期刊
JOURNAL OF PSYCHIATRIC RESEARCH
卷 71, 期 -, 页码 103-111出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jpsychires.2015.10.005
关键词
Depression; Affect; Mental illness; Default mode network; Resting-state; Functional connectivity
类别
资金
- NIH [T32MH018931-23, MH101162]
Depression is a prevalent psychiatric condition characterized by sad mood and anhedonia. Neuroscientific research has consistently identified abnormalities in a network of brain regions in major depression, including subregions of the anterior cingulate cortex (ACC). However, few studies have investigated whether the same neural correlates of depression symptom severity are apparent in subclinical or healthy subjects. In the current study, we used resting-state fMRI to examine functional connectivity for subregions of the ACC in N = 28 participants with subclinical levels of depression. In regression analyses, we examined relationships between depression severity and functional connectivity for pregenual ACC (pgACC), anterior subgenual ACC (sgACC), and posterior sgACC seed regions. Additionally, we examined relationships between ACC subregion connectivity and trait levels of positive and negative affect. We found distinct associations between depression severity and functional connectivity of ACC subregions. Higher depression severity was associated with reduced pgACC-striatum connectivity and reduced anterior sgACC-anterior insula connectivity. Consistent with resting-state findings in major depression, higher depression severity was also related to greater anterior sgACC-posterior cingulate connectivity and greater posterior sgACC-dorsolateral prefrontal connectivity. Lastly, there were distinct correlations between connectivity for anterior versus posterior ACC subregions and positive and negative affective traits. These findings provide novel support linking subclinical depression to the same neural substrates associated with major depression. More broadly, these results contribute to an emerging literature on dimensional approaches to psychiatric illness. (c) 2015 Elsevier Ltd. All rights reserved.
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