Mathematical neuroscience: from neurons to networks

Coombes, Stephen (2015) Mathematical neuroscience: from neurons to networks. In: Actes du colloque "EDP-Normandie" : Le Havre 2015. Fédération Normandie Mathématiques, Caen, pp. 153-160. ISBN 9782954122137

Full text not available from this repository.


The tools of dynamical systems theory are having an increasing impact on our understanding of patterns of neural activity. In this talk I will describe how to build tractable tissue level models that maintain a strong link with biophysical reality. These models typically take the form of nonlinear integro-differential equations. Their non-local nature has led to the development of a set of analytical and numerical tools for the study of waves, bumps and patterns, based around natural extensions of those used for local differential equation models. Here I will present an overview of these techniques. Time permitting I will also present recent results on next generation neural field models obtained via a mean field reduction from networks of nonlinear integrate-and-fire neurons.

Item Type: Book Section
Keywords: Neural field models, Turing instability, Interface dynamics
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Mathematical Sciences
Related URLs:
Depositing User: Coombes, Prof Stephen
Date Deposited: 07 Mar 2016 11:15
Last Modified: 04 May 2020 17:20

Actions (Archive Staff Only)

Edit View Edit View