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Brain mechanisms of anxiety's effects on cognitive control in major depressive disorder
Published online by Cambridge University Press: 13 June 2016
Abstract
Adults with major depressive disorder (MDD) demonstrate increased susceptibility to interfering effects of anxiety on cognitive control; although under certain conditions adults with MDD are able to compensate for these effects. The brain mechanisms that may facilitate the ability to compensate for anxiety either via the recruitment of additional cognitive resources or via the regulation of interference from anxiety remain largely unknown. To clarify these mechanisms, we examined the effects of anxiety on brain activity and amygdala–prefrontal functional connectivity in adults diagnosed with MDD.
A total of 22 unmedicated adults with MDD and 18 healthy controls (HCs) performed the Tower of London task under conditions designed to induce anxiety, while undergoing a functional magnetic resonance imaging assessment.
During the easy condition, the MDD group demonstrated equivalent planning accuracy, longer planning times, elevated amygdala activity and left rostrolateral prefrontal cortex (RLPFC) hyperactivity relative to HCs. Anxiety mediated observed group differences in planning times, as well as differences in amygdala activation, which subsequently mediated observed differences in RLPFC activation. During the easy condition, the MDD group also demonstrated increased negative amygdala–dorsolateral prefrontal cortex (DLPFC) connectivity which correlated with improved planning accuracy. During the hard condition, HCs demonstrated greater DLPFC activation and stronger negative amygdala–DLPFC connectivity, which was unrelated to planning accuracy.
Our results suggest that persons with MDD compensate for anxiety-related limbic activation during low-load cognitive tasks by recruiting additional RLPFC activation and through increased inhibitory amygdala–DLPFC communication. Targeting these neural mechanisms directly may improve cognitive functioning in MDD.
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- Copyright © Cambridge University Press 2016
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