Optimizing the electric field strength in multiple targets for multichannel transcranial electric stimulation

Area of Science:

• Neuroscience
• Biomedical Engineering
• Computational Neuroscience

Background:

• Optimizing electric field patterns in multichannel transcranial electric stimulation (TES) often requires specifying a desired field direction, which may not be known for all neural targets.
• Maximizing electric field strength in target regions without regard to direction presents a more complex optimization challenge.

Purpose of the Study:

• To introduce and validate a novel optimization algorithm for multichannel TES.
• To maximize stimulation focality while maintaining a defined electric field strength in target regions.
• To develop an algorithm that adheres to safety constraints, limits active electrodes, and supports multi-target optimization.

Main Methods:

• Development of a novel optimization algorithm for TES montage generation.
• Validation of the algorithm's performance against naive search methods.
• Application of the algorithm to optimize stimulation for the amygdala as a case study.

Main Results:

• The new algorithm demonstrated superior solution quality and computational efficiency compared to naive search approaches.
• The algorithm successfully achieved a balance between focality and electric field strength in the target region (amygdala).
• Optimizing for field strength alone resulted in less focal stimulation patterns, while the new algorithm enabled balanced stimulation across multiple regions.

Conclusions:

• The developed algorithm automates the creation of individualized, optimal TES montages.
• It eliminates the need to pre-define electric field directions, allowing automatic selection of optimal field orientations.
• This approach facilitates precise targeting of brain regions with improved focality and controlled field strength.