Paper Available: Dynamic Model of Visual Cortex

[rao@cs.rochester.edu]

Dynamic Model of Visual Memory Predicts Neural Response Properties 
                        In The Visual Cortex 

                 Rajesh P.N. Rao and Dana H. Ballard
         	   Department of Computer Science
		      University of Rochester
                    Rochester, NY 14627-0226, USA

  			Technical Report 95.4 
National Resource Laboratory for the study of Brain and Behavior
                         (November 1995)

               		     Abstract

Recent neurophysiological experiments have shown that the responses of
visual cortical neurons in a monkey freely viewing a natural scene can
differ substantially from those obtained when the same image
subregions are flashed while the monkey performs a fixation task.
Neurophysiological research in the past has been based predominantly
on cell recordings obtained during fixation tasks, under the
assumption that this data would be useful in predicting the responses
in more general situations. It is thus important to understand the
differences revealed by the new findings and their relevance to the
study of visual perception.  We describe a computational model of
visual memory which dynamically combines input-driven bottom-up
signals with expectation-driven top-down signals to achieve optimal
estimation of current state by using a Kalman filter-based framework.
Computer simulations of the proposed model are shown to correlate
closely with the reported neurophysiological observations in both
free-viewing and fixating conditions.  The model posits a role for the
hierarchical structure of the visual cortex and its reciprocal
connections between adjoining visual areas in determining the response
properties of visual cortical neurons.

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Retrieval information:

FTP-host:	ftp.cs.rochester.edu
FTP-pathname:	/pub/u/rao/papers/dynmem.ps.Z
URL:		ftp://ftp.cs.rochester.edu/pub/u/rao/papers/dynmem.ps.Z

10 pages; 309K compressed, 646K uncompressed

e-mail: rao at cs.rochester.edu

Hardcopies available upon request at the above address or from the
first author at NIPS*95.
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