Sleep Advances

Study objectives: Aging is associated with increased sleep complaints and changes in sleep architecture, microstructure and rest-activity rhythms. Meditation-based interventions have shown benefits on subjective sleep quality, but their effects on objective sleep parameters remain largely underexplored. This study investigated the effects of an 18-month meditation intervention on sleep combining subjective (questionnaires) and objective (polysomnography and actigraphy) measures in older adults. Methods: A total of 120 cognitively unimpaired older adults ([≥]65 y) with minimal sleep complaint completed questionnaires, one week of actigraphy and in-home polysomnography at baseline, and again 18 months later. Following the baseline visit, participants were randomly assigned to one of 3 groups: meditation training, non-native language training (active control), or passive control. Group-by-visit interactions were examined using mixed-effects models for sleep questionnaires, actigraphy-derived metrics, sleep architecture and microstructure, including slow waves, spindles, and spectral power. Results: Compared to the passive control group only, meditation training was associated with greater ease of morning awakening (p=0.04). No significant intervention effects were observed for any other sleep parameter, including actigraphy- and polysomnography-derived measures. These findings remained unchanged after adjustment for depressive symptoms and trait anxiety. Conclusion: In cognitively unimpaired older adults, this 18-month meditation intervention yielded only limited improvements in subjective sleep assessment. Meditation may therefore have subtle effects on self-reported sleep quality in this healthy older population, although no effects on objective sleep measures were detected. Future studies should examine whether adapting the content, intensity, or timing of meditation practice and enrolling populations with clinically meaningful sleep disturbances or psychoaffective symptoms may yield greater benefits.

Background: Emerging evidence suggested the role of sleep and circadian rhythm in the development of mental resilience, but the association of an integrated analysis of objective sleep and circadian measures with multifaceted mental resilience in healthy adults has been underexplored. Objective: This study aims to explore the associations between multifaceted mental resilience and sleep and circadian rhythm in healthy adults. Methods: A total of 156 healthy adults (Age: Mean (SD): 29.54 (5.28) years; 60.9% female) underwent 14-day actigraphy, one night polysomnography (PSG) and dim light melatonin onset (DLMO) assessments. Resilience was operationalized as both a coping capacity and a positive mental health outcome in the context of accumulative adversity (life stressful events and childhood adversities). We first identified the covariance patterns between multiple sleep and circadian health domains (Sleep macro- and microstructures, dim light melatonin onset, rest activity pattern) and multifaceted mental resilience using partial least squares regression (PLSR), and followed by univariate analysis as complementary to illustrate the distribution trends of sleep and circadian rhythm parameters across integrative resilience score derived from principal component analysis (PCA). Findings: The PLSR model identified a modest but significant association of greater mental resilience with a sleep and circadian profile (Bootstrapping r = 0.15, 95%CI: 0.02-0.28), characterized by greater frontal-central slow waves activity in NREM sleep, greater frontal theta activity in REM sleep, lower occipital spectral power across fast and slow frequency bands in NREM and REM sleep, and probably earlier dim light melatonin onset timing. Conclusions: Sleep and circadian metrics, specifically frontal slow waves and REM theta activity, attenuated overall occipital spectral power during sleep, and earlier dim light melatonin onset time, represent quantifiable targets that may serve to improve resilience and stress-related mental health in adults. Longitudinal and interventional studies are needed to establish whether sleep interventions can be endorsed as evidence-based approaches for resilience enhancement. Clinical implications: Targeting sleep and circadian aspects may be an important approach to promote stress-related mental health.

Sleep disturbances compromise cognition, and overall physical and mental health; however, animal models of these effects remain limited, and typically impose more extreme disturbances than those experienced by humans. Here, we use behavioural interventions in mice to model two common types of sleep disruption: (1) sleep displacement associated with shiftwork and (2) sleep fragmentation associated with aging and disease. C57BL6/J mice were subjected to either a sleep deprivation protocol (n = 8, females = 4) or a fragmentation protocol (n = 8, females = 4), in which they were completely deprived of sleep or awoken every 2 min respectively, for 12 hours during their typical rest phase (lights-on) across 7 consecutive days. Age-matched control mice (n = 14, females = 7) remained undisturbed in their home cages. Activity during the 12-hour active phase was recorded via infrared motion sensors. After protocol completion, mice were injected with bromodeoxyuridine (BrdU, 200mg/kg) 2 hours prior to brain and blood collection; hippocampal neurogenesis and plasma corticosterone were then assessed. Results show that the sleep deprivation and fragmentation protocols had different, dynamic effects on behaviour; sleep deprivation was associated with an accumulating sleep need, operationalized as progressively reduced locomotor activity across the week, whereas fragmentation produced only an acute reduction of locomotor activity. Cell proliferation rates and corticosterone did not differ from controls. These protocols provide a foundation for future research into the mechanistic links between shiftwork and sleep fragmentation on health and cognition.

Background: Although sleep disorders are generally associated with cognitive decline, definitions of sleep conditions and cognitive function vary greatly across studies. Therefore, we evaluated associations between consensus definitions of sleep and cognitive outcomes across multiple studies. Methods: Consensus sleep measures were ascertained at baseline visits in three cohort studies (HCHS/SOL, MESA and ARIC, N=11,563): short and long sleep ([≤]6hours and [≥]9hours), insomnia (Women's Health Initiative Insomnia Rating Scale [≥]10 or [≥]6 for 3 questions), daytime sleepiness (Epworth Sleepiness [≥]11) and obstructive sleep apnea (OSA, Apnea-Hypopnea Index [≥]15). Cognitive measures were ascertained at baseline and follow-up visits in each study and used to calculate harmonized outcomes: global cognitive function (GCF) at baseline, change in GCF between baseline and follow-up, poor GCF at baseline ([≥]1SD below the median), and incident poor GCF at follow-up. Study-specific analyses were adjusted for age, sex, center, education, race/ethnicity, APOE4 and language of cognitive assessments as needed. Results were meta-analyzed across studies. Results: Long sleep was consistently associated with lower baseline GCF ({beta}=-0.19, SE=0.03, p=3.78x10-14, FDR p=7.56x10-13, p-heterogeneity=0.78) and increased odds of poor baseline GCF (OR=1.77, 95% CI=1.49-2.09, p=2.96x10-11, FDR p=2.96x10-10, p-heterogeneity=0.22) across cohorts. Insomnia was also suggestively associated with lower baseline GCF ({beta}=-0.051, SE=0.02, p=0.01, FDR p=0.07, p-heterogeneity=0.005) and increased odds of poor baseline GCF (OR=1.22, 95% CI=1.06-1.41, p=6.76x10-3, FDR p=0.05, p-heterogeneity=0.03). Sleep measures were not associated with change in cognitive function. Discussion: Associations of long sleep and insomnia with harmonized cross-sectional GCF across three large, multiethnic cohorts suggest that cognitive function may be associated with distinct sleep phenotypes.

Study Objectives: To characterize neural correlates of memory and emotion reactivity in individuals with insomnia disorder (INS) compared to good sleepers (GS) and to investigate associated short- and long-term changes following cognitive-behavioural therapy for insomnia (CBTi). Methods: This randomized controlled trial included 56 INS and 20 GS. At baseline, participants underwent resting-state and task-based functional magnetic resonance imaging, including working memory, emotion reactivity, and face-name associative memory tasks. They filled out sleep diaries and self-report questionnaires about sleep, cognition, and emotions, and underwent in-lab polysomnography. Subsequently, participants with INS were randomized to either the 3-month treatment group (TX) or wait-list control group (WL). Both TX and WL groups repeated baseline assessments at three months post-randomization and completed sleep diaries and questionnaires one year after finishing CBTi. Results: At baseline, the INS group reported higher insomnia severity, greater subjective cognitive impairment, and perceived sleep-related stimuli as more negative than GS. Contrasting with these subjective evaluations, no group differences were found in memory performance, task-based brain activity, or resting-state functional connectivity. At three months post-randomization and one-year follow-up, CBTi significantly improved subjective, but not objective, cognitive functioning and sleep in adults with INS. No significant treatment-related changes were observed in valence ratings of sleep images, task-based brain activity, or resting-state functional connectivity. Conclusions: Beyond its primary role in improving insomnia symptoms, CBTi may have long-term benefits for individuals with INS who experience concerns about their cognitive functioning, even in the absence of objective changes in neural processing of cognitive and emotional tasks.

Background: Circadian syndrome (CircS) comprises metabolic abnormalities, short sleep, and depressive symptoms, and is associated with cardiovascular, liver, and lung diseases and mortality; evidence on digestive disease is scarce. We assessed its association with incident non-neoplastic digestive disease in Chinese adults. Methods: In this prospective analysis of the China Health and Retirement Longitudinal Study (CHARLS), we included 2011 baseline participants aged >=45 years free of digestive disease, with follow-up to 2018. CircS (>=4 of 7 components) was analysed as a continuous score and as a binary exposure. Cox models estimated hazard ratios (HRs) adjusting for demographic factors, BMI, smoking, and alcohol use. We did dose-response, component, subgroup, and sensitivity analyses; hs-CRP mediation was explored. Findings: 907 (19.0%) of 4 771 participants developed digestive disease over a median 84 months. Each additional CircS component raised the risk by 9.1% (HR 1.091, 95% CI 1.041-1.144, P<0.001); CircS positivity (36.1%) was associated with a 25.7% higher risk (HR 1.257, 1.084-1.456, P=0.002). Risk rose approximately linearly to about 70% higher at 5-7 components. Short sleep (HR 1.178, 1.017-1.365) and depressive symptoms (HR 1.570, 1.367-1.803) were the only independently associated components; no metabolic component was associated. Results were robust across sensitivity analyses; hs-CRP did not mediate the association. Interpretation: CircS is associated with incident non-neoplastic digestive disease, driven by its circadian-emotional rather than metabolic components. Sleep and mood may be targets for prevention. Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Keywords: circadian syndrome; digestive diseases; cohort study; sleep; depression; brain-gut axis

Sleep disturbances are a significant but underrecognized burden for individuals with Lennox-Gastaut Syndrome (LGS) and their caregivers. We conducted a large LGS caregiver survey to assess sleep quality, duration, specific sleep-related issues, and management strategies. Quantitative analysis revealed a significant association between nocturnal seizures and overall seizure frequency, but general sleep metrics in individuals with LGS (e.g., sleep hours, sleep quality) were not associated with seizure burden. In contrast, caregiver sleep was frequently disrupted - particularly in families who co-slept or reported frequent seizures. Nearly 40% of caregivers experienced nightly sleep disturbances. Respondents reported a range of strategies to manage sleep problems, including medication, environmental adjustments, and behavioral routines. Many also expressed frustrations over the limited effectiveness of strategies and inadequate support for sleep issues. These findings underscore the dual impact of LGS-related sleep disturbances on patients and caregivers, and highlight the need for comprehensive, family-centered approaches to sleep health.

Background: Associations of sleep duration and insomnia symptoms with cognitive decline are inconsistent, and whether they represent modifiable risk factors or early manifestations of neurodegeneration may depend on life stage. We examined how sleep-cognition associations vary with age (44 to >90 years). Methods: We studied 16,884 participants from three cohorts with harmonised measures. In the English Longitudinal Study of Ageing (ELSA: n=9,473, median age 64, range 50 to >=90), linear mixed-effects models examined age-specific differences in cognitive change (recall and fluency) associated with sleep duration, difficulty falling asleep, nocturnal awakenings, incorporating sleep-by-age-by-time interactions, with initial adjustment for sociodemographic factors and further adjustment for health and lifestyle factors. Sleep characteristics showing consistent age-dependent associations in ELSA were further evaluated in Whitehall II (n=5,580, median age 55, range 44 to 68) and the Rush Memory and Aging Project (MAP: n=1,831, median age 80, range 53 to 102). Findings: In ELSA, difficulty falling asleep >=1 time/week (vs <1 time/week) was associated with less favourable 5-year change in recall at age 50 (difference -0.12 SD, 95% CI -0.20 to -0.04), with the association attenuating and reversing towards more favourable change at older ages (p-interaction=0.009 [linear], 0.016 [quadratic]). These persisted after further adjustment for health and lifestyle factors. Short sleep (<=6 h) showed similar patterns that attenuated after further adjustment. Similar age gradients were observed for difficulty falling asleep in Whitehall II and MAP. There was no evidence of age modification on long sleep and nocturnal awakenings. Interpretation: The cognitive implications of sleep disturbances vary by life stage. In midlife, difficulty falling asleep was associated with faster cognitive decline, supporting its role as a modifiable risk factor. In advanced age, the reversal is consistent with diminished arousal capacity accompanying prodromal dementia. Funding: US National Institute on Aging

Borderline personality disorder (BPD) is a serious mental illness that often emerges in adolescence. Although efficacious treatments have been developed, they are often lengthy, expensive, inaccessible, and require specialized training to deliver. Optimizing BPD prevention and early treatment is an important public health priority. Disrupted sleep is closely linked to key BPD features, and prior research has documented a range of sleep problems among BPD samples that appear to worsen symptom course and duration. This intervention trial (NCT04507308) assessed the effects of a single-session sleep-focused treatment on adolescent sleep and BPD-related symptoms. Fifty-seven adolescents (ages 13-18) with 3+ clinically impairing BPD features and at least some self-reported sleep-related difficulties participated with a caregiver. Participants completed baseline surveys, interviews, and 10-day ecological momentary assessment (EMA) protocol to examine BPD symptoms and sleep in daily life. Youth also collected at-home ambulatory electroencephalogram (EEG) recordings before undergoing the treatment informed by the Transdiagnostic Sleep and Circadian Intervention. Post-treatment, youth practiced their new sleep routine for approximately one month before undergoing reassessment (EMA, EEG, surveys). Many indices of sleep quantity and quality improved across both objective (EEG) and subjective assessments (EMA and self- and caregiver-report). Youth reported an earlier bedtime and waketime, more sleep, and fewer awakenings in daily life. Every sleep-related questionnaire score improved at post-intervention and was maintained at one-month follow-up. Multiple indices of BPD symptoms also improved significantly. Findings suggest sleep may be a promising intervention target for at-risk youth.

Abstract Background: Insomnia is highly prevalent in major depressive disorder (MDD), yet the clinical and biological significance of dysfunctional beliefs and attitudes about sleep (DBAS) in MDD remains poorly understood. We examined whether distinct DBAS dimensions are associated with insomnia severity, depressive phenotypes, and neuroimmune-metabolic-oxidative (NIMETOX) biomarkers. Methods: DBAS-30 dimensions, clinical phenotypes, and NIMETOX biomarkers were assessed in 87 hospitalized patients with MDD and 31 healthy controls. Principal component analysis (PCA) was used to ascertain DBAS cognitive dimensions, and associations were examined using multivariable analyses. Results: Compared with controls, MDD patients showed lower scores on "perceived consequences of insomnia," "sleep-related worry and helplessness," and "medication-related beliefs," but higher "causal attributions to aging or biochemical imbalance" scores. A composite DBAS score reflecting these 4 MDD-associated cognitive dimensions was constructed, labeled DBAS dimensional index (DBAS-DI). This score was lower in MDD and inversely associated with Insomnia Severity Index (ISI) scores, overall MDD severity, physiosomatic symptoms, current suicidal ideation, and recurrence of illness. DBAS-DI and the expectations domain jointly explained 35.4% of the variance in ISI scores, with inverse and positive associations, respectively. The DBAS-DI score was inversely associated with indices of the acute-phase inflammatory response, oxidative stress, fecal branched-chain short-chain fatty acids (SCFAs) and positively associated with serum antioxidant capacity and protective SCFAs, such as acetate, propionate, and butyrate. Conclusions: DBAS abnormalities in MDD extend beyond insomnia-related cognitions and are associated with illness severity, suicidality, recurrence, and NIMETOX alterations. These findings suggest that dysfunctional sleep-related cognitions are embedded within broader immune-oxidative and gut microbial-metabolic processes that may contribute to the insomnia-depression interface.

For sleep scoring in rodents, the use of electromyography (EMG) is considered the gold standard to assess muscle tone; however, EMG electrodes require invasive surgical implantation, are sensitive to muscular placement, can have extensive noise due to non-muscular signal contamination, and are at risk of failure due to mechanical stress. The use of an accelerometer (Acc) integrated on the recording headstage offers an alternative for movement detection. However, the degree of agreement between these two approaches has never been systematically evaluated. To understand if these tools allow similar scoring outcomes, seven trained scorers manually classified mouse sleep recordings using hippocampal local field potential (LFP) together with EMG or Acc. When comparing scoring between EMG and Acc, overall epoch-by-epoch accuracy exceeded 90% with a kappa score above 0.8, indicating excellent agreement. However, Acc was found to under classify Wake by 4.92% while overclassifying NREM sleep by 3.29%, possibly reflecting a decreased sensitivity of Acc to subtle changes in muscle tone used in distinguishing Wake from NREM sleep. Comparing EMG and Acc signal for agreed epochs vs disagreed epochs revealed a weaker correlation between the two signals for disagreed epochs, especially for Wake and NREM, suggesting that disagreements reflected genuine signal differences rather than scorer subjectivity. These findings support LFP/Acc as a valid approach to sleep scoring, however, it is noted that Acc based scoring slightly underestimated Wake epochs, favoring NREM sleep, relative to traditional EMG approach.

Study Objectives: Glucagon-like peptide-1 (GLP-1) receptor agonists raise resting heart rate. We asked whether, after semaglutide initiation, the increase is larger during rapid eye movement (REM) sleep than during non-rapid eye movement (NREM) sleep. Methods: In the Human Phenotype Project, an Israeli cohort of generally healthy adults aged 40 to 70 years, 96 of 494 self-reported semaglutide initiators had a home sleep study (WatchPAT; sleep stages estimated from peripheral arterial tone and actigraphy) before and at least three months after starting. Each was propensity-matched 1:1 to a never-user of GLP-1 drugs measured at the same visits. We estimated the initiators' change minus their controls' change (difference-in-differences). The REM minus NREM contrast was designated primary after an exploratory analysis. Results: Relative to controls (90 to 94 pairs), heart rate rose during nocturnal wake (+3.89 beats per minute [bpm], 95% confidence interval 2.35 to 5.44), NREM sleep (+4.82 bpm, 3.12 to 6.52) and REM sleep (+6.25 bpm, 4.42 to 7.91); the REM increase exceeded the NREM increase by 1.42 bpm (0.98 to 1.89). The excess persisted across matching designs and on a relative scale; the proportion of REM sleep did not change. Never-users with similar weight loss showed no REM sleep heart-rate rise (+0.40 bpm, -0.63 to 1.50). Heart-rate variability decreases disappeared after adjustment for heart rate. Conclusions: Semaglutide initiation was associated with higher heart rate throughout sleep, most during REM sleep, unexplained by weight loss. Clinic measurements may understate this effect. Confirmation with polysomnographic staging is needed.

Seasonal daylight saving time (DST) transitions abruptly alter the alignment between clock time, environmental light, and sleep. In preregistered analyses, we used longitudinal Fitbit data from the All of Us Research Program to compare sleep around 13 seasonal transitions in Colorado, New Mexico, and Utah with sleep on the same dates in Arizona, where clocks do not change. The sample included 1,522 participants and 6,658 participant-transition windows. Following the spring transition, sleep duration changed more from one night to the next in Mountain states than in Arizona (14.6 minutes, 95% CI [7.2, 22.0]), even though sleep duration itself on day +1 showed little evidence of a DST-related reduction (-8.4 minutes, 95% CI [-17.3, 0.6]). Sleep timing shifted later after the spring transition and about 28 minutes earlier after the fall transition. Among Mountain-state observations with a large post-transition departure from usual sleep duration, the median return to the usual range was two nights. Nearly the same two-night pattern appeared in Arizona after similarly large sleep departures, indicating that this return pattern was not specific to DST. Greater baseline sleep-duration variability predicted a greater likelihood of remaining outside the usual range at days +7 and +14. Seasonal clock changes produced acute sleep disruption, while the Arizona comparison shows that a rapid return to baseline should not be interpreted as the duration of recovery from DST itself.

Chronic social isolation induces persistent behavioral and physiological changes across species. In humans, prolonged social isolation is associated with insomnia and increased risks of cognitive decline, cardiovascular disease, compromised immunity, and premature mortality. Yet whether these consequences are modified by the environment in which social isolation is experienced remains unclear. In particular, can access to social sensory information from conspecifics alleviate the effects of isolation and can various ambient environmental settings modify them? A related question arises during behavioral measurement because behavioral assays themselves impose a new environmental context. Whether these assays simply capture the enduring effects of prior social experience or further modify those effects remains unknown. Using social isolation-induced sleep loss in Drosophila as a model, we systematically examined how the social, spatial, and photoperiodic environments during isolation and behavioral monitoring influence the isolation phenotype. Providing isolated flies with visual, olfactory, or tactile social cues from conspecifics living behind a divider, either individually or in combination, was insufficient to alleviate sleep loss. Spatial confinement exacerbated isolation-induced sleep loss, while winter-like photoperiod in spatially confined Drosophila Activity Monitor assays revealed the clearest progressive decline in sleep during sleep monitoring. Together, these findings demonstrate that social isolation-induced sleep loss is both enduring and dynamic: it persists despite exposure to social cues yet remains sensitive to the environmental context in which isolation is experienced and behavior is measured. More broadly, our study establishes a tractable framework for investigating the environmental modulation of chronic social isolation.

Objective This study aimed to develop and validate a predictive model for sleep disorders in young and middle-aged adults with anemia, providing evidence for early identification, risk stratification, and individualized sleep management. Methods Data in the NHANES were analyzed and randomly divided into development and validation cohorts. LASSO regression was used to screen optimal predictors in the development cohort, followed by univariate and multivariate logistic regression to identify independent predictors and construct a nomogram. Model performance was evaluated using receiver operating characteristic curves, calibration curves, Brier scores, and decision curve analysis. Results The weighted prevalence of sleep disorders among young and middle-aged adults with anemia was 10.19%. Multivariate logistic regression identified seven independent predictors: sex, monocyte count, asthma, overweight, arthritis, congestive heart failure, and hypertension. The model showed good discrimination, with area under the curve values of 0.817 in the development cohort and 0.791 in the validation cohort. Calibration was satisfactory, with Brier scores of 0.074 and 0.075, respectively. Decision curve analysis indicated favorable clinical net benefit in both cohorts. Conclusion The proposed predictive model demonstrated good discrimination, calibration, and may help healthcare providers identify young and middle-aged adults with anemia who are at high risk for sleep disorders.

Background: Patients increasingly consult free artificial intelligence (AI) chatbots about their symptoms, but these models may favour agreement with the patient over accuracy. In obstructive sleep apnoea (OSA), where most cases in the general population remain undiagnosed and diagnosis depends on referral, this could validate symptom denial. We tested whether consumer chatbots maintain guideline-concordant referral when a simulated patient minimises symptoms. Methods: Seven guideline-concordant and standardised OSA vignettes (apnoea-hypopnoea-index, AHI 8-52 events/h; body mass index 28-42 kg/m2) were presented to five free chatbots (GPT-5, Gemini 2.5 Flash, Claude Sonnet 4.6, DeepSeek V4 Flash and Grok-4.3) under neutral and symptom-minimising conditions (10 simulated conversations per model-vignette-condition cell; N=700). Referral maintenance was scored by a structured rubric and every capitulation was human-confirmed. Results: All chatbots maintained referral recommendations in neutral conversations (350/350; 100%). When simulated patients minimised symptoms and resisted referral, maintenance fell to 64.3% (225/350), a reduction of 35.7 percentage points (95% CI 5.5-66.0; p=0.028). Rates ranged from 55.7% to 85.7% across chatbots, but evidence of between-chatbot differences was inconsistent across analyses. Rates differed across clinical vignettes (p=0.001). A variance analysis estimated greater variation between vignettes than between chatbots. In the three driving-risk vignettes, referral recommendations were abandoned in 46-68% of symptom-minimising conversations, pooling all five chatbots within each vignette. Conclusions: Consumer AI chatbots abandoned correct OSA referral recommendations in about one-third of symptom-minimising conversations, with higher observed abandonment in simulated cases involving driving risk. This may delay appropriate assessment and raises patient- and public-safety concerns.

Objectives: Opioids disrupt sleep, but how repeated exposure reorganizes thalamocortical networks is unknown. We asked whether morphine alters sleep architecture, regional oscillations, and phase synchronization, and how exposure history modifies these effects. Methods: From mice, we analyzed cortical electroencephalogram (EEG), central medial thalamic (CMT) local field potentials (LFP), and electromyography (EMG) for 24h after the first and fourth injections of morphine and in abstinence, and quantified vigilance-state occupancy, spectral power, state-power correlations, and the weighted phase-lag index (wPLI), which minimizes volume conduction. Results: Morphine produced hyperlocomotion, wake promotion persisting with repeated exposure, non-rapid eye movement (NREM) sleep suppression, complete rapid eye movement (REM) sleep loss, and rebound sleep. Cortex and thalamus dissociated: in NREM sleep after the first injection, cortical delta and low-gamma power increased, while CMT delta, theta, alpha, and beta power decreased. NREM occupancy coupled more strongly to CMT delta and theta power after both injections, whereas cortical wake correlations in theta, alpha, and beta fell and reversed during abstinence. Overall synchronization was altered only in theta and alpha: corticocortical alpha synchronization decreased acutely, and repeated exposure reduced thalamocortical theta synchronization in wake and NREM sleep. During abstinence, sleep architecture and synchronization largely normalized while spectral and state-power abnormalities persisted alongside mechanical hypersensitivity. Conclusions: We found that morphine does not merely reduce sleep; it reorganizes it: cortex and CMT move in opposite directions, thalamocortical phase synchronization is redistributed, and the resulting spectral and state-power abnormalities outlast the recovery of sleep architecture itself rather than producing tolerance.

Study Objectives: Sleep disturbances are common in youth with anxiety disorders, yet most prior work relies on subjective measures and does not capture underlying neural processes. We examined whether alterations in non-rapid eye movement (NREM) sleep oscillations are present in children with anxiety disorders and whether these features relate to internalizing symptoms and emotional functioning. Methods: Children aged 9-13 years with diagnosed anxiety disorders (ANX; n = 17) and typically developing non-psychiatric comparison participants (NC; n = 26) completed overnight polysomnography. Slow oscillations (SO) and slow and fast sleep spindles were characterized using validated automated detection algorithms. Participants also completed a pre-sleep emotional processing task, and parents provided standardized measures of youth mental health. Group differences and dimensional associations between NREM oscillations, internalizing symptoms, and behavioral indices of emotional processing were examined. Results: Sleep architecture did not differ between groups. Slow spindle duration was shorter in the ANX group. Across the full sample, shorter slow spindle duration was associated with greater internalizing symptoms, whereas higher SO density was positively associated with internalizing symptoms. Children in the ANX group exhibited greater facial emotional arousal and more frequent look-away behavior during the emotional processing task. Across participants, greater emotional arousal and look-away behavior were associated with shorter spindle duration during subsequent sleep. Conclusions: Specific features of NREM microarchitecture were associated with individual differences in internalizing symptoms and emotional functioning during early adolescence. These findings highlight the potential relevance of NREM oscillations for understanding developmental links between sleep and youth psychopathology.

Many studies using mouse models of human brain disorders rely on extended recordings of brain electrical activity through electroencephalogram, or EEG. The features that researchers measure in these recordings, such as seizures and epileptiform activity, are deeply influenced by whether the animal is awake, in non-rapid eye movement (NREM) sleep, or in rapid eye movement (REM) sleep. Because total sleep duration varies naturally across animals, rigorous experimental comparisons require classifying the sleep state of every few seconds of a recording. Manual annotation is highly labor-intensive, often requiring hours per subject. While automated scoring tools accelerate this process, they are typically trained exclusively on healthy cohorts and frequently fail when applied to disease models that exhibit atypical or fragmented sleep architecture. Somnus is an open-source Python package designed to automate rodent sleep staging using EEG, muscle activity (EMG), and optional video-tracking data. It includes a robust base model trained on diverse recordings from six independent laboratories, enabling out-of-the-box classification across various equipment setups without requiring prior manual labeling. A central feature of Somnus is its capacity for rapid adaptation to pathological sleep structure. The software provides a graphical interface that directs researchers to the specific epochs where the base model is least certain. Users can manually correct these targeted epochs in a built-in viewer by comparing the model's classification to the raw EEG signal and video, and then use their corrections to fine-tune the model. This workflow empowers researchers to generate accurate custom scorers for complex disease models or novel treatments with just a few minutes of manual correction, bypassing the need to hand-score entire experimental cohorts or develop their own models from scratch.

Background: Sleep-wake-circadian disorders are prevalent and contribute substantially to morbidity, mortality and reduced quality of life. Evaluation in real-world settings is essential to capture their complexity and association with long-term outcomes. Most sleep-wake registries are restricted to selected populations, lack systematic integration of objective sleep-wake-circadian assessments with the clinical data and provide limited follow-up. To address these limitations, we established the Bern Sleep-Wake Registry based on real-world data from a tertiary University Hospital sleep center. Methods: The registry includes data from patients referred to the multidisciplinary Sleep- Center at Inselspital, University Hospital Bern (funded in 1990), from the year 2000 onwards who underwent at least one objective assessment such as polysomnography, daytime sleep-wake recordings, vigilance tests, and actigraphy. The registry integrates clinical information, questionnaire scores, outputs of objective assessments and raw signal data, and is regularly updated to incorporate new patients and longitudinal follow-up information. Results: As of September 2025, records from over 11000 patients were evaluated (median age: 50 years (interquantile range 36, 61); 65% male). The most common sleep-wake-circadian disorders were sleep-related breathing disorders (67%), insomnia disorders (15%) and central disorders of hypersomnolence (9%). Available assessments included more than 12000 polysomnographies, 2400 multiple sleep latency tests, 2100 maintenance of wakefulness tests, 1800 vigilance tests and 4500 actigraphies. Conclusions: By longitudinally integrating multimodal deep clinical phenotyping with objective assessments and raw physiological signals, the Bern Sleep-Wake Registry provides a foundation for investigating disease trajectories, identifying novel biomarkers and developing data-driven approaches to precise diagnosis, prognosis and individualized treatment.