Numerical solution of the stochastic neural field equation with applications to working memory

The main goal of the present work is to investigate effect noise in some neural fields, used simulate working memory processes. underlying mathematical model a stochastic integro-differential equation. In order approximate this equation we apply numerical scheme which uses Galerkin method for space discretization. way obtain system differential equations, are then approximated two different ways, using Euler–Maruyama and Itô–Taylor methods. We explain how population cortical neurons may encode its firing pattern simultaneously nature time sequential stimulus events. Numerical examples presented their results discussed.