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Large-scale neural dynamics: Simple and complex

Coombes, S.

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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.


Coombes, S. (2010). Large-scale neural dynamics: Simple and complex. NeuroImage, 52(3), 731-739.

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
Keywords brain wave equation, EEG, fMRI
Public URL
Publisher URL


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