Network Analysis of EEG Data of Alzheimer’s Disease

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Tahaei, Marzieh Sadat | 2011

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 42233 (19)
University: Sharif University of Technology
Department: Computer Engineering
Advisor(s): Jalili, Mahdi
Abstract:
Recently complex networks, have been widely used as a model to study the behavior of human brain. By affecting different parts the brain, Neuronal disorders change the structure of functional brain networks. Investigating these changes using different graph theory metrics can be a useful methodology for human brain analysis in health and disease. Alzheimer's disease (AD) is a neural disease causing impairment in different brain activities including memory and cognition.The aim of this study is to construct the functional brain network of 17 AD patients and 17 healthy control subjects at resting state condition and analyzing them using the theory of complex networks in order to achieve a deeper insight of Alzheimer’s disease. The functional connectivity is computed by three methods of, correlation, partial correlation, and phase synchronization. The result indicate decrease in synchronizability, clustering coefficient, efficiency,modularity, nodebetweenness centrality and average path length in AD patients compared to control group.
Keywords:
Complex Network ; Electroencephalography ; Alzheimer ; Graph Metrics

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