A Leadfield-Free Optimization Framework for Transcranially Applied Electric Currents

Area of Science:

• Neuroscience
• Biomedical Engineering
• Computational Modeling

Background:

• Transcranial Electrical Stimulation (TES), Temporal Interference Stimulation (TIS), Electroconvulsive Therapy (ECT), and Tumor Treating Fields (TTFields) utilize electric current patterns applied to the brain.
• Individual anatomical variations necessitate personalized electrode positioning for optimal current delivery.

Purpose of the Study:

• To develop a flexible and efficient computational approach for determining individually optimal electrode montages.
• To enable precise current pattern generation in the brain through electric field simulations.

Main Methods:

• A leadfield-free optimization framework was developed, allowing free placement of electrodes on the head surface.
• The approach supports arbitrary electrode shapes and configurations, preventing spatial overlaps.
• Optimization targets maximizing field intensity in regions-of-interest and achieving a desired focality-intensity tradeoff.

Main Results:

• Montage optimization was demonstrated for TES, TIS, ECT, and TTFields.
• Algorithm performance was validated against reference simulations.
• The framework requires moderate system resources, suitable for regular notebooks.

Conclusions:

• The new framework expands possibilities for optimizing electrode montages for specific applications.
• It complements existing methods by supporting spatially extended electrodes and arbitrary configurations.
• The tool aids researchers in discovering innovative brain stimulation schemes and is available in SimNIBS.