Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback

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 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 parameters 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.

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Faculty Opinions recommendation of Three-dimensional distribution of the electric field induced in the brain by transcranial magnetic stimulation using figure-8 and deep H-coils.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.725758941.793510977 ◽

2015 ◽

Author(s):

Thomas E Schlaepfer

Keyword(s):

Transcranial Magnetic Stimulation ◽

Electric Field ◽

Magnetic Stimulation ◽

Three Dimensional ◽

Dimensional Distribution ◽

The Brain

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Task-Modulated Brain Activity Predicts Antidepressant Responses of Prefrontal Repetitive Transcranial Magnetic Stimulation: A Randomized Sham-Control Study

Chronic Stress ◽

10.1177/24705470211006855 ◽

2021 ◽

Vol 5 ◽

pp. 247054702110068

Author(s):

Cheng-Ta Li ◽

Chih-Ming Cheng ◽

Chi-Hung Juan ◽

Yi-Chun Tsai ◽

Mu-Hong Chen ◽

...

Keyword(s):

Transcranial Magnetic Stimulation ◽

Magnetic Stimulation ◽

Antidepressant Treatment ◽

Repetitive Transcranial Magnetic Stimulation ◽

Brain Activity ◽

Characteristic Curve ◽

Depression Score ◽

Double Blind ◽

Antidepressant Efficacy ◽

Group B

Background Prolonged intermittent theta-burst stimulation (piTBS) and repetitive transcranial magnetic stimulation (rTMS) are effective antidepressant interventions for major depressive disorder (MDD). Cognition-modulated frontal theta (frontalθ) activity had been identified to predict the antidepressant response to 10-Hz left prefrontal rTMS. However, whether this marker also predicts that of piTBS needs further investigation. Methods The present double-blind randomized trial recruited 105 patients with MDD who showed no response to at least one adequate antidepressant treatment in the current episode. The recruited patients were randomly assigned to one of three groups: group A received piTBS monotherapy; group B received rTMS monotherapy; and group C received sham stimulation. Before a 2-week acute treatment period, electroencephalopgraphy (EEG) and cognition-modulated frontal theta changes (Δfrontalθ) were measured. Depression scores were evaluated at baseline, 1 week, and 2 weeks after the initiation of treatment. Results The Δfrontalθ at baseline was significantly correlated with depression score changes at week 1 (r = −0.383, p = 0.025) and at week 2 for rTMS group (r = −0.419, p = 0.014), but not for the piTBS and sham groups. The area under the receiver operating characteristic curve for Δfrontalθ was 0.800 for the rTMS group (p = 0.003) and was 0.549 for the piTBS group (p = 0.619). Conclusion The predictive value of higher baseline Δfrontalθ for antidepressant efficacy for rTMS not only replicates previous results but also implies that the antidepressant responses to rTMS could be predicted reliably at baseline and both piTBS and rTMS could be effective through different neurobiological mechanisms.

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Proof of concept study to develop a novel connectivity-based electric-field modelling approach for individualized targeting of transcranial magnetic stimulation treatment

Neuropsychopharmacology ◽

10.1038/s41386-021-01110-6 ◽

2021 ◽

Author(s):

Nicholas L. Balderston ◽

Joanne C. Beer ◽

Darsol Seok ◽

Walid Makhoul ◽

Zhi-De Deng ◽

...

Keyword(s):

Transcranial Magnetic Stimulation ◽

Electric Field ◽

Magnetic Stimulation ◽

Depression Symptoms ◽

Single Subject ◽

Proof Of Concept ◽

Concept Study ◽

Field Modelling ◽

Left Dlpfc ◽

Modelling Approach

AbstractResting state functional connectivity (rsFC) offers promise for individualizing stimulation targets for transcranial magnetic stimulation (TMS) treatments. However, current targeting approaches do not account for non-focal TMS effects or large-scale connectivity patterns. To overcome these limitations, we propose a novel targeting optimization approach that combines whole-brain rsFC and electric-field (e-field) modelling to identify single-subject, symptom-specific TMS targets. In this proof of concept study, we recruited 91 anxious misery (AM) patients and 25 controls. We measured depression symptoms (MADRS/HAMD) and recorded rsFC. We used a PCA regression to predict symptoms from rsFC and estimate the parameter vector, for input into our e-field augmented model. We modeled 17 left dlPFC and 7 M1 sites using 24 equally spaced coil orientations. We computed single-subject predicted ΔMADRS/HAMD scores for each site/orientation using the e-field augmented model, which comprises a linear combination of the following elementwise products (1) the estimated connectivity/symptom coefficients, (2) a vectorized e-field model for site/orientation, (3) rsFC matrix, scaled by a proportionality constant. In AM patients, our connectivity-based model predicted a significant decrease depression for sites near BA9, but not M1 for coil orientations perpendicular to the cortical gyrus. In control subjects, no site/orientation combination showed a significant predicted change. These results corroborate previous work suggesting the efficacy of left dlPFC stimulation for depression treatment, and predict better outcomes with individualized targeting. They also suggest that our novel connectivity-based e-field modelling approach may effectively identify potential TMS treatment responders and individualize TMS targeting to maximize the therapeutic impact.

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