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Summary: Unemployed people could be at risk of developing inefficient sleep habits by spending excessive time in bed, as they lack a structuring activity. This could impact their mental health and reintegration into labour. This study aims to analyse possible associations between employment status and sleep parameters using actigraphy. Subjects (148 employed and 50 unemployed) were drawn from a German population‐based cohort. Sleep parameters were measured with the SenseWear Bodymedia Pro 3 armband. Comparison of means concerning sleep duration, sleep efficiency, time of sleep and sleep fragmentation was performed separately for week days and weekends. Multiple linear regression analysis was performed to analyse group differences controlling for covariates. Finally, we defined cut‐off scores for each sleep variable, and analysed the distribution of subjects above and below these values. Unemployed people did not sleep significantly longer than employed people. However, on week days, they displayed night sleep efficiency reduced by on average > 5% points, they lay down for 28 min longer, had later mid sleep time (38 min) and sleep offset (55 min), as well as more frequent awakenings after sleep onset accounting for being awake 28 min longer (all p ≤ 0.005). Sleep in unemployed subjects compared with employed subjects aged 41–64 years was less efficient, more fragmented and shifted to a later point of the night. Results support prior findings that unemployment has a negative influence on sleep quality. Unemployed individuals could benefit from intervention programmes aiming at the adoption of healthier sleep habits. [ABSTRACT FROM AUTHOR]

Background: The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behaviour but their small size hampers their manual segmentation in multicenter datasets. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors. We applied a new high‐resolution atlas in two independent cohorts of older and younger healthy adults. Method: Sixty‐four older (PharmaCog study; age range: 50‐78 years) and 67 younger subjects (CoRR consortium; age range: 18‐43 years) underwent repeated 3D‐T1 MRI at two different time points between 1 and 90 days. Amygdala and hippocampus segmentation was performed using FreeSurfer v6.0. Reliability of functional parcellations was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session. Nuclei/subfields were considered as single structures and grouped into relevant subregions (for the amygdala, basolateral and the centromedial complexes; for the hippocampus, head, body, and tail subdivisions). Result: Differences in MRI site/vendor had a significant impact (p<.05) for the ε of few subfields/nuclei, while extensively impacted DICE of most structures. The effect on DICE was limited by the functional parcellation only in the younger cohort. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (|rs|>.43, p<.001). In line, nuclei larger than 200 mm3 and subfields larger than 300 mm3 (except for molecular layer) had the best test‐retest reproducibility (ε<5% and DICE>0.80). Conclusion: Our results support the use of volumetric measures derived automatically from larger amygdalar nuclei and hippocampal subfields as reliable measures in multisite longitudinal MRI studies. These measures could be useful for studies evaluating disease progression and treatment response. [ABSTRACT FROM AUTHOR]

The genetic basis of sleep is still poorly understood. Despite the moderate to high heritability of sleep-related phenotypes, known genetic variants explain only a small proportion of the phenotypical variance. However, most previous studies were based solely upon self-report measures. The present study aimed to conduct the first genome-wide association (GWA) of actigraphic sleep phenotypes. The analyses included 956 middle- to older-aged subjects (40-79 years) from the LIFE Adult Study. The SenseWear Pro 3 Armband was used to collect 11 actigraphic parameters of night- and daytime sleep and three parameters of rest (lying down). The parameters comprised measures of sleep timing, quantity and quality. A total of 7 141 204 single nucleotide polymorphisms ( SNPs) were analysed after imputation and quality control. We identified several variants below the significance threshold of P ≤ 5× 10−8 (not corrected for analysis of multiple traits). The most significant was a hit near UFL1 associated with sleep efficiency on weekdays ( P = 1.39 × 10−8). Further SNPs were close to significance, including an association between sleep latency and a variant in CSNK2A1 ( P = 8.20 × 10−8), a gene known to be involved in the regulation of circadian rhythm. In summary, our GWAS identified novel candidate genes with biological plausibility being promising candidates for replication and further follow-up studies. [ABSTRACT FROM AUTHOR]

Objectives The arousal regulation model of affective disorders attributes an important role in the pathophysiology of affective disorders to dysregulation of brain arousal regulation. According to this model, sensation avoidance and withdrawal in depression and sensation seeking and hyperactivity in mania can be explained as auto-regulatory attempts to counteract a tonically high (depression) or unstable (mania) arousal. The aim of this study was to compare brain arousal regulation between manic and depressive bipolar patients and healthy controls. We hypothesized that currently depressed patients with bipolar disorder show hyperstable arousal regulation, while currently manic patients show unstable arousal regulation. Methods Twenty-eight patients with bipolar disorder received a 15-min resting electroencephalogram ( EEG) during a depressive episode and 19 patients received the same during a manic/hypomanic episode. Twenty-eight healthy control subjects were matched for age and sex. The Vigilance Algorithm Leipzig ( VIGALL), which classifies 1-s EEG segments as one of seven EEG-vigilance substages, was used to measure brain arousal regulation. Results Manic patients showed more unstable EEG-vigilance regulation as compared to the control sample ( P = .004) and to patients with a depressive episode ( P ≤ .001). Depressive patients had significantly higher mean vigilance levels ( P = .045) than controls. Conclusions A clear difference was found in the regulation of brain arousal of manic patients vs depressive patients and controls. These data suggest that brain arousal might depend on the current mood state, which would support the arousal regulation model of affective disorders. [ABSTRACT FROM AUTHOR]

Positive affect and the activity of the neurotransmitter dopamine seem to shift the balance between cognitive flexibility vs stability towards increased flexibility. Here we examined the impact of prospective monetary gains on this balance. Seventy healthy volunteers performed a set-shifting task comprising a condition in which a bias towards new stimuli helped to overcome perseveration and increased flexibility, and a second condition in which directing attention towards new stimuli increased distractibility. From previous studies of executive functions, two contrasting predictions can be derived: the prospect of monetary gains might either increase cognitive flexibility due to a dopamine release in the prefrontal cortex or increase stability due to an assessment of high utility of action processed in the anterior cingulated cortex and orbitofrontal cortex. Overall, we observed increased cognitive stability in the face of prospective gains (η2 = 7%). However, this effect was modulated by the subjective evaluation of the reward cues: participants who reported increasing their effort in response to reward cues showed increased cognitive stability, whereas those who reported a positive and relaxed attitude towards the reward cues showed increased flexibility (η2 = 11%). The results thus suggest that the flexibility–stability balance is modulated by the perceived effort needed to receive the potential reward. On a neuropsychological level, an interaction of dopaminergic and noradrenergic processes might be involved in the allocation of control. [ABSTRACT FROM AUTHOR]