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SUMMARY:Statistical Neuroimaging Analysis: An Overview - Prof. Lexin Li - 
 University of California\, Berkeley
DTSTART:20230803T100000Z
DTEND:20230803T110000Z
UID:TALK203611@talks.cam.ac.uk
CONTACT:Paula Smith
DESCRIPTION:Abstract:\nUnderstanding the inner workings of human brains\, 
 as well as their connections with neurological disorders\, is one of the m
 ost intriguing scientific questions. Studies in neuroscience are greatly f
 acilitated by a variety of neuroimaging technologies\, including anatomica
 l magnetic resonance imaging (MRI)\, functional magnetic resonance imaging
  (fMRI)\, electroencephalography (EEG)\, diffusion tensor imaging\, positr
 on emission tomography (PET)\, among many others. The size and complexity 
 of medical imaging data\, however\, pose numerous challenges\, and call fo
 r constant development of new statistical methods. In this talk\, I give a
 n overview of a range of neuroimaging topics our group has been investigat
 ing\, including imaging tensor analysis\, brain connectivity network analy
 sis\, multimodality analysis\, and imaging causal analysis. I also illustr
 ate with a number of specific case studies. \n\nSpeaker:\nLexin Li\, Ph.D.
 \, is a Professor of Biostatistics at the Department of Biostatistics and 
 Epidemiology\, and Helen Wills Neuroscience Institute\, of the University 
 of California\, Berkeley. His research interests include neuroimaging anal
 ysis\, brain connectivity analysis\, deep brain stimulation\, brain comput
 er interface\, and deep learning. He is a Fellow of the American Statistic
 al Association (ASA)\, a Fellow of the Institute of Mathematical Statistic
 s (IMS)\, and an Elected Member of the International Statistical Institute
  (ISI).    \n
LOCATION:Centre for Mathematical Sciences\, MR4
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