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Integration of Fiber Tracts in Anatomically Accurate Brain Models during Transcranial Magnetic Stimulation
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  • Connor Lewis ,
  • Connor Harris ,
  • Neil Mittal ,
  • Carrie Peterson ,
  • Ravi Hadimani
Connor Lewis
Virginia Commonwealth University

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Connor Harris
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Neil Mittal
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Carrie Peterson
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Ravi Hadimani
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Abstract

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique used in the treatment of several neurological conditions. The dosage parameter for TMS protocols is the resting motor threshold (RMT) which has been shown to vary between participants with limited understanding. The goal of this study was to investigate how white matter-derived fiber tracts integrated into finite element analysis simulations influence TMS response in the form of RMT. Ten healthy participants were included in this study who underwent TMS, diffusion tensor imaging, and structural magnetic resonance imaging (MRI). Anatomically accurate head models were created and fiber tracts were extracted from Diffusion tensor imaging and integrated into these head models before finite element analysis simulations were performed to model the effects of empirical TMS. Linear mixed effects models were used to evaluate how the induced electric field strength on the fiber tracts (EFSTract) influenced RMT. We found the induced electric field strength along fiber tracts did influence RMT, however the effect of this relationship on RMT is not clinically relevant due to its small magnitude. This suggests finite element analysis of the fiber tracts is not meaningful when tracts are considered a homogenous material and thus lacking physiology. However, tractography provides a valuable framework within which to organize physiological models of signal transmission, and it is likely a combination of this approach with more physiologically detailed modeling would provide more accurate RMT prediction.