Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.661125
Title: Understanding the awake and anaethetized brain through oscillations
Author: Hansard , Tom
Awarding Body: Lancaster University
Current Institution: Lancaster University
Date of Award: 2012
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Abstract:
Despite an elaborate int;icacy the brain can, to some degree, be understood in terms of surprisingly simple features. This thesis considers the brain from one such perspectivethat of oscillatory dynamics-in order to study, compare and fina.lly model the awake and anresthetized states of consciousness. Anresthesia provides a comparatively simple state in which to study the brain and understanding how this state differs from the awake state could help improve the safety of many modern surgical procedures which require general anresthetics. The importance of including glia-an often overlooked group of brain cells-is also argued, leading to a novel neuron-glia brain model. This thesis is comprised of four parts: a literature-based review of brain dynamics and anresthesia; analysis of human electroencephalograms (EEGs); a.n oscillation-based brain model; and a unifying discussion of this work. Part one begins with the cellular (i.e. neuronal and glial) dynamics of the brain, thus describing the underlying oscillatory nature of brain dynamics. This is followed by a detailed overview of macroscopic "brain-waves", their hypothetical functional correlates and likely mechanisms of generation. This discussion proceeds to an overview of the mechanisms of general anresthesia and their effects upon brain dynamics. Part two of this thesis begins with a description of the relevant mathematical concepts and tools-a necessary precursor to the technical analysis of EEG data which will follow. Conclusions drawn from this analysis compliment those presented in the preceding sections and provide a foundation upon which the model can be built. Part three initially overviews various brain-models and then utilizes preceding sections in order to formulate an oscillation-based brain model. The resulting model hence depends upon a multi-scale understanding of brain dynamics and replicates some of the conclusions drawn from my own analysis while also demonstrating.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.661125  DOI: Not available
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