Evidence map›Paper›PMID 38895215›Full record

ArticlebioRxiv : the preprint server for biology2024

Fast and Accurate EEG/MEG BEM-Based Forward Problem Solution for High-Resolution Head Models.

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

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

William A WartmanDept. of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.ORCID 0000-0001-7286-3313
Guillermo Nuñez PonassoDept. of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.ORCID 0000-0002-2938-6782
Zhen QiDept. of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.
Jens HaueisenTechnische Universität Ilmenau, Ilmenau, Germany.
Burkhard MaessMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Thomas R KnöscheMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Konstantin WeiseMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Gregory M NoetscherDept. of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.ORCID 0000-0001-9786-7206
Tommi RaijAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Sergey N MakaroffDept. of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.

Funding

Re-Wiring the Human BrainR01NS126337 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Tommi Raij · 2022 to 2026
$3.4M
Charge-Based Brain Modeling Engine with Boundary Element Fast Multipole MethodR01MH130490 · NIMH · WORCESTER POLYTECHNIC INSTITUTE · PI Sergey N Makaroff · 2023 to 2026
$3.3M
CRSNS: Development of EEG/MEG Source Reconstruction with Fast Multipole MethodR01EB035484 · NIBIB · WORCESTER POLYTECHNIC INSTITUTE · PI Sergey N Makaroff · 2023 to 2026
$777k
NIBIB NIH HHS R01 EB035484NIMH NIH HHS R01 MH130490NINDS NIH HHS R01 NS126337
6 · The paper itself

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

Indexed as

5-Shell head modelsBoundary Element Fast Multipole Method (BEM-FMM)b-RefinementDetailed head modelsEEG Forward problemMEG Forward problem

Identifiers

PMID38895215
PMCPMC11185788

What OpenQuestion holds

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Registered trials

None linked

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.