title: Modeling transcranial magnetic stimulation from the induced electric fields to the membrane potentials along tractography-based white matter fiber tracts.
abstract: OBJECTIVE
  Transcranial magnetic stimulation (TMS) is a promising non-invasive tool for modulating the brain activity. Despite the widespread therapeutic and diagnostic use of TMS in neurology and psychiatry, its observed response remains hard to predict, limiting its further development and applications. Although the stimulation intensity is always maximum at the cortical surface near the coil, experiments reveal that TMS can affect deeper brain regions as well.
  
  
  METHODS
  The explanation of this spread might be found in the white matter fiber tracts, connecting cortical and subcortical structures. When applying an electric field on neurons, their membrane potential is altered. If this change is significant, more likely near the TMS coil, action potentials might be initiated and propagated along the fiber tracts towards deeper regions. In order to understand and apply TMS more effectively, it is important to capture and account for this interaction as accurately as possible. Therefore, we compute, next to the induced electric fields in the brain, the spatial distribution of the membrane potentials along the fiber tracts and its temporal dynamics.
  
  
  RESULTS
  This paper introduces a computational TMS model in which electromagnetism and neurophysiology are combined. Realistic geometry and tissue anisotropy are included using magnetic resonance imaging and targeted white matter fiber tracts are traced using tractography based on diffusion tensor imaging. The position and orientation of the coil can directly be retrieved from the neuronavigation system. Incorporating these features warrants both patient- and case-specific results.
  
  
  CONCLUSIONS
  The presented model gives insight in the activity propagation through the brain and can therefore explain the observed clinical responses to TMS and their inter- and/or intra-subject variability. We aspire to advance towards an accurate, flexible and personalized TMS model that helps to understand stimulation in the connected brain and to target more focused and deeper brain regions.
authors.affiliation: Department of Electrical Energy, Systems and Automation, Ghent University, Technologiepark 913, B-9052 Zwijnaarde, Belgium.
authors.forename: Nele De
authors.initials: ND
authors.lastname: Geeter
authors.forename: Luc
authors.initials: L
authors.lastname: Dupré
authors.forename: Guillaume
authors.initials: G
authors.lastname: Crevecoeur
mesh_terms: D000328:Adult; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D008564:Membrane Potentials / Q000502:physiology*; D008959:Models, Neurological; D009434:Neural Pathways / Q000502:physiology; D050781:Transcranial Magnetic Stimulation / Q000379:methods*; D066127:White Matter / Q000502:physiology*