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Multi-objective optimization via evolutionary algorithm (MOVEA) for high-definition transcranial electrical

Mo Wang1, Kexin Lou2, Zeming Liu1

  • 1Department of Biomedical Engineering, Southern University of Science and Technology, China.

Neuroimage
|August 21, 2023
PubMed
Summary

Designing effective transcranial electrical stimulation (tES) is complex. A new framework, MOVEA, optimizes multiple stimulation goals simultaneously, improving focality and intensity for tES applications like tACS and tTIS.

Keywords:
Evolutionary algorithmMulti-objective optimizationPersonalized neuromodulationTranscranial alternating current stimulation (tACS)Transcranial electrical stimulation (tES)Transcranial temporal interference stimulation (tTIS)

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Computational Neuroscience

Background:

  • Transcranial electrical stimulation (tES) design involves balancing conflicting objectives like intensity, focality, and depth.
  • Existing methods often require predefined directions or manual adjustments, limiting optimization flexibility.

Purpose of the Study:

  • To introduce a general framework, Multi-Objective Optimization via Evolutionary Algorithm (MOVEA), for designing tES strategies.
  • To enable simultaneous optimization of multiple, often conflicting, tES objectives without predefined directions.

Main Methods:

  • Developed MOVEA, a Pareto optimization framework utilizing evolutionary algorithms.
  • Applied MOVEA to compare transcranial alternating current stimulation (tACS) and transcranial temporal interference stimulation (tTIS) systems (HD and two-pair).
  • Evaluated stimulation intensity, focality, and steerability across different target depths and in eight subjects.

Main Results:

  • MOVEA generates a Pareto front of optimal solutions, respecting trade-offs between objectives like intensity and focality.
  • Transcranial temporal interference stimulation (tTIS) improved focality by 60% compared to other methods.
  • High-definition tACS/tTIS achieved higher maximum intensities than two-pair tTIS, with individual differences noted in optimal protocols.

Conclusions:

  • MOVEA offers a versatile approach for optimizing tES strategies, applicable to tACS and tTIS.
  • Findings highlight tTIS's advantage in focality and guide the selection of stimulation systems based on specific objectives.
  • Personalized stimulation protocols are crucial due to observed inter-subject variability.