Modelling of large-scale brain network dynamicsTools Forrester, Michael J. (2021) Modelling of large-scale brain network dynamics. PhD thesis, University of Nottingham.
AbstractLike many systems in nature, the brain is a highly organised unit of interacting components. A natural way to study such systems is through the lens of mathematics, from which we may attempt to delineate the mechanisms that underlie seemingly unfathomable brain functionality using prescribed parameters and equations. In this thesis, we use large-scale neural mass network models of the human cortex to simulate brain activity. Moreover, we utilise techniques from graph, linear and weakly-coupled oscillator theory to describe the network states that are exhibited by such models. In particular, we focus on how the emergent patterns of synchrony (which are thought to be fundamental to the function of brain), or so-called functional connectivity, are dependent on the structural connectivity, which is the anatomical substrate for brain dynamics. Through large-scale network simulations and linear analysis we find that the structure--function relationship is highly dependent on-- and indeed, predictable from-- the dynamical state of individual nodes in the network, highlighting the role of dynamics in facilitating emergent functional connectivity.
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