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Abstract:
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Brain connectivity analysis is now at the foreground of neuroscience research. A connectivity network is often characterized by a graph, where nodes represent neural elements such as neurons and brain regions, and links represent statistical dependency and interactions among those neural elements. Such a graph is derived from neuroimaging data such as electroencephalography and functional magnetic resonance imaging. In this talk, we discuss a number of projects addressing brain connectivity network analysis, including estimation of multiple networks across groups, hypothesis testing of inferring and comparing networks, and association modeling of networks and other biological phenotypes.
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