Postsynaptic organizations of directional selective visual neural networks for collision detection

Yue, Shigang and Rind, F. Claire (2013) Postsynaptic organizations of directional selective visual neural networks for collision detection. Neurocomputing, 103 . pp. 50-62. ISSN 0925-2312

Full content URL: http://dx.doi.org/10.1016/j.neucom.2012.08.027

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Abstract

In this paper, we studied the postsynaptic organizations 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 organizations of these directional selective neurons through evolutionary processes. The evolved postsynaptic organizations 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 organizations can play.

Keywords:visual motion, directional selective neuron, vision, postsynaptic, properties, collision
Subjects:G Mathematical and Computer Sciences > G730 Neural Computing
Divisions:College of Science > School of Computer Science
ID Code:9308
Deposited On:03 May 2013 07:38

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