Is short sleep bad for the brain? Brain structure and cognitive function in short sleepers

Many sleep less than recommended without experiencing daytime tiredness. According to prevailing views, short sleep increases risk of lower brain health and cognitive function. Chronic mild sleep deprivation could cause undetected sleep debt, negatively affecting cognitive function and brain health. However, it is possible that some have less sleep need and are more resistant to negative effects of sleep loss. We investigated this question using a combined cross-sectional and longitudinal sample of 47,029 participants (age 20-89 years) with measures of self-reported sleep, including 51,295 MRIs of the brain and cognitive tests. 701 participants who reported to sleep < 6 hours did not experience daytime tiredness or sleep problems. These short sleepers showed significantly larger regional brain volumes than both short sleepers with daytime tiredness and sleep problems (n = 1619) and participants sleeping the recommended 7-8 hours (n = 3754). However, both groups of short sleepers showed slightly lower general cognitive function, 0.16 and 0.19 standard deviations, respectively. Analyses using acelerometer-estimated sleep duration confirmed the findings, and the associations remained after controlling for body mass index, depression symptoms, income and education. The results suggest that some people can cope with less sleep without obvious negative consequences for brain morphometry, in line with a view on sleep need as individualized. Tiredness and sleep problems seem to be more relevant for brain structural differences than sleep duration per se. However, the slightly lower performance on tests of general cognitive function warrants closer examination by experimental designs in natural settings

White matter diffusivity and its correlations to state measures of psychopathology in male refugees with posttraumatic stress disorder

Post-traumatic stress disorder (PTSD) is a heterogenous condition and the underlying neurobiology is still poorly understood. In this study, we tested the hypothesis that PTSD is associated with microstructural changes in white matter (WM) fibre tracts that connect regions involved in emotional processing, memory, attention, and language. Furthermore, we examined how different response patterns to individualized trauma-provoking stimuli related to underlying WM microstructure. Sixty-nine trauma-affected male refugees with PTSD (N = 38) or without PTSD (N = 31) underwent clinical assessments and diffusion-weighted magnetic resonance imaging (DWI) of the whole brain at 3 Tesla. Diffusion tensor metrics were computed from DWI data and used to characterize regional white-matter microstructure. An automated tract segmentation method was used to extract diffusion tensor metrics from subject-based reconstructions of tract segments (ROI), including uncinate fasciculus (UF), cingulum bundle (CB), superior longitudinal fasciculus (SLF) in three subdivisions (SLF I - III), and fibre bundles connecting orbito-frontal cortex to striatum (OF-ST). Outside the scanner we obtained measures of immediate (state) arousal, avoidance and dissociation symptoms assessed in response to auditory exposure to a personal traumatic memory. Using mean FA of the middle part of each ROI, mixed ANOVA revealed a significant interaction between group, ROI and hemisphere. Post-hoc comparisons showed that, relative to refugees without PTSD, refugees with PTSD had lower FA in right CB, left SLF-I, bilateral OF-ST and bilateral SLF-II. Mean FA scaled negatively with avoidance in right CB while mean FA in bilateral UF scaled positively with individual scores reflecting dissociation symptoms. The results support a pathophysiological model of PTSD that implicates limbic structures, prefrontal cortex and striatum. The results also emphasize the need to consider PTSD’s multifaceted manifestations when searching for functional-structural relationships

Associations of depression and regional brain structure across the adult lifespan : Pooled analyses of six population-based and two clinical cohort studies in the European Lifebrain consortium

Objective: Major depressive disorder has been associated with lower prefrontal thickness and hippocampal volume, but it is unknown whether this association also holds for depressive symptoms in the general population. We investigated associations of depressive symptoms and depression status with brain structures across population-based and patient-control cohorts, and explored whether these associations are similar over the lifespan and across sexes. Methods: We included 3,447 participants aged 18–89 years from six population-based and two clinical patient-control cohorts of the European Lifebrain consortium. Cross-sectional meta-analyses using individual person data were performed for associations of depressive symptoms and depression status with FreeSurfer-derived thickness of bilateral rostral anterior cingulate cortex (rACC) and medial orbitofrontal cortex (mOFC), and hippocampal and total grey matter volume (GMV), separately for population-based and clinical cohorts. Results: Across patient-control cohorts, depressive symptoms and presence of mild-to-severe depression were associated with lower mOFC thickness (rsymptoms = −0.15/ rstatus = −0.22), rACC thickness (rsymptoms = −0.20/ rstatus = −0.25), hippocampal volume (rsymptoms = −0.13/ rstatus = 0.13) and total GMV (rsymptoms = −0.21/ rstatus = −0.25). Effect sizes were slightly larger for presence of moderate-to-severe depression. Associations were similar across age groups and sex. Across population-based cohorts, no associations between depression and brain structures were observed. Conclusions: Fitting with previous meta-analyses, depressive symptoms and depression status were associated with lower mOFC, rACC thickness, and hippocampal and total grey matter volume in clinical patient-control cohorts, although effect sizes were small. The absence of consistent associations in population-based cohorts with mostly mild depressive symptoms, suggests that significantly lower thickness and volume of the studied brain structures are only detectable in clinical populations with more severe depressive symptoms