Evidence map›Paper›PMID 38826206›Full record

ArticlebioRxiv : the preprint server for biology2024

Accuracy of dipole source reconstruction in the 3-layer BEM model against the 5-layer BEM-FMM model.

Guillermo Nuñez Ponasso, Ryan C McSweeney, William A Wartman, Peiyao Lai, Jens Haueisen, Burkhard Maess, Thomas R Knösche, Konstantin Weise, Gregory M Noetscher, Tommi Raij and 1 more

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.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Guillermo Nuñez PonassoDept. of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.ORCID 0000-0002-2938-6782
Ryan C McSweeneyDept. of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.
William A WartmanDept. of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.
Peiyao LaiDept. of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.
Jens HaueisenTechnische Universität Ilmenau, Ilmenau, Germany.
Burkhard MaessMax Plank Insititute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Thomas R KnöscheMax Plank Insititute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Konstantin WeiseMax Plank Insititute 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

Objective: To compare cortical dipole fitting spatial accuracy between the widely used yet highly simplified 3-layer and modern more realistic 5-layer BEM-FMM models with and without Methods: We generate simulated noiseless 256-channel EEG data from 5-layer (7-compartment) meshes of 15 subjects from the Connectome Young Adult dataset. For each subject, we test four dipole positions, three sets of conductivity values, and two types of head segmentation. We use the Results: The average position error (across all tested dipoles, subjects, and models) is ~4 mm, with a standard deviation of ~2 mm. The orientation error is ~20° on average, with a standard deviation of ~15°. Without AMR, the numerical inaccuracies produce a larger disagreement between the 3- and 5-layer models, with an average position error of ~8 mm (6 mm standard deviation), and an orientation error of 28° (28° standard deviation). Conclusions: The low-resolution 3-layer models provide excellent accuracy in dipole localization. On the other hand, dipole orientation is retrieved less accurately. Therefore, certain applications may require more realistic models for practical source reconstruction. AMR is a critical component for improving the accuracy of forward EEG computations using a high-resolution 5-layer volume conduction model. Significance: Improving EEG source reconstruction accuracy is important for several clinical applications, including epilepsy and other seizure-inducing conditions.

Indexed as

adaptative mesh refinement (AMR)boundary element method (BEM)EEG dipole reconstructionEEG source analysiselectroencephalography (EEG)fast multipole method (FMM)head modeling

Identifiers

PMID38826206
PMCPMC11142039

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