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dc.contributor.authorRennie, Christopher Johnen_AU
dc.date.accessioned2006-03-31
dc.date.available2006-03-31
dc.date.issued2001-01-01
dc.identifier.urihttp://hdl.handle.net/2123/816
dc.descriptionIncludes publicationsen_AU
dc.description.abstractModeling of brain activity is often seen as requiring great computing power. However in the special case of modeling scalp EEG it is possible to adopt a continuum approximation for the cortex, and then to use the techniques of wave physics to describe its consequent large-scale dynamics. The model incorporates the following critical components: two classes of neurons (excitatory and inhibitory), the typical number and strength of connections between these two classes, the corresponding connections within the thalamus and between the thalamus and cortex, the time constants and basic physiology of neurons, and the propagation of activity between neurons. Representing the immense intricacy of brain anatomy and physiology with suitable summary equations and average parameter values has meant that the model is able to capture the essential characteristics of EEG and ERPs, and to do so in a computationally manageable way.en_AU
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dc.languageenen_AU
dc.language.isoen_AU
dc.rightsCopyright Rennie, Christopher John;http://www.library.usyd.edu.au/copyright.htmlen_AU
dc.subjectelectroencephalographyen_AU
dc.subjectmathematical modelingen_au
dc.subjectEEGen_au
dc.subjectERPen_au
dc.subjectdynamicsen_au
dc.titleModeling the large-scale electrical activity of the brainen_AU
dc.typeThesisen_AU
dc.type.thesisDoctor of Philosophyen_AU
usyd.facultyFaculty of Science, School of Physicsen_AU
usyd.degreeDoctor of Philosophy Ph.D.en_AU
usyd.awardinginstThe University of Sydneyen_AU


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