ArticleBrain topography2026
Improved Source Localization of Auditory Evoked Fields using Reciprocal BEM-FMM.
Article in Brain topography, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Selective Modulation of Evidence Accumulation by Hippocampal Theta Oscillations During Mnemonic Decision-Making.Human brain mapping · 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
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13 authors.
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Abstract
Precise localization of auditory evoked fields (AEFs) from magnetoencephalography (MEG) data is very important for the functional understanding of the auditory cortex in medicine and cognitive neuroscience. The numerical solution of the field equations in the human head using the boundary element method (BEM) is a powerful tool for achieving this. The spatial resolution of the BEM is crucial for the achievable accuracy of localized neural sources. However, in classical BEM (as implemented, e.g., in MNE-Python), very high resolutions are impractical due to the associated prohibitive computational effort. In contrast, our recently introduced reciprocal boundary element fast multipole method (reciprocal BEM-FMM) allows for hitherto unprecedented spatial resolution of forward models. In this work, we employ reciprocal BEM-FMM to construct high-resolution forward models to localize AEFs. Simulated AEFs were generated using a direct BEM-FMM approach on realistic 40-tissue Sim4Life segmentations. Comparative analyses from simulated data demonstrate that high-resolution BEM-FMM forward models yield statistically superior source estimates relative to the 3-layer BEM. We also compare BEM-FMM forward models with source dipole resolution varying from 25,000 to 3,200,000 sources, and find that resolutions above 200,000 sources are sufficient for achieving accurate, high-resolution source estimates. We therefore recommend using the high-resolution reciprocal BEM-FMM to utilize high spatial anatomical precision for the modeling of neural activity.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.