A Unified Self-organizing Model of the Primary Visual Cortex

How do cells in the primary visual cortex process visual input? This has been perhaps one of the most intensely explored questions in vision research, psychology and neuroscience in the last two decades. To answer the question, it is necessary to understand and model how cells learn to pick out features of the visual image, group features together and interpret them.

Some of the elementary feature detecting properties of the visual cortex are orientation selectivity and ocular dominance. During visual perception, activities of such cells are grouped by long range lateral interconnections between the feature detecting cells. Our research aims to build a computational model of the visual cortex in which both the feature detectors and the lateral connections develop by a single fundamental self-organizing process to form the basic neural substrate for visual perception. The virtual posters below walks you through some of our research efforts in that direction.

Ocular Dominance and Patterned Lateral Connectivity in a Unified Self-organizing Model of the Primary Visual Cortex


This research is supported in part by National Science Foundation under grant #IRI9309273. Computer time for the simulations was provided by the Pittsburgh Supercomputing Center (PSC) under grants #IRI930005P and #TRA940029P. We also thank Dr. Nigel Goddard and Dr. Gary Beckwith for assistance with the computing resources at PSC.

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