Journal of Sleep Research

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.

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.

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.

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.

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.

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.

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.

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.

Animals and humans often forgo sleep in response to other physiological needs. Prolonged wakefulness leads to a compensatory homeostatic sleep response involving enhanced amounts of sleep and electroencephalographic delta (0.5-4 Hz) power, yet how the type of preceding wakefulness and brain activity affects this response is poorly understood. Here we compared the pattern of brain activity and the homeostatic sleep response following sustained wakefulness induced by either gentle handling (GH), a widely used form of sleep deprivation in rodents; or optogenetic stimulation of neurons involved in avoidance/defensive responses, basal forebrain (BF) vesicular glutamatergic transporter type 2 (vGluT2) neurons. Local infusion of ionotropic glutamate receptor antagonists partially attenuated the wake-inducing effect of vGluT2-stimulation, but not that of GH, suggesting mediation by other non-glutamatergic BF subtypes. These antagonists also tended to produce more NREM sleep and a shorter NREM latency in the recovery period following vGluT2-stimulation. Both manipulations increased high theta (7-9 Hz) during wakefulness, an effect partially blocked by local infusion of the glutamate antagonist cocktail. Enhanced NREM sleep time and NREM delta power in the recovery period were more pronounced following GH than following vGluT2 stimulation. Whole-brain cFos immunohistochemistry revealed stronger neuronal activity in brain regions involved in stress and avoidance/defensive behaviors with vGluT2 stimulation, compared to GH. Our results demonstrate that activation of a brain system involved in defensive behavior (BF vGluT2) elicits a distinct and diminished homeostatic sleep response compared to GH, potentially an evolutionary sleep adaptation which would maintain vigilance in the face of an ongoing threat.

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.

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.

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 People diagnosed with severe mental illnesses (SMI) including bipolar disorder, schizophrenia and psychosis are disproportionately exposed to adverse social determinants of health, contributing to premature morbidity and mortality. Social prescribing aims to address social risk factors for poor health by linking patients in primary care to community activities. However, whether people with SMI access social prescribing through primary care remains unexplored. Aims To describe prevalence of, and sociodemographic characteristics associated with, social prescribing consultations in patients with SMI in primary care. Methods Using the UK Clinical Practice Research Datalink, we identified patients aged 18+ with a diagnosis of SMI between 2004-2019. We calculated the percentage of patients with SMI who received a social prescribing consultation between 2019-2023 and used logistic regression to examine associations between sociodemographic, health-related factors and social prescribing consultations and refusals. We used fixed effects analysis to determine whether a new diagnosis of SMI made between 2019-2023 was associated with an increased odds of receiving a social prescribing consultation. Results Among 112,334 patients with SMI, 0.8% received a social prescribing consultation in 2019 increasing to 9.5% in 2023. Between 2020-2023, older age (OR=1.18-2.34), being female (OR=1.16-1.31) and living in more deprived areas (OR=1.14-1.49) were associated with higher odds of receiving a social prescribing consultation amongst patients with SMI. Across all years, patients with SMI and depression (OR=1.32-1.92), diabetes (OR=1.19-1.35) or obesity (OR=1.17-1.54) also had increased odds. In 140,514 patients with time-varying SMI status, a new diagnosis of SMI was associated with higher odds of receiving a social prescribing consultation (OR=1.39, 95% CI 1.26-1.53). Conclusion Since 2019, social prescribing consultations among patients with SMI in primary care have increased and are reaching those in areas of higher deprivation and with greater health needs. Strategies to remove barriers to consultations among younger adults and males are still needed

Background: Adolescent mental health problems have risen alongside increasing sleep disruption and widespread social media use (SMU). However, the mechanisms linking these factors remain unclear. This study concurrently examined objectively measured sleep and SMU in relation to psychopathology to test whether SMU moderates the sleep-mental health association and to characterize day-to-day bidirectional relations among sleep, affect, mood, and SMU during the school year. Methods: Eighty-five adolescents (ages 12-18) completed 14 days of wrist actigraphy, smartphone-based ecological momentary assessments of mood and affect, and objective SMU duration tracking. Cross-sectional models tested whether SMU moderated associations between sleep and psychopathology, and multilevel daily models examined within-person lagged associations among sleep, SMU, and affect, controlling for age and sex. False discovery rate correction was applied. Results: Shorter average sleep duration and greater variability in sleep duration between weekdays and weekends were associated with higher psychopathology symptoms, primarily externalizing problems. SMU duration neither moderated nor directly predicted psychopathology or sleep. Within-person analyses showed that longer-than-usual sleep predicted more positive and less negative affect and lower next-day SMU, though these associations did not survive correction for multiple comparisons. Conclusions: Sleep disruption showed consistent associations with adolescent psychopathology, whereas the amount of time spent on social media did not. These findings suggest that duration-based measures of SMU may incompletely capture adolescents digital experiences and highlight the need for more granular, context-sensitive indicators of online behavior in understanding youth mental health.

NREM slow waves emerge from the synchronization of neuronal activity across multiple spatial scales. During childhood, local synchronization and large-scale propagation undergo distinct maturational trajectories, paralleling cortical synaptic remodeling and the maturation of long-range brain connectivity. How alterations in this local-to-global organization relate to arousal instability remains poorly understood. Here, we used 256-channel high-density EEG to characterize NREM oscillatory organization in 17 children with disorders of arousal (DOA) and 17 age- and sex-matched healthy controls. Children with DOA showed a marked dissociation between local synchronization and large-scale coordination: slow waves were locally larger, steeper and more synchronized, yet recruited the cortex less globally and exhibited a more spatially restricted distribution of origins. This phenotype preferentially involved Type 1 slow waves, a subtype associated with widespread cortical and subcortico-cortical recruitment and late developmental maturation. Children with DOA also showed reduced centro-posterior slow spindle density, providing convergent evidence for altered coordination of distributed NREM oscillations. These microstructural abnormalities occurred despite largely preserved conventional sleep architecture. Together, our findings reveal an altered local-to-global organization of NREM sleep in pediatric DOA and suggest that vulnerability to incomplete arousals may emerge when strong local synchronization is not matched by effective large-scale network coordination during brain development.

Homeostatic mechanisms adjust synaptic strengths to regulate neuronal activity across wake-sleep cycles. Although sleep supports memory consolidation, limited research has explored how sleep-induced homeostatic changes influence memory outcomes in humans. The EEG-derived aperiodic slope (1/f) could be a candidate measure of homeostatic memory processes through its reflection of neural excitation-inhibition balance. In this study, 27 participants learned object-word pairs, and completed an immediate recognition test before either a nap or equivalent wakeful period. Resting-state EEG was recorded, both before and after learning and the interval, to derive changes in aperiodic slope values. A delayed recognition test then assessed whether changes in the aperiodic slope (i.e., homeostatic activity) across learning and the interval predicted memory accuracy and N400 amplitude, an index of stimulus expectancy and recognition. Our study found evidence to suggest homeostatic renormalisation, for the nap condition only, indicated by a shift towards inhibition across sleep which was inversely related to the slope change across learning. Although the aperiodic slope change across the nap and wake intervals did not predict delayed memory accuracy, a shift towards inhibition during learning was beneficial for memory accuracy, only in the nap condition. Similarly, a shift towards inhibition across learning, followed by a shift towards excitation in the nap condition, predicted reduced N400 amplitudes. This suggests that homeostatic renormalisation across the nap influenced model updating and stimulus expectancy. This study provides evidence for a link between synaptic homeostatic processes and memory consolidation, emphasising the importance of encoding-related aperiodic activity in this relationship.

Communication between the brain and cardiovascular system is increasingly recognized as a fundamental determinant of health, yet the mechanisms coordinating neural and cardiac rhythms remain poorly understood. Sleep provides a unique physiological state for investigating neurovisceral integration because cortical slow oscillations (SOs), thalamocortical sleep spindles, and autonomic activity undergo profound reorganization during non-rapid eye movement (NREM) sleep. We analyzed overnight high-density electroencephalography and electrocardiography recordings from 30 healthy adults and quantified interactions among SOs, sleep spindles, cardiac R-peaks, heart rate variability (HRV), spectral slope, and Lempel-Ziv complexity. To assess integrated brain-heart coordination, we developed a Joint Phase-Amplitude Coupling (JPAC) metric that quantifies the corelation between SO phase-dependent modulation of spindle amplitude and cardiac timing. SO-spindle coupling showed the expected fronto-central distribution but was not significantly related to autonomic or cortical state markers. In contrast, SO-R-peak coupling and JPAC systematically tracked physiological state. Stronger JPAC was associated with higher high-frequency HRV, steeper spectral slopes, and lower neural complexity, indicating enhanced coupling during synchronized, parasympathetically dominated NREM sleep. These findings demonstrate coordinated organization of cortical, thalamocortical, and cardiac rhythms within a common oscillatory framework and identify NREM sleep as a state and potential treatment target of large-scale neurovisceral integration.

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

Background Anxiety, depression and menstrual problems are conditions that significantly impact an individual's health and wellbeing yet, barriers to healthcare can prevent access to appropriate medical care. Trust in doctors is a notable factor as previous studies have shown that it affects engagement with healthcare services and has declined in recent years. Methods Using the Avon Longitudinal Study of Parents and Children, we investigated associations between trust in doctors and healthcare access at two timepoints, for anxiety, depression (mothers and partners) and menstrual problems (mothers only). Results Mothers reporting greater trust in doctors were more likely to access care for anxiety (n=1849, adjusted odds ratio (AOR) 1.11, 95% confidence interval (95% CI) 1.08-1.14), depression (n=2411, AOR 1.10, 95% CI 1.07-1.12), and menstrual problems (n=1723, AOR 1.04 95% CI 1.01-1.06). If mothers and partners endorsed 'the doctor is always helpful', they were more likely to access care for depression (mothers: n=2005, AOR 1.30, 95% CI 1.16-1.46; partners: n=580, AOR 1.46, 95% CI 1.05-2.03) and for anxiety (mothers: n=1892, AOR 1.35, 95% CI 1.19 to 1.54; partners: n=734, AOR 1.40, 95% CI 1.02-1.91). Implications This study supports association between trust in doctors and healthcare access for anxiety, depression and menstrual problems, particularly amongst mothers. This contributes to previous literature that suggests that trust remains an important factor in understanding treatment gaps, and that researchers and clinicians must work to improve public trust in healthcare systems.