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.
Type de document :
Communication dans un congrès
Workshop on Biological and Computer Vision Interfaces, 2012, Lyon, France. Springer, 2012
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https://hal.inria.fr/hal-00845605
Contributeur : Pierre Kornprobst <>
Soumis le : mercredi 17 juillet 2013 - 14:14:11
Dernière modification le : jeudi 11 janvier 2018 - 16:51:53

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  • HAL Id : hal-00845605, version 1

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

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