Evidence map›Paper›PMID 39938863›Full record

ArticleBrain stimulation

Statistical method accounts for microscopic electric field distortions around neurons when simulating activation thresholds.

Konstantin Weise, Sergey N Makaroff, Ole Numssen, Marom Bikson, Thomas R Knösche

Abstract read
In one paragraph

Article in Brain stimulation. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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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

9 citing papers in PubMed.

  1. Article
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  4. Optimizing and assessing multichannel TMS focality.bioRxiv : the preprint server for biology · 2025
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Konstantin WeiseLeipzig University of Applied Sciences, Leipzig, Germany; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. Electronic address: kweise@cbs.mpg.de.
Sergey N MakaroffECE Department, Math Department, Worcester Polytechnic Institute, Worcester, MA, USA; Massachusetts General Hospital, Boston, MA, USA.
Ole NumssenMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Marom BiksonThe City College of New York, NY, USA.
Thomas R KnöscheMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Technische Universität Ilmenau, Ilmenau, Germany.

Funding

Charge-Based Brain Modeling Engine with Boundary Element Fast Multipole MethodR01MH130490 · NIMH · WORCESTER POLYTECHNIC INSTITUTE · PI Sergey N Makaroff · 2023 to 2026
$3.3M
Open-source computational modeling of Spinal Cord Stimulation (SCS) to enhance dissemination of 1R01NS112996R01NS112996 · NINDS · CITY COLLEGE OF NEW YORK · PI BIKSON, MAROM · 2020 to 2024
$2.0M
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 NS112996
6 · The paper itself

Abstract

introductionNotwithstanding advances in computational models of neuromodulation, there are mismatches between simulated and experimental activation thresholds. Transcranial Magnetic Stimulation (TMS) of the primary motor cortex generates motor evoked potentials (MEPs). At the threshold of MEP generation, whole-head models predict macroscopic (at millimeter scale) electric fields (50-70 V/m) which are considerably below conventionally simulated cortical neuron thresholds (175-350 V/m).

methodsWe hypothesize that this apparent contradiction is in part a consequence of electrical field warping by brain microstructure. Classical neuronal models ignore the physical presence of neighboring neurons and microstructure and assume that the macroscopic field directly acts on the neurons. In previous work, we performed advanced numerical calculations considering realistic microscopic compartments (e.g., cells, blood vessels), resulting in locally inhomogeneous (micrometer scale) electric field and altered neuronal activation thresholds. Here we combine detailed neural threshold simulations under homogeneous field assumptions with microscopic field calculations, leveraging a novel statistical approach.

resultsWe show that, provided brain-region specific microstructure metrics, a single statistically derived scaling factor between microscopic and macroscopic electric fields can be applied in predicting neuronal thresholds. For the cortical sample considered, the statistical method matches TMS experimental thresholds.

conclusionsOur approach can be broadly applied to neuromodulation models, where fully coupled microstructure scale simulations may not be computationally tractable.

Indexed as

Evoked Potentials, MotorModels, NeurologicalMotor CortexNeuronsTranscranial Magnetic StimulationComputer SimulationElectromagnetic FieldsHumansBiophysical modelingBrain stimulationMultiscale brain modelingTMS

Identifiers

PMID39938863
PMCPMC12009170

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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.