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UID:20250514T081500EDT-3595aP3ulh@132.216.98.100
DTSTAMP:20250514T121500Z
DESCRIPTION:Dynamical modeling\, decoding\, and control of multiscale brain
  networks: from motor to mood\n\nMaryam M. Shanechi\, University of Southe
 rn California\n	Tuesday May 11\, 12-1pm\n	Zoom Link: https:/mcgill.zoom.us/j
 /91589192037\n\nAbstract: In this talk\, I will discuss our work on dynami
 cal modeling\, decoding\, and control of large-scale brain network activit
 y underlying naturalistic motor and mood states. I present a multiscale dy
 namical modeling framework that allows us to decode human mood variations 
 and identify brain regions that are most predictive of mood. I then develo
 p a system identification approach that can predict multiregional brain ne
 twork dynamics (output) in response to time-varying electrical stimulation
  (input) toward enabling closed-loop control of brain activity. Further\, 
 I extend our modeling framework to enable dissociating and uncovering beha
 viorally relevant neural dynamics that can otherwise be missed\, such as t
 hose during naturalistic movements. Finally\, I show how our framework can
  model brain network activity across multiple spatiotemporal scales simult
 aneously\, thus uncovering multiscale neural dynamics that explain natural
 istic reach-and-grasp behavior. These dynamical models\, decoders\, and co
 ntrollers can provide new neuroscientific insight and enable brain-machine
  interfaces for personalized therapy in neurological and neuropsychiatric 
 disorders.\n
DTSTART:20210511T160000Z
DTEND:20210511T170000Z
LOCATION:CA\, QC
SUMMARY:QLS Seminar - Maryam M. Shanechi
URL:/qls/channels/event/qls-seminar-maryam-m-shanechi-
 330750
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