Natalie Schaworonkow | Computational modeling of the effects of transcranial magnetic stimulation

Guest Lecture

  • Date: Apr 27, 2017
  • Time: 04:00 PM - 05:00 PM (Local Time Germany)
  • Speaker: Natalie Schaworonkow
  • Frankfurt Institute for Advanced Studies (FIAS) J.W. Gothe University, Frankfurt
  • Location: MPI for Human Cognitive and Brain Sciences
  • Room: Wilhelm Wundt Room (A400)
Transcranial magnetic stimulation is a promising technique for non-invasive therapeutic treatment of psychiatric and neurological conditions. However, the same stimulation protocol can elicit opposing effects on excitability and plasticity in different subjects. The effects of TMS on neural circuits remain poorly understood, which hinders the development of maximally effective stimulation protocols. In this talk, I discuss computational modeling approaches to understanding the high variability of TMS effects. Detailed electrical field modeling combined with compartmental model neurons can reveal subject-specific excitability response differences to TMS. Additionally, taking spontaneous oscillatory activity into account yields a phase-dependency in a model of TMS-induced I-waves, showing that ongoing brain activity can contribute to observed variability.
Transcranial magnetic stimulation is a promising technique for non-invasive therapeutic treatment of psychiatric and neurological conditions. However, the same stimulation protocol can elicit opposing effects on excitability and plasticity in different subjects. The effects of TMS on neural circuits remain poorly understood, which hinders the development of maximally effective stimulation protocols. In this talk, I discuss computational modeling approaches to understanding the high variability of TMS effects. Detailed electrical field modeling combined with compartmental model neurons can reveal subject-specific excitability response differences to TMS. Additionally, taking spontaneous oscillatory activity into account yields a phase-dependency in a model of TMS-induced I-waves, showing that ongoing brain activity can contribute to observed variability.

Poster
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