Comparative performance of the finite element method and the boundary element fast multipole method for problems mimicking transcranial magnetic stimulation (TMS)
Year: 2019
Type: article
Abstract: 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. 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. 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. This study may provide a justification for anticipated use of the BEM-FMM algorithm for high-resolution realistic transcranial magnetic stimulation scenarios.
Source: Journal of Neural Engineering
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: bronze
Funders: Lundbeckfonden, Novo Nordisk, Danmarks Tekniske Universitet, Novo Nordisk Fonden, National Institutes of Health, National Institute of Mental Health, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institute of Biomedical Imaging and Bioengineering, U.S. National Library of Medicine, Division of Mathematical Sciences
Awards: Modeling TMS-induced Cortical Network Activity, G2311230054, Modeling TMS-induced Cortical Network Activity, On-Body Passive-RFID Antenna Array and Testbed to Assess Changes in Bone Structure, G4844452946, Integrated multichannel system for transcranial magnetic stimulation and parallel magnetic resonance imaging, G6044503446, G6511987614, Visible Human Project Full Body Finite-Element Phantom and Workflow
OpenAlex ID: W2949423550