ArticleScientific reports2025
Dose standardization for transcranial electrical stimulation: an accessible approach.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Transcranial electrical stimulation (tES) is a widely used non-invasive brain stimulation technique. However, due to high inter-individual variability in the induced electric fields (E-fields), a fixed stimulation current delivers an inconsistent dose. We developed a dose standardization method without the requirement of participant-specific structural imaging and E-field modeling. Robust multiple linear regression models were trained to predict peak E-field strengths across 10 electrode montages and 418 healthy adults. These regression models predicted peak E-field strengths in unseen participants from accessible demographic and morphological parameters. Estimated peak E-field strength values were subsequently used to standardize tES dosages across our population. Additionally, we developed montage-agnostic models which incorporated inter-electrode distances for each participant. Compared to fixed dosing, our approach significantly reduced peak E-field strength variation for conventional montages, though results were inconsistent for high-definition (HD) montages. Models trained on specific montages accounted for 43% of peak E-field strength variability in conventional montages and 21% in HD montages on average. Our montage-agnostic models accounted for 36% and 13% of the average peak E-field strength variability for conventional and HD montages, respectively. These results have been validated across a large dataset, demonstrating robust performance against unseen data, a significant advancement over current approaches.
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Registered trials
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