Resonant Frequency rTMS: A Novel Approach to Target Circuit Modulation in Major Depressive Disorder
At a glance
Conditions
Where it's being run
1 sites across 1 statesStudy leadership
- Joe Gibbs · STUDY_CHAIR · University of California, Los Angeles
Who to contact
This trial hasn't published a contact. View it on ClinicalTrials.gov
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What this trial measures
- Repeatability of the Resonant Frequency measure1 week per subject (Three RF measurements will happen within 1 week)
Resonant Frequency (RF) of brain oscillations will be measured three times for each participant. Each time, all unique frequencies will be assigned a ranking corresponding to the degree of elicited network activity. We will then compute pairwise Spearman's correlation coefficients (R) between individual rankings obtained at time 1 (T1) vs time 2 (T2), T1 vs Time 3 (T3), and T2 vs T3. We expect that all R-values will be above R = 0.4. This will be single-subject level analysis.
- Changes in Electroencephalograms (EEG) functional connectivityTen days for each subject (2 sessions (RFmax/RFmin) separated by one week).
Electroencephalograms functional connectivity (EEG-FC) will be measured after rTMS stimulation 1) at the maximal and 2) at the minimal RF (RFmax, RFmin, respectively), as derived from the ranking using Outcome Measure 1. We will compare changes in EEG-FC after RFmax to changes in EEG-FC after RFmin. This will be a group-level analysis.
- Spatial maps of source-localized EEG connectivityTen days for each subject (2 sessions (RFmax/RFmin) separated by one week)
We will quantitatively compare the spatial extend of source-localized connectivity elicited by RFmax vs. RFmix stimulation. Binary statistical connectivity maps will be compared for size and percentage of overlap between the two conditions.
- Percent overlap between spatial maps of source-localized EEG connectivity and fMRI-based MDD-rTMS responsive network1 week per subject.
Similar to Outcome measure 3, but instead of comparing the spatial extend of EEG connectivity between RFmax vs. RFmin, this analysis will quantify the similarity to an MDD-rTMS responsive network derived from functional MRI data (Siddiqi et al. 2020).