Sleep

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.

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: Rapid eye movement (REM) sleep is commonly divided into phasic and tonic substates based on higher and lower oculomotor activity, respectively. Our previous study described an alternative framework in which REM temporal structure forms a continuum of infraslow rhythms (~0.01 Hz) across brain and body physiology. We now ask whether these infraslow rhythms vary with neuropsychiatric symptoms, given the long-standing but still inconsistent links between REM and mood- or trauma-related disorders. Methods: Using a cross-sectional polysomnographic dataset from male veterans, we examined 59 participants for correlations between REM infraslow rhythms and neuropsychiatric symptom scores, excluding participants with moderate/severe apnea. Results: Oscillations in REM respiratory rate, but not cardiac rate or electroencephalogram beta power, showed higher infraslow frequencies in participants with multiple symptoms, including posttraumatic stress, pain, anxiety, depression, and cognitive difficulties. No significant correlations were found between these symptoms and conventional REM metrics (e.g., REM density, latency and duration). To further examine REM beyond phasic/tonic binarization, we analyzed the timing between oculomotor activity and infraslow oscillations. Eye movements occurred preferentially during periods of high respiratory rate, low beta power and intermediate cardiac rate, with no changes in these temporal relationships across symptom severity. Conclusions: Neuropsychiatric associations with REM infraslow rhythms spanned multiple symptom domains but were physiologically specific, with respiratory rate oscillations representing the strongest readout of symptom burden. Furthermore, REM infraslow cycles across brain and body were differentially aligned with eye movements: a temporal pattern that may serve as a physiological target for neuropsychiatric and mechanistic research.

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.

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.

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: 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.

Abstract Sleep disturbance is common and clinically consequential across mental disorders. Yet its transdiagnostic role remains difficult to interpret because sleep is often reduced to a global score and psychiatric symptoms to diagnosis-specific outcomes. Here, we leveraged the YaleNeuroConnect cohort to test whether subjective sleep components align with separable dimensions of symptom-related features and connectome-wide organization. We applied canonical correlation analysis to seven Pittsburgh Sleep Quality Index components and 55 clinical, affective, cognitive and interpersonal measures in 260 diagnostically diverse subjects, and mapped the resulting dimensions onto resting-state functional connectivity using network-based statistics. We identified two sleep-psychopathology dimensions. The dominant and cross-validated dimension linked widespread subjective sleep disturbance, especially daytime dysfunction, to general symptom burden, including global severity, perceived stress and fatigue. This dimension was expressed in reduced coupling between the default mode network and frontoparietal and cerebellar systems, reduced cerebellar-subcortical coupling, and stronger coupling between the somatomotor network and higher-order systems. A second, more circumscribed dimension linked shorter sleep duration and prolonged sleep latency to lower self-assurance and positive affect, together with heightened affective and perceptual sensitivity. This dimension showed stronger coupling between cerebellar and dorsal attention systems, together with weaker coupling between the default mode network and attention or cerebellar systems. These findings suggest that sleep is not merely a comorbid symptom, but a multidimensional organizing feature of transdiagnostic psychopathology. Distinguishing broad sleep-related distress from sleep-initiation and sensitivity profiles may help refine brain-based stratification and identify sleep dimensions relevant to intervention. Keywords: sleep disturbance; transdiagnostic psychopathology; multidimensional sleep; canonical correlation analysis; resting-state functional connectivity; connectome-wide networks

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.

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.

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.

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: 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.

Sleep disorders and wakefulness constitute a pronounced and pervasive health risk that contributes to numerous cerebral pathologies such as stroke, depression, and neurodegenerative disorders. The hippocampus (HC) plays vital roles in learning and memory and is especially susceptible to the pathological insults imposed by sleep deprivation (SD). While SD disrupts neuronal network signaling and triggers inflammatory processes, the impact of SD on metabolism within the HC presently remains poorly understood. In this study, we assessed the progressive and cumulative effects of partial SD in the live mouse HC CA1 region using two-photon microscopy. Using a custom-designed implantable cannula enabling direct HC visualization and administration of dyes and pharmacological agents directly to HC tissue, we longitudinally monitored spontaneous neuronal activity and partial pressure of oxygen (pO2) within HC CA1 tissue before and during a 7-day period of partial SD and after a 7- day period of recovery. Our results revealed a progressive decline in spontaneous neural activity, alongside sustained elevation in tissue pO2; during the 7-day partial SD period. Notably, after 7 days of recovery, neuronal activity did not return to baseline, and tissue oxygenation continued to increase. Our findings emphasize chronic SD's cumulative and enduring impairments to neuronal function and metabolism in the HC and reveal uncoupling between metabolic and functional recovery that outlasts the sleep restriction period.

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.

Introduction The basal forebrain is an early site of pathology in Alzheimer's disease (AD). Within this region, the nucleus basalis of Meynert (NbM) provides the primary cholinergic input to the neocortex and supports cortical activation during rapid eye movement (REM) sleep. REM electroencephalography (EEG) slowing is observed in older adults with AD and amnestic mild cognitive impairment (MCI). This study examined the relationship between REM EEG slowing and NbM volume, and whether it differed by cognitive status, sex, or sleep apnea severity. Methods Participants aged [&le;] 60 years with cognitive concerns underwent neuropsychological and medical assessments, polysomnography, and magnetic resonance imaging (MRI). REM EEG slowing was quantified as the ratio of delta and theta (<8Hz) to alpha, sigma, and beta (8-32Hz) power. Bilateral NbM and Ch1-3 volume were derived from T1-weighted MRI images. Multiple linear regression and moderation analyses adjusted for age, sex, and sleep apnea severity. Exploratory analyses examined associations between NbM volume, sleep macroarchitecture, and memory. Results The sample comprised 116 participants (59.5% female; mean age = 70.5 years, 64.7% MCI). Greater REM EEG slowing was associated with smaller NbM volume (all p < 0.05). Although moderation effects were not significant after FDR correction, within-group analyses suggested a stronger relationship in MCI. Smaller NbM volume was associated with longer sleep latency and poorer episodic memory (all p < 0.05). Discussion REM EEG slowing may reflect early NbM degeneration and provide a non-invasive biomarker of basal forebrain integrity in older adults with cognitive concerns. Longitudinal studies are required to establish its prognostic value.

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.

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.