| Literature DB >> 26068725 |
Christian A Webb1, Daniel G Dillon1, Pia Pechtel1, Franziska K Goer1, Laura Murray1, Quentin J M Huys2,3, Maurizio Fava4, Patrick J McGrath5, Myrna Weissman5, Ramin Parsey6, Benji T Kurian7, Phillip Adams5, Sarah Weyandt7, Joseph M Trombello7, Bruce Grannemann7, Crystal M Cooper7, Patricia Deldin8, Craig Tenke5, Madhukar Trivedi7, Gerard Bruder5, Diego A Pizzagalli1.
Abstract
Major depressive disorder (MDD) is clinically, and likely pathophysiologically, heterogeneous. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes. Guided by the NIMH Research Domain Criteria initiative, we used source localization of scalp-recorded EEG resting data to examine the neural correlates of three emerging endophenotypes of depression: neuroticism, blunted reward learning, and cognitive control deficits. Data were drawn from the ongoing multi-site EMBARC study. We estimated intracranial current density for standard EEG frequency bands in 82 unmedicated adults with MDD, using Low-Resolution Brain Electromagnetic Tomography. Region-of-interest and whole-brain analyses tested associations between resting state EEG current density and endophenotypes of interest. Neuroticism was associated with increased resting gamma (36.5-44 Hz) current density in the ventral (subgenual) anterior cingulate cortex (ACC) and orbitofrontal cortex (OFC). In contrast, reduced cognitive control correlated with decreased gamma activity in the left dorsolateral prefrontal cortex (dlPFC), decreased theta (6.5-8 Hz) and alpha2 (10.5-12 Hz) activity in the dorsal ACC, and increased alpha2 activity in the right dlPFC. Finally, blunted reward learning correlated with lower OFC and left dlPFC gamma activity. Computational modeling of trial-by-trial reinforcement learning further indicated that lower OFC gamma activity was linked to reduced reward sensitivity. Three putative endophenotypes of depression were found to have partially dissociable resting intracranial EEG correlates, reflecting different underlying neural dysfunctions. Overall, these findings highlight the need to parse the heterogeneity of MDD by focusing on promising endophenotypes linked to specific pathophysiological abnormalities.Entities:
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Year: 2015 PMID: 26068725 PMCID: PMC5130121 DOI: 10.1038/npp.2015.165
Source DB: PubMed Journal: Neuropsychopharmacology ISSN: 0893-133X Impact factor: 7.853