Large-scale neural dynamics: Simple and complex

Coombes, S.

Abstract

We review the use of neural field models for modelling the brain at the large scales necessary for interpreting EEG, fMRI, MEG and optical imaging data. Albeit a framework that is limited to coarse-grained or mean-field activity, neural field models provide a framework for unifying data from different imaging modalities. Starting with a description of neural mass models, we build to spatially extend cortical models of layered two-dimensional sheets with long range axonal connections mediating synaptic interactions. Reformulations of the fundamental non-local mathematical model in terms of more familiar local differential (brain wave) equations are described. Techniques for the analysis of such models, including how to determine the onset of spatio-temporal pattern forming instabilities, are reviewed. Extensions of the basic formalism to treat refractoriness, adaptive feedback and inhomogeneous connectivity are described along with open challenges for the development of multi-scale models that can integrate macroscopic models at large spatial scales with models at the microscopic scale. © 2010 Elsevier Inc.

Citation

Coombes, S. (2010). Large-scale neural dynamics: Simple and complex. NeuroImage, 52(3), 731-739. https://doi.org/10.1016/j.neuroimage.2010.01.045

• Journal Article Type: Review
• Acceptance Date: Jan 13, 2010
• Online Publication Date: Jan 22, 2010
• Publication Date: Sep 1, 2010
• Deposit Date: Jan 6, 2010
• Publicly Available Date: Jan 22, 2010
• Journal: NeuroImage
• Print ISSN: 1053-8119
• Electronic ISSN: 1053-8119
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 52
• Issue: 3
• Pages: 731-739
• DOI: https://doi.org/10.1016/j.neuroimage.2010.01.045
• Keywords: brain wave equation, EEG, fMRI
• Public URL: https://nottingham-repository.worktribe.com/output/705852
• Publisher URL: http://www.sciencedirect.com/science/journal/10538119