Evidence map›Paper›PMID 29993385›Full record

ArticleIEEE transactions on bio-medical engineering2018

A Quasi-Static Boundary Element Approach With Fast Multipole Acceleration for High-Resolution Bioelectromagnetic Models.

Sergey N Makarov, Gregory M Noetscher, Tommi Raij, Aapo Nummenmaa

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing 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

46 citing papers in PubMed.

  1. Article
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  16. A survey on integral equations for bioelectric modeling.Physics in medicine and biology · 2024
    Review
  17. Quasistatic approximation in neuromodulation.Journal of neural engineering · 2024
    Review
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sergey N Makarov
Gregory M Noetscher
Tommi Raij
Aapo Nummenmaa

Funding

Scalable Software for Distributed Processing and Visualization of Multi-Site MEG/EEG DatasetsR01NS104585 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI MATTI HAMALAINEN · 2018 to 2026
$4.3M
Mapping the intrinsic functional organization of auditory cortex in individual subjects using 7T MRIR01DC017991 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI AHVENINEN, JYRKI · 2019 to 2023
$4.0M
Integrated multichannel system for transcranial magnetic stimulation and parallel magnetic resonance imagingR01MH111829 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI NUMMENMAA, AAPO · 2016 to 2019
$3.2M
Non-invasive measures of multisensory cortical feedforward and feedback influencesR01DC016765 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI AHLFORS, SEPPO PENTTI, AHVENINEN, JYRKI · 2018 to 2022
$2.7M
Non-invasive integrated system for brain stimulation and magnetocorticographyR44NS090894 · NINDS · TRISTAN TECHNOLOGIES, INC. · PI PAULSON, DOUGLAS N · 2015 to 2018
$2.4M
Human Neocortical NeurosolverR01EB022889 · NIBIB · BROWN UNIVERSITY · PI HAMALAINEN, MATTI, HINES, MICHAEL L · 2016 to 2018
$1.7M
Modeling TMS-induced Cortical Network ActivityR00EB015445 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI NUMMENMAA, AAPO · 2015 to 2017
$747k
On-Body Passive-RFID Antenna Array and Testbed to Assess Changes in Bone StructureR43AR071220 · NIAMS · NEVA ELECTROMAGNETICS, LLC · PI MAKAROFF, SERGEY N · 2017 to 2017
$225k
Modeling TMS-induced Cortical Network ActivityK99EB015445 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI NUMMENMAA, AAPO · 2013 to 2014
$180k
Visible Human Project Full Body Finite-Element Phantom and WorkflowR43LM012352 · NLM · NEVA ELECTROMAGNETICS, LLC · PI MAKAROFF, SERGEY N · 2015 to 2015
$149k
NIAMS NIH HHS R43 AR071220NIBIB NIH HHS K99 EB015445NIBIB NIH HHS R00 EB015445NIBIB NIH HHS R01 EB022889NIDCD NIH HHS R01 DC016765NIDCD NIH HHS R01 DC017991NIMH NIH HHS R01 MH111829NINDS NIH HHS R01 NS104585NINDS NIH HHS R44 NS090894NLM NIH HHS R43 LM012352
6 · The paper itself

Abstract

objectiveWe develop a new accurate version of the boundary element fast multipole method for transcranial magnetic stimulation (TMS) related problems. This method is based on the surface-charge formulation and is using the highly efficient fast multipole accelerator along with analytical computations of neighbor surface integrals.

resultsThe method accuracy is demonstrated by comparison with the proven commercial finite-element method (FEM) software ANSYS Maxwell 18.2 2017 operating on unstructured grids and with adaptive mesh refinement. Five realistic high-definition head models from the Population Head Repository (IT'IS Foundation, Switzerland) have been acquired and augmented with a commercial TMS coil model (MRi-B91, MagVenture, Denmark). For each head model, simulations with our method and simulations with the FEM software ANSYS Maxwell 18.2 2017 have been performed. These simulations have been compared with each other and an excellent agreement was established in every case. SIGNIFICANCE: At the same time, our new method runs approximately 500 times faster than the ANSYS FEM, finishes in about 200 s on a standard server, and naturally provides a submillimeter field resolution, which is justified using mesh refinement.

conclusionsOur method can be applied to modeling of brain stimulation and recording technologies such as TMS and magnetoencephalography, and has the potential to become a real-time high-resolution simulation tool.

Indexed as

Finite Element AnalysisBrainHeadHumansImage Processing, Computer-AssistedMagnetoencephalographySignal Processing, Computer-AssistedTranscranial Magnetic Stimulation

Identifiers

PMID29993385
PMCPMC7388683

What OpenQuestion holds

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Registered trials

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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.