Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Computational Neuroscience

Background:

• Transcranial Magnetic Stimulation (TMS) is a key tool in brain research and treating neurological disorders.
• Optimal targeting and electric field direction for TMS remain undetermined, hindering therapeutic efficacy.

Purpose of the Study:

• To create an automated closed-loop system for real-time adjustment of TMS parameters.
• To optimize stimulus orientation based on TMS-evoked electroencephalography (EEG) responses.

Main Methods:

• Developed an automated closed-loop TMS-EEG system with multi-locus TMS for electronic parameter adjustment.
• Created an algorithm to optimize stimulation orientation using single-trial EEG responses.
• Validated the system with six healthy volunteers, repeating orientation optimization twenty times per subject.

Main Results:

• The closed-loop system effectively controlled TMS parameters, achieving desired outcomes despite high variability in single-trial EEG.
• Optimal stimulation orientation, maximizing EEG amplitude, was frequently achieved within tens of pulses.

Conclusions:

• Closed-loop optimization of TMS using EEG feedback is feasible.
• This approach enables effective and precise coupling of TMS to brain activity.