Boundary Element Fast Multipole Method for Enhanced Modeling of Neurophysiological Recordings.


Journal

IEEE transactions on bio-medical engineering
ISSN: 1558-2531
Titre abrégé: IEEE Trans Biomed Eng
Pays: United States
ID NLM: 0012737

Informations de publication

Date de publication:
01 2021
Historique:
pubmed: 4 8 2020
medline: 25 6 2021
entrez: 4 8 2020
Statut: ppublish

Résumé

A new numerical modeling approach is proposed which provides forward-problem solutions for both noninvasive recordings (EEG/MEG) and higher-resolution intracranial recordings (iEEG). The 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. For 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. Our results indicate that the BEM-FMM approach may be well suited to support numerical multiscale modeling pertinent to modern high-resolution and submillimeter iEEG. 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.

Identifiants

pubmed: 32746015
doi: 10.1109/TBME.2020.2999271
pmc: PMC7704617
mid: NIHMS1616388
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

308-318

Subventions

Organisme : NIDCD NIH HHS
ID : R01 DC016915
Pays : United States
Organisme : NLM NIH HHS
ID : R43 LM012352
Pays : United States
Organisme : NINDS NIH HHS
ID : R44 NS090894
Pays : United States
Organisme : NIMH NIH HHS
ID : R13 MH127866
Pays : United States
Organisme : NIBIB NIH HHS
ID : R00 EB015445
Pays : United States
Organisme : NIBIB NIH HHS
ID : K99 EB015445
Pays : United States
Organisme : NIDCD NIH HHS
ID : R01 DC017991
Pays : United States
Organisme : NIDCD NIH HHS
ID : R01 DC016765
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB022889
Pays : United States
Organisme : NIAMS NIH HHS
ID : R43 AR071220
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH111829
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS104585
Pays : United States

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