Randy P. Auerbach, Ph.D.
Fellow in Child & Adolescent Depression
Project Details
Mentor
Diego A. Pizzagalli, Ph.D.
Institution
McLean Hospital
Project
Predicting Adolescent Major Depressive Disorder: A Multimodal Brain Imaging Approach
PROJECT TITLE
Predicting Adolescent Major Depressive Disorder: A Multimodal Brain Imaging Approach
PROJECT SUMMARY
Emerging evidence indicates that dysfunction within mesocorticolimbic pathways, including the anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLPFC), and glutamatergic dysfunction play key roles in adolescent major depressive disorder (MDD). Whether these abnormalities are a consequence or cause of MDD and whether they might help explain the higher prevalence of MDD in females remain unknown. To fill this critical gap in the literature, the current study will utilize functional magnetic resonance imaging (fMRI) and magnetic resonance spectroscopy (MRS) to probe neurobiological mechanisms underlying reward deficits in healthy and at-risk female adolescents ages 12 to 14. First, fMRI data will be collected while youth complete a reward and a peer evaluation task. Relative to healthy adolescents, at-risk youth will exhibit: (a) reduced monetary sensitivity and a blunted ventral striatal and rostral ACC response to reward; (b) reduced dorsal ACC and striatal activation in response to peer acceptance; and (c) greater subgenual ACC and insula activation following peer rejection. Second, MRS will probe glutamate levels within the ACC. In comparison to healthy female adolescents, at-risk youth will show lower glutamate levels, and such differences, may account for increased vulnerability to future depressive episodes. Last, blunted reward response within the mesocorticolimbic pathways as well as lower glutamate levels in the ACC will prospectively predict higher levels of depressive symptoms in at-risk adolescents. Results are expected to significantly advance our understanding of the neurocognitive mechanisms implicated in adolescent MDD, which, ultimately, may lead to early identification of and more effective treatment for MDD.
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