EEG Signal Data and Brain Network Dynamics
报告人简介：Jianzhong Su（苏建忠），美国德州大学阿灵顿分校数学系主任，教授，1984年毕业于上海交通大学，获学士学位；1984-1990年在美国 University of Minnesota获得博士学位，主要研究领域包括医疗大数据的建模与分析，曾多次获得美国NSF和NIH等基金的资助。
内容简介：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.