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To develop and test a neurocomputational model of ketamine treatment response predictions in TRD.
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The investigators propose applying a previously validated computational model of the MMN and the ensuing effects of NMDAR antagonism to predict treatment response following ketamine infusions in TRD patients and distinguish ketamine's antisuicidal effects from those related to mood improvements. The study has two subgoals: first, the computational mechanisms underlying MMN reductions that predict ketamine treatment response in TRD patients will be examined. Second, the computational mechanisms will be linked to their underlying neural causes using neural circuit models. Beyond understanding ketamine's short- and long-term mechanisms of action in TRD, the parameters obtained from fitting these models to noninvasive EEG recordings may facilitate single-patient treatment predictions. If successful, this approach may provide clinically useful prognostic statements in individual patients.
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Inclusion criteria
1.18 to 65 years of age 2. Meeting Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria for MDD and in a Major Depressive Episode and ≥10 on the Montgomery-Asberg Depression Rating Scale (MADRS).
Competent to consent-based on their ability to provide a spontaneous narrative description of the key elements of the study.
Failure of at least two trials of antidepressant therapy during the current episode (treatment-resistant depression) and receiving ketamine treatment clinically as administered by their clinician 5. Staying on stable dosages of any concomitant psychotropic medications.
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Central trial contact
Venkat Bhat, MD MSc
Data sourced from clinicaltrials.gov
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