title: Complexity reduction of rate-equations models for two-choice decision-making.
abstract: We are concerned with the complexity reduction of a stochastic system of differential 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.
authors: Department of Mathematics, Imperial College London, London, United Kingdom.
authors: José Antonio
authors: JA
authors: Carrillo
authors: Stéphane
authors: S
authors: Cordier
authors: Gustavo
authors: G
authors: Deco
authors: Simona
authors: S
authors: Mancini
mesh_terms: D002755:Choice Behavior / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D007700:Kinetics; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology; D013269:Stochastic Processes