Self-Organization in Large Scale Population Network Models
Document Type
Presentation Abstract
Presentation Date
12-8-2005
Abstract
In large-scale population networks the emergence of global behavioral patterns is driven by self-organization of local groups into synchronously functioning ensembles. However, the laws governing such macrobehavior are poorly understood. Here, we propose an extension of the Wilson-Cowan-Amari system which models the behavior of populations of excitatory and inhibitory neurons. We have two goals in this talk: the first is to explain how self-organization of local populations arises in the model in the form of self-sustained synchronous oscillations both in one and two space dimensions. In addition, we show how organization in one spatial region promotes or inhibits organization in another. Theoretical predictions are confirmed by comparison with human electrocorticographic recordings. The second goal is to show how rotating waves arise in the model and how they were used to predict, and subsequently confirm, the existence of rotating waves in rat brain experiments.
All results will be illustrated by videos.
Recommended Citation
Troy, Bill, "Self-Organization in Large Scale Population Network Models" (2005). Colloquia of the Department of Mathematical Sciences. 209.
https://scholarworks.umt.edu/mathcolloquia/209
Additional Details
Thursday, 8 December 2005
4:10 p.m. in Math 109