心理学
功能磁共振成像
重性抑郁障碍
认知
默认模式网络
神经影像学
听力学
认知心理学
临床心理学
神经科学
医学
作者
Arielle S. Keller,Tali M. Ball,Leanne M. Williams
标识
DOI:10.1017/s0033291719002290
摘要
Abstract Background Attention impairment is an under-investigated feature and diagnostic criterion of Major Depressive Disorder (MDD) that is associated with poorer outcomes. Despite increasing knowledge regarding mechanisms of attention in healthy adults, we lack a detailed characterization of attention impairments and their neural signatures in MDD. Methods Here, we focus on selective attention and advance a deep multi-modal characterization of these impairments in MDD, using data acquired from n = 1008 patients and n = 336 age- and sex-matched healthy controls. Selective attention impairments were operationalized and anchored in a behavioral performance measure, assessed within a battery of cognitive tests. We sought to establish the accompanying neural signature using independent measures of functional magnetic resonance imaging (15% of the sample) and electroencephalographic recordings of oscillatory neural activity. Results Greater impairment on the behavioral measure of selective attention was associated with intrinsic hypo-connectivity of the fronto-parietal attention network. Not only was this relationship specific to the fronto-parietal network unlike other large-scale networks; this hypo-connectivity was also specific to selective attention performance unlike other measures of cognition. Selective attention impairment was also associated with lower posterior alpha (8–13 Hz) power at rest and was related to more severe negative bias (frequent misidentifications of neutral faces as sad and lingering attention on sad faces), relevant to clinical features of negative attributions and brooding. Selective attention impairments were independent of overall depression severity and of worrying or sleep problems. Conclusions These results provide a foundation for the clinical translational development of objective markers and targeted therapeutics for attention impairment in MDD.
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