Journal article
Dose standardization for transcranial electrical stimulation: an accessible approach
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 3.9MB, Terms of use)
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- Publisher copy:
- 10.1038/s41598-025-25649-2
Authors
+ Engineering and Physical Sciences Research Council
More from this funder
- Funder identifier:
- https://ror.org/0439y7842
- Publisher:
- Nature Research
- Journal:
- Scientific Reports More from this journal
- Volume:
- 15
- Issue:
- 1
- Article number:
- 41791
- Publication date:
- 2025-11-25
- Acceptance date:
- 2025-10-23
- DOI:
- EISSN:
-
2045-2322
- ISSN:
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2045-2322
- Language:
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English
- Pubs id:
-
2338423
- UUID:
-
uuid_79f47ddd-211d-4264-8942-9e46f42850a3
- Local pid:
-
pubs:2338423
- Source identifiers:
-
3506562
- Deposit date:
-
2025-11-25
- ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.
Terms of use
- Copyright date:
- 2025
- Licence:
- CC Attribution (CC BY)
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