Feed-forward contour integration in primary visual cortex based on asynchronous spike propagation

Abstract Most current models of visual contour integration involve iterative lateral or feed-back interactions among neurons in V1 and V2. However, some forms of visual processing are too fast for such time-consuming loops. We propose a model avoiding iterative computation by using the fact that real neurons in the retina or LGN fire asynchronously, with the most activated firing first. Thus, early firing V1 neurons can influence processing of their neighbors which are still integrating information from LGN. By limiting the number of spikes to one per neuron, we show that contour integration can be obtained in a purely feed-forward way.

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