Major depressive disorder (MDD) is of immense public health importance because of its high prevalence, early onset, chronicity, and functional impairment. While behavioral and peripheral physiological studies have identified a deficit in emotional reactivity associated with MDD, leading to an emotion context insensitivity (ECI) theoretical model, neuro imaging studies have yielded evidence of both hypo- and hyperactivity depending on the region of interest and the type of affective stimuli used. One possibility is that emotional reactivity in MDD is moderated by the personal relevance of stimuli, such that reactivity to normative stimuli is blunted and reactivity to idiographic stimuli is increased, although this has yet to be tested within a single sample. The proposed study seeks to examine this issue using three direct measures of brain activity: event-related potentials (ERPs), spectral analysis of the electroencephalogram (EEG), and functional magnetic resonance imaging (fMRI). By integrating these three methods, this study will be well-equipped to enhance our understanding of the pathophysiological mechanisms underlying abnormal emotional processing in MDD, which is consistent with the mission of the Division of Neuroscience and Basic Behavioral Science at the National Institute of Mental Health. Further, by seeking to systematically characterize specific neural abnormalities in MDD, the current study may provide objective biological measures that can inform future work on clinical issues such as treatment selection, tracking treatment progress, and predicting recovery. To examine the influence of personal relevance on abnormal emotional processing in MDD, the proposed research will consider neural activity among 30 adults with current MDD and 30 never-depressed controls, with three specific aims: (a) to compare ERP/EEG responses to normative and idiographic emotional stimuli;(b) to compare ERP/EEG responses to reward- and performance-based feedback;and (c) to use fMRI to examine neural activation to emotional faces and rewards. This research also incorporates several essential training components that will provide the opportunity for the applicant to attain further clinical and methodological expertise in several domains. As a co-sponsor of this application, Dr. Daniel Klein will provide advanced training in the assessment of mood disorders. Dr. Lilianne Mujica-Parodi, also a co-sponsor, will provide training in the acquisition, analysis, and interpretation of fMRI data. Two consultants are also included in this proposal to provide advanced statistical training: Dr. Joseph Dien has expertise in the application of principal components analysis and source localization techniques to ERP/EEG data sets, and Dr. Andreas Keil has expertise in using time-frequency approaches to analyze oscillatory EEG data. Finally, the implementation of the proposed research and training will be overseen by Dr. Greg Hajcak, the sponsor of this proposal and the primary academic mentor of the applicant.
Major depressive disorder (MDD) is an illness that is of immense public health importance because of its high prevalence rate, early onset, chronicity, and functional impairment. The current project seeks to use examine specific patterns of brain activity in response to emotional stimuli, in order to shed light on the neural mechanisms underlying abnormal emotional reactivity in MDD. In doing so, this will aid recent research efforts to identify biological markers associated with MDD that can be used to facilitate effective treatment selection, track treatment progress, and predict recovery.
|Proudfit, Greg Hajcak; Bress, Jennifer N; Foti, Dan et al. (2015) Depression and Event-related Potentials: Emotional disengagement and reward insensitivity. Curr Opin Psychol 4:110-113|
|Proudfit, Greg Hajcak (2015) The reward positivity: from basic research on reward to a biomarker for depression. Psychophysiology 52:449-59|
|Foti, Dan; Carlson, Joshua M; Sauder, Colin L et al. (2014) Reward dysfunction in major depression: multimodal neuroimaging evidence for refining the melancholic phenotype. Neuroimage 101:50-8|