Neuronal Coherence

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Neuronal coherence during selective attentional processingand sensorymotor integration

Thilo Womelsdorf a, * , Pascal Fries a,b

a F.C. Donders Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Kapittelweg 29, 6525 EN Nijmegen, The Netherlandsb Department of Biophysics, Radboud University Nijmegen, 6525 EZ Nijmegen, The Netherlands

Abstract

Groups of neurons synchronize their activities during a variety of conditions, but whether this synchronization is functionally relevanthas remained a matter of debate. Here, we survey recent ndings showing that synchronization is dynamically modulated during cog-nitive processes. Based on this evidence, synchronization appears to reect a general mechanism that renders interactions among selectivesubsets of neurons effective. We show that neuronal synchronization predicts which sensory input is processed and how efficient it is trans-mitted to postsynaptic target neurons during sensorymotor integration. Four lines of evidence are presented supporting the hypothesisthat rhythmic neuronal synchronization, also called neuronal coherence, underlies effective and selective neuronal communication. (1)Findings from intracellular recordings strongly suggest that postsynaptic neurons are particularly sensitive to synaptic input that is syn-chronized in the gamma-frequency (3090 Hz) range. (2) Neurophysiological studies in awake animals revealed enhanced rhythmic syn-chronization among neurons encoding task-relevant information. (3) The trial-by-trial variation in the precision of neuronalsynchronization predicts part of the trial-by-trial variation in the speed of visuo-motor integration. (4) The planning and selection of specic movements can be predicted by the strength of coherent oscillations among local neuronal groups in frontal and parietal cortex.

Thus, neuronal coherence appears as a neuronal substrate of an effective neuronal communication structure that dynamically linksneurons into functional groups processing task-relevant information and selecting appropriate actions during attention and effective sen-sorymotor integration.

2007 Elsevier Ltd. All rights reserved.

Keywords: Coherence; Synchronization; Attention; Sensorymotor integration; Decision

1. Introduction

Oscillatory synchronization is a prevalent propertyencountered among groups of neurons throughout the

mammalian brain ( Buzsaki and Draguhn, 2004; Kruseand Julicher, 2005; Lachaux et al., 2003; Laurent, 2002;Steriade, 1999; Usrey, 2002; Usrey and Reid, 1999; Varelaet al., 2001). Despite its widespread occurrence, only recentexperimental evidence succeeded to show that synchro-nized oscillatory activity (or: coherence) among neuronalgroups within and across cortical areas could be function-

ally relevant and support the dynamics of cognitive pro-cesses in a variety of tasks (Engel et al., 2001; Varelaet al., 2001). The emerging view from these ndings is thatneuronal coherence subserves the selective and effective

transmission of information among neuronal groups dur-ing the integration of sensory information to ultimatelytrigger adaptive motor performance ( Fries, 2005; Laughlinand Sejnowski, 2003; Salinas and Sejnowski, 2001; Sejnow-ski and Paulsen, 2006 ). In this review, we will survey recentexperimental results suggesting such a central role of neu-ronal coherence for effective neuronal communication.

Investigating the nature of effective neuronal communi-cation is central to an understanding of the dynamics of cognitive processes. Neurons communicate via the trans-mission of action potentials along anatomical connections.

0928-4257/$ - see front matter 2007 Elsevier Ltd. All rights reserved.doi:10.1016/j.jphysparis.2007.01.005

* Corresponding author. Tel.: +31 024 36 68295; fax: +31 024 36 10989.E-mail address: [email protected] (T. Womelsdorf).

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During cognitive processing, only a selected subset of theseconnections become effective and convey task-relevantinformation. Moreover, varying task contexts require aexible routing of information among varying groups of neurons in sensory and motor cortex. This is particularlyevident during top-down attentional control: While the

visual system is typically stimulated by a multitude of dif-ferent stimuli, voluntary attention allows us to restrict pro-cessing resources to only one stimulus in the scene and toselect the appropriate behavioral action. At the neuronallevel, this involves the selective communication betweenthose groups of sensory neurons processing the attendedstimulus and ultimately those groups in motor cortexinstructing the required behavioral response. At the sametime, the communication between unattended sensoryneurons and motor cortical neurons is prevented.

This example demonstrates the necessity of a dynamicmechanism that imposes an effective neuronal communica-tion structure on top of the anatomical infrastructure as afunction of the cognitive processing demands. In thisreview, we propose that coherent neuronal oscillations(i.e. phase synchronized oscillatory activity, from now on:neuronal coherence) between local groups of neuronsis the basic ingredient to make neuronal communicationeffective and selective. In the following, we will rst outlinethe hypothesis of neuronal communication through neu-ronal coherence ( Fries, 2005) and survey its physiologicalevidence at a mechanistic level. We will then review studiesdemonstrating that neuronal coherence is modulated dur-ing cognitive processes in a variety of tasks. This evidenceshows that within sensory cortex, selective attention

enhances oscillatory activity among neurons processingattended sensory signals and reduces coherent activityamong neurons processing distracting information. Addi-tionally, for a fully attended sensory stimulus, the strengthof neuronal coherence within a local group of visual corti-cal neurons predicts the processing speed, or efficiency, of sensory changes in that stimulus. Within motor-relatedparietal and frontal cortical areas, coherent neuronal cou-pling is especially enhanced during the planning of move-ments and can selectively predict which movement typeand direction of movement will be selected.

2. Characteristics and functional implications of neuronalcoherence

During sensory stimulation, neurons in sensory cortexreceive a multitude of afferent inputs over short periodsof time, but only a subset of synaptic inputs will be effectiveand contribute to the generation of a postsynaptic spike.Elucidating the factors that determine which inputs areeffective in eliciting postsynaptic spiking within a localgroup of neurons is a critical rst step in understandinghow neurons interact effectively. Based on recent insightsinto the effects of high-frequency oscillatory input on spik-ing probability, the following will outline the possible

implications for effective neuronal communication.

2.1. The role of synchronization for spike generation

One important insight from intracellular recordings isthat the average pre-synaptic activity level frequently doesnot predict spiking activity of a postsynaptic (or receiv-ing) neuron. Increases in input rate can actually lead to

decreases in the size of individual excitatory postsynapticpotentials and to enhanced spike thresholds (see Fig. 1a)(Tsodyks and Markram, 1997; Wespatat et al., 2004 ).While this limits the role that the input rate can play in trig-gering postsynaptic spikes, the same studies highlighted therole of input synchronization. They found the absolutespike threshold reduced for rapid postsynaptic membranedepolarizations ( Ho and Destexhe, 2000 ). In an elegantset of experiments Azouz and Gray (2000, 2003) showedthat postsynaptic spiking is more likely when the mem-brane potential rises quickly immediately preceding a spike(Fig. 1b). Such rapid increases in membrane depolarizationcorrespond to a high temporal input density. On the side of the neurons generating these input, this corresponds to pre-cisely synchronized ring ( Azouz and Gray, 2000, 2003;Salinas and Sejnowski, 2000; Stuart and Hausser, 2001 ).Such precise synchronization is found as gamma-band(3090 Hz) synchronization in many studies (see below).

In addition to the described inuence of synchronizedinputs, spike generation is strongly modulated by excitabil-ity uctuations at the postsynaptic membranes, i.e. on theside of receiving neuronal groups ( Lampl et al., 1999).These uctuations are frequently oscillatory in natureand provide short periods of enhanced excitability occur-ring rhythmically as a function of the phase of the oscilla-

tion cycle (Traub et al., 2004; Whittington and Traub,2003). Various studies have shown that postsynaptic spiketimes are aligned to the phase of the oscillations, with thestrongest spiking output evident in the rising ank of depo-larization ( Burchell et al., 1998; Chrobak and Buzsaki,1998; Csicsvari et al., 2003; Pouille and Scanziani, 2001;Volgushev et al., 1998 ).

Taken together, the described impact of synchronousinputs and phase-dependent spiking provide complimen-tary effects for the generation of neuronal spiking output.Local groups of neurons are most sensitive to coincident,synchronized inputs and at excitability peaks of their oscil-lation cycles.

2.2. Neuronal communication through neuronal coherence

The described phase dependency of effective spike gener-ation could have widespread implications for the couplingbetween sending and receiving neuronal groups. In partic-ular, we argue that the oscillatory phase corresponding tothe excitability peaks during high-frequency oscillationswithin local neuronal groups serves as the time windowfor effective neuronal communication with other groupsof neurons ( Fries, 2005). Fig. 1c illustrates how inputs toa group of neurons arriving during these narrow time win-

dows around the excitability peaks of the oscillation cycle

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might be most effective in triggering a postsynaptic spikingresponse. In order to produce spike input that arrives atthose rhythmic excitability peaks, the neurons producingthose spikes will have to be active rhythmically and in

synchrony with their targets. In other words, phase-syn-chronization, or coherence, between a receiving and a send-ing neuronal group makes their neuronal communicationeffective.

In addition, neuronal coherence likely also renders neu-ronal communication selective. Neuronal groups that areactivated out of phase (or at variable phases) relative tothe oscillation in the receiving group, will have reducedimpact on the receiving neuronal group because they missthe epochs of excitability and more likely arrive duringmoments in which the receiving neurons are hyperpolarizedor undergo shunting ( Csicsvari et al., 2003). Moreover, thereduced inuence of non-coherent input will mutuallyaffect the sending group of neurons because it will itself receive less efficient feedback (cf. Fig. 1c). According tothe described scenario, coherent neuronal oscillationscould reect a general mechanism ensuring effective neuro-nal communication between selected subgroups of neurons.

2.3. Mechanistic characteristics of neuronal coherence

The outlined hypothesis of neuronal communicationthrough neuronal coherence ( Fries, 2005) targets particu-larly interactions among separate groups of neurons. How-ever most current knowledge is restricted to coherent

oscillations within local groups of neurons. Insights into

the local consequences of coherent activity agree with thehypothesized role of neuronal coherence for longer-rangeinteractions between groups of neurons. Moreover, theysuggest possible mechanisms in the generation of coherence

at the level of local groups of neurons.Complementing the intracellular work on the inputout-put relationship of neuronal activity reported above, com-putational studies show that already moderate amounts of input synchronization are capable of enhancing several-fold neuronal sensitivity and the gain of neuronal spikingresponses (Borgers et al., 2005; Galarreta and Hestrin,2001; Kopell et al., 2000; Salinas and Sejnowski, 2000,2001; Tiesinga et al., 2005; Tiesinga and Sejnowski, 2004;Whittington et al., 2000 ). In other words, even smallincreases in synchronization increase the impact of a giveninput, and small increases of stimulus strength can result inmultiplicatively scaled increases in spiking responses dur-ing coherent activity ( Tiesinga et al., 2005).

This effect of input synchronization on the gain of spik-ing activity appears particularly pronounced for oscillatorysynchronization in the gamma-frequency band ( Burchellet al., 1998; Csicsvari et al., 2003; Deans et al., 2001; Pent-tonen et al., 1998; Tiesinga et al., 2005 ). The gamma-fre-quency band is typically a signature of activated brainstates (Hoogenboom et al., 2005 ). Gamma-band uctua-tions have also been shown to occur spontaneously in theabsence of sensory stimulation, and as subthreshold mem-brane potential uctuations within local groups of neurons(Arieli et al., 1995; Ganguly et al., 2000; Gray and McCor-

mick, 1996; Jagadeesh et al., 1992; Lampl et al., 1999; Vida

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Fig. 1. Inuence of oscillations on spike generation and its hypothesized role on neuronal communication. (a) Spike threshold is plotted against theaverage subthreshold membrane potential in the 250 ms preceding the spike (adapted from Azouz and Gray, 2003 ). (b) Spike probability as a function of the slope of the membrane potential immediately preceding the spike (adapted from Azouz and Gray, 2000 ). (c) Hypothesized impact of neuronalcoherence on the communication between neuronal groups (A, B, and C). Spikes (vertical lines) are most likely at excitability peaks of the localeld potential (troughs of the oscillations). When excitability uctuations of a sending and a receiving neuronal group (groups A and B) arecoherent their spiking output will arrive within short windows and neuronal communication will be effective. When excitability uctuations of sendingand receiving groups of neurons are not coherent (groups A and C) spikes will miss excitability windows and communication between these groupsis prevented.

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et al., 2006). Recent evidence suggests that changes in theseongoing gamma-band uctuations exert subtle inuenceson the functional coupling of neuronal groups even beforesensory inputs activate a neuron ( Fries et al., 2001). In par-ticular, ongoing gamma-band oscillations of the local eldpotential synchronize neuronal response onset latencies to

a sensory stimulus within and across hemispheres in visualcortex (Fries et al., 2001). After stimulus onset, neuronsalign the onset of their spike response to the peak excita-bility of the ongoing gamma-band oscillations. Fig. 2 illus-trates this phase-dependent mechanistic coupling of spikingresponses and eld potential uctuations recorded in sepa-rate hemispheres ( Fries et al., 2001). The covariation of response latencies is particularly pronounced among neu-rons sharing tuning preferences for orientation and havingoverlapping receptive elds. These ndings suggest thatuctuations in the gamma-frequency band link neuronsto functional groups by latency covariations ( Fries et al.,2001; Samonds and Bonds, 2005 ). Such a mechanism isconsistent with the hypothesis that coherence establishesan effective communication structure. Latency covariationsphase-align neuronal activity and thus could ultimatelyspeed up the functional coupling among neurons inresponse to new sensory input.

Such a functional role of neuronal coherence is centralto the outlined hypothesis of neuronal communicationthrough neuronal coherence and should be particularlyevident during cognitive processes that demand selectiveneuronal interactions as during states of expectation, atten-tion, working memory, sensorymotor integration andplanning of actions. According to the delineated view, neu-

ronal coherence should selectively improve the signaling of those groups of neurons that process behaviorally relevantsensory input and trigger adaptive motor actions. The fol-lowing sections will survey recent empirical ndings fromneurophysiology that support this hypothesis.

3. Coherent oscillations and selective attention in visualcortex

Selective attention is the primary cognitive mechanismto exibly enhance the processing of behaviorally relevantsensory input at the expense of distracting input. The

dynamic attentional prioritizing of selected subsets of sen-sory information makes attentional paradigms an idealcandidate to investigate the mechanisms of effective neuro-nal communication. Common to selective attention para-digms is that neuronal responses are compared underidentical sensory stimulation while only the focus of atten-tion is varied across conditions. Based on this paradigm,neurophysiological studies consistently show that attendedvisual stimuli result in enhanced neuronal representationscompared to the representation of the same stimuli whenthey are unattended. Attentional modulation of neuronalactivity levels has been observed within all investigatedareas along the visual cortical processing pathway ( Rey-nolds and Chelazzi, 2004; Treue, 2001 ). However, selectivemodulation of neuronal synchronization during states of attention has only recently been demonstrated in monkeysensory cortices (Bichot et al., 2005; Fries et al., 2001;Steinmetz et al., 2000; Taylor et al., 2005; Womelsdorf et al., 2006) and by scalp recordings in human subjects(Bauer et al., in press; Debener et al., 2003; Fell et al.,2002; Gross et al., 2004; Gruber et al., 1999; Howardet al., 2003; Tallon-Baudry et al., 1997 ).

Consistent with the hypothesis outlined above, attentionmodulates not only the rate of spiking activity, butincreases neuronal synchronization in the gamma-

frequency band within local neuronal groups in visual areaV4. When monkeys are spatially cued to attend a movinggrating, neurons with receptive elds overlapping theattended stimulus show stronger coherence in thegamma-band than neurons with receptive elds overlap-

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Fig. 2. Ongoing gamma-band oscillations induce latency covariation to stimulus onsets in cat visual cortex (adapted from Fries et al., 2001). (a) OngoingLFP gamma-frequency oscillations around the onset of a visual stimulus in one hemisphere (top panel) predicts spiking latencies (bottom panel) in theopposite hemisphere. The traces show the average LFP and spiking responses for trials with falling (black) and rising (grey) LFP uctuations at the time of stimulus onset. (b) Rank correlation (upper panel) and signicance of the correlation (lower panel) between pre-stimulus cross-power spectra of the on-

going LFP and the latency covariation from 0 to 100 Hz. The upper horizontal line (lower panel) indicates signicance at the 1% level.



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ping a distractor stimulus ( Fries et al., 2001). In addition tothis effect of spatial selection, a recent study reports anenhancement of spike-eld coherence during feature-basedselection of visual stimuli (Bichot et al., 2005). Feature-based attention is known to enhance the ring rates of neurons in extrastriate visual cortex ( Hopf et al., 2005;

Martinez-Trujillo and Treue, 2004; Treue and MartinezTrujillo, 1999 ). Bichot and collegues ( Bichot et al., 2005)required monkeys to search for stimuli in a multi-stimulusdisplay, while they recorded at multiple sites in area V4spiking activity and local eld potentials. In different trials,monkeys had to search for a stimulus of a cued targetcolor, e.g. a red or blue stimulus, by shifting the gaze acrossthe display until they made a saccade to the target stimulus.During the visual search, the receptive elds of V4 neuronscould encompass stimuli with the target or the distractingfeature. Interestingly, spike-LFP coherence was found tobe enhanced for neurons preferring the target feature dur-ing times when the target stimulus was shifted in theirreceptive eld compared to distractor features in theirreceptive elds. Enhanced neuronal coherence occurredbefore the monkey actually found the target stimulus.Thus, attention modulated gamma-band synchronizationamong the selective subset of neurons sharing a preferencefor the target color and irrespective of the spatial positionof that stimulus.

This nding reveals a high selectivity of synchronizationof spiking activity with the eld potential. To our knowl-edge, feature-preference for color has not been demon-strated to be strictly retinotopically organized withinvisual area V4. Therefore, the observed synchronization

shows that a selective subset of widely distributed neuronsphase-lock their spiking activity with the eld potentials.This feature-based synchronization differs from space-basedsynchronization during spatial attention where coherenceis enhanced among neurons containing the target stimulusinside their receptive elds.

The observed effects of selective attention suggest thatenhanced neuronal coherence among a subset of neuronsindicates that they effectively communicate task-relevantinformation. In a strict sense, however, they do not providea direct link that enhanced synchronization is functionallyrelevant to predict task performance. Recent studies havebegun to provide such a link and suggest that trial-by-trialvariations of the strength of synchronization are predictiveof perceptual performance. Taylor and colleagues ( Tayloret al., 2005) report that oscillatory synchronization invisual cortex predicts successful performance in an atten-tional tracking task. In this study, local eld potentialswere recorded with epidural electrodes above visual areaV4 while monkeys tracked a continuously changing polyg-onal shape in order to detect a cued target shape. Thestrength of gamma-band synchronization was found tobe strongest in correct trials and lowest for trials in whichthe monkey responded to a distractor shape indicatingattention away from the receptive eld. Importantly, miss

trials in which the monkey did not respond to any shape

resulted in intermediate levels of synchronization, while tri-als in which the monkey made a false positive response to adistractor inside the receptive eld resulted in strongresponses indicating that attention was erroneously direc-ted inside the receptive eld when the cue required atten-tion outside the receptive eld ( Taylor et al., 2005 ).

This pattern of error-trial related responses shows thatgamma-band synchronization allows to predict where inthe visual eld attentional resources are allocated. In otherwords, gamma-band synchronization among neuronsindexes which sensory inputs are processed within visualcortex (Fries et al., 2002; Sederberg et al., 2003 ). Thesendings support the hypothesis of a central role of coher-ence for neuronal communication and efficient sensory pro-cessing, particularly of oscillatory synchronization in thegamma-frequency band.

4. Neuronal coherence and efficient sensorymotorintegration

In the previous section, coherence among local groupsof neurons was shown to reect the processing of task-rel-evant information compared to reduced coherence amongneurons encoding distracting information. This evidencehas been gathered in extra-striate sensory cortex withinthe ventral pathway, reecting an early processing stageof sensorymotor integration ( Bichot et al., 2005; Frieset al., 2001; Taylor et al., 2005; Womelsdorf et al., 2006 ).Recent studies suggest that coherent activity in these earlystages of sensorymotor integration is closely linked to aneffective transmission of information to later stages in cor-

tical processing concerned with the planning and selectionof movements. In the following, we survey this evidencecoming from visual cortex. We then extend the review todemonstrate the relevance of neuronal coherence duringthe planning and selection of task-specic movementswithin parietal and frontal cortices.

4.1. Enhanced gamma-band synchronization in sensorycortex reects efficient sensorymotor integration

Selective attention does not only enhance perceptualsensitivity, but also shortens reaction times to behaviorallyrelevant changes in the environment. The enhancement of coherent oscillations among neurons processing relevantstimuli described in the previous section is consistent withboth of these behavioral effects. However, this evidencedoes not yet demonstrate a direct inuence of coherenceon the speed of processing and hence on the efficiency of neuronal communication. In order to ll this gap, werecently analyzed the relation between oscillatory synchro-nization and the speed of detection of a sensory changewithin an attended visual stimulus ( Womelsdorf et al.,2006). We trained monkeys to attend to a stimulus pre-sented within the receptive elds of neurons recorded inarea V4 and to respond to a subtle color change of the

stimulus in order to obtain a juice reward. The relevant



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change event occurred at unpredictable times between 0.5and 5 s in the trial. Intriguingly, despite the random timesof the change, the degree of oscillatory synchronizationpredicted the speed of change detection already beforethe change event. Fig. 3 demonstrates that trial-by-trialuctuations of synchronization around the time of the

change can predict trial-by-trial variability of behavioralreaction times to the change. Notably, the average spikingresponse did not correlate with reaction times until afterthe change ( Fig. 3c). This nding suggests that enhancedlevels of coherence in the gamma-frequency band at thetime of the sensory change allow for more efficient signal-ing of the change among phase-coupled neurons and is thusinstrumental in subserving efficient sensorymotorintegration.

In addition to the predictive enhancement of neuronalcoherence before the sensory change, we observed thatafter the change, all measures of neuronal activity showedsignicant correlations with reaction time. Quantifying thedifference of gamma-band coherence in trials with the fast-est and slowest reaction times in a 75 ms window followingthe change showed an enhancement of 1020% for trialswith fast reaction times. Moreover, an analysis of the spik-ing response revealed that fast behavioral detection of thesensory change occurred on trials with short latencies of neuronal responses to the sensory change. This ndingagrees well with previous studies that reported a morerapid and steeper response onset of single neurons to

attended sensory events in trials with faster reaction timesin visual areas V4 and MT, and within the intra-parietalsulcus (Cook and Maunsell, 2002; Ghose and Maunsell,2002; Janssen and Shadlen, 2005 ). However, in those stud-ies, synchronization of neuronal activity was not assessed.

There might be a mechanistic link between our two obser-

vations that fast behavioral responses occur in trials inwhich the change event is (1) preceded by enhancedgamma-band activity and (2) followed by short neuronalresponse onset latencies. As noted above, stronger gamma-band synchronization at the time of stimulus onsetsshortens and synchronizes latencies of neurons within andacross hemispheres in visual cortex (cf. Fig. 2) (Fries et al.,2001). If the reported gamma-band related shortening andalignment of spikes to stimulus onsets is extended to stimu-lus changes, then the reported enhanced gamma-band syn-chronization at the time of a change could be instrumentalfor a the more rapid spiking response. According to this sce-nario, gamma-band synchronization directly improves thesignaling of behaviorally relevant changes to postsynaptictargets by means of latency shifted and temporally alignedspike response onsets.

It is of particular interest that the observed correlationsbetween behavior and neuronal activity were found invisual cortex. Recently, a non-invasive EEG study inhuman subjects reported enhanced gamma-band synchro-nization during a simple visuo-motor reaction time taskthat occurred in an epoch after a warning signal and prior

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Fig. 3. Gamma-band synchronization in visual area V4 predicts the speed of change detection. (a) Illustration of the task. Monkeys xated a cross anddirected attention to one of two moving gratings, one of which was inside and the other one outside the receptive eld (dashed black line) of the neuronsrecorded in area V4. The task required detecting a color change of the attended grating occurring at a random time during the trial while ignoring changesof the unattended grating. (b) Correlation of neuronal activity and reaction times around the time of the color change (time 0 ms) in trials with attentioninside the receptive eld. Shown are the Z-scores of correlation coefficients of reaction time with LFP power (upper panel), spike-LFP coherence (middlepanel), and multi-unit ring rate (lower panel). (c) Firing rate (convoluted with a Gaussian kernel with a standard deviation of 10 ms) around the time of the color change for the 25% of trials with the fastest reaction time to the change (red lines) and for the 25% trials with the slowest reaction times (blue line)

(adapted from Womelsdorf et al., 2006 ).



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to the response ( Gonzalez Andino et al., 2005 ). In contrastto the reported effects in visual cortex, this study reportedenhanced synchronization in a fronto-parietal networkknown to be more closely linked to the control of attentionand movement plans.

Taken together, the provided link between enhanced

gamma-band synchronization and the speed of changedetection suggests that neuronal coherence in visual cortexhas direct effects on visually triggered behavior and thusreects an early correlate of efficient visuo-motor integra-tion. While these ndings have begun to demonstrate thatcoherence in local groups of neurons in visual cortex hasfunctional consequences on behavior, the existing evidencedoes not yet show that distant groups in sensory and motorcortex are functionally linked by coherence. This hypothe-sis of a long-range coupling of task-relevant neuronalgroups still awaits to be tested empirically.

4.2. Precise synchronization underlying movementselection within frontal and parietal areas

As noted above, recent human EEG evidence demon-strated a functional role of gamma-band activity withinfrontal and parietal regions, known to form a networknot only to control the focus of attention, but also to con-trol the selection of action ( Gonzalez Andino et al., 2005 ).This nding complements various neurophysiological stud-ies that begin to delineate the task-specicity of neuronalcoherence during attention, working memory and the plan-ning and selection of actions within parietal and frontal

cortex.Neuronal activity in parietal cortex is frequently associ-ated with higher order cognitive functions involving thegeneration of movement intention, attentional control, deci-sion making and working memory ( Andersen and Buneo,2002; Gottlieb and Goldberg, 1999; Gottlieb et al., 1998;Janssen and Shadlen, 2005 ). However, only few studieshave investigated the role of coherence among parietalgroups of neurons during these processes.

Within intraparietal cortical area LIP, the degree of gamma-band coherence has been shown to indicate the tar-get location of an eye movement in a delayed saccade task(Pesaran et al., 2002 ). Scherberger and collegues ( Scherber-ger et al., 2005) extended this nding to the parietal reachregion and reaching movements of the arm. These authorsrecently showed that gamma-band coherence between spik-ing responses and local eld potentials can be used to effec-tively decode the direction of arm-movements in a delayedpointing task involving eight possible reaching positions(Scherberger et al., 2005 ). These results show that localoscillatory coupling predicts the movement direction thatwill be selected as the target movement. Coherence also dis-sociated the type of movement that was selected. Whilereaches are predicted by neuronal coherence in the parietalreach region, saccadic movements were not well predicted

in this region, but rather are decoded by synchronized neu-

ronal groups in area LIP ( Pesaran et al., 2002; Scherbergeret al., 2005).

Common to the described studies is the enhancement of neuronal coherence in area LIP and the parietal reachregion during a delay period in which not only a movementdirection is planned and maintained in working memory,

but which also involves the allocation of spatial attentiontowards the target location of the movement ( Pesaranet al., 2002; Scherberger et al., 2005). Previous studies haveshown that the neuronal activity related to the planning, orintention to move and activity related to spatial attentionare closely intermingled within parietal groups of neurons(Andersen and Buneo, 2002; Gottlieb et al., 1998 ). It istherefore intriguing to speculate that phase-coupling of activity in separable subsets of neurons in parietal cortexmay provide a substrate of attentional and intentionalprocessing.

Such a spatial dissociation of attention- and intention-related gamma-band synchronization has recently beenshown within frontal cortex during intracranial EEGrecordings in a human subject ( Brovelli et al., 2005). In thisstudy, attentional and intentional processing aspects wereseparated in time by two successive cueing intervals. An ini-tial attentional cue directed the subjects spatial attention toa position at which, after a delay, an instructional cue for amovement appeared. During performance of this task,enhanced gamma-band synchronization related to atten-tion and motor intention was found at separable sites withinpre-motor and cingulate cortex ( Brovelli et al., 2005).

Neurophysiological recordings in the awake and behav-ing animal begin to relate oscillatory synchronization

within frontal and pre-frontal cortex to selective cognitiveprocesses during action selection in a variety of further taskcontexts. In pre-frontal cortex, the degree of synchroniza-tion has been reported to correlate with reaction times dur-ing the expectation of a behaviorally relevant targetstimulus in a pattern discrimination task ( Liang et al.,2002). Neurons within the supplementary motor cortexsynchronize with local eld oscillations specically duringthe selection of complex sequences of arm and hand move-ments (Lee, 2004, 2003; Sanes and Donoghue, 1993 ).Within pre-motor and motor cortex, neurons synchronizetheir activities specically at times during a trial when themonkeys expect a visual instruction signal that triggers apre-specied movement, as well as during the initiation of a movement ( Aoki et al., 1999; Baker et al., 2001; Cram-mond and Kalaska, 2000; Donoghue et al., 1998; Laubachet al., 2000; Mehring et al., 2003; Ohara et al., 2001; Rick-ert et al., 2005; Riehle, 2005; Riehle et al., 2000; Sanes andDonoghue, 1993 ). In particular, enhanced synchronizationis found around times of an expected Go-signal, still in theabsence of the actual movement execution. In a set of stud-ies, Riehle and collegues (Grammont and Riehle, 2003;Riehle et al., 2000) investigated the inuence of informa-tion about movements in pre-motor, motor, and somato-sensory cortex during a preparatory period and before

the monkey executed the movement. The authors found



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that synchronization among single neurons predicts reac-tion times and the direction of the movement but did rarelyindicate its force or velocity ( Grammont and Riehle, 2003;Riehle et al., 2000) see also (Hatsopoulos et al., 1998 ).

Of particular interest is the observation that spike syn-chronization became more precise during the trial, i.e. with

increasing probability and expectancy of target occurrence(Grammont and Riehle, 2003; Riehle et al., 2000 ). A simi-lar increase of neuronal synchronization was observed byLee in the supplemental motor cortex in trials with delayedtarget stimulus onsets during a visuo-motor reaching task(Lee, 2003). The transient increase of neuronal coherenceconcomitant to the subjects certainty of target occurrencestrongly suggests its functional relevance for the selectionand preparation of a motor plan.

However, from these ndings in motor-related frontalareas, it remains unclear whether coherence between dis-tant areas occurs and is functionally relevant.

Recently, Schoffelen et al. (2005) provided evidence thatcloses this gap and which strongly suggests a functionalrole of long-range cortico-spinal coherence. In this study,cortical MEG was recorded together with EMG (indexingspinal alpha-motor-neuron activity) in human subjectswhile they were required to keep the right wrist extendeduntil a Go-signal occurred. The time of the Go-signal dur-ing the course of the trial was systematically varied acrossblocks of trials. This Go-signal probability, i.e. the hazardrate, was either a decreasing or increasing function of thetime in the trial. Subjects learned this hazard rate implic-itely and modulated their readiness to respond accordingly,as evidenced by shortened reaction times when the go-cue

occurred during high hazard rates. Interestingly, gamma-band coherence between motor cortex and spinal cordwas modulated dynamically in close relation to the hazardrate. In particular, gamma-band coherence increased withincreasing probability of target occurrence and shorterreaction times, while decreasing target probability andslower reaction times were accompanied by decreasing cor-tico-spinal coherence ( Schoffelen et al., 2005). Analysis of the spectral pattern of the relative phase of the observedcortico-spinal gamma-band coherence indicated thatgamma oscillations in motor cortex drove the spinalgamma-band oscillations. These results are among fewstudies suggesting a critical role of phase coherence amongdistant neuronal groups for effective neuronal communica-tion (Gross et al., 2004; Hummel and Gerloff, 2005; Roseand Buchel, 2005; von Stein et al., 2000 ).

5. Perspectives and conclusion

This review surveyed existing evidence suggesting thatoscillatory synchronization subserves a pivotal role inestablishing a communication structure that allows effec-tive transmission of task-relevant information within andacross selective subsets of neuronal groups. The outlinedconcept is grounded in the mechanistic principles of spike

generation recently elucidated by in vitro and in vivo intra-

cellular recordings. Postsynaptic membranes are particu-larly sensitive to synchronous inputs ( Azouz and Gray,2003), and during the excitability peaks of oscillatory mem-brane potential uctuations ( Burchell et al., 1998; Volgu-shev et al., 1998). We argue that these characteristicsessentially provide short time-windows for effective com-

munication and could selectively establish a functional cou-pling among sending and receiving neuronal groups byneuronal coherence ( Fries, 2005).

We derived the functional relevance of communicationthrough coherence from neurophysiological recordingsduring selective attentional processing and sensorymotorintegration. Consistent with predictions of the hypothesis,coherent oscillatory activity has been observed duringstates of enhanced expectation, selective attention, workingmemory, motor preparation, and action selection. Addi-tionally, the strength of coherent neuronal coupling cov-aries with and predicts the speed of visual detection, thecertainty of subjects to expect a behaviorally relevant stim-ulus, and the readiness to initiate a motor response. Com-mon to these many aspects of cognitive functioning is therequirement to dynamically regulate the information owon a short time scale among selective subsets of neurons.

An intriguing aspect of the cognitive modulation of neu-ronal coherence in the different experimental paradigmssurveyed in this article is its frequency specicity. The spec-tral signature of coherence most often entailed uctuationsin the gamma-frequency band. This implication of localgamma-band oscillation in dynamic neuronal communica-tion corresponds well to intracellular and computationalwork suggesting a particular efficiency and feature selectiv-

ity of spike generation in this frequency band ( Azouz andGray, 2003; Bo rgers et al., 2005; Fries et al., 2001; Tiesingaet al., 2005). Intriguingly, the cycle length of gamma-banductuations (1030 ms) has not only been implicated in thedynamic aspects of cognitive functioning. In addition, thesame cycle length plays a critical role in neuronal plasticityand hence in long term shaping of synaptic connectionstrength ( McBain and Fisahn, 2001; Paulsen and Sejnow-ski, 2000; Sjostrom et al., 2002). With the period of gammacycles, the relative order of pre- and postsynaptic spikingdetermines whether synaptic connectivity is strengthened(LTP) or weakend (LTD) ( Bi and Poo, 1998; Goldinget al., 2002; Huerta and Lisman, 1995; Lengyel et al.,2005; Magee and Johnston, 2005; Salazar et al., 2004a,b;Sederberg et al., 2003 ). However, whether neuronal coher-ence in the gamma-band during ongoing rapid neuronalinteractions is related to the shaping of neuronal connectiv-ity is far from understood and will be interesting to be seenin future studies.

In addition to the gamma-frequency band, other spec-tral signatures have recently been implicated in cognitiveprocesses. A particular role in functional interactionsamong distant groups of neurons has been assigned totheta frequency oscillations ( Kahana, 2006; Sarntheinet al., 1998; Siapas et al., 2005). Recently, Siapas and col-

legues (Siapas et al., 2005) investigated hippocampal and



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pre-frontal activity in rats during a spatial navigation task.Intriguingly, the authors report that spiking activity in pre-frontal cortex is phase-locked to the theta rhythm of thelocal eld potential in the hippocampus, despite theabsence of theta oscillations in the pre-frontal cortex. Con-sistent with the outlined communication through coherence

hypothesis, the phase-locking occurred task specic andcould thus reect a dynamic gating mechanism for an effec-tive interaction among distant groups of neurons ( Buzsaki,2005; Fries, 2005; Jensen, 2005). Moreover, theta- andgamma-band oscillations have been shown to frequentlyco-occur such that gamma-band oscillations are nested atparticular phases of an underlying theta rhythm (e.g. Chro-bak and Buzsaki, 1998 ). Whether such cross-frequencyinteractions reect a functional correlate of cognitive pro-cesses is an intriguing prospect for future studies and hasonly recently begun to be empirically tested ( Palva et al.,2005; Sederberg et al., 2003).

The reviewed data suggest that coherence is exploited bythe nervous system to regulate information transfer. How-ever, the available evidence is predominantly correlationalin nature. Only few experiments have succeeded to manip-ulate the degree of synchronization and to investigate moredirectly the inuence of potentiated or suppressed synchro-nization on cognitive function ( Ishikane et al., 2005; Rodri-guez et al., 2004; Stopfer et al., 1997). This endeavor couldprove promising when testing the generality of coherencefor effective communication in the nervous system andalready suggests its relevance for ne sensory discrimina-tions and adaptive selection of movements ( Ishikaneet al., 2005; Stopfer et al., 1997).

We proposed that effective neuronal communicationrelies mechanistically on neuronal coherence within as wellas across functionally linked groups of neurons. This con-cept is distinct from the hypothesis that synchronizationamong neurons provides a tag to link neurons representingparts of the same perceptual object ( Singer, 1999). Whilesuch binding by synchrony focuses on a representationalrole of neuronal synchronization, the hypothesis outlinedhere stresses the mechanistic implications of neuronal syn-chronization to establish effective neuronal communica-tion. Despite this conceptual distinctness, both approachesare fully compatible with each other: We reviewed evidencethat enhanced neuronal coherence not only increases theeffective coupling among neuronal groups but that thiscoupling is highly selective for neuronal groups processingtask-relevant information. When such task-relevant infor-mation affects distributed neuronal populations respondingto different features of a visual object, then enhanced neu-ronal communication entails feature binding as hypothe-sized by the binding-by-synchrony hypothesis.

The majority of the surveyed studies provided evidencefor the relevance of coherence of neuronal groups withincortical areas during attention and sensorymotor integra-tion. Few studies have explicitly analyzed long-rangecoherence and inter-areal interaction. However, among

those studies, results point unequivocally to the relevance

of long-range coherence for neuronal communication dur-ing as diverse cognitive contexts as perceptual shape dis-crimination, working memory, and speeded reaction timetasks (Bernasconi et al., 2000; Bressler et al., 1993; Oharaet al., 2001; Rodriguez et al., 1999; Roelfsema et al.,1997; Sarnthein et al., 1998; Schoffelen et al., 2005; Tal-

lon-Baudry, 2003; Tallon-Baudry and Bertrand, 1999;von Stein et al., 2000). According to the outlined hypothe-sis, future studies will benet from extending their analysisto investigate the exible nature of coherent couplingacross distant cortical areas. Progress with simultaneousrecording of neuronal activity at multiple cortical sitesbecomes more and more likely with recent developmentsof new recording and analysis techniques ( Buzsaki, 2004;Musallam et al., 2004; Nicolelis et al., 2003; Scherbergeret al., 2003). With the advent of these techniques, rapidprogress in the eld will further elucidate the basic mecha-nisms of dynamic neuronal communication that ultimatelyunderlies our remarkable cognitive exibility.

Acknowledgements

This research was supported by The Human FrontierScience Program Organization, grant RGP0070/2003 (P.F.),and by The Netherlands Organization for Scientic Re-search, grant 452-03-344 (P.F.), and the Volkswagen Foun-dation Grant I/79876 (P.F.).

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Neuronal Coherence