Evidence map›Paper›PMID 37716590›Full record

SynthesisNeuroImage2023

Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study.

Sybren Van Hoornweder, Marten Nuyts, Joana Frieske, Stefanie Verstraelen, Raf L J Meesen, Kevin A Caulfield

Abstract readSystematic Review
In one paragraph

Synthesis in NeuroImage, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 2 mA is NOT 2 mA: Electric field variability in high-definition tDCS and its implications for precision neuromodulation in aging.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2026
    Article
  3. Review
  4. Females have shorter scalp-to-cortex distances and receive stronger TMS electrical fields: Implications for clinical treatment.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Article
  5. Review
  6. Emotional and Social Dimension of Abstract Concepts Meet with Interoception in Right Anterior Insula.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  7. Article
  8. Variable E-field properties of dual-site tACS with phase lags.Imaging neuroscience (Cambridge, Mass.) · 2026
    Article
  9. Review
  10. Group optimization methods for dose planning in tES.Journal of neural engineering · 2025
    Article
  11. Review
  12. Review
  13. Article
  14. Electric-field-based dosing for TMS.Imaging neuroscience (Cambridge, Mass.) · 2024
    Article
  15. Article
  16. Review
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Sybren Van HoornwederREVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium. Electronic address: sybren.vanhoornweder@uhasselt.be.
Marten NuytsREVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium.
Joana FrieskeREVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium; Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, Leuven, Belgium.
Stefanie VerstraelenREVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium.
Raf L J MeesenREVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium; Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, Leuven, Belgium.
Kevin A CaulfieldBrain Stimulation Laboratory, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, United States. Electronic address: caulfiel@musc.edu.

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
Techniques DevelopmentP2CHD086844 · NICHD · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BOGER, HEATHER A · 2015 to 2024
$12.7M
TRD4 - Ultrahigh Field Engineering and SafetyP41EB027061 · NIBIB · UNIVERSITY OF MINNESOTA · PI Mehmet Akcakaya · 2019 to 2026
$11.7M
Computer Aided Diagnostic System for Prostate Cancer Detection Using Quantitative Multiparametric MRIR01CA241159 · NCI · UNIVERSITY OF MINNESOTA · PI METZGER, GREGORY JOHN · 2021 to 2025
$3.0M
Personalizing tDCS Dose in Healthy Adults and Chronic Ischemic StrokeF31NS126019 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI CAULFIELD, KEVIN A. · 2022 to 2023
$81k
NCI NIH HHS R01 CA241159NIBIB NIH HHS P41 EB027061NICHD NIH HHS P2C HD086844NIMH NIH HHS U54 MH091657NINDS NIH HHS F31 NS126019
6 · The paper itself

Abstract

backgroundElectric field (E-field) modeling is a potent tool to estimate the amount of transcranial magnetic and electrical stimulation (TMS and tES, respectively) that reaches the cortex and to address the variable behavioral effects observed in the field. However, outcome measures used to quantify E-fields vary considerably and a thorough comparison is missing.

objectivesThis two-part study aimed to examine the different outcome measures used to report on tES and TMS induced E-fields, including volume- and surface-level gray matter, region of interest (ROI), whole brain, geometrical, structural, and percentile-based approaches. The study aimed to guide future research in informed selection of appropriate outcome measures.

methodsThree electronic databases were searched for tES and/or TMS studies quantifying E-fields. The identified outcome measures were compared across volume- and surface-level E-field data in ten tES and TMS modalities targeting two common targets in 100 healthy individuals.

resultsIn the systematic review, we extracted 308 outcome measures from 202 studies that adopted either a gray matter volume-level (n = 197) or surface-level (n = 111) approach. Volume-level results focused on E-field magnitude, while surface-level data encompassed E-field magnitude (n = 64) and normal/tangential E-field components (n = 47). E-fields were extracted in ROIs, such as brain structures and shapes (spheres, hexahedra and cylinders), or the whole brain. Percentiles or mean values were mostly used to quantify E-fields. Our modeling study, which involved 1,000 E-field models and > 1,000,000 extracted E-field values, revealed that different outcome measures yielded distinct E-field values, analyzed different brain regions, and did not always exhibit strong correlations in the same within-subject E-field model.

conclusionsOutcome measure selection significantly impacts the locations and intensities of extracted E-field data in both tES and TMS E-field models. The suitability of different outcome measures depends on the target region, TMS/tES modality, individual anatomy, the analyzed E-field component and the research question. To enhance the quality, rigor, and reproducibility in the E-field modeling domain, we suggest standard reporting practices across studies and provide four recommendations.

Indexed as

BrainTranscranial Direct Current StimulationCerebral CortexElectricityGray MatterHumansReproducibility of ResultsTranscranial Magnetic StimulationElectric field (E-field) modelingFinite element method (FEM)Region of interest (ROI) analysesTranscranial direct current stimulation (tDCS)Transcranial electrical stimulation (tES)Whole brain analyses

Identifiers

PMID37716590
PMCPMC11008458

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.