A recurrent model of contour integration in primary visual cortex

Physiological and psychophysical studies have demonstrated the importance of colinearity in visual processing. Motivated by these empirical findings we present a novel computational model of recurrent long-range processing in the primary visual cortex. Unlike other models we restrict the long-range interaction to cells of parallel orientation with colinear aligned receptive fields. We also employ a recurrent interaction using modulatory feedback, in accordance with empirical findings. Self-normalizing shunting equations guarantee the saturation of activities after a few recurrent cycles. The primary computational goal of the model is to evaluate local, often noisy orientation measurements within a more global context and to selectively enhance coherent activity by excitatory, modulating feedback. All model simulations were done with the same set of parameters. We show that the model qualitatively reproduces empirical data of response facilitation and suppression for a single bar element depending on the local surround outside the classical receptive field (M. K. Kapadia, M. Ito, C. D. Gilbert, & G. Westheimer, 1995). Next we evaluate the model performance for the processing of artificial and natural images. We quantitatively evaluate the model using two measures of contour saliency and orientation significance. We show that both measures monotonically increase during the recurrent interaction and saturate after a small number of recurrent cycles. The model clarifies how basic tasks of early vision can be accomplished within a single, biologically plausible architecture.