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Deconstructing Synchrony (Invited Talk)

 J. Anthony Movshon
  
 

Abstract:
In the early stages of visual processing, objects and scenes are represented by neurons with small visual receptive fields. Each neuron provides information about local features of a scene, but to describe a scene in terms of objects requires that these features be combined. Objects can cover wide areas of visual space and be partially occluded by other objects, so the problem of binding the separate representations of parts into coherent wholes is not a simple one. Some theorists have advanced the view that binding is a special problem and requires a special solution because it is necessary to "tag" each visual neuron to signify the object to which its activity relates. Each neuron therefore has to carry two distinct signals, one that indicates how effective a stimulus is falling on its receptive field, and a second that tags it as a member of a particular cell assembly. To make these signals distinct, von der Malsburg proposed that the "effectivenes" signal would be carried by a conventional rate code, while the "tag" signal would be created by synchronizing the spike activity of the neuron with spikes from other neurons in the same assembly. First, I will consider whether the theory is an a priori reasonable approach to solving the binding problem, and conclude that it is at best incomplete. Next, I will ask whether spike synchrony can plausibly be used as an informational code, and conclude that there are significant practical and theoretical obstacles both to encoding and to decoding information in this way. I will examine the experimental evidence usually adduced to support the synchrony hypothesis, and conclude that the evidence is largely indirect and has no proven relevance to the issue of binding per se. I will finish by asking whether the binding problem is truly of unique difficulty and requires a unique solution, and by considering some strategies for solving the binding problem that do not require the creation of a special neural code.

 
 


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