rTMS Study in Depression to Evaluate the Relationship Between Brain Plasticity and Clinical Outcome

Overview

Depression is a highly prevalent condition characterized by persistent low mood, energy, and activity that can affect one's thoughts, mood, behavior, and sense of well-being. Repetitive transcranial magnetic stimulation (rTMS), a non-invasive neuromodulatory technique, is an effective treatment for depression. However, remission rates are suboptimal and ideal stimulation parameters are unknown. The overarching goal of this study is to elucidate how brain changes accumulate during rTMS, and how these changes relate to clinical outcome. I plan to recruit patients with medication-resistant depression and treat with four weeks of rTMS in a randomized, double-blind, sham-controlled fashion. I will measure brain changes using TMS-EEG and determine how these changes relate to clinical outcome. This study will 1) test how brain changes relate to clinical outcome and 2) establish a computational model to help predict outcome and propose novel treatment protocols.

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for major depressive disorder, but remission rates are 20-40%, and ideal stimulation parameters are unknown. rTMS is thought to work by changing the synaptic strength of neurons. The ability of our brain to make these changes is referred to as plasticity. rTMS-induced changes are thought to build with successive treatment sessions, a process referred to as metaplasticity. While both plasticity and metaplasticity are well-established in single cell physiology, relevance to rTMS in humans remains unknown. To improve clinical efficacy, the investigators seek to understand 1) the neural response to a single rTMS session (plasticity), 2) the neural response to repeated daily rTMS sessions (metaplasticity), and 3) whether computational models of plasticity based on single-cell physiology apply to human patients receiving rTMS for depression. Goals of the study are as follows: 1. establish a detailed mechanistic understanding of the brain changes during current rTMS treatment 2. identify clinically meaningful electrophysiological biomarkers for rTMS treatment 3. establish a computational model to help predict both brain and clinical changes. This project tests the hypothesis that neural changes that accumulate during rTMS treatment can predict clinical outcome. 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 be randomized to four weeks (20 sessions) of daily 10Hz left dorsolateral prefrontal cortex (DLPFC) active or sham rTMS. Following the completion of sham treatment, participants will be offered open-label active rTMS treatment for four weeks to ensure that all participants receive active treatment if desired. Single pulse TMS-evoked potential (TEP), a well-studied causal EEG measure of brain excitability, will be measured before, during, and after every rTMS session. TEPs will be measured locally in the left lateral prefrontal cortex and compared to downstream sites in parietal and medial prefrontal cortex. Aim 1: To determine the electrophysiological response to single and repeated rTMS sessions in depression. Through this aim, I will establish a detailed mechanistic understanding of the electrophysiological effects of rTMS treatments. Aim 2: To determine the relationship between brain state, plasticity, metaplasticity, and antidepressant response in depression. Through this aim, I will identify clinically meaningful electrophysiological biomarkers for rTMS treatment. Aim 3: To test whether a computational model of metaplasticity applies to human patients. This computational model will help predict both neurophysiological and clinical changes. Findings from this study will provide the basis for novel stimulation protocols that will maximize clinically-relevant brain changes and improve clinical outcomes.

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Eligibility

Outcomes