ArticleNeuroImage2025
Fast EEG/MEG BEM-based forward problem solution for high-resolution head models.
Article in NeuroImage, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Charge based boundary element method with residual driven adaptive mesh refinement for high resolution electrical stimulation modeling.Scientific reports · 2026Article
- Article
- Selective Modulation of Evidence Accumulation by Hippocampal Theta Oscillations During Mnemonic Decision-Making.Human brain mapping · 2026Article
- Charge Based Boundary Element Method with Residual Driven Adaptive Mesh Refinement for High Resolution Electrical Stimulation Modeling.bioRxiv : the preprint server for biology · 2026Article
- Improved Source Localization of Auditory Evoked Fields using Reciprocal BEM-FMM.Brain topography · 2026Article
- Inferring neural sources from electroencephalography: foundations and frontiers.Journal of neural engineering · 2026Review
- High-definition MEG source estimation using the reciprocal boundary element fast multipole method.NeuroImage · 2025Article
- Improving EEG Forward Modeling Using High-Resolution Five-Layer BEM-FMM Head Models: Effect on Source Reconstruction Accuracy.Bioengineering (Basel, Switzerland) · 2024Article
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Abstract
A fast BEM (boundary element method) based approach is developed to solve an EEG/MEG forward problem for a modern high-resolution head model. The method utilizes a charge-based BEM accelerated by the fast multipole method (BEM-FMM) with an adaptive mesh pre-refinement method (called b-refinement) close to the singular dipole 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 within 90 s after initial model assembly using a regular workstation. The forward method is validated by comparison against an analytical solution on a spherical shell model as well as comparison against a full h-refinement method on realistic 1M facet human head models, both of which yield agreement to within 5 % for the EEG skin potential and MEG magnetic fields. The method is further applied to an EEG source localization (inverse) problem for real human data, and a reasonable source dipole distribution is found.
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