Title	Estimation and Inference for Brain Connectivity Analysis
Creator	Li, Lexin
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2016-02-04T09:02
Description	Brain connectivity analysis is now at the foreground of neuroscience research. A connectivity network is characterized by a graph, where nodes represent neural elements such as neurons and brain regions, and links represent statistical dependences that are often encoded in terms of partial correlations. Such a graph is inferred from neuroimaging data such as electroencephalography and functional magnetic resonance imaging. In this talk, we discuss a number of projects addressing estimation and inference of brain connectivity network through partial correlation matrix.
Extent	38 minutes
Subject	Mathematics; Statistics; Game theory, economics, social and behavioral sciences
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: University of California-Berkeley
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2016-08-05
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0307377
URI	http://hdl.handle.net/2429/58678
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

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