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Abstract:
(Contributed Talk)
Part binding is one of the various types of binding in
cognitive psychology where the parts of an object must be
segregated from the background, and bound together. In noisy
environments there is more then one solution to the part binding
problem, yet the brain chooses one such solution based on the
relations among the parts. One model of the situation may consist
of binding of the representation of some primitive parts of an
image to create a composite object. Expecting to see a specific
object may effect which parts will be bound. A synfire chain is a
feed forward excitatory network consisting of a large number of
pools. Synfire chain models may account for the representation of
composite objects by dynamic binding (synchronization of activity
waves) among such chains. Using synfire chains for part binding
calls for some binding sensitive inhibitory mechanism which
controls the total amount of synchronization in the network. Most
known solutions assume some specific inhibitory connections which
are not biologically plausible. To control the synchronization
level we introduce a synfire chain with excitatory as well as
inhibitory neurons within the pools. We study the main properties
of this control mechanism with simple models. Using this control
mechanism we solve a simple part binding problem and the effect
of priming using a neural network simulation and a theoretical
model.
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