Increased Coupling of Intrinsic Networks in Remitted Depressed Youth Predicts Rumination and Cognitive Control

Rachel H Jacobs, Lisanne M Jenkins, Laura B Gabriel, Alyssa Barba, Kelly A Ryan, Sara L Weisenbach, Alvaro Verges, Amanda M Baker, Amy T Peters, Natania A Crane, Ian H Gotlib, Jon-Kar Zubieta, K Luan Phan, Scott A Langenecker and Robert C Welsh

PLOS ONE, 2014, vol. 9, issue 8, 1-11

Abstract: Objective: Functional connectivity MRI (fcMRI) studies of individuals currently diagnosed with major depressive disorder (MDD) document hyperconnectivities within the default mode network (DMN) and between the DMN and salience networks (SN) with regions of the cognitive control network (CCN). Studies of individuals in the remitted state are needed to address whether effects derive from trait, and not state or chronic burden features of MDD. Method: fcMRI data from two 3.0 Tesla GE scanners were collected from 30 unmedicated (47% medication naïve) youth (aged 18–23, modal depressive episodes = 1, mean age of onset = 16.2, SD = 2.6) with remitted MDD (rMDD; modal years well = 4) and compared with data from 23 healthy controls (HCs) using four bilateral seeds in the DMN and SN (posterior cingulate cortex (PCC), subgenual anterior cingulate (sgACC), and amygdala), followed by voxel-based comparisons of the whole brain. Results: Compared to HCs, rMDD youth exhibited hyperconnectivities from both PCC and sgACC seeds with lateral, parietal, and frontal regions of the CCN, extending to the dorsal medial wall. A factor analysis reduced extracted data and a PCC factor was inversely correlated with rumination among rMDD youth. Two factors from the sgACC hyperconnectivity clusters were related to performance in cognitive control on a Go/NoGo task, one positively and one inversely. Conclusions: Findings document hyperconnectivities of the DMN and SN with the CCN (BA 8/10), which were related to rumination and sustained attention. Given these cognitive markers are known predictors of response and relapse, hyperconnectivities may increase relapse risk or represent compensatory mechanisms.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0104366

DOI: 10.1371/journal.pone.0104366

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