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Neural fields models of visual areas: principles, successes, and caveats

Olivier Faugeras 1 
1 NEUROMATHCOMP - Mathematical and Computational Neuroscience
CRISAM - Inria Sophia Antipolis - Méditerranée , JAD - Laboratoire Jean Alexandre Dieudonné : UMR6621
Abstract : I discuss how the notion of neural fields, a phenomenological averaged description of spatially distributed populations of neurons, can be used to build models of how visual information is represented and processed in the visual areas of primates. I describe in a pedestrian way one of the basic principles of operation of these neural fields equations which is closely connected to the idea of a bifurcation of their solutions. I then apply this concept to several visual features, edges, textures and motion and show that it can account very simply for a number of experimental facts as well as suggest new experiments. I outline several outstanding open problems and sketch out briefly interesting connections with computer vision and machine learning.
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Contributor : Pierre Kornprobst Connect in order to contact the contributor
Submitted on : Wednesday, July 17, 2013 - 2:14:11 PM
Last modification on : Thursday, August 4, 2022 - 4:58:16 PM


  • HAL Id : hal-00845605, version 1



Olivier Faugeras. Neural fields models of visual areas: principles, successes, and caveats. Workshop on Biological and Computer Vision Interfaces, 2012, Lyon, France. ⟨hal-00845605⟩



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