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SUMMARY:Neuro-X Seminar: Dynamical modeling\, decoding\, and control of mu
 ltiscale brain network activity: from motor to mood
DTSTART:20230517T160000
DTEND:20230517T170000
DTSTAMP:20260406T230437Z
UID:c633be49eeb507105fe20bc1c9582562da20da31f2f5f323de095c41
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof Maryam Shanechi\nAbstract:               
                                      
         \nA major challenge in engineering and neuroscience is to 
 model\, decode\, and control the activity of large populations of neurons 
 that underlie our brain’s functions and dysfunctions. I will present our
  work toward addressing this challenge. First\, I discuss a multiscale dyn
 amical modeling framework that can decode mood variations from multisite h
 uman brain activity and identify brain regions that are most predictive of
  mood. Second\, I develop a system identification approach that can predic
 t multiregional brain network dynamics (output) in response to time-varyin
 g electrical stimulation (input) to enable closed-loop control of neural a
 ctivity. Third\, I present the PSID dynamical modeling framework for neura
 l-behavioral data that can dissociate behaviorally relevant neural dynamic
 s\, learn them more accurately\, and uncover their dimensionality. I also 
 show how we can further disentangle the intrinsic behaviorally relevant dy
 namics from input dynamics\, thus revealing that the former can be remarka
 bly similar across animals and tasks unlike overall intrinsic dynamics. Fi
 nally\, I turn my attention to nonlinear dynamical modeling. I present a n
 ew neural network modeling framework that localizes the nonlinearity in th
 e neural-behavioral transformation to enable interpretation\, prioritizes 
 the learning of behaviorally relevant dynamics\, and extends across data m
 odalities. These dynamical models\, decoders\, and controllers can enable 
 a new generation of brain-machine interfaces for personalized therapy in n
 eurological and neuropsychiatric disorders.\n \nBio:\nMaryam M. Shanechi 
 is Professor in Electrical and Computer Engineering (ECE) and a member of 
 the Neuroscience Graduate Program and Departments of Computer Science and 
 Biomedical Engineering at the University of Southern California (USC). She
  is also the founder and director of a newly established USC Center for Ne
 urotechnology. Prior to joining USC\, she was Assistant Professor at Corne
 ll University’s ECE department in 2014. She received her B.A.Sc. degree 
 in Engineering Science from the University of Toronto\, her S.M. and Ph.D.
  degrees in Electrical Engineering and Computer Science from MIT\, and her
  postdoctoral training in Neural Engineering at Harvard Medical School and
  UC Berkeley. Her research focuses on developing closed-loop neurotechnolo
 gy and studying the brain through decoding and control of neural dynamics.
  She is the recipient of several awards including the NIH Director’s New
  Innovator Award\, NSF CAREER Award\, ONR Young Investigator Award\, ASEE
 ’s Curtis W. McGraw Research Award\, MIT Technology Review’s top 35 In
 novators Under 35\, Popular Science Brilliant 10\, Science News SN10\, One
  Mind Rising Star Award\, and a DoD Multidisciplinary University Research 
 Initiative (MURI) Award.\n 
LOCATION:https://epfl.zoom.us/j/64914530754?pwd=QVAxY0tYTlBzUFJRWHJzMm90aD
 V2UT09
STATUS:CONFIRMED
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