Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback

Aino E. Tervo, Jaakko O. Nieminen*, Pantelis Lioumis, Johanna Metsomaa, Victor H. Souza, Heikki Sinisalo, Matti Stenroos, Jukka Sarvas, Risto J. Ilmoniemi

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

46 Citations (Scopus)
180 Downloads (Pure)

Abstract

Background: Transcranial magnetic stimulation (TMS) is widely used in brain research and treatment of various brain dysfunctions. However, the optimal way to target stimulation and administer TMS therapies, for example, where and in which electric field direction the stimuli should be given, is yet to be determined. Objective: To develop an automated closed-loop system for adjusting TMS parameters (in this work, the stimulus orientation) online based on TMS-evoked brain activity measured with electroencephalography (EEG). Methods: We developed an automated closed-loop TMS–EEG set-up. In this set-up, the stimulus parameters are electronically adjusted with multi-locus TMS. As a proof of concept, we developed an algorithm that automatically optimizes the stimulation orientation based on single-trial EEG responses. We applied the algorithm to determine the electric field orientation that maximizes the amplitude of the TMS–EEG responses. The validation of the algorithm was performed with six healthy volunteers, repeating the search twenty times for each subject. Results: The validation demonstrated that the closed-loop control worked as desired despite the large variation in the single-trial EEG responses. We were often able to get close to the orientation that maximizes the EEG amplitude with only a few tens of pulses. Conclusion: Optimizing stimulation with EEG feedback in a closed-loop manner is feasible and enables effective coupling to brain activity.

Original languageEnglish
Pages (from-to)523-531
Number of pages9
JournalBrain Stimulation
Volume15
Issue number2
DOIs
Publication statusPublished - 1 Mar 2022
MoE publication typeA1 Journal article-refereed

Keywords

  • Bayesian optimization
  • Closed-loop
  • Electroencephalography
  • Multi-channel TMS
  • Multi-locus TMS
  • Transcranial magnetic stimulation

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