ArticleIEEE transactions on bio-medical engineering2021
Boundary Element Fast Multipole Method for Enhanced Modeling of Neurophysiological Recordings.
Article in IEEE transactions on bio-medical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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27 citing papers in PubMed.
- Charge based boundary element method with residual driven adaptive mesh refinement for high resolution electrical stimulation modeling.Scientific reports · 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
- High-definition MEG source estimation using the reciprocal boundary element fast multipole method.NeuroImage · 2025Article
- High-Resolution EEG Source Reconstruction from PCA-Corrected BEM-FMM Reciprocal Basis Funcions: A Study with Visual Evoked Potentials from Intermittent Photic Stimulation.bioRxiv : the preprint server for biology · 2025Article
- Article
- [Fontanel compensation for infant electroencephalography forward modeling method].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024Article
- Improving EEG Forward Modeling Using High-Resolution Five-Layer BEM-FMM Head Models: Effect on Source Reconstruction Accuracy.Bioengineering (Basel, Switzerland) · 2024Article
- A survey on integral equations for bioelectric modeling.Physics in medicine and biology · 2024Review
- CutFEM-based MEG forward modeling improves source separability and sensitivity to quasi-radial sources: A somatosensory group study.Human brain mapping · 2024Review
- Quasistatic approximation in neuromodulation.Journal of neural engineering · 2024Review
- Fast and Accurate EEG/MEG BEM-Based Forward Problem Solution for High-Resolution Head Models.bioRxiv : the preprint server for biology · 2024Article
- An adaptive h-refinement method for the boundary element fast multipole method for quasi-static electromagnetic modeling.Physics in medicine and biology · 2024Article
- Estimations of Charge Deposition Onto Convoluted Axon Surfaces Within Extracellular Electric Fields.IEEE transactions on bio-medical engineering · 2024Article
- How to assess the accuracy of volume conduction models? A validation study with stereotactic EEG data.Frontiers in human neuroscience · 2024Article
- A fast direct solver for surface-based whole-head modeling of transcranial magnetic stimulation.Scientific reports · 2023Article
- An Adaptive H-Refinement Method for the Boundary Element Fast Multipole Method for Quasi-static Electromagnetic Modeling.bioRxiv : the preprint server for biology · 2023Article
- Influence of charges deposited on membranes of human hyperdirect pathway axons on depolarization during subthalamic deep brain stimulation.Journal of neural engineering · 2023Article
- Brainstorm-DUNEuro: An integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity.NeuroImage · 2023Article
- Bioelectromagnetism in Human Brain Research: New Applications, New Questions.The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry · 2023Review
- Modeling transcranial magnetic stimulation coil with magnetic cores.Journal of neural engineering · 2023Article
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6 authors.
Funding
Abstract
objectiveA new numerical modeling approach is proposed which provides forward-problem solutions for both noninvasive recordings (EEG/MEG) and higher-resolution intracranial recordings (iEEG).
methodsThe algorithm is our recently developed boundary element fast multipole method or BEM-FMM. It is based on the integration of the boundary element formulation in terms of surface charge density and the fast multipole method originating from its inventors. The algorithm still possesses the major advantage of the conventional BEM - high speed - but is simultaneously capable of processing a very large number of surface-based unknowns. As a result, an unprecedented spatial resolution could be achieved, which enables multiscale modeling.
resultsFor non-invasive EEG/MEG, we are able to accurately solve the forward problem with approximately 1 mm anatomical resolution in the cortex within 1-2 min given several thousand cortical dipoles. Targeting high-resolution iEEG, we are able to compute, for the first time, an integrated electromagnetic response for an ensemble (2,450) of tightly packed realistic pyramidal neocortical neurons in a full-head model with 0.6 mm anatomical cortical resolution. The neuronal arbor is comprised of 5.9 M elementary 1.2 μm long dipoles. On a standard server, the computations require about 5 min.
conclusionOur results indicate that the BEM-FMM approach may be well suited to support numerical multiscale modeling pertinent to modern high-resolution and submillimeter iEEG. SIGNIFICANCE: Based on the speed and ease of implementation, this new algorithm represents a method that will greatly facilitate simulations at multi-scale across a variety of applications.
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