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Comparative performance of the finite element method and the boundary element fast multipole method for problems mimicking transcranial magnetic stimulation (TMS)

Research output: Contribution to journalJournal articleResearchpeer-review

DOI

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  2. Optimizing the electric field strength in multiple targets for multichannel transcranial electric stimulation

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  3. Transducer modeling for accurate acoustic simulations of transcranial focused ultrasound stimulation

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  4. Frequency of different subtypes of cervical dystonia: a prospective multicenter study according to Col-Cap concept

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  5. Electric field simulations for transcranial brain stimulation using FEM: an efficient implementation and error analysis

    Research output: Contribution to journalJournal articleResearchpeer-review

  1. Optimizing the electric field strength in multiple targets for multichannel transcranial electric stimulation

    Research output: Contribution to journalJournal articleResearchpeer-review

  2. Accurate and robust whole-head segmentation from magnetic resonance images for individualized head modeling

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. Accurate TMS Head Modeling: Interfacing SimNIBS and BEM-FMM in a MATLAB-Based Module

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  4. Probing EEG activity in the targeted cortex after focal transcranial electrical stimulation

    Research output: Contribution to journalJournal articleResearchpeer-review

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Objective. A study pertinent to the numerical modeling of cortical neurostimulation is conducted in an effort to compare the performance of the finite element method (FEM) and an original formulation of the boundary element fast multipole method (BEM-FMM) at matched computational performance metrics. Approach. We consider two problems: (i) a canonic multi-sphere geometry and an external magnetic-dipole excitation where the analytical solution is available and; (ii) a problem with realistic head models excited by a realistic coil geometry. In the first case, the FEM algorithm tested is a fast open-source getDP solver running within the SimNIBS 2.1.1 environment. In the second case, a high-end commercial FEM software package ANSYS Maxwell 3D is used. The BEM-FMM method runs in the MATLAB ® 2018a environment. Main results. In the first case, we observe that the BEM-FMM algorithm gives a smaller solution error for all mesh resolutions and runs significantly faster for high-resolution meshes when the number of triangular facets exceeds approximately 0.25 M. We present other relevant simulation results such as volumetric mesh generation times for the FEM, time necessary to compute the potential integrals for the BEM-FMM, and solution performance metrics for different hardware/operating system combinations. In the second case, we observe an excellent agreement for electric field distribution across different cranium compartments and, at the same time, a speed improvement of three orders of magnitude when the BEM-FMM algorithm used. Significance. This study may provide a justification for anticipated use of the BEM-FMM algorithm for high-resolution realistic transcranial magnetic stimulation scenarios.

Original languageEnglish
Article number024001
JournalJournal of Neural Engineering
Volume16
Issue number2
Pages (from-to)1-13
ISSN1435-1463
DOIs
Publication statusPublished - Apr 2019

    Research areas

  • boundary element fast multipole method, comparison, finite element method, neurostimulation, numerical modeling, transcranial magnetic stimulation

ID: 56118450