Using rTMS to Treat Depression (NCT05424224)

🩺 Plain-English Summary (8th-Grade Level)

Repetitive Transcranial Magnetic Stimulation (rTMS) is a promising, novel, non-invasive therapy for depression. In fact, there is an FDA-approved depression protocol to stimulate the dorsolateral prefrontal cortex (dlPFC). Its efficacy and safety have improved significantly with continued research and clinical experience. However, it is not known how to identify potential patients who would benefit most from treatment. The primary goal of this study is to determine if changes in specific electroencephalogram (EEG) parameters after treatment can predict whether patients are responders or non-responders to rTMS. The second objective is to analyze changes in the functional connectivity of specific brain regions in responders compared to non-responders. The hypothesis is that through rTMS treatment, investigators will be able to increase the activity in the frontal region that includes the dorsolateral prefrontal cortex (DLPFC). Scalp EEG signals will be processed in order to compare EEG brain connectivity and Frontal alpha asymmetry index (FAA) to determine if there are differences before and after the treatment. EEG FAA is usually calculated by subtracting the right-side EEG power estimates from the respective counterpart on the other side. According to literature, depressive patients seem to have comparatively higher left frontal alpha power. Cortical activity is related to a reduced EEG power, which is reflected in depressed subjects. On the other hand, higher alpha power could also be interpreted as inhibition. Investigators will try to delineate changes in resting EEG functional connectivity before and after high-frequency left prefrontal rTMS, by using biomarkers such as: time/frequency connectivity, Alpha asymmetry index, among others. TMS also allows cortical properties, such as excitability, inhibition, oscillatory activity and connectivity to be directly probed within a specific region of the cortex. Other studies suggest that alterations in gamma oscillations in the dorsolateral prefrontal cortex and neighboring frontal regions are also potential shared biomarkers in psychiatry, highlighting the potential of EEG signals to help identify suitable biomarkers. Given its relative low cost and ease of use, when compared to brain imaging tools such as magnetic resonance imaging (MRI) or positron emission tomography (PET), EEG could be added to the clinical study so that precise neurophysiological changes before and after treatments can be assessed.

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Location: Florida International University — Miami, Florida

Age range: 18 Years to 80 Years