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Complexity Reduction of Rate-Equations Models for Two-Choice Decision-Making

Abstract : We are concerned with the complexity reduction of a stochastic system of di erential equations governing the dynamics of a neuronal circuit describing a decision-making task. This reduction is based on the slow-fast behavior of the problem and holds on the whole phase space and not only locally around the spontaneous state. Macroscopic quantities, such as performance and reaction times, computed applying this reduction are in agreement with previous works in which the complexity reduction is locally performed at the spontaneous point by means of a Taylor expansion.
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Contributor : Simona Mancini <>
Submitted on : Tuesday, July 9, 2013 - 2:13:49 PM
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José Antonio Carrillo, Stéphane Cordier, Gustavo Deco, Simona Mancini. Complexity Reduction of Rate-Equations Models for Two-Choice Decision-Making. PLoS ONE, Public Library of Science, 2013, pp.e80820. ⟨10.1371/journal.pone.0080820⟩. ⟨hal-00842779⟩



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