A Causal Neural Network-level Understanding of Depression and Its Treatment Through Concurrent TMS and fMRI
A Causal Neural Network-level Understanding of Depression and Its Treatment Through Concurrent TMS and fMRI
The overarching goal of this research program is to elucidate causal and directional neural network- level abnormalities in depression, and how they are modulated by an individually-tailored, circuit-directed intervention. By using concurrent TMS and fMRI, the investigators can overcome a major limitation of neuroimaging - the inability to demonstrate causality. The investigators' findings will serve as a platform for future studies wherein TMS treatment can be directly guided by the investigators' ability to image and causally manipulate specific neural networks.
Aim 1: To examine causal interactions between two major brain networks in depression.
Aim 2: To examine the impact of antidepressant TMS on causal network abnormalities in depression.
Hypothesis 1: Depressed subjects will show blunted responses, compared to healthy controls, in two targeted and interacting networks, using concurrent transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI).
Hypothesis 2: Treatment of patients with high-frequency repetitive TMS (rTMS) will result in normalization of baseline network-level deficits, and be predicted by degree of baseline network abnormalities.
This study has a single primary outcome measure and other measures are exploratory. Previous versions of this study record incorrectly listed some exploratory outcome measures as secondary.
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