Modeling Brain Activity Using Mathematical Physics

Professor David Liley
Brain and Psychological Sciences Research Centre, Swinburne University of Technology

3:30 pm Friday, 28 April 2017, EN103 Lecture Theatre (EN Building), Hawthorn.

The thin rind of the cerebrum that comprises the cortex of humans is densely populated with neurons that interact with each other over a range of temporal and spatial scales. The collective activity emerging from these 100 billion neurons interacting by the 1000 trillion or so connections forms the basis for human behaviour. To date the most familiar approach to studying such activity has been directed towards enumerating, characterising and simulating these vast neural networks. However there exist empirically and computationally much less burdensome approaches to studying such collective activity that rely on a range of insights derived from mathematical physics. Such approaches, variously referred to as mass action or neural field theories, replace interactions between individual neurons by effective averages in order to constitute mean fields. The dynamical activity of the brain, and in particular the cortex, is then modelled by the spatio-temporal evolution of these mean fields.

The aim of this talk will be to outline one neural field approach to modeling brain activity that has been particularly successful in articulating the genesis of rhythmic brain electrical activity and the modification of such activity by anaesthetic and sedative agents. The presentation will conclude with an example of how the physiological insights afforded by this approach can be translated into improved approaches to the clinical monitoring of depth of anaesthesia, an important step towards defining the neural correlates of conscious experience.

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