SLEEP DEPRIVATION, EEG, & FUNCTIONAL MRI IN DEPRESSION

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DESCRIPTION (Adapted from applicant's abstract): The objective of this 5-year Mentored Clinical Scientist Development Award for Cametlia Clark, M.D. is to develop the candidate's expertise in functional magnetic resonance imaging (MRI) while building on her previous skills in neuroimaging and sleep research. This goal will be accomplished through a carefully designed training plan involving didactic courses and mentorship by experts (at and outside UCSD) in basic neuroscience, structural MRI, functional MRI (fMRI) physics, sleep and affective disorders research, and statistics as well as intensive instruction in fMRI research in a setting featuring state-of-the-art scanners, innovative pulse sequences (particularly perfusion-weighted), and the first fMRI studies utilizing sleep deprivation (SD) to study cognitive function in normal subjects (published recently in Nature and NeuroReport. This training program will enable Dr. Clark to complete the transition to independent investigator and provide the foundation for a long-term research program utilizing fMRI and polysomnography to investigate brain function in affective disorders. The research plan utilizes one night of partial SD (PSD), an excellent model of antidepressant treatment which is fast-acting, and does not require medications. The applicants hypothesize: I) depressed responders' baseline perfusion signal intensity in the ventral anterior cingulate (BA 25 and ventral 24) / medial prefrontal cortical (BA 32) areas will be greater than that of nonresponders and controls; 2) following PSD, perfusion in the ventral anterior cingulate (BA 25 and ventral 24) / medial prefrontal cortical (BA 32 and 10) areas will significantly decrease in responders only. The applicants will also look for between-groups and within-groups differences in other regions where functional abnormalities have been reported in depression, including (but not limited to) dorsal anterior cingulate, dorsolateral prefrontal cortices, medial frontal cortices, amygdala, hippocampus, thalamus, and basal ganglia. Finally, the applicants will look for possible between-groups structural MRJ differences, which could potentially confound fMRI analyses. FMRI perfusion data will be analyzed by the analysis of variance algorithm in AFNI (Analysis of Functional Neural Images) software.