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Dose standardization for transcranial electrical stimulation: an accessible approach.

Jake Toth1,2,3,4, Méadhbh Brosnan5,6,7,8, Rory-Jay King9,10,11

  • 1School of Electrical and Electronic Engineering, University of Sheffield, Sheffield, S1 3JD, UK. jake.toth@eng.ox.ac.uk.

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Summary

This study introduces a new method to standardize transcranial electrical stimulation (tES) dosage by predicting electric field strengths, reducing variability in brain stimulation for better consistency.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Medical Physics

Background:

  • Transcranial electrical stimulation (tES) is a non-invasive brain stimulation technique.
  • High inter-individual variability in induced electric fields (E-fields) leads to inconsistent tES dosing.
  • Current methods often require participant-specific imaging and complex modeling.

Purpose of the Study:

  • To develop and validate a novel dose standardization method for tES.
  • To predict and reduce peak E-field strength variability without structural imaging.
  • To enable consistent tES dosing across diverse individuals.

Main Methods:

  • Trained multiple linear regression models to predict peak E-field strengths.
  • Utilized demographic and morphological parameters from 418 healthy adults.
  • Developed both montage-specific and montage-agnostic models incorporating inter-electrode distances.

Main Results:

  • The proposed method significantly reduced peak E-field strength variation for conventional tES montages.
  • Montage-specific models explained 43% of variability in conventional montages and 21% in HD montages.
  • Montage-agnostic models explained 36% of variability in conventional montages and 13% in HD montages.

Conclusions:

  • The developed dose standardization method offers a robust and practical advancement over fixed dosing in tES.
  • The approach demonstrates consistent performance on unseen data, paving the way for more reliable tES applications.
  • Further refinement may be needed for high-definition (HD) tES montages to achieve similar variability reduction.