Unification of optimal targeting methods in transcranial electrical stimulation

Area of Science:

• Neuroscience
• Biomedical Engineering
• Computational Modeling

Background:

• High-density transcranial electrical stimulation (TES) presents challenges in optimizing current delivery for targeted brain regions.
• Existing methods for current distribution, such as least squares (LS) and reciprocity-based approaches, lack a unified theoretical framework.
• Defining optimality and formulating the mathematical optimization problem are crucial for effective TES.

Purpose of the Study:

• To theoretically unify and analyze various current distribution methods in high-density TES.
• To demonstrate that simple closed-form solutions are specific cases of a more general optimization problem.
• To elucidate the intensity-focality trade-off in TES targeting.

Main Methods:

• Mathematical formulation of an extended optimization problem for TES current distribution.
• Theoretical proof demonstrating that LS, weighted LS (WLS), and reciprocity-based solutions are specific instances of the extended problem.
• Validation through computational simulations on an atlas head model.

Main Results:

• The LS, WLS, and reciprocity-based solutions are identified as specific cases of a directional intensity maximization problem.
• These solutions represent extreme points of an intensity-focality trade-off, influenced by constraints on electric fields in non-target regions.
• A unified approach is presented, offering a clearer understanding of TES optimization.

Conclusions:

• The study provides a unified theoretical framework for understanding TES current optimization.
• This unified approach clarifies the relationship between different methods and the intensity-focality trade-off.
• The findings facilitate the development of more sophisticated and effective TES targeting strategies.