التفاصيل البيبلوغرافية
العنوان: |
Fast EEG/MEG BEM-based forward problem solution for high-resolution head models |
المؤلفون: |
William A. Wartman, Guillermo Nuñez Ponasso, Zhen Qi, Jens Haueisen, Burkhard Maess, Thomas R. Knösche, Konstantin Weise, Gregory M. Noetscher, Tommi Raij, Sergey N. Makaroff |
المصدر: |
NeuroImage, Vol 306, Iss , Pp 120998- (2025) |
بيانات النشر: |
Elsevier, 2025. |
سنة النشر: |
2025 |
المجموعة: |
LCC:Neurosciences. Biological psychiatry. Neuropsychiatry |
مصطلحات موضوعية: |
Electroencephalography (EEG), Magnetoencephalography (MEG), Forward problem, Inverse problem, Adaptive mesh refinement (AMR), Boundary Element Fast Multipole Method (BEM-FMM), Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571 |
الوصف: |
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. |
نوع الوثيقة: |
article |
وصف الملف: |
electronic resource |
اللغة: |
English |
تدمد: |
1095-9572 |
Relation: |
http://www.sciencedirect.com/science/article/pii/S1053811924004956; https://doaj.org/toc/1095-9572 |
DOI: |
10.1016/j.neuroimage.2024.120998 |
URL الوصول: |
https://doaj.org/article/bb4349c665f74ac88c5251435b4cfefa |
رقم الانضمام: |
edsdoj.bb4349c665f74ac88c5251435b4cfefa |
قاعدة البيانات: |
Directory of Open Access Journals |