Neuronal Synchrony As A Binding Mechanism Research Paper

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Neuronal systems have to solve immensely complex combinatorial problems and require efficient binding mechanisms in order to generate representations of perceptual objects and movements. In the context of cognitive functions, combinatorial problems arise from the fact that perceptual objects are defined by a unique constellation of features, the diversity of possible constellations being virtually unlimited. Combinatorial problems of similar magnitude have to be solved for the acquisition and execution of motor acts. Although the elementary components of motor acts—the movements of individual muscle fibres—are limited in number, the spatial and temporal diversity of movements that can be composed by combining the elementary components in ever-changing constellations is again virtually infinite. In order to establish neuronal representations of perceptual objects and movements the manifold relations among elementary sensory features and movement components have to be encoded in neural responses. This requires binding mechanisms that can cope efficiently with combinatorial complexity. Evolved brains have acquired an extraordinary competence to solve such combinatorial problems and it appears that this competence is a result of the evolution of the cerebral cortex.

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1. Two Complementary Binding Strategies

In the primary visual cortex of mammals, relations among the responses of retinal ganglion cells are evaluated and represented by having the output of selected arrays of ganglion cells converge in diverse combinations onto individual cortical neurons. Distributed signals are bound together by selective convergence of feed forward connections (Hubel and Wiesel 1962). Through iteration of this strategy neurons in higher cortical areas acquire increasingly sophisticated response properties, representing complex constellations of features and, in the special case of faces, even whole perceptual objects (Gross 1992, Tanaka 1997).

However, this strategy—of binding features together by recombining input connections in ever-changing variations and representing relations explicitly by responses of specialized binding cells— results in a combinatorial explosion of the number of required binding units. This problem is further accentuated by the fact that perceptual objects are often defined by conjunctions of features encoded in different sensory systems; they have specific visual, haptic, or acoustic properties. Moreover, if binding is achieved solely by the formation of conjunctionspecific neurons, difficulties arise if novel objects with unfamiliar feature constellations need to be represented. It has been proposed, therefore, that the cerebral cortex uses a second, complementary strategy, which permits utilization of the same neurons for the representation of different objects (Hebb 1949). Here, the particular constellation of features characterizing perceptual objects is thought to be represented by the joint and coordinated activity of a dynamically associated ensemble of cells, whereby each of the participating neurons represents explicitly only one of the elementary features that characterize a particular perceptual object. Different objects can then be represented by recombining in various constellations neurons tuned to elementary features, whereby a particular cell can participate at different times in different assemblies. This sharing of neurons economizes on neuron numbers and copes effectively with the huge combinatorial space occupied by real-world objects.

For assembly coding two constraints need to be met, however. First, a selection mechanism is required that permits dynamic, context-dependent association of neurons into distinct, functionally coherent assemblies. Second, grouped responses must get labeled so that they can be distinguished by subsequent processing stages as components of one coherent representation and do not get confounded with other unrelated responses.

Such labeling can be achieved by jointly raising the saliency of the selected neurons, because this ensures that they are processed and evaluated together at the subsequent processing stage. Neuronal systems have three options to increase the relative saliency of selected responses: first, non-grouped responses can be inhibited; second, the amplitude of the selected responses can be enhanced; and third, the selected cells can be made to discharge in precise temporal synchrony. Inhibition simply eliminates potentially confounding signals, while enhanced firing raises the impact of the grouped responses through temporal summation and synchronization through spatial summation of synaptic potentials (Singer 1999). Selection of responses by enhancing discharge rates is common in attentional gating (Luck et al. 1997) but it has certain disadvantages when used as the only mechanism for the distinction of assemblies (von der Malsburg 1981, Singer 1999). Discharge rates of feature selective cells can vary over a wide range when stimuli change and since these modulations of response amplitude would not be distinguishable from those signaling membership of a cell in an assembly, ambiguities could arise. Problems could also arise when simultaneous maintenance of different assemblies is required at the same processing stage. This may be the case when different objects and their relations to one another need to be represented simultaneously. If the corresponding assemblies were defined solely by the increasing discharge rate of their member neurons it would be impossible to distinguish which of the enhanced responses belonged to which assembly.

These ambiguities can be overcome if the selection and labeling of responses is achieved through synchronization because it can be adjusted independently of rate fluctuations, and relations between responses can be defined with very high temporal resolution. Synchronization enhances only the saliency of those discharges that are precisely synchronized and generate coincident synaptic potentials in target cells at the subsequent processing stage. Hence the selected event is the individual spike or a brief burst of spikes. Thus, different relations can be defined on short timescales and hence different assemblies can alternate with one another at fast rate within the same neuronal network without getting confounded. The rate at which assemblies can be multiplexed is limited only by the duration of the interval over which synaptic potentials are integrated. If this interval is in the range of 10 to 15 ms, different assemblies can alternate with a frequency up to 40 Hz and hence several different feature constellations can be corepresented within perceptually relevant time windows.

2. Synchrony As A Signature Of Relatedness

The discharges of neurons in the cerebral cortex reflect with great precision the temporal structure of stimuli. Synchronously presented stimuli evoke synchronous responses. This makes it possible to examine with psychophysical experiments whether synchronized responses are indeed interpreted as a signature of relatedness. The results indicate that the synchronous responses evoked by simultaneously presented stimuli are indeed bound perceptually and get segregated from the temporally offset responses evoked by asynchronously presented pattern elements. In the visual system the temporal resolution with which synchronous responses can be segregated from temporally offset responses is considerably better than 10 ms (for review see Singer 1999). This indicates that precise temporal relations among the discharges of distributed neurons are exploited for perceptual grouping and that offset intervals are resolved that are considerably shorter than those that can be consciously perceived.

In the mid-1980s it was discovered that neurons distributed across the visual cortex synchronize their responses when responding to a single visual object (Gray and Singer 1987, 1989). This synchronization was found to be due to dynamic interactions among reciprocally-coupled cortical neurons. It was often associated with rhythmic firing in the frequency range of 40 Hz—the so-called gamma frequency band—and was as precise as the synchrony induced by external, temporally modulated stimuli. Based on the theoretical considerations exposed above it had been proposed that this internal synchronization could serve to select and bind responses in all those cases where selection and binding by rate enhancement might lead to ambiguity. Since then numerous experiments have been performed in order to test predictions derived from this hypothesis (for review see Singer 1999). In particular, evidence needed to be obtained that response synchronization is not simply an epiphenomenon of neuronal operations but does have a function in sensory and motor processing. This requires demonstration that (a) synchronous activity has a stronger impact in target structures than nonsynchronous activity, (b) synchrony can be established and changed sufficiently rapidly to be compatible with processing speed, and (c) synchronization patterns are related closely to cognitive processes requiring dynamic selection and binding of responses. Such is the case for feature binding and perceptual grouping, for response selection by attention, for the establishment of novel conjunctions between stimuli or between stimuli and responses in learning paradigms, and for the coordination of complex movements.

3. Rapid Synchronization

Both simulation studies with spiking neurons and recordings from the brain revealed that networks can undergo very rapid transitions from uncorrelated to synchronized states (e.g., Gerstner 1996). One factor contributing to very rapid synchronization is the coordinated fluctuations of neuronal excitability. Evidence from the visual cortex indicates that ongoing activity is not random but exhibits correlated fluctuations. Cortical neurons with colinearly aligned receptive fields tend to engage in coherent excitability fluctuations due to strong reciprocal coupling. These fluctuations act like a dynamic filter and cause a virtually instantaneous synchronization of the very first discharges of responses (Fries et al. 2001a). The spatio-temporal patterns of these spontaneous fluctuations of excitability reflect the architecture and the actual functional state of the intracortical association connections which mediate the reciprocal interactions among distributed cortical neurons and are held responsible for the grouping and binding of responses. Spontaneous activity can thus be considered as the reflection of a continuous readout of the grouping criteria that reside in the functional architecture of cortical connections. Because of this anticipatory patterning, grouping by synchronization can be extremely fast and occur as a function of both the prewired associational dispositions and the current functional state of the cortical network.

4. Relation To Perception

Stimulus-induced synchronization does not simply reflect anatomical connectivity but depends critically on the configuration of the stimuli. It is the result of a dynamic and context-dependent self-organization process that follows, so far without exception, the Gestalt rules that govern perceptual grouping. In the visual domain this has been shown for the criteria of continuity, proximity, similarity in the orientation domain, colinearity, and common fate (Gray et al. 1989, Castelo-Branco et al. 2000).

Most of the early experiments on response synchronization were performed in anesthetized animals but more recent evidence indicates that internally generated synchrony is even more pronounced in the awake brain, exhibiting similar sensitivity to context (Kreiter and Singer 1996), and becoming particularly precise when the EEG is desynchronized (Munk et al. 1996) and the animals are attentive (Roelfsema et al. 1997, Steinmetz et al. 2000, Fries et al. 2001b).

Direct relations between response synchronization and perception have been found in cats that suffered from strabismic amblyopia, a developmental impairment of vision associated with suppression of the amblyopic eye, reduced visual acuity and disturbed perceptual grouping in this eye. Quite unexpectedly, the discharge rates of individual neurons in the primary visual cortex fail to reflect these deficits (see Roelfsema et al. 1994 for references). The only significant correlate of amblyopia at the level of the primary visual cortex is the drastically reduced ability of neurons driven by the amblyopic eye to synchronize their responses (Roelfsema et al. 1994), and this accounts well for the perceptual deficits: reduced synchronization leads to reduced saliency of responses, and this could explain the suppression of signals from the amblyopic eye. If synchronization has a function in response selection and binding, disturbed synchronization could explain the reduced visual acuity and the impaired figure-ground segregation in amblyopic vision.

Another close correlation between response synchronization and perception has been found in experiments on binocular rivalry (Fries et al. 1997). A highly significant correlation existed between changes in the strength of response synchronization in primary visual cortex and the outcome of rivalry. Responses to stimulation of the eye that won in interocular competition that were perceived by the animal increased their synchronicity upon presentation of the rival stimulus to the other, losing eye, while the reverse was true for cells driven by the eye that became suppressed. Interestingly, however, there were no rivalry-related changes in the response amplitudes of the neurons.

These results support the hypothesis that precise temporal relations between the discharges of spatially distributed neurons play a role in cortical processing and that synchronization may be exploited to jointly raise the saliency of the responses selected for further processing, i.e., for the dynamic binding of distributed responses.

The example of rivalry also illustrates how synchronization and rate modulation depend on each other. The signals from the suppressed eye failed to induce tracking eye movements and were not perceived by the animal, suggesting that the vigorous but poorly synchronized responses in primary visual areas eventually failed to drive the neurons responsible for the execution of eye movements. Direct evidence for a loss of neuronal responses in higher cortical areas to stimuli presented to the suppressed eye has been obtained in awake monkeys (Leopold and Logothetis 1996). Thus, changes of synchronicity result in changes of response amplitudes at subsequent processing stages. This convertibility provides the option to use both coding strategies in parallel in order to encode complementary information.

5. Epilogue

The discovery of stimulus-induced response synchronization and the proposal that synchronization might serve as a neuronal code for the definition of relations have solicited highly controversial debates in the scientific community. Most of the arguments raised in this context have been summarized recently in a series of reviews that have been published in the journal Neuron (1999, Vol. 24, pp. 7–125). These contributions focus on the putative role of synchronization in visual perception, as does this research paper. However, evidence has been obtained that response synchronization is an ubiquitous phenomenon not only in the cerebral cortex and its many subdivisions but also in the nervous systems of invertebrates. As in the visual cortex these synchronization phenomena are often associated with an oscillatory modulation of the underlying discharge patterns, whereby the oscillation frequencies tend to concentrate in the beta and gamma-frequency band (20–60 Hz). Due to effective summation of currents associated with synchronous activity, the episodes of response synchronization can be detected with non-invasive recording techniques such as electroencephalography (EEG) and magneto encephalography (MEG). Following the demonstration of stimulus and task-dependent synchronous oscillations in the visual system, numerous EEG and MEG studies have been performed on human subjects, in search of correlations between the occurrence of response synchronization on the one hand and cognitive or executive functions on the other. The results of these studies are compatible with the view that an oscillatory patterning of neuronal activity in the beta-and gamma-frequency band and the synchronization of this oscillatory activity are associated with a wide diversity of higher brain functions, such as perceptual grouping, object recognition, short-term memory, associative learning, selective attention, and calibration of motor functions (for review see Tallon-Baudry and Bertrand 1999, Singer 1999).

Likewise, close relations have been found between patterns of response synchronization and cognitive functions in the insect olfactory system (reviewed in Singer 1999). Apart from the investigations in insects, most of the evidence for a functional role of synchronization is still correlative in nature because it is difficult to selectively interfere with synchronization without affecting other response variables. It is undeniable, however, that the new approach—to register neuronal activity simultaneously from different sites and to search for temporal relations among the activity of distributed neuronal populations, rather than measuring only the rate variations of individual cells— provides new and fascinating insights into the dynamics of neuronal processes. In a number of investigated paradigms, changes in temporal correlations among distributed neuronal responses turned out to be a better predictor of stimulus configurations, of attentional states and of the outcome of a perceptual process than the rate changes of individual neurons. This suggests that the nervous system exploits the option to encode information in the precise temporal relations between responses of distributed neurons. It is highly likely that massive parallel recording from large numbers of neurons will reveal synchronization to be merely a special and rather simple state in a highly complex state space, and it is one of the challenges for systems physiology to decipher the alphabet of these temporal codes.


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