Using computational models to relate structural and functional brain connectivity

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Hlinka, Jaroslav and Coombes, Stephen (2012) Using computational models to relate structural and functional brain connectivity. European Journal of Neuroscience, 36 (2). pp. 2137-2145. ISSN 0953-816X

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Abstract

Modern imaging methods allow a non-invasive assessment of both structural and functional brain connectivity. This has lead to

the identification of disease-related alterations affecting functional connectivity. The mechanism of how such alterations in

functional connectivity arise in a structured network of interacting neural populations is as yet poorly understood. Here we use

a modeling approach to explore the way in which this can arise and to highlight the important role that local population

dynamics can have in shaping emergent spatial functional connectivity patterns. The local dynamics for a neural population is

taken to be of the Wilson–Cowan type, whilst the structural connectivity patterns used, describing long-range anatomical

connections, cover both realistic scenarios (from the CoComac database) and idealized ones that allow for more detailed

theoretical study. We have calculated graph–theoretic measures of functional network topology from numerical simulations of

model networks. The effect of the form of local dynamics on the observed network state is quantified by examining the

correlation between structural and functional connectivity. We document a profound and systematic dependence of the

simulated functional connectivity patterns on the parameters controlling the dynamics. Importantly, we show that a weakly

coupled oscillator theory explaining these correlations and their variation across parameter space can be developed. This

theoretical development provides a novel way to characterize the mechanisms for the breakdown of functional connectivity in

diseases through changes in local dynamics.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/1007161
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Mathematical Sciences
Identification Number: 10.1111/j.1460-9568.2012.08081.x
Depositing User: de Sousa, Mrs Shona
Date Deposited: 25 Mar 2014 11:14
Last Modified: 04 May 2020 20:21
URI: https://eprints.nottingham.ac.uk/id/eprint/2512

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