Sleep

Study Objectives Co morbid insomnia and sleep apnea (COMISA) is challenging clinically and difficult to treat. Our goal was to assess how much COMISA is the mere addition of two phenotypes or display features indicative of genuine statistical interactions. Methods A total of 152,487 patients from 240 sleep centers across 30 US states were included. Insomnia was defined as difficulty initiating/maintaining sleep with daytime fatigue/sleepiness occurring "often"/"always". OSA was defined as having an Apnea Hypopnea Index (AHI) more than 15 events/h. Modified Poisson regression was conducted to evaluate multiplicative interactions between insomnia and OSA on common comorbidities and sleep symptoms. Additive interactions were also examined. Linear regression models were used to evaluate additive interactions for PSG parameters. The false discovery rate was controlled using the Benjamini Hochberg procedure. Results After adjustment for confounders, insomnia and OSA demonstrated positive interactions for depression, chronic muscular pain, headache, subjective excessive daytime sleepiness (EDS), naps, and pre-sleep anxious and muscular tension (adjusted p < 0.05). Furthermore, insomnia and OSA demonstrated positive interactions for parameters related to respiratory disturbance, including AHI, oxygen desaturation index (ODI), respiratory disturbance index (RDI), total arousal index (AI) and respiratory AI, and negative interactions for minimum oxygen saturation and percentage of rapid eye movement stage (REM%) (adjusted p < 0.05). Furthermore, the adverse effects of insomnia and OSA on AHI, ODI, RDI and REM% were substantially amplified in males. Conclusions Our findings demonstrate that insomnia and OSA do not merely coexist but genuinely interact synergistically to amplify selected adverse clinical outcomes.

Objectives. To test whether one week of self-administered morning bright light therapy (BLT) improves sleep, daytime sleepiness and alertness, mood, and objective cognition in healthy university students. Methods. Thirty-three healthy students completed a two-week randomized within-subject crossover trial comparing one week of morning BLT (30 min of 10,000 lx; melanopic equivalent daylight illuminance of approximately 8,989 lx) with one week of usual-light control in counterbalanced order, with no washout. Sleep was assessed with wrist-worn Fitbit sleep tracking and daily diaries; daytime sleepiness (Karolinska and Stanford Sleepiness Scales), positive and negative affect (PANAS), mood (POMS), and a cognitive battery (Stroop, Flanker, Corsi, verbal span) were also assessed, alongside post-trial semi-structured interviews. Outcomes were analyzed with linear mixed-effects models, with Holm correction across five primary outcomes. Results. BLT reduced daytime sleepiness in a time-of-day-specific manner (condition x time-of-day interaction; largest reduction at 12:00, dz = -0.58, with a smaller but still significant reduction at 15:00), reduced night-to-night variability in sleep duration (dz = -0.52), increased Fitbit sleep efficiency (dz = 0.81), and increased PANAS positive affect (dz = 0.41). Objective cognition was unchanged across all measures. Interviews indicated that participants experienced BLT primarily as a sleep and alertness intervention, with minor tolerability issues. Conclusions. Brief morning BLT improved alertness, sleep regularity and efficiency, and positive affect, but not objective cognition, in healthy students, supporting morning light as a low-burden strategy for daytime functioning while cautioning against overstating cognitive benefits.

This study aimed to explore night-to-night variability of multiscale sleep patterns by analyzing subcutaneous electroencephalography (sqEEG) from 20 healthy participants over one year (205-388 nights per participant, 6,429 nights in total). We utilized the time series of aperiodic slopes, sigma and slow-wave power as a new whole-night unit of sleep macrostructure. Using dynamic time warping, we calculated the distances (differences) between those time series to assess night-to-night sleep macrostructure dissimilarity. We found that the overall sleep macrostructural patterns were relatively similar across nights (20% dissimilarity), while their temporal alignment was quite variable (time series warped by ~60% for the best alignment). Lower variation in macrostructure dissimilarity was associated with better subjective sleep quality (r=-0.25). Then, we qualitatively compared yearlong variation in macroscale, microscale (sleep stage proportions, mean spectral power) and mesoscale (sleep cycle duration) metrics. We found that intra-individual night-to-night variation was '"low (coefficients of variation < 20%) for spectral power, sleep duration, N2 and REM sleep; ''medium'' (20-40%) - for N3 and macrostructure dissimilarity; and "high" (>40%) - for sleep cycle duration, wake and N1. In summary, different sleep metrics showed differential night-to-night variability, which was more metric-specific than scale-dependent. This might reflect a distinction between more trait-like versus more dynamically varying features of sleep, although this assumption needs further clarification.

RationaleThere is no effective pharmacotherapy for obesity hypoventilation syndrome (OHS). Intranasal leptin augments the hypercapnic ventilatory response (HCVR), attenuates upper airway obstruction, and increases ventilation during sleep in diet-induced obese (DIO) mice. Respiratory effects of leptin can be attenuated by serotonergic antagonists. ObjectivesTo establish if serotonergic innervation of the hypoglossal motoneurons (XII MN) mediates effects of leptin on OHS. MethodsWe examined effects of intranasal leptin on the HCVR, sleep architecture, arousal latency, flow limited (obstructed) and non-flow limited breathing, genioglossus muscle (GG) activity and metabolic rate across sleep/wake states in the presence and absence of serotonergic neurons innervating XII MN in DIO Sert-flp mice expressing FlpO recombinase in the serotonergic neurons. These mice were transfected into the XII MN with retrograde adeno-associated virus carrying either FlpO-dependent caspase or control yellow fluorescent protein (YFP). Measurements and Main ResultsControl YFP virus was densely localized to the serotonergic neurons of the medullary raphe (MR), but not the dorsal raphe (DR), and these neurons were ablated by caspase. Leptin enhanced the HCVR, increased arousal latency in males, but not in females, and these effects were abolished by caspase. Neither leptin nor caspase affected sleep architecture or metabolic rate. Leptin increased GG activity awake and during NREM sleep, attenuated pharyngeal obstruction and increased minute ventilation in NREM and REM sleep. All effects of leptin were abolished by the FlpO-dependent caspase. ConclusionsLeptin treats OHS by stimulating MR serotonergic neurons, which project to XII MN and stimulate pharyngeal muscles during sleep.

The slow oscillation (SO) of non-rapid eye movement (NREM) sleep has been implicated in the restorative properties of sleep. Slow oscillatory transcranial direct current stimulation (SO-tDCS), involving a positive oscillatory current applied to the scalp at a peak frequency of 0.75 Hz, has been used to enhance SO power during NREM sleep. We examined whether enhancing SO power with SO-tDCS during a restricted nighttime sleep opportunity would accelerate the restorative properties of sleep during an otherwise insufficient sleep period and help sustain performance during subsequent extended wakefulness. A total of twenty-six healthy young adults (ages 18-39, n=16 females) completed a 15-day study. After 7 baseline nights at home and 3 baseline nights in the laboratory, participants entered the laboratory for 5 consecutive days including a baseline day, a 2-hour nighttime sleep period with participants randomized to the SO-tDCS (n=11) or SHAM (n=15) condition, 46 hours of sleep deprivation, and two recovery nights. In the SO-tDCS condition, stimulation was administered for one hour starting exactly 60 minutes after sleep onset, with intervals of five minutes of continuous stimulation followed by one minute of no stimulation. Polysomnographic recordings were conducted during each sleep period. Performance was assessed using the Psychomotor Vigilance Test (PVT) approximately every 75 minutes across baseline, sleep deprivation, and recovery. Prior to the two-hour sleep opportunity, a Paired Words Associate Task was administered. Participants listened to 54-word pairs and were asked to recall 46 of the word pairs, with up to three attempts to successfully recall at least 60% of word pairs (T0). Recall was also assessed 20- (T20) and 120-minutes (T120) after awakening from the two-hour sleep period. Data were analyzed using mixed-effects ANOVA. PVT performance (defined as mean response time and number of response times greater than 1,000 ms) significantly declined across sleep deprivation with performance degradations peaking in the early morning hours. Participants in the STIM condition demonstrated significantly better performance during sleep deprivation relative to the SHAM condition. On the PWAT, participants in the SHAM condition recalled fewer word-pairs upon awakening relative to T0. In sharp contrast, performance of participants in the SO-tDCS condition did not deteriorate at T20 and was actually improved at T120 relative to T0. We conclude that SO-tDCS can robustly accelerate the restorative properties of sleep and can additionally enhance sleep related memory consolidation when sleep opportunity is restricted.

Importance Sleep-disordered breathing (SDB) is common in childhood and is associated with attentional and behavioral impairments despite largely preserved sleep macrostructure and minimal abnormalities in conventional electroencephalographic measures. This discrepancy has contributed to the perception that sleep is relatively preserved in pediatric SDB and has limited understanding of the physiological mechanisms underlying morbidity. Objective To determine whether pediatric SDB is associated with disruption of the regional organization and homeostatic dynamics of slow-wave activity (SWA), a key physiological marker of sleep-dependent neural recovery and development. Design, Setting, and Participants Cross-sectional study of 62 children aged 4 to 12 years who underwent overnight polysomnography with high-density electroencephalography in a laboratory setting. Participants were recruited from clinical referrals and the community, spanning the full spectrum of SDB severity. Exposures SDB severity indexed by hypopnea index (HI), apnea-hypopnea index (AHI), and obstructive apnea index (OAI). Main Outcomes and Measures Regional electroencephalogram-derived SWA (0.5 to 4 Hz) topography and exponential decay parameters derived from frontal and posterior cortical regions. The frontal-to-posterior decay-rate ratio was evaluated as a summary measure of regional sleep homeostasis. Results In children with lower hypopnea index, SWA demonstrated the expected developmental pattern, with posterior predominance in younger children and a progressive shift toward a more balanced anterior-posterior distribution with age. Increasing HI was associated with attenuation or reversal of this spatial organization. Global SWA showed no meaningful association with SDB severity. In contrast, regional frontal and posterior decay parameters were strongly associated with HI (adjusted R2 = 0.53; p < 1e-6) but not OAI (adjusted R2 = 0.05; p = .95). The frontal-to-posterior decay-rate ratio showed the strongest association with HI {beta} = 4.15; 95% CI, 3.17-5.13; p < 1e-10; adjusted R2 = 0.55. Conclusions and Relevance Pediatric SDB was associated with regional disruption of slow-wave sleep homeostasis rather than global loss of deep sleep. These alterations affected both the spatial organization and temporal dynamics of SWA during a period of active cortical maturation and were not captured by conventional sleep metrics. Regional SWA dynamics may provide a developmentally sensitive marker of physiological disease burden in children with SDB.

Monogenic epilepsies are 1.6 times more likely to be treatment-resistant compared to other epilepsies, emphasizing the need for additional therapeutic strategies. Sleep dysfunction beyond sleep-related breathing disorders is common yet insufficiently characterized and treated in monogenic epilepsies. We therefore sought to study sleep phenotypes across these epilepsies, examine associations with seizure severity, and assess the diagnostic rate of sleep disorders. From 2,519 individuals enrolled in the Epilepsy Genetics Research Project at Children's Hospital of Philadelphia, we identified the monogenic epilepsies most frequently associated with sleep-related diagnoses, yielding 252 individuals across nine genetic diagnoses (STXBP1, n = 79; SCN1A, n = 57; SCN2A, n = 34; KCNQ2, n = 21; SLC6A1, n = 14; SYNGAP1, n = 13; WDR45, n = 13; KCNT1, n = 11; PCDH19, n = 10). Monogenic epilepsies exhibited distinct sleep endophenotypes, including insomnia, parasomnia, and sleep-related movement disorders in SCN1A-related disorders; frequent epileptiform discharges in sleep with insomnia symptoms in SCN2A-related disorders; sleep dysfunction restricted to the developmental and epileptic encephalopathy subtype in KCNQ2-related disorders; and insomnia without nocturnal seizure involvement in SYNGAP1-related disorders. Formal sleep diagnoses were present in only 25% of individuals (63/252), yet 58% (145/252) reported sleep difficulties, suggesting substantial underdiagnosis. Persistent seizures were associated with higher odds of sleep disorder diagnoses (OR 2.87, 95% CrI 1.57-5.36), disrupted sleep architecture (OR 2.06, 95% CrI 1.08-4.16), nocturnal seizures (OR 4.47, 95% CrI 2.50-8.28), hypersomnolence (OR 2.38, 95% CrI 1.27-4.58) and insomnia (OR 1.80, 95% CrI 1.06-3.05). Neuropsychiatric comorbidities were independently associated with sleep burden after adjustment for seizure severity (OR 2.49, 95% CrI 1.40-4.49). We find that monogenic epilepsies exhibit distinct, gene-specific sleep endophenotypes that are underdiagnosed. Treating sleep difficulties beyond obstructive sleep apnoea may improve seizure control and developmental outcomes, highlighting the need for timely diagnosis of co-occurring sleep disorders.

Study Objectives To develop and initially validate the Circadian Disruption Index (CDI), a self-report measure of circadian disruption, and obtain preliminary evidence of its responsiveness to circadian health education. Methods In Study 1, 244 participants completed a 22-item CDI version and external measures. The sample was randomly divided for exploratory and confirmatory factor analyses. Internal consistency, external associations, and discrimination of poor sleep quality were examined. In Study 2, 72 postgraduate students completed the CDI before and 1 week after a 16-hour circadian health education program in an uncontrolled pre-post design. Results Analyses yielded a 15-item, three-factor structure comprising rhythm stability and light exposure, behavioral habits and diet, and sleep quality and subjective complaints. Total-score internal consistency was acceptable (Cronbach's = 0.871). Confirmatory factor analysis showed a comparative fit index of 0.902 and a root mean square error of approximation of 0.072, although the Tucker-Lewis index was 0.882. CDI scores correlated with sleep quality, chronotype, corrected midsleep on free days, depression, and anxiety, but not social jetlag. The area under the curve for poor sleep quality was 0.807 (95% confidence interval, 0.753-0.862), with an exploratory cutoff of [&le;] 23. In Study 2, CDI scores decreased from 22.26 to 19.88 (p = 0.002; Cohen's dz = 0.36). Conclusions The CDI demonstrated satisfactory internal consistency, a meaningful multidimensional structure, and responsiveness to short-term changes following circadian health education, supporting its potential utility for assessing circadian disruption and monitoring circadian-related behavioral changes.

Study Objectives. To determine whether sleep-related respiratory disruption is associated with regionally specific alterations in sleep spindle topography and whether hypopnea-sensitive spindle features are associated with attentional performance in children. Methods. We recorded overnight high-density EEG in children across a wide range of respiratory disruption severity. Slow and fast spindle metrics were extracted per channel, and channel-wise regression models characterized topographic associations with hypopnea index (HI). Cluster-based permutation testing controlled for multiple comparisons. Hierarchically defined regions of interest were tested as predictors of attentional performance on the Test of Variables of Attention (TOVA). Results. Canonical slow-anterior and fast-posterior spindle organization was detectable across the cohort. Two HI-related topographic effects survived cluster-based permutation correction: higher HI was associated with shortened anterior fast spindle duration and with slower anterior slow spindle peak frequency. In cognitive models, anterior fast spindle duration was the strongest and most consistent predictor of attentional performance, associated with higher signal detection sensitivity, fewer omission errors, and fewer commission errors. By contrast, slow spindle peak frequency showed no attentional associations. Conclusions. Pediatric respiratory disruption is associated with regionally specific alterations in spindle morphology rather than global spindle reduction. Shortened anterior fast spindle duration showed convergent respiratory and attentional associations, suggesting that localized spindle integrity may provide a neurophysiological marker of cognitive vulnerability in pediatric sleep-disordered breathing beyond conventional clinical respiratory metrics.

ABSTRACT Objective To assess the comparative efficacy and acceptability of cognitive behavioural therapy for insomnia (CBT-I), its abbreviated versions and control conditions. Design Systematic review and network meta-analysis. Methods Screening, data extraction, coding, and risk of bias assessment were performed independently and in duplicate. Frequentist, random-effects network meta-analyses estimated odds ratios (ORs) or mean differences with 95% confidence intervals (CIs). The primary outcome was insomnia remission post-treatment. Secondary outcomes included dropout and subjective sleep continuity measures. Quality of the evidence for each arm was graded using the confidence in network meta-analysis (CINeMA). Data sources We searched MEDLINE, Embase, PsycINFO and Cochrane CENTRAL from inception to December 15, 2025, with a medical information specialist. Eligibility criteria for selecting studies Randomized controlled trials (RCTs) comparing CBT-I and its abbreviated versions with each other or with control conditions, in adults with insomnia, with or without comorbidities. To reduce clinical heterogeneity related to treatment intensity and adherence, we restricted inclusion to in-person delivery. Results We identified 11,379 records and included 77 RCTs (5,731 participants; mean age 52.2 years; 3,473 female). CBT-I (number of arms k = 53; number of participants n = 2,002), sleep restriction and stimulus control therapy (SRT+SCT; k = 16; n = 549), sleep restriction therapy (SRT; k = 5; n = 196) and stimulus control therapy (SCT; k = 7; n = 144) were associated with higher remission than sleep hygiene, relaxation therapy and other control conditions. These interventions were also effective in improving subjective sleep continuity measures. Cognitive therapy for insomnia (CT-I) was more beneficial than relaxation therapy. Dropout did not differ meaningfully between interventions and controls. Confidence in evidence was moderate for CBT-I, low for SRT&SCT and SRT, very low for SCT. Given the weighted mean proportion of insomnia remission among sleep hygiene arms of 20%, CBT-I probably leads to a remission rate of 41% (95% CI, 34%; 48%), SRT&SCT may lead to a remission rate of 40% (30%; 52%), SCT 43% (25%; 63%), and SRT 41% (26%; 57%). Conclusions CBT-I doubles the absolute insomnia remission compared with sleep hygiene, and its abbreviated behavioural therapies, namely, SRT+SCT, SCT and SRT may offer similar benefits with lower resource requirements, but evidence is less certain. CT-I needs further investigations. Relaxation therapy was inferior to these therapies. Implementation decisions should consider resource requirements and evidence certainty. Systematic review registration The Open Science Framework, https://osf.io/z48r2/.

Study Objectives: Onsets of Narcolepsy type-1 (NT1) increased following A/H1N1 vaccination with PandemrixTM in Europe and with A/H1N1pdm2009 infections in China and other countries. To test if other strains could trigger narcolepsy, we measured strain-specific antibodies in patients with recent onset NT1 compared to controls. Methods: Antibodies against hemagglutinin (HA) and neuraminidase (NA) were tested in 62 patients with very recent onset (onset and blood collection following a single flu season, mean +/- SEM: 0.44 +/- 0.06 years since onset) and 100 controls matched by age, sex, season and year of collection (2000-2025). Results were next extended to 181 recent onset patients (mean +/- SEM: 1.00 +/- 0.05 years) versus 260 controls, matched by sex, season and year, but having a slightly higher mean age. HA inhibition (HAI) and NA inhibition (NAI) assays were conducted using flu strains known to circulate during the corresponding flu seasons. HAI results are shown as % positive (titers >= 40) and NAI results as geometric mean titers. Odds ratio (OR) and coefficient were used to compare antibody titers in NT1 versus controls. The contribution of each assay to prediction was finally quantified in the larger sample set using Shapley decomposition. Results: NT1 patients had increased anti-HA and anti-NA antibodies against A/H1N1pdm2009 (anti-HA OR = 3.86, anti-NA coefficient = 0.35) and B/Victoria (anti-HA OR =1.90, anti-NA coefficient = 0.22), but not A/H1N1pre2009, A/H3N2, or B/Yamagata, independent of HLA-DQB1*06:02 status, age, sex, and flu season. Correlations between anti-HA and anti-NA antibodies titers were weak to moderate but significant (r2=-0.10 to 0.34). Multivariable model outperformed age-only baseline (McFadden R2 = 0.19 vs. 0.03; AUC = 0.79 vs. 0.64; likelihood-ratio test X2 = 51, p<0.001), with anti-HA against A/H1N1pdm2009 (coefficient = 0.78, p < 0.001) and anti-NA against B/Victoria (coefficient = 0.69, p < 0.001) emerging as the strongest independent predictors. Conclusions: A/H1N1pdm2009 and B/Victoria, but not other strains can trigger the autoimmune process leading to orexin cell loss in narcolepsy.

Background: Accurate REM identification is critical for diagnosing REM sleep behaviour disorder (RBD), yet many automated sleep staging systems, especially single-channel EEG models trained on healthy cohorts, do not generalise well to real-life polysomnography (PSG) performed in patients. Objective: To compare a feature-based Random Forest (RF) model tuned for RBD with a state-of-the-art single-EEG deep architecture (AttnSleep), and to assess the impact of cohort adaptation and multimodal inputs (EEG, EOG, EMG, ECG). Methods: Experiments used 89 multi-site in-clinic PSGs (SleepWearables Phase-1) plus 53 MASS healthy controls (mean age 63, std 5 years), with 10-fold cross-validation and out-of-fold evaluation. Model performance was assessed using Cohen's kappa, and attention-based modality analysis was performed to quantify signal contributions. Results: When applied out-of-the-box after training on open-source healthy datasets, both models achieved moderate agreement overall (Cohen's kappa = 0.46), but performance declined in RBD, particularly for REM sleep (AttnSleep Cohen's kappa = 0.19 vs RF Cohen's kappa = 0.44), highlighting limited cross-cohort generalisation. The multimodal model improved overall agreement (Cohen's kappa 0.59 - 0.60) and performance in RBD (Cohen's kappa 0.45 - 0.46), with gains most pronounced in REM (Cohen's kappa 0.45 - 0.49). Attention-based modality analysis identified EEG as the dominant signal, increased EOG contribution during REM, and elevated ECG importance during N3. In RBD subjects, EOG weighting increased relative to non-RBD controls (Delta = +0.081). Guided by these weights, a reduced four-channel EEG model matched full multimodal performance in non-RBD subjects, and adding EOG achieved the best overall configuration (Cohen's kappa = 0.61 overall; Cohen's kappa = 0.48 in RBD) with improved REM classification (53% vs 45% recall). Inclusion of EOG also reduced inter-dataset variability in REM staging. Nonetheless, staging performance in RBD remained lower than in controls, particularly for REM. Conclusions: These results highlight the limited generalisability of minimal-sensor models trained on healthy cohorts, the value of mixed cohort-specific training, and the benefit of multimodal integration and attention-guided channel selection, rather than minimal-sensor approaches alone, for robust clinical sleep staging in pathological populations such as RBD.

Background: Bidirectional next-day associations between sleep disturbances and affective symptoms have been shown in previous research, yet the consecutive day effects between these factors remains poorly understood. Methods: We analysed longitudinal ecological momentary assessment (EMA) data obtained from a subsample of young persons in the Brazilian High-Risk Cohort (BHRC) study collected in 2020-2021. Participants reported sleep quality each morning and rated affective symptoms relating to mood, anxiety, and energy four times daily for 28 days. We selected 88 individuals (17.83{+/-}1.74 years, 56 [63.6%] female gender) with at least one instance where individuals were observed three-days in a row. Within-person bidirectional next-day effects between sleep quality and affective symptoms were estimated using mixed-effects regression analysis adjusting. We then applied g-estimation approaches to estimate the effect that lagged sleep quality and consecutive improvements in sleep quality had on affective symptoms. Results: Sleep quality and affective symptoms had bidirectional next-day effects, with sleep quality tending to have greater influence on affective symptoms than the reverse. Improved lagged sleep quality had positive effects on affective symptoms incrementally above the prior night's sleep quality. Also, improvement of sleep quality across consecutive days had incremental and approximately equal effects on affective symptoms. Conclusions: Sleep quality and affective symptoms exhibit a feedback loop, whereby poor sleep quality influences affective symptoms over consecutive days. Breaking these feedback loops, by improving sleep quality across several consecutive nights should improve affective symptoms. This supports interventions that target sustained improvement in sleep and possibly circadian regulation to improve affective symptoms.

Maternal sleep disturbance is an underrecognized risk factor for adverse offspring outcomes. Prolonged sleep disruption can elicit inflammation, an established risk factor for neuropsychiatric disorders in offspring. Sleep disruptions and inflammation elevate tryptophan degradation via the kynurenine pathway (KP), increasing kynurenic acid (KYNA), a metabolite that inhibits glutamatergic and cholinergic neurotransmission and may thereby affect neurodevelopment. Because KYNA is elevated in the brains of individuals with neurodevelopmental psychotic illnesses, we hypothesize that prenatal KYNA elevation may represent a mechanism link between disturbed maternal sleep, inflammation, and adverse offspring neurodevelopmental health. To test this hypothesis, we employed a novel maternal sleep fragmentation (SleepFrag) paradigm during the final week of gestation. We found that six days of SleepFrag increased maternal plasma inflammatory markers, placental KP metabolism, sex-specific placental inflammation, and fetal brain KP metabolism, including elevated KYNA, without altering KP metabolism in maternal plasma or brain. A parallel embryonic kynurenine (EKyn) model was tested to increase prenatal KP metabolism via a maternal kynurenine-supplemented diet. EKyn increased maternal plasma kynurenine and KYNA, and fetal brain KYNA, with a male-specific increase in fetal brain KYNAto-kynurenine ratio, despite minimal effects on maternal sleep-wake architecture or inflammation. Together, these findings identify elevated fetal brain KYNA as a convergent outcome through which maternal sleep disruption, inflammation, and KP activation may influence sex-specific neurodevelopment. They further support the EKyn model as a translational tool for isolating consequences of increased prenatal KP metabolism. Protecting maternal sleep and stabilizing fetal brain KYNA levels may promote long-term offspring brain health.

Automated severity rating of rapid eye movement (REM) sleep behavior disorder (RBD) movements would enable multi-night monitoring to detect potentially injurious behaviors and provide objective endpoints for clinical trials. We compared a heuristic classifier using optical flow-derived features against V-JEPA2, a self-supervised video foundation model, for clip-level severity classification (3329 mild versus 284 moderate-to-severe) of in-laboratory video-polysomnography infrared recordings in 86 isolated RBD patients. V-JEPA2 with checkpoint fine-tuning and maximum optical flow-based frame sampling achieved the best performance across both evaluation conditions -- Macro F1 of 0.76 and 93% accuracy in the clip-level split, and 0.68 and 85% in the patient-level split -- outperforming heuristic and domain-specific pretrained models. Clip duration was the dominant heuristic predictor. Whole-night severity scores preserved patient-level ordering despite systematic overestimation, with V-JEPA2 achieving a mean absolute error of 25% versus 52% for the heuristic classifier. These findings establish a foundation for objective, home-deployable monitoring of RBD severity.

Chronic partial and acute total sleep loss have a distinct impact on sleep architecture. Namely, acute sleep deprivation primarily leads to a strong rebound of slow wave sleep, while chronic sleep restriction results in an increased propensity of REM sleep. The aim of this work was to examine whether these different effects would translate into quantifiable changes in sleep state boundaries and dynamics using a model-based method. Besides conventional sleep stage scoring, we applied an EEG model (state space approach) for dynamic analysis of nocturnal EEG recordings in 14 healthy subjects under experimental chronic sleep restriction (last of 7 nights with 5 hours of time in bed) and after acute sleep deprivation (sleep following 40 hours of wakefulness), in comparison to baseline sleep. Subjects under chronic sleep restriction revealed increased similarities in the frequency composition of REM sleep and wakefulness and thus, a decreased differentiation of state boundaries between the two behavioral states. Contrarily, acute sleep deprivation affected the spectral composition of NREM sleep. Only acute sleep deprivation resulted in more stable slow wave sleep. Our explorative study confirmed that the distinct effects of increased REM sleep and slow wave sleep propensity following acute total and chronic partial sleep loss are reflected in differential changes of behavioral state boundaries and sleep dynamics. This suggests that these sleep structure characteristics are state dependent, which may allow using such measures in the future to track treatment effects in clinical populations characterized by sleep behavioral state dysregulation.

The apnea-hypopnea index (AHI), the conventional metric of obstructive sleep apnea (OSA) severity, is typically studied using scalar summaries of sleep architecture, such as the total time spent in each sleep stage. Although clinically interpretable, these summaries fail to capture the temporal organization of overnight sleep-stage sequences and may obscure stage-specific associations with OSA severity. Modeling the complete sleep-stage trajectory provides substantially richer temporal information; however, because total sleep duration varies across individuals, sleep-stage trajectories are observed over subject-specific domains, limiting the applicability of conventional functional regression methods that assume a common observation interval. We therefore applied Variable-Domain Functional Regression (VDFR) to overnight polysomnographic data from the APPLES study (n= 1,103), treating the epoch-by-epoch sleep-stage sequence as a continuous, variable-length functional predictor of AHI. We compared three levels of sleep-stage granularity: five stages (Wakefulness, N1, N2, N3, REM), three stages (Wakefulness, Non-REM, REM), and binary staging (Wakefulness vs. Sleep). Functional sleep-stage terms were significant across all staging granularities and model structures (all p-values [&le;]0.001). Wake, N1, and N2 were positively associated with AHI, whereas N3 and REM were negatively associated, with REM exhibiting the strongest association. These effects were attenuated under coarser staging representations, highlighting the importance of preserving fine-grained sleep architecture. To our knowledge, this is the first application of VDFR to overnight polysomnographic data in OSA, showing that accommodating subject-specific sleep durations enables the identification of stage-specific temporal associations with AHI severity that are attenuated or obscured by coarser staging and conventional scalar analyses.

Background: Automatic sleep staging algorithms are increasingly applied in clinical and home-based recordings. However, their performance may degrade when transferred to new montages and clinical populations. This is particularly relevant in reduced-channel portable PSG and in disorders such as REM sleep behaviour disorder (RBD), where altered sleep architecture may challenge pretrained models. Objective: To evaluate and compare multiple open-source sleep staging algorithms on a minimal portable PSG setup in controls and patients with and without RBD, and to assess the impact of fine-tuning on clinic-ascertained data. Methods: Six open-source models were applied to 76 subjects recruited from three clinical sleep medicine sites. Performance was assessed using accuracy, F1 scores, and Cohen's kappa, both overall and per sleep stage. Each model was evaluated out-of-the-box and after fine-tuning on clinical data. Results: Out-of-the-box performance varied substantially across models (Cohen's kappa 0.21-0.54). Fine-tuning consistently improved agreement, with the best-performing model (GSSC) reaching Cohen's kappa = 0.58 indicating moderate to good agreement. Performance was highest in controls and lower in patient groups. N3 was the most reliably classified stage across models, whereas N1 remained consistently challenging. REM classification improved after fine-tuning in several architectures but remained model, and subgroup-dependent, particularly in RBD subjects. Conclusion: Fine-tuning substantially mitigates domain shift, updating model parameters to align with new data distributions, when applying automatic sleep staging algorithms to portable clinical recordings. Model architecture influences robustness, with feature-learning approaches demonstrating greater adaptability than fixed-feature models. Despite moderate agreement after adaptation, performance, especially for REM and N1 remains insufficient for fully automated diagnostic use in clinical populations.

Sleep disturbances and neurodegeneration form a bidirectional vicious cycle. During slow-wave sleep, glymphatic processes are thought to facilitate the clearance of metabolic waste, including proteins implicated in Alzheimers disease (AD). Aging, and more prominently neurodegeneration, is associated with reductions in slow-wave activity (SWA), which may impair these processes. Within SWA, slow oscillations (SO, <1 Hz) and their coupling to sleep spindles capture key aspects of sleep microstructure. Non-invasive brain stimulation during sleep has emerged as a potential approach to modulate these dynamics; however, human evidence linking such modulation to AD biomarkers remains scarce. In this exploratory mechanistic study, ten healthy older adults underwent one night of slow-oscillatory transcranial current stimulation (so-tDCS) and one sham night in a randomized crossover design, followed by five consecutive stimulation nights. Stimulation was applied during NREM sleep (N2/N3) in the first half of the night. Plasma phosphorylated tau (p-tau)181, {beta}-amyloid (A{beta})42, A{beta}40, and total tau were assessed overnight and longitudinally. EEG analyses quantified SO power and SO-spindle coupling. Due to the exploratory character of the study, analyses emphasized effect size estimation and explained variance. So-tDCS induced small-to-moderate increases in SO power and SO-spindle coupling. Overnight increases in plasma p-tau181 were observed following stimulation relative to sham. Increases in SO power were strongly and positively associated with p-tau181 changes, explaining a substantial proportion of inter-individual variance. In contrast, shifts in SO-spindle coupling phase toward the SO up-state were associated with overnight increases in A{beta}42 and A{beta}40 and with longitudinal decreases in A{beta}42 and the A{beta}42/40 ratio. Enhancing slow oscillatory dynamics during sleep is associated with changes in peripheral AD biomarkers. Differential associations for SO power and SO-spindle coupling timing suggest partially distinct links to tau and A{beta} dynamics. These findings support sleep microstructure as a potential intervention target, and should be confirmed in larger cohorts.

BackgroundChronic sleep restriction (CSR) impairs cognitive function, but its effects on the cortical dynamics underlying active motor performance remain poorly understood. High-density EEG provides a means to examine task-related oscillatory activity across sensorimotor and attentional networks during movement. MethodsFifteen healthy males completed a randomized crossover study involving a CSR condition (five hours sleep per night for four nights) and a control condition (normal sleep). Before and after each intervention, participants performed sustained isometric ankle contractions at 40% of their maximal force while EEG was recorded. Source-reconstructed event-related desynchronization (ERD) was computed across theta, alpha, beta, and gamma bands in the sensorimotor network and dorsal attention network. Sustained attention was assessed with the Psychomotor Vigilance Task (PVT) and perceived workload with the NASA Task Load Index. ResultsCSR successfully reduced sleep duration by 2.36 hours on average (p < .001). Following CSR, PVT reaction times increased significantly ({Delta} = +31 ms, p = .002) and attentional lapses increased ({Delta} = +9.87, p < .001). CSR produced a significant overall increase in ERD across bands, networks, and movement directions (F(1, 5713) = 14.20, p < .001). This effect was present in both the sensorimotor and dorsal attention networks. The ERD increase was specific to dorsiflexion and absent during plantarflexion (condition x session x movement direction: F(1, 5713) = 9.13, p = .003). Subjective mental demand increased following CSR (p = .027), while objective motor performance was largely unimpaired. ConclusionCSR increased broadband ERD during dorsiflexion across both sensorimotor and attentional networks, alongside impaired sustained attention and greater perceived mental demand. As motor performance was largely preserved, this increased ERD may reflect compensatory neural recruitment under sleep pressure.