Cortical simple cells: modeling physiology and image processing applications

Abstract

One of the fundamental questions i n visual system physiology is how cells acquzre their receptive field properties. The present p a p e r addresses the question of how cortical simple cell behavior orzginates through the specification of an associated neural circuit which nonlanearly combines inputs f r o m O N and OFF streams. T h e responses of the model closely follow the static nonlinear behavior observed i n the recordings of Hammond and Macliay [4] and suggest that simple cells should not be viewed as linear devices as commonly assumed since the work of Hubel and Wiesel [7]. We also evaluate the model with both camera and artificial images. Our circuit exhibits a higher positional selectivity (better contrast localization) when compared t o a corresponding linear scheme and can be used as an efective "edge detection" algorithm.