Evidence map›Paper›PMID 37736398›Full record

ArticleFrontiers in neural circuits2023

Template MRI scans reliably approximate individual and group-level tES and TMS electric fields induced in motor and prefrontal circuits.

Jennifer Y Cho, Sybren Van Hoornweder, Christopher T Sege, Michael U Antonucci, Lisa M McTeague, Kevin A Caulfield

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neural circuits, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 32% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
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

6 authors at 3 institutions in 2 countries.

Jennifer Y ChoDepartment of Neuroscience, Medical University of South Carolina, Charleston, SC, United States.
Sybren Van HoornwederFaculty of Rehabilitation Sciences, REVAL-Rehabilitation Research Center, Hasselt University, Diepenbeek, Belgium.
Christopher T SegeDepartment of Psychiatry, Medical University of South Carolina, Charleston, SC, United States.
Michael U AntonucciDepartment of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, United States.
Lisa M McTeagueDepartment of Psychiatry, Medical University of South Carolina, Charleston, SC, United States.
Kevin A CaulfieldDepartment of Neuroscience, Medical University of South Carolina, Charleston, SC, United States.
Medical University of South Carolina · USHasselt University · BERalph H. Johnson VA Medical Center · US

Funding

TREATING ETHANOL WITHDRAWAL WITH LORAZEPAM/NALTREXONEP50AA010761 · NIAAA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI Patrick J. Mulholland · 1996 to 2026
$46.8M
Treating Depression and Enhancing Locomotor Recovery Post-strokeP20GM109040 · NIGMS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI KAUTZ, STEVEN A. · 2014 to 2024
$23.5M
Techniques DevelopmentP2CHD086844 · NICHD · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI THOMPSON, AIKO · 2015 to 2024
$12.7M
Personalizing tDCS Dose in Healthy Adults and Chronic Ischemic StrokeF31NS126019 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI CAULFIELD, KEVIN A. · 2022 to 2023
$81k
NIAAA NIH HHS P50 AA010761NICHD NIH HHS P2C HD086844NIGMS NIH HHS P20 GM109040NINDS NIH HHS F31 NS126019
6 · The paper itself

Abstract

Background: Electric field (E-field) modeling is a valuable method of elucidating the cortical target engagement from transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES), but it is typically dependent on individual MRI scans. In this study, we systematically tested whether E-field models in template MNI-152 and Ernie scans can reliably approximate group-level E-fields induced in Methods: We computed 788 E-field models using the CHARM-SimNIBS 4.0.0 pipeline with 4 E-field models per participant (motor and prefrontal targets for TMS and tES). We additionally calculated permutation analyses to determine the point of stability of E-fields to assess whether the 152 brains represented in the MNI-152 template is sufficient. Results: Group-level E-fields did not significantly differ between the individual vs. MNI-152 template and Ernie scans for any stimulation modality or location ( Conclusion: MNI-152 and Ernie models reliably estimate group-average TMS and tES-induced E-fields transdiagnostically. The MNI-152 template includes sufficient scans to control for interindividual anatomical differences (i.e., above the point of stability). Taken together, using the MNI-152 and Ernie brains to approximate group-level E-fields is a valid and reliable approach.

Indexed as

Transcranial Direct Current StimulationTranscranial Magnetic StimulationAnxietyBrainHumansMagnetic Resonance Imagingelectric field (E-field) modelingfinite element method (FEM)MNI-152non-invasive brain stimulationtDCStemplate MRI scantESTMS

Identifiers

PMID37736398
PMCPMC10510202
OpenAlexW4386476226

What OpenQuestion holds

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LicenceCC BY
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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.