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  A fast direct solver for surface-based whole-head modeling of transcranial magnetic stimulation

Makaroff, S. N., Qi, Z., Rachh, M., Wartman, W. A., Weise, K., Noetscher, G. M., et al. (2023). A fast direct solver for surface-based whole-head modeling of transcranial magnetic stimulation. Scientific Reports, 13(1): 18657. doi:10.1038/s41598-023-45602-5.

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 Creators:
Makaroff, S. N.1, 2, Author
Qi, Z.3, Author
Rachh, M.4, Author
Wartman, W. A.1, Author
Weise, Konstantin5, 6, Author                 
Noetscher, G. M.1, Author
Daneshzand, M.2, Author
Deng, Zhi-De7, Author
Greengard, L.4, 8, Author
Nummenmaa, A. R.2, Author
Affiliations:
1Electrical and Computer Engineering Department, Worcester Polytechnic Institute, MA, USA, ou_persistent22              
2Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA, ou_persistent22              
31, ou_persistent22              
4Center for Computational Mathematics, Flatiron Institute, New York, NY, USA, ou_persistent22              
5Methods and Development Group Brain Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205650              
6Department of Advanced Electromagnetics, TU Ilmenau, Germany, ou_persistent22              
7Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institutes of Health, Bethesda, MA, USA, ou_persistent22              
8Courant Institute of Mathematical Sciences, New York, NY, USA, ou_persistent22              

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Free keywords: Biophysical models; Computational neuroscience; Software
 Abstract: When modeling transcranial magnetic stimulation (TMS) in the brain, a fast and accurate electric field solver can support interactive neuronavigation tasks as well as comprehensive biophysical modeling. We formulate, test, and disseminate a direct (i.e., non-iterative) TMS solver that can accurately determine global TMS fields for any coil type everywhere in a high-resolution MRI-based surface model with ~ 200,000 or more arbitrarily selected observation points within approximately 5 s, with the solution time itself of 3 s. The solver is based on the boundary element fast multipole method (BEM-FMM), which incorporates the latest mathematical advancement in the theory of fast multipole methods-an FMM-based LU decomposition. This decomposition is specific to the head model and needs to be computed only once per subject. Moreover, the solver offers unlimited spatial numerical resolution. Despite the fast execution times, the present direct solution is numerically accurate for the default model resolution. In contrast, the widely used brain modeling software SimNIBS employs a first-order finite element method that necessitates additional mesh refinement, resulting in increased computational cost. However, excellent agreement between the two methods is observed for various practical test cases following mesh refinement, including a biophysical modeling task. The method can be readily applied to a wide range of TMS analyses involving multiple coil positions and orientations, including image-guided neuronavigation. It can even accommodate continuous variations in coil geometry, such as flexible H-type TMS coils. The FMM-LU direct solver is freely available to academic users.

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Language(s): eng - English
 Dates: 2023-06-182023-10-212023-10-31
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1038/s41598-023-45602-5
PMID: 37907689
 Degree: -

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Project name : -
Grant ID : 1R01MH130490; 5P41EB030006; 1R01MH128421; 1R01DC020891;
Funding program : -
Funding organization : National Institutes of Health (NIH)
Project name : -
Grant ID : ZIAMH002955
Funding program : -
Funding organization : National Institute of Mental Health (NIMH)

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Title: Scientific Reports
  Abbreviation : Sci. Rep.
Source Genre: Journal
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Affiliations:
Publ. Info: London, UK : Nature Publishing Group
Pages: - Volume / Issue: 13 (1) Sequence Number: 18657 Start / End Page: - Identifier: ISSN: 2045-2322
CoNE: https://pure.mpg.de/cone/journals/resource/2045-2322