Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study
•This combined systematic review and modeling study identified 308 studies reporting tES or TMS E-Field values.•The effect of outcome measures on tES and TMS modeling results was quantified via over 1000,000 measurements.•Outcome measure choices critically affect the obtained E-field value and analy...
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Published in | NeuroImage (Orlando, Fla.) Vol. 281; p. 120379 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.11.2023
Elsevier Limited Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | •This combined systematic review and modeling study identified 308 studies reporting tES or TMS E-Field values.•The effect of outcome measures on tES and TMS modeling results was quantified via over 1000,000 measurements.•Outcome measure choices critically affect the obtained E-field value and analyzed brain region.•Between-measure differences are E-field component-, person-, modality, and region specific.•We present four recommendations to enhance the quality, consistency, and rigor of E-field outcome reporting.
Electric 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.
This 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.
Three 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.
In 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.
Outcome 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. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Feature-3 ObjectType-Evidence Based Healthcare-1 ObjectType-Undefined-1 content type line 23 These authors share last-authorship |
ISSN: | 1053-8119 1095-9572 1095-9572 |
DOI: | 10.1016/j.neuroimage.2023.120379 |