Priscilla (Cindy) Greenwood

Our topic is pattern formation by stochastic neural field equations, a class of stochastic differential-integral equations using a Mexican hat kernel, arising as a model of the dynamics of visual cortex. We explore how the parameters that control width of local noise-sharing and coupling strength influence the pattern produced by the resulting evolving random field. We determine optimal parameter combinations for the formation of clear pattern and look at some simulations.