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Arousal is a central component of many emotional symptoms and can contribute to insomnia. Here we assessed how the timing and fluctuating nature of arousal-related symptoms over the course of the day relate to insomnia symptom severity. In this study, 361 participants (M age = 31.9 years, 282 women, 77 men, 2 non-binary individuals) completed the Insomnia Severity Index to assess severity of insomnia symptoms, followed by repeated ratings of anxiety or nervousness, stress, sleepiness, and feeling down via their mobile phone between ~08:00 hours and 00:00 hours across 1 day. Measures of dynamics included: mean levels across the day; variation (standard deviation); instability (mean squared successive differences); and resistance to change/inertia (first-order autocorrelation). Time-of-day patterns were modelled using generalized additive mixed effects models. Insomnia symptom severity (mean Insomnia Severity Index = 9.1, SD = 5.2, range 0-25) was associated with higher mean levels of all arousal-related symptoms, and increased instability and variation throughout the day in anxiety or nervousness, stress, and feeling down. Resistance to change (inertia) was not associated with insomnia symptom severity. Generalized additive mixed effects analyses showed that while individuals with more severe insomnia symptoms had elevated symptoms across the entire day, they were especially more anxious or nervous and sleepy in the early morning (~08:00 hours), anxious or nervous, stressed and sleepy in the late afternoon/early evening (~16:00 hours-21:00 hours), and anxious or nervous and stressed in the late evening (~22:00 hours). Remarkably, higher arousal occurred in the presence of high subjective sleepiness. Together these results indicate that insomnia symptom severity is associated with problems with daytime and evening arousal regulation.

OBJECTIVE: Insomnia disorder is the most common sleep disorder. A better understanding of insomnia-related deviations in the brain could inspire better treatment. Insufficiently recognized heterogeneity within the insomnia population could obscure detection of involved brain circuits. The present study investigated whether structural brain connectivity deviations differ between recently discovered and validated insomnia subtypes.METHODS: Structural and diffusion weighted 3-Tesla MRI data of four independent studies were harmonized. The sample consisted of 73 controls without sleep complaints and 204 participants with insomnia grouped into five subtypes based on their fingerprint of mood and personality traits assessed with the Insomnia Type Questionnaire. Linear regression correcting for age and sex evaluated group differences in structural connectivity strength, indicated by fractional anisotropy, streamline volume density and mean diffusivity, and evaluated within three different atlases.RESULTS: Insomnia subtypes showed differentiating profiles of deviating structural connectivity which concentrated in different functional networks. Permutation testing against randomly drawn heterogeneous subsamples indicated significant specificity of deviation profiles in four of the five subtypes: highly distressed, moderately distressed reward sensitive, slightly distressed low reactive and slightly distressed high reactive. Connectivity deviation profile significance ranged from p= 0.001 to p=0.049 for different resolutions of brain parcellation and connectivity weight.CONCLUSIONS: Our results provide a first indication that different insomnia subtypes exhibit distinct profiles of deviations in structural brain connectivity. Subtyping of insomnia could be essential for a better understanding of brain mechanisms that contribute to insomnia vulnerability.

While standard polysomnography has revealed the importance of the sleeping brain in health and disease, more specific insight into the relevant brain circuits requires high-density electroencephalography (EEG). However, identifying and handling sleep EEG artifacts becomes increasingly challenging with higher channel counts and/or volume of recordings. Whereas manual cleaning is time-consuming, subjective, and often yields data loss (e.g., complete removal of channels or epochs), automated approaches suitable and practical for overnight sleep EEG remain limited, especially when control over detection and repair behavior is desired. Here, we introduce a flexible approach for automated cleaning of multichannel sleep recordings, as part of the free Matlab-based toolbox SleepTrip. Key functionality includes 1) channel-wise detection of various artifact types encountered in sleep EEG, 2) channel- and time-resolved marking of data segments for repair through interpolation, and 3) visualization options to review and monitor performance. Functionality for Independent Component Analysis is also included. Extensive customization options allow tailoring cleaning behavior to data properties and analysis goals. By enabling computationally efficient and flexible automated data cleaning, this tool helps to facilitate fundamental and clinical sleep EEG research.

Background: Twin studies show moderate heritability of sleep traits: 40% for insomnia symptoms and 46% for sleep duration. Genome-wide association studies (GWAS) have identified genetic variants involved in insomnia and sleep duration in adults, but it is unknown whether these variants affect sleep during early development. We assessed whether polygenic risk scores for insomnia (PRS-I) and sleep duration (PRS-SD) affect sleep throughout early childhood to adolescence. Methods: We included 2,458 children of European ancestry (51% girls). Insomnia-related items of the Child Behavior Checklist were reported by mothers at child's age 1.5, 3, and 6 years. At 10–15 years, the Sleep Disturbance Scale for Children and actigraphy were assessed in a subsample (N = 975). Standardized PRS-I and PRS-SD (higher scores indicate genetic susceptibility for insomnia and longer sleep duration, respectively) were computed at multiple p-value thresholds based on largest GWAS to date. Results: Children with higher PRS-I had more insomnia-related sleep problems between 1.5 and 15 years (BPRS-I < 0.001 =.09, 95% CI: 0.05; 0.14). PRS-SD was not associated with mother-reported sleep problems. A higher PRS-SD was in turn associated with longer actigraphically estimated sleep duration (BPRS-SD < 5e08 =.05, 95% CI: 0.001; 0.09) and more wake after sleep onset (BPRS-SD < 0.005 =.25, 95% CI: 0.04; 0.47) at 10–15 years, but these associations did not survive multiple testing correction. Conclusions: Children who are genetically predisposed to insomnia have more insomnia-like sleep problems, whereas those who are genetically predisposed to longer sleep have longer sleep duration, but are also more awake during the night in adolescence. This indicates that polygenic risk for sleep traits, based on GWAS in adults, affects sleep already in children.

Inappropriate sleep-related beliefs and behaviours are considered key maladaptive mechanisms in the development and maintenance of insomnia in the otherwise healthy population. The aim of this study was to evaluate critically the role of sleep-related beliefs and behaviours in insomnia after acquired brain injury. Cross-sectional data of 51 outpatients with insomnia disorder and acquired brain injury were used to evaluate associations of the insomnia severity index with the dysfunctional beliefs and attitudes about sleep scale and sleep-related behaviours questionnaire. Seven (44%) of the dysfunctional beliefs and attitudes about sleep scale items and 10 (31%) of the sleep-related behaviours questionnaire items correlated significantly with insomnia severity. Ten experts were consulted on whether they considered the questionnaire items maladaptive or accurately reflecting coping with conditions experienced by people with acquired brain injury. Although multiple linear regression showed that the total scores of the questionnaires explained a significant part of interindividual differences in insomnia severity (R2 = 0.27, F(2,48) = 8.72, p < 0.01), the experts unanimously rated only four (25%) of the dysfunctional beliefs and attitudes about sleep scale items as dysfunctional beliefs and three (9%) of the sleep-related behaviours questionnaire items as safety behaviours. In people with brain injury, sleep related beliefs and behaviours may also play a role in insomnia, especially a diminished perception of control and worry about sleep. However, more than half of the questionnaire items on sleep-related beliefs and behaviours may not be considered inappropriate and maladaptive for the acquired brain injury population, and may reflect adequate observations and efforts in coping with consequences of the brain damage.

The nature and degree of objective sleep impairments in insomnia disorder remain unclear. This issue is complicated further by potential changes in sleep architecture on the first compared with subsequent nights in the laboratory. Evidence regarding differential first-night effects in people with insomnia disorder and controls is mixed. Here, we aimed to further characterize insomnia- and night-related differences in sleep architecture. A comprehensive set of 26 sleep variables was derived from two consecutive nights of polysomnography in 61 age-matched patients with insomnia and 61 good sleeper controls. People with insomnia expressed consistently poorer sleep than controls on several variables during both nights. While poorer sleep during the first night was observed in both groups, there were qualitative differences regarding the specific sleep variables expressing a first-night effect. Short sleep (total sleep time < 6 hr) was more likely during the first night and in insomnia, although approximately 40% of patients with insomnia presenting with short sleep on night 1 no longer met this criterion on night 2, which is important given the notion of short-sleeping insomnia as a robust subtype.

Together with (physical and mental) exercise, diet, and social activities, sleep is a key health behavior that occupies one third of our lives, yet remains neglected. In the first part of this review, we present the current knowledge on how sleep promotes body, brain, mental, occupational, and social health as well as creativity, productivity, and well-being. In the second part, we discuss how good sleep and screening for sleep–wake disorders may improve health and reduce the burden of brain, mental, cardiovascular, metabolic disorders and cancer. We also review the literature on measurements of sleep health and present the Bernese Sleep Health Questionnaire, a new and simple tool to assess sleep health and screen for sleep–wake circadian disorders in clinical practice.

OBJECTIVE: While studies suggested that locus coeruleus (LC) neurodegeneration contributes to sleep-wake dysregulation in Alzheimer's disease (AD), the association between LC integrity and circadian rest-activity patterns remains unknown. Here, we investigated the relationships between 24-hour rest-activity rhythms, cognitive trajectories, and autopsy-derived LC integrity in older adults with and without cortical AD neuropathology.METHODS: This retrospective study leveraged multi-modal data from participants of the longitudinal clinical-pathological Rush Memory and Aging Project. Indices of 24-hour rest-activity rhythm fragmentation (intradaily variability) and stability (interdaily stability) were extracted from annual actigraphic recordings, and cognitive trajectories were computed from annual cognitive evaluations. At autopsy, LC neurodegeneration was determined by the presence of hypopigmentation, and cortical AD neuropathology was assessed. Contributions of comorbid pathologies (Lewy bodies, cerebrovascular pathology) were evaluated.RESULTS: Among the 388 cases included in the study sample (age at death = 92.1 ± 5.9 years; 273 women), 98 (25.3%) displayed LC hypopigmentation, and 251 (64.7%) exhibited cortical AD neuropathology. Logistic regression models showed that higher rest-activity rhythm fragmentation, measured up to ~7.1 years before death, was associated with increased risk to display LC neurodegeneration at autopsy (odds ratio [OR] = 1.46, 95% confidence interval [CI95% ]: 1.16-1.84, pBONF = 0.004), particularly in individuals with cortical AD neuropathology (OR = 1.56, CI95% : 1.15-2.15, pBONF = 0.03) and independently of comorbid pathologies. In addition, longitudinal increases in rest-activity rhythm fragmentation partially mediated the association between LC neurodegeneration and cognitive decline (estimate = -0.011, CI95% : -0.023--0.002, pBONF = 0.03).INTERPRETATION: These findings highlight the LC as a neurobiological