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  • EEG信號數據與大腦網絡動力學學術報告

    發布者:張程冬發布時間:2019-03-12瀏覽次數:1003

    報告題目:

    EEG Signal Data and Brain Network Dynamics

    EEG信號數據與大腦網絡動力學

    報告人:Jianzhong Su(蘇建忠)

    報告時間:2019315日(周五)下午13:30-15:00

    報告地點:bwin必贏306

    報告人簡介:Jianzhong Su(蘇建忠),美國德州大學阿靈頓分校數學系主任,教授,1984年畢業于上海交通大學,獲學士學位;1984-1990年在美國 University of Minnesota獲得博士學位,主要研究領域包括醫療大數據的建模與分析,曾多次獲得美國NSFNIH等基金的資助。

    內容簡介:Full brain EEG and its source localization is a brain imaging modality based on multi-channel Electroencephalography (EEG) signals. It measures the brain field potential fluctuations on the entire scalp for a period of time, and then we mathematically calculate the electric current density inside the brain by solving an inverse Poisson problem at each time. The time trajectories of EEG signal on the scalp and inside the brain reveal brain dynamics at rest or during brain cognitions. In this talk, we introduce mathematical methods for the EEG source reconstruction problems and discuss its methodology and applications. One application is in identifying abnormality in brain activities during seizures of an infant patient with Glucose Transporter Deficiency Syndrome. Another application is to find the neuronal signatures in response to pain stimulations. Further work shows these data can be further used to study the brain network properties that glean into the inner working of brain functions.

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