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GT Neuro Seminar Series

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Maryam Shanechi, Ph.D.
Assistant Professor
Viterbi Early Career Chair in Electrical and Computer Engineering
Viterbi School of Engineering
University of Southern California

“Neural Decoding and Control of Multiscale Brain Networks: From Motor to Mood”

In this talk, I first discuss our recent work on modeling, decoding, and controlling multisite human brain activity underlying mood states. I present a multiscale dynamical modeling framework that allows us, for the first time, to decode mood variations and identify brain sites that are most predictive of mood. I then develop a system identification approach that can predict large-scale brain network dynamics (output) in response to electrical stimulation (input) to enable closed-loop control of brain activity. Finally, I demonstrate that our modeling framework can uncover multiscale neural dynamics from hybrid spike-field activity in monkeys performing unconstrained movements and can further combine information from multiple scales of activity and model their different time-scales and statistical profiles. These models, decoders, and controllers could facilitate future closed-loop therapies for neurological and neuropsychiatric disorders and help probe neural circuits.

Status

  • Workflow Status:
    Published
  • Created By:
    Floyd Wood
  • Created:
    09/18/2019
  • Modified By:
    Floyd Wood
  • Modified:
    09/18/2019

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