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BackgroundSleep disturbance plays an important role in major depressive disorder (MDD). Prior investigations have demonstrated that slow wave activity (SWA) during sleep is altered in MDD; however, results have not been consistent across studies, which may be due in part to sex-related differences in SWA and/or limited spatial resolution of spectral analyses. This study sought to characterize SWA in MDD utilizing high-density electroencephalography (hdEEG) to examine the topography of SWA across the cortex in MDD, as well as sex-related variation in SWA topography in the disorder.MethodsAll-night recordings with 256 channel hdEEG were collected in 30 unipolar MDD subjects (19 women) and 30 age and sex-matched control subjects. Spectral analyses of SWA were performed to determine group differences. SWA was compared between MDD and controls, including analyses stratified by sex, using statistical non-parametric mapping to correct for multiple comparisons of topographic data.ResultsAs a group, MDD subjects demonstrated significant increases in all-night SWA primarily in bilateral prefrontal channels. When stratified by sex, MDD women demonstrated global increases in SWA relative to age-matched controls that were most consistent in bilateral prefrontal regions; however, MDD men showed no significant differences relative to age-matched controls. Further analyses demonstrated increased SWA in MDD women was most prominent in the first portion of the night.ConclusionsWomen, but not men with MDD demonstrate significant increases in SWA in multiple cortical areas relative to control subjects. Further research is warranted to investigate the role of SWA in MDD, and to clarify how increased SWA in women with MDD is related to the pathophysiology of the disorder.

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A cortico-limbic network consisting of the amygdala, medial prefrontal cortex (mPFC), and ventral striatum (vSTR) has been associated with altered function in emotional disorders. Here we used rapidly sampled functional magnetic resonance imaging and Granger causality analyses to assess the directional connectivity between these brain structures in a sample of healthy and age-matched participants endorsing moderate to severe depressive symptomatology as they viewed a series of natural scene stimuli varying systematically in pleasantness and arousal. Specifically during pleasant scene perception, dysphoric participants showed reduced activity in mPFC and vSTR, relative to healthy participants. In contrast, amygdala activity was enhanced to pleasant as well as unpleasant arousing scenes in both participant groups. Granger causality estimates of influence between mPFC and vSTR were significantly reduced in dysphoric relative to control participants during all picture contents. These findings provide direct evidence that during visual perception of evocative emotional stimuli, reduced reward-related activity in dysphoria is associated with dysfunctional causal connectivity between mPFC, amygdala, and vSTR.

Global signal regression (GSR) is a controversial analysis method, since its removal of signal has been observed to reduce the reliability of functional connectivity estimates. Here, we used test–retest reliability to characterize potential differences in spatial patterns between conventional, static GSR (sGSR) and a novel dynamic form of GSR (dGSR). In contrast with sGSR, dGSR models the global signal at a time delay to correct for blood arrival time. Thus, dGSR accounts for greater variation in global signal, removes blood‐flow‐related nuisance signal, and leaves higher quality neuronal signal remaining. We used intraclass correlation coefficients (ICCs) to estimate the reliability of functional connectivity in 462 healthy controls from the Human Connectome Project. We tested across two factors: denoising method used (control, sGSR, and dGSR), and interacquisition interval (between days, or within session while varying phase encoding direction). Reliability was estimated regionally to identify topographic patterns for each condition. sGSR and dGSR provided global reductions in reliability compared with the non‐GSR control. Test–retest reliability was highest in the frontoparietal and default mode regions, and lowest in sensorimotor cortex for all conditions. dGSR provides more effective denoising in regions where both strategies greatly reduce reliability. Both GSR methods substantially reduced test–retest reliability, which was most evident in brain regions that had low reliability prior to denoising. These findings suggest that reliability of interregional correlation is likely inflated by the global signal, which is thought to primarily reflect dynamic blood flow.