1:00pm Friday, 4 February 2005:

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Bayesian inference in cortical circuits
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Alexandre Pouget<BR>
Department of Brain and Cognitive Sciences<BR>
University of Rochester
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Recent psychophysical experiments indicate that humans use approximate 
Bayesian inference in a wide variety of tasks, ranging from cue integration 
to decision making to motor control. This implies that neurons both 
represent probability distributions and combine those distributions 
according to a close approximation to Bayes rule. We will demonstrate how 
such Bayesian inference can be implemented in the dynamics of recurrent 
analog circuits using cue integration as an example. We will also present 
recent recordings showing that the receptive field of multisensory neurons 
in area VIP are consistent with the predictions of our model. We will end 
by discussing our recent attempt to generalize this approach to network of 
spiking neurons.