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Perspectives on Optimized Transcranial Electrical Stimulation Based on Spatial Electric Field Modeling in Humans.
- Source :
- Journal of Clinical Medicine; Jun2024, Vol. 13 Issue 11, p3084, 31p
- Publication Year :
- 2024
-
Abstract
- Background: Transcranial electrical stimulation (tES) generates an electric field (or current density) in the brain through surface electrodes attached to the scalp. Clinical significance has been demonstrated, although with moderate and heterogeneous results partly due to a lack of control of the delivered electric currents. In the last decade, computational electric field analysis has allowed the estimation and optimization of the electric field using accurate anatomical head models. This review examines recent tES computational studies, providing a comprehensive background on the technical aspects of adopting computational electric field analysis as a standardized procedure in medical applications. Methods: Specific search strategies were designed to retrieve papers from the Web of Science database. The papers were initially screened based on the soundness of the title and abstract and then on their full contents, resulting in a total of 57 studies. Results: Recent trends were identified in individual- and population-level analysis of the electric field, including head models from non-neurotypical individuals. Advanced optimization techniques that allow a high degree of control with the required focality and direction of the electric field were also summarized. There is also growing evidence of a correlation between the computationally estimated electric field and the observed responses in real experiments. Conclusions: Computational pipelines and optimization algorithms have reached a degree of maturity that provides a rationale to improve tES experimental design and a posteriori analysis of the responses for supporting clinical studies. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20770383
- Volume :
- 13
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- Journal of Clinical Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 177872325
- Full Text :
- https://doi.org/10.3390/jcm13113084