Clinical Trial Details
— Status: Withdrawn
Administrative data
NCT number |
NCT04032015 |
Other study ID # |
133611 |
Secondary ID |
|
Status |
Withdrawn |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
January 1, 2020 |
Est. completion date |
June 1, 2023 |
Study information
Verified date |
April 2021 |
Source |
Stanford University |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
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.
Description:
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.