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Fast and accurate EEG/MEG BEM-based forward problem solution for high-resolution head models

MPS-Authors
/persons/resource/persons19833

Maess,  Burkhard       
Methods and Development Group Brain Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons19779

Knösche,  Thomas R.       
Methods and Development Group Brain Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons212471

Weise,  Konstantin       
Methods and Development Group Brain Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

External Resource

https://github.com/wiwartman/BEM-FMM-with-B-Refinement-for-EEG
(Code)

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Fulltext (public)

Wartman_Ponasso_pre.pdf
(Preprint), 3MB

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Citation

Wartman, W. A., Ponasso, G. C. N., Qi, Z., Haueisen, J., Maess, B., Knösche, T. R., et al. (2024). Fast and accurate EEG/MEG BEM-based forward problem solution for high-resolution head models. bioRxiv. doi:10.1101/2024.06.07.598024.


Cite as: https://hdl.handle.net/21.11116/0000-000F-6401-F
Abstract
A BEM (boundary element method) based approach is developed to accurately solve an EEG/MEG forward problem for a modern high-resolution head model in approximately 60 seconds using a common workstation. The method utilizes a charge-based BEM with fast multipole acceleration (BEM-FMM) and a "smart" mesh pre-refinement (called b-refinement) close to the singular source(s). No costly matrix-filling or direct solution steps typical for the standard BEM are required; the method generates on-skin voltages as well as MEG magnetic fields for high-resolution head models in approximately 60 seconds after initial model assembly. The method is verified both theoretically and experimentally.