Attenuated intrinsic connectivity within cognitive control network among individuals with remitted depression: Temporal stability and association with negative cognitive styles

Abstract

Many individuals with major depressive disorder (MDD) experience cognitive dysfunction including impaired cognitive control and negative cognitive styles. Functional connectivity magnetic resonance imaging studies of individuals with current MDD have documented altered resting-state connectivity within the default-mode network and across networks. However, no studies to date have evaluated the extent to which impaired connectivity within the cognitive control network (CCN) may be present in remitted MDD (rMDD), nor have studies examined the temporal stability of such attenuation over time. This represents a major gap in understanding stable, trait-like depression risk phenotypes. In this study, resting-state functional connectivity data were collected from 52 unmedicated young adults with rMDD and 47 demographically matched healthy controls, using three bilateral seeds in the CCN (dorsolateral prefrontal cortex, inferior parietal lobule, and dorsal anterior cingulate cortex). Mean connectivity within the entire CCN was attenuated among individuals with rMDD, was stable and reliable over time, and was most pronounced with the right dorsolateral prefrontal cortex and right inferior parietal lobule, results that were corroborated by supplemental independent component analysis. Attenuated connectivity in rMDD appeared to be specific to the CCN as opposed to representing attenuated within-network coherence in other networks (e.g., default-mode, salience). In addition, attenuated connectivity within the CCN mediated relationships between rMDD status and cognitive risk factors for depression, including ruminative brooding, pessimistic attributional style, and negative automatic thoughts. Given that these cognitive markers are known predictors of relapse, these results suggest that attenuated connectivity within the CCN could represent a biomarker for trait phenotypes of depression risk. Hum Brain Mapp 38:2939–2954, 2017. © 2017 Wiley Periodicals, Inc.