Citation: Neural Networks, 15, 181-200
Abstract: A neural model is developed to probe how corticogeniculate feedback may contribute to the dynamics of binocular vision. Feedforward and feedback interactions among retinal, lateral geniculate, and cortical simple and complex cells are used to simulate psychophysical and neurobiological data concerning the dynamics of binocular disparity processing, including correct registration of disparity in response to dynamically changing stimuli, binocular summation of weak stimuli, and fusion of anticorrelated stimuli when they are delayed, but not when they are simultaneous. The model exploits dynamic rebounds between opponent ON and OFF cells that are due to imbalances in habituative transmitter gates. It shows how corticogeniculate feedback can carry out a top-down matching process that inhibits incorrect disparity responses and reduces persistence of previously correct responses to dynamically changing displays.