Modeling Neuronal Response to Disparity Gradient

There is a rich literature of physiological studies that a subset of neurons in visual cortices is discriminative of 3-D surface orientation using only the disparity gradient information. One of the physiological models to account for this sensibility to surface slant is the dif-frequency disparity model. Although this model is physiologically plausible, no computational analysis is available to explain how first-order-disparity sensitive neurons detect slanted surface. In this paper a computational model based on the dif-frequency disparity model is presented. In particular, analytical expressions that fit well with neuronal responses to broadband stimuli are obtained when simple cell receptive field is described by log-Gabor filters. It is shown with mathematical analysis and numerical simulations that our proposed model can not only account for physiological data of neuronal response to surface slant but also detect disparity gradient from random dot and sinusoidal grating stereograms.