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| Research article summary (published 30 Jul 2003): |
Variance normalisation: a key mechanism for temporal adaptation in natural vision?
Full Abstract
A major problem in natural vision is how neurons in the early visual system encode the widely varying visual input with the limited dynamic range of their activity. Recent experiments suggest that retinal neurons adapt their response not only to the temporal mean but also to the temporal variance of the visual input. Inspired by these results, we propose a simple model in which temporal adaptation can be achieved by a transformation consisting of a linear filtering followed by a variance normalisation. We show that such transformation efficiently adapts to the temporal statistics of natural time series of intensities by removing most of its redundancy, while no linear transformation alone achieves the same goal. Results reproduce important features of temporal adaptation in real vision.
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Author information
Author/s: Buiatti, Marco (M); van Vreeswijk, Carl (C);
Affiliation: Neurophysique et Physiologie du Système Moteur, CNRS UMR 8119, UFR Biomèdicale, Université René Descartes, 45 rue des Saints Pères, 75270 Paris, France. marco.buiatti(-atsign-)biomedicale.univ-paris5.fr
Journal and publication information
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal: Vision research (Vision Res), published in England. (Language: eng)
Reference: 2003-Aug; vol 43 (issue 17) : pp 1895-906
Dates: Created 2003/06/26; Completed 2003/08/12; Revised 2006/11/15;
PMID: 12826112, status: MEDLINE (last retrieval date: 11/6/2008)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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