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Analyzing Directed Functional Brain Networks Based On Electroencephalogram Data

Afshari, Saeedeh | 2014

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 46326 (19)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Rabiei, Hamid Reza
  7. Abstract:
  8. Over the past few years, various studies have demonstrated that the complex networks can be used to model the structure and functions of human brain. Some of these studies indi- cated that diseases such as Alzheimer, Epilepsy, and Schizophrenia can cause changes in this network. The main idea behind the methods proposed to analyze human brain’s behav- ior, is to identify regions of the brain with specific tasks. Recent studies show that multiple regions of human brain are involved in complex activities, so it’s important to detect their interactions. Using functional high resolution multichannel neurophysiological signals, like electroencephalographic (EEG) and magnetoencephalographic (MEG), the interactions and connectivities between different regions of brain can be estimated.In this research, we focus on Alzheimer disease, which is a kind of brain disorder and one of the most prevalent types of neurodegenerative dementia. Unfortunately there is no cure or effective treatment for this disease.We first review state of the art mathematical methods, which are used to calculate the con-nectivities between different regions of the brain. Then, these mathematical methods, are employed to extract the directed effective connectivities between different regions of the brain from Alzheimer patient’s EEG data. Then, constructed networks are evaluated using a number of network metrics. These metrics, which have neurobiological interpretations and measure different aspects of network’s structure, include clustering coefficient, average path length, global and local efficiency, and economical performance of brain networks. The goal is to investigate the effect of Alzheimer on brain and how it changes brain’s networks. Some of these metrics measure local connections and some others assess overall efficiency of the networks.The results show that Alzheimer patient’s network have lower performance than normal peo-ple.Through these experiments, a decrease in global efficiency and an increase in local ef-ficiency of patient’s network compared with healthy people are detected. From economi- cal point of view, brain networks have shown lower performance in information processing and cognitive tasks due to changes caused by Alzheimer. Also, the resilience of both type of networks is evaluated using random failure and targeted attacks. It is demonstrated that the healthy people’s network, is more resilient to targeted attacks on its hubs, than the pa- tient’s network. These findings indicate the deteriorations and damages caused to the brain by Alzheimer’s disease
  9. Keywords:
  10. Economic Performance ; Brain Functional Network ; Structural Changes ; Complex Network ; Brain ; Directed Connectivity ; Global and Local Efficiency

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