Closed-loop Optimized rTMS for Depression

2019-11-03 15:11:09 | BioPortfolio


Targeted and individualized treatments for mental health disorders are critically needed. Repetitive transcranial magnetic stimulation (rTMS) represents the front-line of new and innovative approaches to normalizing dysfunctional brain networks in those with mental illness. rTMS is FDA-approved for depression and obsessive-compulsive disorder with clinical trials underway for PTSD and addiction, among others. However, remission rates are suboptimal and ideal stimulation parameters are unknown. I recently completed a randomized, double blind clinical trial and a depression severity biomarker that predicts clinical outcome. The overarching goal of this study is to develop the first broadly generalizable platform for real-time biomarker monitoring and personalized rTMS treatment. I plan to recruit patients with medication-resistant depression and in perform a four-phase, cross-over, double-blind, placebo-controlled trial to 1) identify how standard and optimized rTMS patterns engage the depression severity biomarker, and 2) determine the dose-response of these rTMS patterns. Findings from this study will provide the basis for a double-blind, randomized clinical trial comparing rTMS optimized to the individual against standard rTMS.


Nearly 50% of all Americans will suffer from a mental health disorder during their lifetimes. Brain stimulation treatments, including repetitive transcranial magnetic stimulation (rTMS), are increasingly used to normalize dysfunctional brain circuits in these disorders. Mechanistically, rTMS is thought to work by changing the synaptic strength of neurons, referred to as brain plasticity. Despite the variety of disorders targeted and significant between-patient heterogeneity, rTMS is currently applied in a manner that is one-size-fits-all (without any individual optimization of the stimulation pattern) and open-loop (fixed schedule of stimulation pattern, with no measurement or adjustment during rTMS). I believe that the response rate of rTMS for depression, which is at present <50%, can be improved through personalized brain stimulation that enhances target engagement and maximizes plasticity. To personalize brain stimulation, one must (1) measure and monitor brain changes in real-time; (2) determine the optimal stimulation patterns for inducing brain changes; (3) develop adaptive treatments to drive desired changes on an individual patient-specific level over time. Such personalization of brain stimulation will increase our mechanistic understanding of brain plasticity to improve efficacy in non-responders to standard treatments.

The primary goals of my research program are to (1) discover brain biomarkers that predict progression to clinical remission, and (2) develop closed-loop treatment algorithms that optimize these biomarkers and improve clinical outcomes. I will focus on depression as it is the leading cause of disability worldwide and and medications are ineffective or not tolerated for close to half of these patients. Leveraging my previous work, I propose three stages of development of personalized brain stimulation using single pulses of TMS combined with electroencephalography (TMS-EEG) to generate a causal measurement of brain state that can easily be translated to the clinic. The TMS-EEG depression severity biomarker that I recently discovered occurs 30 milliseconds after administering a TMS test pulse (p30) in the fronto-parietal network (FPN), a region implicated in depression. The degree of suppression of this p30 signal predicted clinical outcome in depressed patients following rTMS treatment. Additionally, a single stimulation session was sufficient to suppress the p30 during and for 30 minutes after stimulation. This work indicates that p30 suppression can be monitored in real-time and has the potential to support empiric treatment optimization.

Specific aims are as follows:

Aim 1: To create a platform for monitoring p30 changes (depression severity biomarker) in real-time. Through this aim, I will develop tools to monitor biomarkers in real-time, a necessary step for closed-loop interventions.

Aim 2: To identify the stimulation parameters that causally and maximally suppress the p30. Through this aim, I will establish the causal relationship between stimulation and biomarker change.

Aim 3: To test whether closed-loop rTMS more strongly suppresses the p30 compared to standard rTMS. This aim will yield a closed-loop treatment based on empiric biomarkers that will more effectively modulate an individual's brain circuitry.

This project tests the hypothesis that individualizing and continuously updating rTMS treatment guided by the depression severity biomarker will maximally induce specific brain changes. Specifically, I will develop real-time brain monitoring and test whether optimizing rTMS by maximally suppressing the p30 can more effectively modulate the fronto-parietal network.

I plan to recruit 54 medication-naive depressed patients and for all patients perform a three-phase, cross-over, double-blind, placebo-controlled trial to 1) identify how standard and optimized rTMS patterns engage the depression severity biomarker, and 2) determine the dose-response of these rTMS patterns.

Single pulse TMS-evoked potential (TEP), a well-studied causal EEG measure of brain excitability, will be measured before, during, and after rTMS. Primary outcome in this study will be target engagement of the strength of suppression of the fronto-parietal p30 (30ms positive voltage change after a TMS test pulse). This signal is chosen because the strength of suppression has been shown to predict improvement in clinical symptoms after rTMS.

Participants will first complete a screening procedure to determine eligibility based on the inclusion/exclusion criteria. If the participants are not eligible, no further study procedures will be conducted. Eligible participants will then complete three phases of this cross-over pilot study. All conditions will target the left dorso-lateral prefrontal cortex using neuronavigated rTMS as this is the standard of care treatment site for rTMS. Future work will use similar methods to determine the optimal stimulation site, but this study focuses on identifying the optimal stimulation pattern, as this is the most commonly clinically-adjusted parameter and one that has been shown from animal models to have a direct impact on brain plasticity. The three phases of the study are below and detailed in the Research Strategy:

Phase 1: Determine for each patient which standard open-loop rTMS protocol maximally suppresses the p30 in the fronto-parietal network (target engagement of the depression severity biomarker). Participants will complete one session each of clinically-utilized (1, 5, 10, 20Hz) rTMS and sham rTMS (Fig 8A in Research Strategy). rTMS sessions will be applied in a cross-over, pseudorandomized fashion and separated by 1 week to prevent buildup of brain changes. Target engagement will be measured using the strength of p30 suppression in the fronto-parietal network both during and after rTMS. For each condition, rTMS will be applied for two consecutive days to determine the dose response.

Phase 2: Determine for each patient the optimal open-loop rTMS to maximally suppress the p30. Starting with the standard rTMS pattern that maximally suppresses the p30, participants will receive one session of stimulation while varying power, duration, and frequency in an event-related design (Fig 8B). From the p30 response of each stimulation pattern, an optimal and individualized open-loop rTMS pattern will be generated using machine learning approaches.

Phase 3: Determine if closed-loop rTMS more strongly suppresses the p30 compared to optimized or standard open-loop rTMS. The goal of the third phase is to determine if there is added benefit to closed-loop stimulation (adjustment of stimulation parameters during stimulation) over optimizing open-loop rTMS (Phase 2). In a pseudorandomzied fashion, 3 different conditions of rTMS will be administered over 3 weeks. 2 consecutive doses of each condition will be performed to determine dose response. Each condition will be separated by 1 week. Target engagement will be assessed with the strength of p30 suppression in the frontoparietal network. rTMS conditions are as follows:

1. Open-loop standard rTMS. For each patient, the standard rTMS protocol that maximally suppressed the p30 in Aim 2.1 will be administered.

2. Open-loop optimized rTMS. For each patient, the optimal rTMS pattern derived from Phase 2 (Aim 2.2) of this study will be applied in open-loop fashion.

3. Closed-loop rTMS. For each patient, rTMS will be administered starting with the optimal open-loop solution and updated in real-time using control systems theory. Here, feature inputs (brain state, stimulation frequency, duration, and power) and outputs (p30 suppression) will be continuously compared and feature weights in the model updated to maximally suppress the p30.

Findings from this study will provide the basis for a double-blind, randomized clinical trial of closed-loop rTMS against standard rTMS.

Study Design


Major Depressive Disorder


closed-loop rTMS, open-loop rTMS, sham rTMS


Not yet recruiting


Stanford University

Results (where available)

View Results


Published on BioPortfolio: 2019-11-03T15:11:09-0500

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