Drift-diffusion models for multiple-alternative forced-choice decision making
Roxin, Alex (Centre de Recerca Matemàtica)

Date:	2019
Abstract:	The canonical computational model for the cognitive process underlying two-alternative forced-choice decision making is the so-called drift-diffusion model (DDM). In this model, a decision variable keeps track of the integrated difference in sensory evidence for two competing alternatives. Here I extend the notion of a drift-diffusion process to multiple alternatives. The competition between n alternatives takes place in a linear subspace of dimensions; that is, there are decision variables, which are coupled through correlated noise sources. I derive the multiple-alternative DDM starting from a system of coupled, linear firing rate equations. I also show that a Bayesian sequential probability ratio test for multiple alternatives is, in fact, equivalent to these same linear DDMs, but with time-varying thresholds. If the original neuronal system is nonlinear, one can once again derive a model describing a lower-dimensional diffusion process. The dynamics of the nonlinear DDM can be recast as the motion of a particle on a potential, the general form of which is given analytically for an arbitrary number of alternatives.
Grants:	Ministerio de Economía y Competitividad MTM2015-71509-C2-1-R Agència de Gestió d'Ajuts Universitaris i de Recerca 2014/SGR-1265 Agència de Gestió d'Ajuts Universitaris i de Recerca 2014/SGR-4662
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Decision making ; Networks ; Winner-take-all
Published in:	Journal of Mathematical Neuroscience, Vol. 9 (July 2019) , art. 5, ISSN 2190-8567

DOI: 10.1186/s13408-019-0073-4
PMID: 31270706

23 p, 1.9 MB

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