Conditions for numerically accurate TMS electric field simulation

Luis J. Gomez, Moritz Dannhauer, Lari M. Koponen, Angel V. Peterchev*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)

Abstract

Background: Computational simulations of the E-field induced by transcranial magnetic stimulation (TMS) are increasingly used to understand its mechanisms and to inform its administration. However, characterization of the accuracy of the simulation methods and the factors that affect it is lacking. Objective: To ensure the accuracy of TMS E-field simulations, we systematically quantify their numerical error and provide guidelines for their setup. Method: We benchmark the accuracy of computational approaches that are commonly used for TMS E-field simulations, including the finite element method (FEM) with and without superconvergent patch recovery (SPR), boundary element method (BEM), finite difference method (FDM), and coil modeling methods. Results: To achieve cortical E-field error levels below 2%, the commonly used FDM and 1st order FEM require meshes with an average edge length below 0.4 mm, 1st order SPR-FEM requires edge lengths below 0.8 mm, and BEM and 2nd (or higher) order FEM require edge lengths below 2.9 mm. Coil models employing magnetic and current dipoles require at least 200 and 3000 dipoles, respectively. For thick solid-conductor coils and frequencies above 3 kHz, winding eddy currents may have to be modeled. Conclusion: BEM, FDM, and FEM all converge to the same solution. Compared to the common FDM and 1st order FEM approaches, BEM and 2nd (or higher) order FEM require significantly lower mesh densities to achieve the same error level. In some cases, coil winding eddy-currents must be modeled. Both electric current dipole and magnetic dipole models of the coil current can be accurate with sufficiently fine discretization.

Original languageEnglish
Pages (from-to)157-166
Number of pages10
JournalBrain stimulation
Volume13
Issue number1
DOIs
Publication statusPublished - 1 Jan 2020

Bibliographical note

Funding Information:
Research reported in this publication was supported by the National Institute of Mental Health and the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under Award Numbers K99MH120046 , RF1MH114268 , R01NS088674-S1 , RF1MH114253 , and U01AG050618 . The content of current research is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Funding Information:
Research reported in this publication was supported by the National Institute of Mental Health and the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under Award Numbers K99MH120046 , RF1MH114268 , R01NS088674-S1 , RF1MH114253 , and U01AG050618 . The content of current research is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Publisher Copyright:
© 2019 Elsevier Inc.

Keywords

  • Boundary element method
  • Electric field simulation
  • Finite element method
  • TMS
  • Transcranial magnetic stimulation

ASJC Scopus subject areas

  • Biophysics
  • General Neuroscience
  • Clinical Neurology

Fingerprint

Dive into the research topics of 'Conditions for numerically accurate TMS electric field simulation'. Together they form a unique fingerprint.

Cite this