to a level of organization. In addition to the

dependence that entities have on other entities that they interact with, another aspect of this

analysis is that it includes the notion of context or environment, since this bears on how entities

may interact.


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Chapter 1 20

Therefore, entities interacting in relatively stable and predictable ways are, or give rise to, a

level of organization. Consequently, a level of organization is not some sort of abstract plane

which is occupied by a particular set of entities, which because they are on this particular levelare able to interact with each other. And so, a correct application of Wimsatt s notion of levels of

organization is to say that a series of entities interacting in a stable manner is a level of

organization. It then follows that it is incorrect to say that entities occupy a level of organization,

as if the level of organization would be there even if there were not entities to occupy it. 3

One important feature of Wimsatt s analysis is that composition is not part of the analysis

itself, although it is obviously relevant for many of the uses that we might have when levels of

organization are employed (and he does discuss it, 1976: 243). However, I am going to follow

Wimsatt and treat composition as a secondary or derivative characteristic of levels of

organization. The primary characteristic of a level of organization is entities stably interacting

with each other.

1.2 Interaction versus compostion

Stepping back from Wimsatt s analysis for a moment, I want to consider an alternative way of

defining levels of organization. Listed in the table below is one intuitive way that a partial

hierarchy of levels of organization in the brain might be laid out. I am not going to endorse this

as a hierarchy of levels of organization, but it might be helpful to contrast this list with Wimsatt s

analysis of levels of organization.

3 I agree with Wimsatt s analysis, however, my project of illustrating a two dimensional space of levels isgoing to lead me to sometimes speak in the looser (incorrect) way.


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Chapter 1 21

braindiencephalon (telencephalon, brainstem)thalamus, hypothalamus (cortex, hippocampus, amygdale, midbrain, pons,

medulla)lateral geniculate nucleus, medial geniculate nucleus, ventral posterior nucleus,

etc.cortical layersneuronsmorphological features of the neuron (eg. dendrites, axons, cell body)(macro)molecules (ion channels, receptors, enzymes, etc.)etc.

Table 1.1 . A hierarchy of levels of organization based upon composition.

This hierarchy is based foremost on composition, and so, for instance, the thalamus is

above all of the nuclei (i.e., groups of neurons their cell bodies) that compose it. Looking atone of these nuclei, if we follow the lateral geniculate nucleus (LGN) down this hierarchy, then

below it are the six layers of neurons that compose it. The neurons that compose each of the six

layers are found at the next level down: magnocellular neurons compose layers one and two,

parvocellular neurons compose layers three through six. And at the level below that are the

morphological features of neurons.

A hierarchy of levels that is constructed in this way using composition as the defining

feature does not capture Wimsatt s idea that a level of organization is a feature of stable

interactions among entities. In some places on the composition hierarchy, for instance, at the

level of neurons, there are interactions that can be tracked and are relatively stable and

predictable (that is, the interactions among the neurons). However, at other places on the

composition hierarchy there are entities that do not participate in any specific interactions. For

instance, I think it is stretching matters, or a case of speaking loosely, to say that the thalamus

interacts with the cortex, and even more so to say that the diencephalon interacts with the

telencephalon.


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Chapter 1 22

So the first conclusion to draw, which I believe is uncontroversial, is that a hierarchy of

levels based foremost on interaction among entities (that is, Wimsatt s formulation) is not going

to be the same as a hierarchy of levels based foremost on composition. I will have more to sayabout this in what follows. For the time being I just want to be clear that since interaction and

composition are obviously different relations, when they are used to construct hierarchies of

levels the hierarchies are not going to be the same.

The question that follows from this is why choose interactions among entities, as I am,

instead of composition as the defining feature of levels of organization? The answer is that we

have to start with an idea of why we are interested in levels of organization. For this project the

interest is in investigating the relationship between psychology and neurobiology. Therefore, we

need to have a notion of levels of organization that is at least not inconsistent with what we think

a psychological description might look like. The type of psychological descriptions that I am

interested in are of psychological kinds such as language, memory, vision, and the one that I will

focus my discussion of psychological description on in chapter four: emotion. The only point I

want to make right now concerning these psychological kinds is that they are processes, meaning

that we understand them as being temporally extended and usually including the transformation

of an input into an output. 4

As a consequence it is reasonable to expect that these sorts of psychological processes are

carried out, or realized, biologically by an operation or mechanism of some sort. Thus, with

respect to how we want to think about levels of organization, we can use as a starting point the

idea that a psychological process is going to be carried out biologically by a series of interactions

among entities. Conversely, insofar as hierarchies based upon composition only identify entities

4 I will have more to say about psychological processes in chapters three and four.


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Chapter 1 23

and says nothing about interactions (of which in some cases there may not be any), it is not a

very useful tool for attempting to identify how processes are carried out.

A second, related, reason to employ levels based upon the interactions among entities isthat if we look at even a minimal amount of evidence from neurobiology it shows us that these

processes are in fact extended over some spatial distance (e.g., the process of vision extends from

the retina to the temporal lobe of the cortex). So if we want to be able to describe psychological

kinds at a particular level of organization, then we need a notion of levels of organization that

can accommodate a spatially and temporally extended process. Levels of organization that are

based on the stable interactions among entities are able to do this rather straightforwardly insofar

as each subsequent interaction increases the distance over which the process is carried out. If,

however, levels of organization are based upon composition, they are unable to offer this type of

explanation because they do not identify interactions.

To be clear, I am not saying that levels based on composition have no utility. They are

useful, I presume, for projects such as tracking developmental changes in the brain or

investigating comparative neuroanatomy. They just are less useful when the starting point is

investigating a process, either psychological or otherwise. 5

In the next few sections I am going to sketch out the levels of organization that are found

in the brain when stable interactions among entities are used as the criterion to identify levels. I

am going to focus on identifying stable interactions among entities, and distinguishing the

entities that participate in stable interactions from entities that do not. I should note that I am

going to leave aside identifying the conditions that give rise to those stable interactions. Simply

5 An example of the type of non-psychological process that I have in mind is, for instance, the processthat regulates balance. This begins in the inner ear and includes cells in the brainstem, cerebellum, andspinal cord.


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Chapter 1 24

identifying the interactions will be the criterion that I am going to use here. I will illustrate these

levels of organization by appealing to some examples. I am going to begin with what I am

calling the cell network level of organization and what this looks like in the primary visual cortex(V1). This will be the starting point for determining the levels of organization that we might say,

fall within the scope of the brain . Dropping down a level I have another example, also in V1 of

the sub-cellular level of organization. In addition to these two levels of organization there are of

course lower levels, some of which may fall within the boundaries of neurobiology. And at the

end of this chapter I will also consider a set of entities, brain areas , in order to determine

whether they constitute a level above the cell network level.

1.3 Levels of organization

1.3.1 The cell network level of organization

I will begin with the cell network level of organization. 6 Using Wimsatt s criteria, what makes

this a level of organization are the relatively stable interactions that occur between neurons.

These are primarily the transmission of impulses from one neuron to another that either excite or

inhibit the receiving neuron. 7 Excitatory transmissions cause, or increase the probability, that the

receiving neuron will generate an action potential and thus transmit an inhibitory or excitatory

6 I could perhaps have called this the cell or cellular level of organization, but I want to: (1) Start with aclean slate and avoid confusing what I mean with the way that the term is used to refer to a branch of

neuroscience (i.e., cellular [and molecular] neuroscience); and (2) Stress that at the level of organizationwhere cells are found we are not always considering one or two cells, although we might be. Even verylocal interactions have to be understood as occurring within a larger population of interacting neurons(and vice versa).7 Although I think that it is fair to say that these are considered by most who are interested in cognitiveneurobiology (of one sort or another) as the main types of interactions, I am leaving out other types of cells found in the brain, glial and schwann cells, and their interactions, which do not to have a direct rolein signal transmission.


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Chapter 1 25

signal on to another neuron. The inhibitory transmissions increase the probability that the

receiving neuron will not transmit a signal to another neuron.

In order to transmit an excitatory signal to another neuron the first neuron releases one of the excitatory neurotransmitters (e.g., glutamate, acetylcholine, aspartate) from a presynaptic

terminal on its axon into the space between presynaptic terminal and postsynaptic site on the

receiving cell (usually on a dendrite of the receiving cell). The release of excitatory

neurotransmitter has the effect of shifting the polarity of the postsynaptic membrane towards a

threshold point. If the threshold is reached, then the neuron will fire an action potential that

moves down that neuron s axon thus allowing this neuron to excite or inhibit other neurons.

Generally a number of different presynaptic neurons must release neurotransmitter at the

same time in order for the postsynaptic cell to reach threshold and generate an action potential,

although how many must be active varies with the amount of neurotransmitter that is released by

each particular neuron and the membrane resistance of the post-synaptic cell.


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Chapter 1 26

Figure 1.2 . A drawing of the connections between neurons, showing the axons of the

presynaptic cell and the dendrites where the contacts are made on the receiving

(postsynaptic) cell. From Jody Culham (2005).

Figure 1.2 illustrates the general layout of the contacts between neurons, but in reality the

numbers of these synaptic contacts on any given neuron are quite large. To take one example, in

the primary visual cortex (V1) of macaque monkeys there are, on average, 3900 synapses per

neuron, 83% of which are excitatory (Beaulieu et al 1992). Therefore, for any particular neuron

in V1 it has (i.e., receives) about 3200 excitatory contacts on its dendrites. Not all of these will

be active at the same time, but the potential is there for the neuron to receive input from a large

number of sources.

Inhibitory transmission is more or less the opposite. An inhibitory neurotransmitter (e.g.,

GABA, glycine 8) is released from the presynaptic terminal of a neuron s axon. This lowers the

probability that the receiving cell will be able to reach threshold and generate an action potential.

8 There are many other neurotransmitters than the ones that I have mentioned here, but as excitatory or inhibitory is not exactly the best way to organize them. Dopamine, for instance, can be either excitatory or inhibitory, depending on the type of receptor that it is released onto.


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Chapter 1 27

Given that these excitatory and inhibitory interactions between neurons are stable and relatively

regular this is a level of organization.

We can look at a simplified example of these interactions with a model proposed byJennifer Lund (Lund and Wu 1997, figure 1.4) for the feed-forward disinhibition of pyramidal

neurons in the upper layers of the primary visual cortex (V1). This is a model that attempts to

explain the effects observed in single cell activity when the neuron s response is modulated by

the presentation of stimuli in the region surrounding the neuron s receptive field (Levitt and

Lund, 1997). When a stimulus is placed in the neuron s preferred receptive field (i.e., the

preferred location, orientation, and direction of motion), it causes a strong response from the

neuron. But if the stimulus is placed in the area just outside of this preferred location (the

surround) it does not generate any activity in the neuron. However, when the preferred stimulus

and the surround stimulus are presented together this amplifies the neuron s response in some

cases and suppresses in others (figure 1.3).


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Figure 1.3 . On the left are the responses of two neurons in layer 3 of a monkey s V1 to a moving grating

in their receptive field (the y-axis is impulses per second). As that figure shows, cell D s strongest

response is to a 180 orientation and a smaller response is generated to the same orientation (0) moving

in the opposite direction. Cell E responds strongest when the grating is at 45/ 225 and moving in either direction. The two columns of graphs on the right are the responses of the same neurons when the

preferred stimulus is paired with the surround stimulus (the surround cycles through all of the orientations,

as shown on the x-axis). In the middle column the preferred stimulus is presented in high contrast and on

the far right the preferred stimulus is presented at low contrast.

In the graphs on the right the bar is the neuron s response without the surround stimulus, the

open circles are the neuron s response to only the surround stimulus, and the filled circles are the

neuron s response to both the preferred and the surround presented at the same time. From Levitt and

Lund (1997: 73).

The two columns on the right in figure 1.3 illustrate that when the center and the

surround of the stimulus are at the same orientation (the neuron s preferred orientation) the

neuron s activity is suppressed. However, when the surround is at a different orientation than the


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Chapter 1 29

center, the neuron s activity is in some cases higher than it is when the optimal stimulus is

presented without the surround. This is to say that the surround is amplifying the neuron s

response. And in some cases, the neuron responds differently when the surround is at the sameorientation, but the contrast of the center is different. This is pointed out by the arrow in the two

graphs on the right for cell D. When the contrast is high the activity of the neuron is amplified

and when the contrast is low it is suppressed.

Figure 1.4. A diagram of a simplified neural circuit in the primary visual cortex (V1).

The numbers on the right indicate the cortical layers, and the subdivisions of these

layers. From Lund and Wu (1997: 123).

Now we can look at the model that Lund created to explain this data. The diagram in

figure 1.4 shows two spiny stellate cells (the circles), one in the upper part of layer 4C and one

closer to the 4C -4C border in V1. These cells receive input from cells in the lateral geniculate

nucleus, which are themselves innervated by cells in the retina. The spiny stellate cell in upper

layer 4C excites a pyramidal cell in layer 4B. This causes the pyramidal cell to excite a


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Chapter 1 30

columnar cell, which then releases the inhibitory neurotransmitter GABA onto a chandelier cell

in layer 3B. When the chandelier cell is inhibited it no longer, or to a lesser extent, inhibits the

pyramidal cell that it projects to. So by virtue of the columnar cell inhibiting the chandelier cellthe pyramidal cell is no longer inhibited (i.e., the pyramidal cell is now disinhibited). One

possible purpose for these columnar cells is, as Lund and Wu say, to act as inhibitory

controllers of the chandelier neurons, ensuring that local pyramidal neurons are released from

their inhibition under appropriate conditions, e.g., when the column is active (1997: 124).

If we look at the other activity in this column, the spiny stellate cell in the middle of layer

4C of the diagram is exciting that same pyramidal cell in layer 3B. This pyramidal cell is no

longer receiving inhibitory input from the chandelier cell and is receiving excitatory input from

the spiny stellate cell in 4C. Therefore, it is now able to excite a pyramidal cell in layer 2/3A and

the columnar cell in layer 3B.

The diagram also includes pyramidal cells in the same layer as the other pyramidal cells

but in a different column (to the left). These laterally placed cells are presumed to give rise to the

type of activity shown in figure 1.3. The diagram in figure 1.4 is representing the idea that the

two pyramidal cells on the left and those on the right all respond to the same orientation (let s

say a line at this angle: ). The pyramidal cells in the left column are exciting both the pyramidal

cell and the chandelier cell in their respective layers. The excitation of the pyramidal cell causes

it to fire, but the excitation of the chandelier cell causes the chandelier cell to inhibit the same

pyramidal cell.

Lund and her colleges (Lund and Wu 1997, Lund et al 1995) suggest that as this input

from the pyramidal cell in the left hand column increases the overall effect is the inhibition of the

pyramid cell (on the right) via the chandelier cell. That is, when the pyramidal cell in the left


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Chapter 1 31

column receives strong (or optimal) stimulation the activity of pyramidal cell in the right column

is suppressed. But when the pyramidal cell on the left is receiving sub-optimal stimulation (e.g.,

an orientation that is 45 greater than its optimal orientation), then the response of the pyramidalcell on the right is enhanced. Thus, the pyramidal cells in one column are able to suppress the

activity of the pyramid cells in the same layer but a different column. However, this suppression

is, graded and the result of how strong the lateral input is (Lund and Wu 1997: 124).

Overall this example shows us how a series of neurons interact as inputs that began in the

retina are received. This example from Lund, while it has been helpful for discussing excitatory

and inhibitory projections, is a simplification of the activity at this level. In this example each

cell in the diagram is presumed to represent a number of similar cell types that have similar

projection patterns. And all of the projections that the actual neurons in these locations make are

shown as one or two projections that represent the general pattern of projections for that

population of neurons. In reality the number of connections and hence the number of

interactions are often in the thousands for each neuron. To emphasize this point I want to look

at an actual spiny stellate cell.

In figure 1.5 is a spiny stellate cell with an axon that makes excitatory contacts on cells in

layers 5, 4C and , and in layers 2/3 (Yabuta and Callaway 1998). 9 And for the input that this

cell receives thousands of contacts are made on its dendrites by neurons in the lateral geniculate

nucleus of the thalamus and by other neurons in V1 (Beaulieu et al 1992; Peters et al 1994).

9 This axon has 2545 synaptic terminals (or buotons as they are called in figure 1.2) in layers 5, 4C and4C , and 1066 synaptic terminals in layers 2/3. This spiny stellate is one of the ones Yabuta and Callaway(1998) designate as lower 4C with narrow dendrites .


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Chapter 1 32

Figure 1.5 . A spiny stellate cell. From Yabuta and Callaway (1998). Note that the

dentritic field is draw separately from the cell body and axonal arbor (the dendritic

field is the much smaller clump on the left). The scale bar is 200m.

One might conclude from this description of the spiny stellate cell that a little loss of

detail might be beneficial. Possibly, but this is not a question that I am going to address. Rather I

want to emphasize that the sort of description that we get from Lund is a very simplified

description of the entities and their interactions at this level of organization (although it does give

us traction into understanding these interactions). The actual cell network level of organization is

the actual causal interactions between the entities at that level. When we switch to talking about

the general tendency of one population of neurons to innervate another population of neurons we

are, in a certain sense abstracting away from the actual details of what occurs at this level of

organization. There are numerous ways that we can speak loosely about what is, or might be,

occurring at a level of organization. And the example from Lund is fairly explanatory so we can

see that there can be benefits to abstracting away from the details. I will have more to say in later

chapters about abstracting away from a particular level of organization. For now I just want to

make the point that there is a way of talking that describes the entities and their interactions at a


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Chapter 1 33

level of organization, and then there is also a looser way of talking that captures the sorts of

things that occur at a level of organization but does not completely describe them (as in the

example from Lund). Offering a less detailed description of what is occurring at a particular levelof organization does not mean that we have introduced another level of organization. We are still

dealing with the same level of organization because we are still talking about the same entities

and the same activities, just in a different a looser way.

1.3.2 The sub-cellular level of organization

I now want to move down one level to what I am calling the sub-cellular level of organization

and again look at activity in V1. The entities at this level are for the most part the large

molecules (enzymes, proteins, ion channels, organelles, etc.) that interact with each other within

and around neurons. The exemplar that I am going to look at here is ocular dominance plasticity.

This is a good example because plasticity, that is, a change to the way that neurons and their

activities are organized, is one obvious reason to look at the activity at the sub-cellular level.

This is to say that if we observe a significant change at the cell network level, then we are

inclined to look to the sub-cellular level and the processes that are occurring there in order to

understand what drives the change. There are other reasons to examine the activity at the sub-

cellular level, for instance, we might want a clearer understanding of how excitatory input causes

a cell to respond and under what conditions it does. However, plasticity is one good reason to be

interested in this level of organization.

Starting our explanation at the cell network level, ocular dominance plasticity is the

process whereby depriving one eye of input for a period (e.g., by sewing it closed, or having a

cataract) causes the cells in V1, which normally are organized into ocular dominance columns, to


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shift to responding predominantly to the non-deprived (open) eye. Ocular dominance columns do

not exist at birth. In the monkey for instance, at birth the axons that enter layer 4C from the LGN

branch over a large area and there is little or no segregation between the inputs from each eye(Hubel and Wiesel 1977: 51). During early development the axon branches become smaller,

more focused, and organize into the ocular dominance columns. It also appears that these

geniculate-cortical axonal branches become denser in this narrower area that they occupy.

However, if one eye is deprived of stimulation during the critical period after birth the

axons entering V1 (in layer 4C) that serve the deprived eye become greatly reduced while the

axons serving the non-deprived eye expand. 10 Deprivation is effective in causing these changes

in as little as a week. The result is that the cells in V1 respond predominantly to the eye that was

not deprived. Whereas if the deprivation had not occurred the columnar organization would have

developed, the deprivation causes almost all of the cells in V1 to become innervated by the non-

deprived eye (and, consequently, the deprived eye to lose almost all of the cortical territory that it

would have innervated in V1). This change this plasticity is therefore a result of how

stimulation of the eyes is manipulated.

10 This plasticity occurs, under the right conditions, during a window, the critical period, between birthand puberty. The length of this critical period differs among species. In the human it lasts until age seven(Berardi et al, 2000). In the monkey it is competed twelve weeks after birth (Berardi et al, 2000). In thecat it does not begin until the eyes open two weeks after birth, and extends past week ten (Antonini andStryker, 1993b: 3549). And in mice it lasts until the mouse is about 32 days old (Gordon and Stryker,1996). The length of time that one eye must be occluded for the full ocular dominance shift to occur likewise differs among species, and is relative to the length of the critical period.


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Chapter 1 35

Figure 1.6 . The figure on the left shows axons, deprived and non-deprived, from kittens that had one eye

deprived for one week beginning at five weeks after birth. 'ND' are axons serving the non-deprived eye,

'D' are axons serving the deprived eye. The figure on the right shows axons from kittens that had one eye

sewn shut from before eye opening to age 39 days. Note that the non-deprived axons in the long-term

monocular deprivation have branches that are dense, widespread, and not restricted to 0.4 mm columns.

From Antonini and Stryker (1993a: 1819).

The figure above shows the axons of cells in the LGN that innervate cells in layer 4C of

V1. The dramatic changes in these genticulate-cortical axon branches in layer 4C are the end

result of this plasticity. Prior to the changes that occur in layer 4C are the loss of the spines that

form on the dendrites (and are sites of synaptic contact) in other layers. The loss of dendritic

spines on the pyramidal cells in layers 2/3 (Mataga et al, 2004) and 5 (Oray et al, 2004) of V1 is

the first change in this form of plasticity, occurring after brief (2 4 days) monocular deprivation

during the critical period in mice. So the basic outline of this plasticity process is: first there is a

change in visual experience, this then causes changes in the synaptic connections outside of layer

4C (i.e., the loss of spines), which in turn drives significant changes to the axons that enter V1

(in 4C).


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In the rest of this section I will review some of the sub-cellular activities that lead to the

spine loss outside of layer 4C. The beginning of this process, from calcium influx to gene

expression is sketched out in the figure below.

calmodulin

CaMKII

CREB CRE gene expression

Ca 2+ influxNMDA receptor

nucleus

extracellular

cytoplasm

Figure 1.7 . A sketch of the intracellular cascade that begins with

calcium ions entering the cell and eventually leads to gene expression.

CaMKII: Calcium-calmodulin kinase II.

When a pre-synaptic neuron releases the neurotransmitter glutamate it binds to receptors

in the post-synaptic membrane. This allows positively charged sodium ions (Na +) to enter the

cell. If enough Na + enters (if there is a strong enough depolarization) the Mg 2+ ion that is

blocking the NMDA receptor is removed. Removal of the magnesium blockade allows an influx

of Ca 2+ through the NMDA receptor (Taha and Stryker 2005a: 104). 11 The influx of Ca 2+ then

begins intercellular processing. 12

11 The first important component in ocular dominance plasticity, once the stimulation the eyes receive isaltered, is the disruption of the balance between inhibitory and excitatory activity. This inhibitory input isnot merely a (direct) consequence of the altered sensory input (from the eyes) to V1. It also seems to be afeature of the critical period during which plasticity can occur. However, it is not entirely clear what theexact balance is between excitatory and inhibitory input that is required for ocular dominance plasticity.The inhibitory neurotransmitter -Aminobutyric acid (GABA) provides the inhibitory input. And theGABA A receptors containing the 1 subunit, which are found on the soma of pyramidal cells where


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Chapter 1 37

The influx of calcium allows calcium-calmodulin kinase II (CaMKII), a protein which

has been shown to be important for this form of plasticity, to become active (Taha and Stryker,

2005b; Gordon et al, 1996; and Taha et al, 2002).13

Once a sufficient amount of calcium entersthe neuron it can bind to the protein calmodulin, thereby changing the conformation of this

protein. The Ca 2+/calmodulin complex then binds to CaMKII, activating the CaMKII. Once

activated CaMKII can autophosphorylate, which allows it to remain in its active state once the

calcium influx has ended. 14 The active CaMKII can then phosphorylate the protein cyclic AMP

response element binding protein (CREB, [Pham et al, 1999]). 15

synapses are made with large basket cells, also appear to have a role here. The basic idea is that thecorrect balance of excitatory and inhibitory activity allows plasticity to proceed. When mice aregenetically manipulated so that they produce significantly less of the inhibitory neurotransmitter GABA(GAD65 KO mice glutamic acid decarboxylase 65-kD is one of two enzymes that synthesizes theneurotransmitter GABA) these mice fail to exhibit this ocular dominance shift after one eye is occluded.12 Experiments by Roberts et al (1998), demonstrated that the NMDA receptor is involved in ocular dominance plasticity. She and her colleagues demonstrated this by using antisense oligonucleotides toreduce expression of the NMDAR1 subunit of the NMDA receptor (an antisense oligodeoxynucleotide isan engineered string of nucleotides that when injected binds to a particular sequence of a strand of DNA,which then effectively silences the gene). This technique blocks the NMDA receptor activity, withoutdisrupting general visual activity, and it prevents ocular dominance plasticity.13 Other enzymes, notably protein kinase A (PKA) (Beaver et al, 2001), and extracellular signal-regulatedkinase (ERK) (Di Cristo et al, 2001) have also been shown to have a role in ocular dominance plasticity.This suggests that there may be several, perhaps interrelated or overlapping, intracellular cascades thatcontribute to ocular dominance plasticity.14 That the autophosphorylation of CaMKII is critical for rapid ocular dominance plasticity was shown

by Sharif Taha and Michael Stryker (2002). They genetically modified mice so that the amino acidalanine was substituted for threonine (at position 286), which makes CaMKII unable toautophosphorylate. In mice with this genetic modification ocular dominance was significantly impaired ascompared to wild-type mice.

This study was followed by another (Taha and Stryker, 2005b) testing the effects of longer periods of monocular deprivation (10-26 days) on mice in which CaMKII could not autophosphorylate. They foundthat there was plasticity in these mice (indistinguishable from wild-type), perhaps driven by CaMKIIactivity that was dependent on Ca 2+/calmodulin, or another kinase-dependent cascade (Taha and Stryker,2005b: 16441).15 That CaMKII is necessary for ocular dominance seems clear, but its exact role is less clear. Stryker (Taha and Stryker 2005a) and Hensch (2004, 2005) both suggest that it is part of the cascade that beginswith calcium influx and leads to CREB activation. CaMKII s role in CREB activation is however,


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Chapter 1 38

CREB is a transcription factor that binds to the cAMP response element (CRE) sequence

of DNA, and so if it is activated it promotes the synthesis (transcription) of RNA from a strand

of DNA (Nestler and Greengard, 1999: 490 2).16

Once active CREB regulates the expression of numerous genes (i.e., different genes that all contain the CRE sequence for CREB to bind to),

one of which is brain-derived neurotrophic factor (BDNF [Pham et al 1999]). BDNF has been

shown, in vitro, to stimulate the expression of tissue plasminogen activator (i.e., the expression

of tPA mRNA), as well as its release from neurons into the extracellular space (Fiumelli et al

1999).

Tissue plasminogen activator (tPA) is a protease that when released from a cell causes the

conversion of plaminogen into plasmin. Plasmin is an enzyme that participates in proteolysis, the

breakdown of proteins. Although, it is not known if in this particular process tPA is directly

participating in the proteolysis, or if its role is to catalyze the plasminogen (Berardi et al, 2004:

906). 17 Mataga et al (2004) suggest the process that is illustrated in the figure below, as the way

somewhat complicated. CaMKII can, like CaMKIV (and PKA and ERK), phosphorylate CREB on serine133, making CREB active. However, CaMKII also phosphorylates CREB on serine 142, which appears todisactivate CREB (Sun et al 1994). But as a reminder, I am here only trying to illustrate the sort of entities and their activity that are found at the sub-cellular level.16 CREB has been shown to be required for ocular dominance plasticity by Tony Pham and his colleagues(Pham et al, 1999) who found that it is upregulated in mice that are monocularly deprived, but not in micethat are binocularly deprived or in mice that do not experience deprivation. And in another study Mower et al (2002) were able to suppress CREB activity in ferrets using a virus that caused a dominant negative

form of CREB (which could not become active) to be expressed in V1. This manipulation preventedocular dominance from occurring.17 Returning to the cell-network level, Mataga et al (2004) imaged the dendrites of pyramidal cells inlayers 2/3 of V1, which had been labeled with lipophilic dye, and found that the number of protrusionsincreased steadily during development (from 9 days after birth eyes still closed, to 66 days old adult)in normal (wt) mice. Monocular deprivation for four days during the critical period significantly reducedthe number of protrusions as compared to non-deprived mice of the same age (and monocular deprivationof adult mice showed no effect on the number of protrusions).


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Chapter 1 39

in which the monocular deprivation induced release of tPA causes the degeneration and eventual

removal of the spines from pyramidal cells.

Figure 1.8 . In all three diagrams the presynaptic terminal is the shape at the top of the

diagram and the dendritic spine is below it. See text for further explanation. From Mataga et al(2004).

The area around the synapse (outside the cells) is composed of an extracellular matrix of

proteins, as well as cell adhesion proteins that attach to the presynaptic terminal and the

postsynaptic dendritic spine. The tPA (or plasmin) in the area of the synapse (the pac-man

shapes) breaks down some of the proteins that compose the extracellular matrix (laminin and

phophacan these are represented by the gray background that is fading from A to B to C), and

the neuronal cell adhesion molecules (yellow bars). This begins the process of spine loss. These

extracellular events may then be followed by signaling from the soma of the postsynaptic cell

(e.g., by serum-inducible kinase, SNK) that causes spine removal.


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Chapter 1 40

In contrast to this activity that is downstream of the deprived eye, the extracellular matrix

around the synapses that are driven by the non-deprived eye are not affected, although they are

also exposed to tPA. One reason for this may be that tPA is inhibited by one or both of two protease inhibitors: neuroserpin and nexin-1 (the green triangles in the figure), which are

released at active synapses along with tPA. Another possibility is that adhesion molecules that

are not sensitive to tPA: N-cadherin and -catenin (green bars), protect the active synapses from

the tPA activity.

This tPA activity the breakdown of the extracellular matrix occurs in layers 2/3 of

V1. It is not known how this activity connects with the changes that occur in layer 4. And I have

not talked at all about the positive changes that occur during this shift in ocular dominance. This

is also not well understood, although it is presumed that BDNF has a role in driving the growth

of new axonal branches that serve the non-deprived eye (Hensch 2005, Taha and Stryker 2005a).

This is a summary account of some of the entities that are found at the sub-cellular level

of organization and the activities that they participate in during the occurrence of this type of

plasticity. Although I have given somewhat more detail about tPA and its activities, even that

was less than a complete description of the entities and their behavior at this level. For instance,

obviously tPA are not little pac men chomping their way through protein in the intracellular

matrix. A more detailed picture of the entities and their activity would look more like what is

shown in the diagram below illustrating calmodulin binding to the regulatory domain of the

alpha subunit of calcium/calmodulin-dependent protein kinase II ( CaMKII). This binding

relieves the autoinhibition of that subunit of the CaMKII, which in turn sets in motion a series of

event that make the CaMKII active and hence able to phosphorylate the proteins that it targets.


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Chapter 1 41

Figure 1.9 . From Vetter and Leclerc (2003: 406). This is one way of

representing macro-molecules. The ribbon shapes represent the secondary

structure of these proteins. The blue ribbon is calmodulin (the yellow spheres

are the calcium ions), and the red ribbon is the calmodulin binding site of the form of the CaMKII.

The point is to be clear about the range of ways of talking about what is occurring at the level of

organization. It is often the case that these activities are discussed not in the context of a

discussion of levels of organization, but in the context of trying to understand an extended

process that is incompletely understood. Hence, it is not always important to be explicit about

how calmodulin binds to CaMKII (which is well understood) or whether tPA acts directly on the

extracellular matrix molecules or via plasminogen activation (which is not yet known, so being

explicit is not an option). Nevertheless, as I said in the previous section, whether we are being

explicit about them or not, the actual activities remain the same and an explicit description of

them is what constitutes a description of a level of organization. All other talk is a looser,

although perhaps still informative, description of the activity at the particular level of

organization.


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Chapter 1 42

1.3.3 The chemical level of organization

One level of organization that is below the sub-cellular level is what can be called the chemical

(or biophysical) level of organization. At this level the entities are atoms (chemical elements)and their interactions are such things as: the chemical bonds that form between atoms whether

these are covalent bonds or the weaker ion-ion, hydrogen, or dipole-dipole bonds; non-bonding

interactions between atoms, and the interactions between atoms and the solvent that they are in

(van Holde et al 1998: 10 11, 95 8).

One question, however, is whether there is a level between this chemical level and the

sub-cellular level. The obvious candidate for an intermediate level would, I believe, be a level

occupied by entities such as amino acids, sugars, and lipids. These are entities and they do have

interactions. However, the issue here is whether these interactions are actually different in type

than the interactions at the lower, chemical, level. An example that can help to address this issue

is shown in the figure below.

H

C

C

C

N

C

N

N NH

H

H

N

C

N

C

C

C

O

AdenineThymine

CH

H

C

N

O

Figure 1.10 . Adapted from van Holde et al (1998: 55). Except for

the hydrogen bonds that are represented as dotted lines, the

different types of bonds are not represented. The filled circles are

where the nitrogen atoms bond to the deoxyribose.


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Chapter 1 43

Illustrated here are two of the bases, thymine and adenine, that compose

deoxyribonucleic acid (DNA). Now there certainly is a way of talking where we say that these

two bases interact, that is, they bind together. I am not interested in critiquing that way of talking. All that I want to clarify, for the purposes of constructing a hierarchy of levels of

organization, is whether or not there is one interaction that the bases have and a different

interaction that atoms have. It seems to me that there is only one type of interaction here. And

furthermore that type of interaction, the bonds that form between atoms, occurs at this chemical

level of organization. 18 Therefore, the consequence of this is that although these bases, amino

acids, sugars, and so on are entities, because they do not have unique interactions they do not

have their own level of organization when levels of organization are based upon interactions

among entities. 19

1.3.4 Higher levels

The three levels of organization that I have just discussed, the cell network level , subcellular

level , and the chemical level qualify in a straightforward way as levels of organization. The

entities are identifiable and the interactions that these entities have with each other are, if not

18 One other possibility is that although the same term, bonding , is being used when talking about aminoacids and when talking about atoms the term has a somewhat different meaning in each case. I am notsure and I am going to put this possibility aside.19 One objection here may be that the difference in strength between hydrogen bonds and covalent bondsindicates that they are should be at different levels. After all the strength of the interactions here aremarkedly different. I prefer to think that both of these interactions (hydrogen bonds and covalent bonds)occur at the same level of organization. They are just different interactions that occur at the same level.And this type of objection I address in the last section of this chapter. On this particular point however, Iwill say that although hydrogen bonds and covalent bonds differ in their strength, each is not a type of interaction that occurs between different sorts of entities. There are differences, but it is not the case (for instance) that we can look at one type of bond as occurring between atoms and the other type as occurring

between amino acids, which is the important point for this section.


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Chapter 1 44

easy to discover, still easy to describe once they have been determined. I am not convinced that

there are higher levels within the brain (i.e., below the level of the whole brain) that have these

features. If we look at some of the entities that have been mentioned while discussing the early part of the visual process we have: the lateral geniculate nucleus, the primary visual cortex (V1),

V2, and so on. We might intuitively think that these entities these brain areas constitute a

level. However, when we look at these entities, it is difficult to say what sorts of interactions they

participate in, which of course is required if we are to establish that this is a level of organization.

If we take the LGN and V1, the two structures do not touch each other, and merely saying that

they are connected by axons is not an option since axons occur at the cell network level of

organization.

The most plausible suggestion that can be made here, I think, is that they interact by way

of axon tracks or axon bundles . That is, structures like the optic track or optic radiations, which

are bundles of axons that all have their cell bodies in the same place (in this case in the retina,

and in the LGN) and that all terminate in the same general place. In order to make this move I

think that there has to be at least some minimal justification for understanding these axon

bundles as different than just the axons that are found at the cell network level of organization.

One justification is that, at least in some cases, an axon track is a visible entity. The optic

nerve for instance can be seen with the naked eye (when the brain is removed from the skull).

And presumably there is at least an intuitive desire to call something that we can see and touch,

and distinguish from other things an entity. So this is perhaps one reason to say that the optic

radiations are what connect the lateral geniculate nucleus and primary visual cortex. But, on the


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Chapter 1 45

face of it all that introducing optic radiations does is give us another entity. What sort of

interactions these entities have is another question that still has not been answered. 20

So, it is still not clear how we might describe, at this brain areas level, the interactionsthat are supposed to occur between the LGN and V1. As a contrast we can look at a

magnocellular neuron in the lateral geniculate nucleus that sends its axon into V1 where it

synapses on spiny stellate cells that are in layer 4C . This magnocellular neuron interacts with

the spiny stellate cells by way of an excitatory impulse, which under the right conditions will

contribute to the spiny stellate cells generating an action potential and themselves exciting other

neurons. In this case we have the type of activity that neurons engage in: generating action

potentials, and we have a description of the interactions between neurons that drive this type of

activity: multiple neurons concurrently releasing excitatory neurotransmitter onto the spiny

stellate cell can drive that cell to threshold such that it will generate the action potential.

In the case of the interaction between the LGN and V1 it is not obvious that we can

describe the interactions in as straightforward a manner. We could say that there are additive

effects of these neurons in the LGN exciting cells in V1, however, it does not really seem to be

the case that the effects are exactly what we would call additive. 21 In the case of this vision

example when we are looking at the activity of neurons and their interactions (at the cell network

20 It can be noted that in this discussion I am not pressing Wimsatt s criteria very hard i.e., the issue isnot one of where the most significant interactions are found, or where the most regular interactions are

found. Rather it is more simply just a question of whether there are any interactions among these brainareas at all.21 Recall that in the discussion of the cell-network level of organization I pointed out that there are looser ways of talking about what is occurring at a level of organization, namely describing the tendency for cells in one area to transmit to cells in another area. This is in contrast to an actual description of theactivity at this level of organization which is of the specific entities and their activities. This looser way of talking about what is occurring at the cell-network level of organization is not a higher level of organization. To move to the higher level of organization we need different entities.


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level) we can investigate the processing of orientation, motion, color and so on. However, when

we move to talking about brain areas, if we merely add up the activity of the neurons, then we

lose the focus on the perception of these different features.Possibly we could say something such as: there is a flow of visual information from the

lateral geniculate nucleus to V1, but it is not clear what this visual information is. It is wrong to

say that the visual scene (out in the world) is simply encoded as a whole and transferred from the

LGN to V1. But when we are more specific about what sort of information is being transferred,

then we are again talking about the activities that occur at the cell network level not among brain

areas.

Therefore, I am taking the position that brain areas do not constitute a level of

organization. I will however, investigate this at more length in the next chapter with some of the

cases that Patricia Churchland (1986) offers. The difficulty that there is in putting together

support for this brain areas level of organization suggests, rather convincingly, that there are

not any levels of organization that are even higher, but below the level of the whole brain, for

example, a level where brain lobes interact.

As a reminder this entire discussion is about levels of organization where a level is

occupied by particular entities interacting in predictable ways. Levels based on something else,

for instance composition, give us a way of ordering higher level entities such as the thalamus or

the occipital lobe of the cortex. But when focusing on levels of organization in the way that

Wimsatt defines level of organization these sorts of entities (thalamus, occipital lobe of the

cortex, etc.) do not have a place they may very well be used to reference where some

interaction is occurring or where some entity is located, but they are not themselves entities that

participate in the sorts of interactions that constitute a level of organization.


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In the next section I will consider some objections, but first I want to reiterate where we

stand. I have suggested that there are three levels of organization that fall within the scope of the

brain: the cell network level, the sub-cellular level, and the chemical level. There is no way,which I know of, to prove that there are only these three levels of organization within the scope

of the brain. All that can be done is to examine other potential candidates. This I have done for

brain areas and I will look at more cases in the next chapter.

1.4 Objections

Now that I have discussed the different levels of organization that fall within the scope of

neurobiology I want to address a few potential objections to the idea that a level of organization

is identified by stable and regular interactions and to the hierarchy that I have developed. I take

these entities and their activities to be real, in the sense that they exist in nature and I do not take

myself to be imposing an artificial organizational scheme on them. However, I also recognize

that when trying to organize them there may be gray areas, as well as areas where some may

disagree about how to conceive of a particular type of interaction or what counts as an entity.

Although I said that I am taking a (more or less) realist stance with respect to these levels

of organization, my aim here is not to organize the furniture of nature. Rather, it is to set up a

scheme that can be useful for thinking about how psychology and neurobiology are related. To

that end, the hierarchy of levels of organization that I have offered is laid out for that purpose

and so ultimately it is just meant to be a useful tool for getting some traction into that

relationship. There are however, three issues that I want to address

(1) First, how do we know when some interaction should be explained at one level rather

than another? For instance, the excitatory interactions between neurons, and the subsequent


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generation of an action potential can be described at the cell network level, but a series of

interactions that occur at the sub-cellular level of organization can explain the same events. 22

However, while it seems clear that the event can be understood at both levels, there do seem to be reasons to select one level over another.

To back up a bit, when establishing levels of organization there are two ways in which

we can proceed. We can look at the entities that are studied by neurobiology and then determine

if each class of entities participates in specific interactions. When we do this we find that neurons

participate in specific interactions, as do the macromolecules that are found in the brain. Brain

areas, however, although they are entities, do not participate in specific interactions. Conversely,

we can proceed by looking for the interactions first. For instance we can look at the process by

which ocular dominance plasticity occurs, or a process such as the one Lund describes in V1. If

we are successful these two approaches should coincide, and we will have identified some

specific levels of organization.

Returning to the question of how to decide the level at which an interaction should be

described, these two cases indicate that the problem is solved for us if we just allow the

descriptions of the entities and the interactions to, in a sense, take their natural course. Or more

specifically, if we just follow the way in which the scientists describe these interactions, then the

level at which an interaction should be described is answered for us. Therefore, in the case of the

excitatory interactions, when we find that there are times when we want to describe excitatory

22 For instance, at the sub-cellular level the generation of the action potential is explained as the bindingof the neurotransmitter to receptors in the membrane of the postsynaptic neuron. This either directly or indirectly causes ion channels to open, allowing positively charged ions that the channel is selective for toenter. This influx of positively charged ions spreads down the dendrite to the base of the axon wherethere are voltage gated channels. When the voltage gated channels are opened this is usually sufficient todrive the membrane potential to threshold. This at the cell network level is the generation of an action

potential.


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interactions among neurons (as Lund does), then we utilize the cell network level. On the other

hand, if we want more detail concerning how the interactions occur, then the activity at the sub-

cellular level must be investigated. The gain in choosing the lower level is a more completeunderstanding of what the event in this case excitatory transmission entails. The cost,

however, in choosing the lower level is the added complexity of grasping a large series of these

events (excitatory transmissions) and the downstream effects that a large number of excitatory

transmissions will have.

A second answer expands upon this. In a case like the example that I used from Lund of

the different responses of a neuron to only slightly different stimuli, there is a clear sense in

which this activity is tracked more easily at the cell network level and not at the sub-cellular

level. And not only is it tracked more easily there, but there is no gain in our understanding of

the case by investigating the activity at the sub-cellular level rather than at the cell-network level

(so far as I know). Given that it is most easily tracked at the cell-network level and there is no

advantage to investigating the activities at the sub-cellular level, this makes the cell network

level the natural level at which to explain these activities. And likewise for other levels; it seems

reasonable to say that as long as we are not losing any (needed) content in the description of an

activity, then the level at which the activity is most easily described should be the one that should

be selected. 23

(2) A second issue is that there do appear to be some genuinely gray areas. We saw one of

these in the section on the sub-cellular level, namely the interaction between calcium ions and

the protein calmodulin. I would normally take these two entities to be at different levels of

23 Note that this discussion about the level at which an activity should be described, is not the same as thediscussion concerning the status of brain areas and whether or not they occupy a level at all.


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organization, but in a straightforward way of talking about them they do appear to interact:

calcium binds to calmodulin, thus changing the calmodulin s conformation. The case could

perhaps be manipulated so that it would fit better with my notion of levels of organization. For example, we might say something like this: when calmodulin s environment changes from a free

Ca2+ concentration of ~10 7 moles to a concentration of ~10 5 moles the calmodulin becomes

active (Cates et al 2002). 24 This is a legitimate way of talking about the activities of calmodulin.

However, it seems more straightforward just to say that calcium ions

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Levels in the Cognitive and Biological Sciences Dissertation