Departmental Papers (ESE)


In this paper, a new model seeking to emulate the way the visual cortex processes information and interacts with subcortical areas to produce higher level brain functions is described. We developed a macroscopic approach that incorporates salient attributes of the cortex based on combining tools of nonlinear dynamics, information theory, and the known organizational and anatomical features of cortex. Justifications for this approach and demonstration of its effectiveness are presented. We also demonstrate certain capabilities of this model in producing efficient sparse representations and providing the cortical computational maps.

Document Type

Journal Article

Date of this Version



Copyright 2009 IEEE. Reprinted from IEEE Transactions on Neural Networks, Volume 20, Issue 4, April 2009, pages 597-608.

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Chaos, Visual Cortex, Pattern recognition, Logistic Map



Date Posted: 14 May 2009

This document has been peer reviewed.