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| Research article summary (published 30 Mar 2003): |
Basic mechanisms for graded persistent activity: discrete attractors, continuous attractors, and dynamic representations.
Full Abstract
Persistent neural activity is observed in many systems, and is thought to be a neural substrate for holding memories over time delays of a few seconds. Recent work has addressed two issues. First, how can networks of neurons robustly hold such an active memory? Computer systems obtain significant robustness to noise by approximating analogue quantities with discrete digital representations. In a similar manner, theoretical models of persistent activity in spiking neurons have shown that the most robust and stable way to store the short-term memory of a continuous parameter is to approximate it with a discrete representation. This general idea applies very broadly to mechanisms that range from biochemical networks to single cells and to large circuits of neurons. Second, why is it commonly observed that persistent activity in the cortex can be strongly time-varying? This observation is almost ubiquitous, and therefore must be taken into account in our models and our understanding of how short-term memories are held in the cortex.
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Author information
Author/s: Brody, Carlos D (CD); Romo, Ranulfo (R); Kepecs, Adam (A);
Affiliation: Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA. brody@cshl.edu
Journal and publication information
Publication Type: Journal Article; Research Support, Non-U.S. Gov't; Review
Journal: Current opinion in neurobiology (Curr Opin Neurobiol), published in England. (Language: eng)
Reference: 2003-Apr; vol 13 (issue 2) : pp 204-11
Dates: Created 2003/05/14; Completed 2003/07/08; Revised 2006/11/15;
PMID: 12744975, 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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