Postsynaptic organisations of directional selective visual neural networks for collision detection

Abstract

In this paper, we studied the postsynaptic organisations of directional selective visual neurons for collision detection. Directional selective neurons can extract different directional visual motion cues fast and reliably by allowing inhibition spreads to further layers in specific directions with one or several time steps delay. Whether these directional selective neurons can be easily organised for other specific visual tasks is not known. Taking collision detection as the primary visual task, we investigated the postsynaptic organisations of these directional selective neurons through evolutionary processes. The evolved postsynaptic organisations demonstrated robust properties in detecting imminent collisions in complex visual environments with many of which achieved 94% success rate after evolution suggesting active roles in collision detection directional selective neurons and its postsynaptic organisations can play.