Personalized transcranial electrical stimulation: A review of computational modeling and optimization

Mo Wang; Kexin Zheng; Yang Xin; Xiang Chen; Yiling Liu; Huichun Luo; Jingsheng Tang; Tifei Yuan; Hongkai Wen; Pengfei Wei; Quanying Liu

doi:10.1088/1741-2552/ae4d8d

March 4, 2026Journal of Neural EngineeringOpen Access

Personalized transcranial electrical stimulation: A review of computational modeling and optimization

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Key Points

The aim is to explore advancements in computational modeling for enhancing personalized transcranial electrical stimulation (tES).
Reviewed existing computational models for personalized tES
Identified challenges in precision neuromodulation
Discussed future directions for optimization
Highlighted key advancements in computational methodologies
Outlined opportunities for improved personalization
Emphasized the need for addressing existing challenges in tES

Implication

This review highlights challenges and opportunities in personalized neuromodulation using computational modeling.

Abstract

By integrating the latest developments in computational modeling for personalized tES, this review highlights current challenges, emerging opportunities, and future directions for achieving precision neuromodulation.

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69abc0de5af8044f7a4e97c9 https://doi.org/10.1088/1741-2552/ae4d8d

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Personalized transcranial electrical stimulation: A review of computational modeling and optimization

Key Points

Implication

Abstract

Discussion

Cite This Study

Personalized transcranial electrical stimulation: A review of computational modeling and optimization

Key Points

Implication

Abstract

Discussion

Cite This Study

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