Sleep

ObjectiveTo examine whether hypoxic burden is distinctly associated with key drivers of glymphatic activity, independent of sleep fragmentation. BackgroundOSA is a robust risk factor for multiple neurodegenerative conditions, including Alzheimers disease, with glymphatic impairment representing a potential mechanistic pathway. However, it remains unknown whether distinct pathological features of OSA, including hypoxic burden and sleep fragmentation, are differentially associated with the two key physiological drivers of glymphatic activity: (1) coordination between brain pulsations and CSF flow and (2) brain pulsation strength. MethodTwenty-eight individuals with newly identified OSA and eight healthy individuals without OSA completed either in-lab polysomnography or WatchPAT, providing estimates of hypoxic burden, quantified as time spent below 90% oxygen saturation (T90), and sleep fragmentation, quantified as non-hypoxic respiratory effort-related arousals (RERAs). Participants also completed 7T resting-state fMRI to quantify the coordination between brain pulsations and CSF flow using gBOLD-CSF coupling (i.e., cross-correlation between gray matter blood oxygen level dependent signal pulsations and CSF inflow) and brain pulsation strength using gBOLD amplitude. Hierarchical regression and Pearson correlations were used to examine associations between sleep measures and fMRI-derived metrics. ResultsGreater T90 was associated with weaker gBOLD-CSF coupling, independent of age, sex, race, and RERAs (Table 2; {beta}=0.07, p=0.008). T90 also significantly improved model-explained variance in gBOLD-CSF coupling (Table 2; {Delta}R2=0.20, p=0.008). Contrary to expectations, greater T90 was associated with higher gBOLD amplitude across the temporal lobe and multiple frontal and parietal regions. Within regions showing T90-linked elevations in gBOLD amplitude, higher gBOLD amplitude was not associated with stronger region-specific gBOLD-CSF coupling. This contrasted with regions not associated with T90, where higher gBOLD amplitude was associated with stronger gBOLD-CSF coupling (difference in {beta}=0.0006, p<0.001). RERAs were not associated with gBOLD-CSF coupling and gBOLD amplitude throughout the cerebral cortex. O_TBL View this table: org.highwire.dtl.DTLVardef@107050eorg.highwire.dtl.DTLVardef@1dcf868org.highwire.dtl.DTLVardef@3899baorg.highwire.dtl.DTLVardef@1f4a867org.highwire.dtl.DTLVardef@15c281f_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 2.C_FLOATNO O_TABLECAPTIONAssociation of T90 with the coupling strength between gray matter pulsations and CSF flow derived from a nested, hierarchical modeling approach Acronyms. RERA=respiratory effort-related arousal index; T90=time of sleep spent under 90% oxygen saturation C_TABLECAPTION C_TBL ConclusionsIn OSA, hypoxic burden, rather than respiratory effort-related sleep fragmentation, may be the primary pathological feature associated with impaired brain pulsation and CSF dynamics, both of which are key drivers of glymphatic activity. These alterations may be most prominent in the temporal lobe, potentially reflecting its elevated metabolic demand and vulnerability to hypoxemia.

The effects of diet quality and timing on sleep quality remain poorly understood, particularly at the level of sleep microarchitecture. Traditional visual scoring captures only coarse sleep stages, overlooking the marked heterogeneity of electroencephalographic (EEG) patterns in non-rapid eye movement (NREM) sleep of mice. Here, we apply a pipeline that combines EEG feature extraction with unsupervised machine-learning-based clustering to resolve discrete NREM substates and ask how a high-fat diet (HFD) and time- restricted feeding (TRF) affect sleep microarchitectures. HFD increases sleep latency and sleep fragmentation; both abnormalities were ameliorated by active phase TRF. Clustering of 10s epochs identified two high-amplitude NREM substates sensitive to TRF: Cluster 1, enriched in low-delta power and peaking early in the light phase (ZT 0-6), consistent with canonical slow-wave sleep, and Cluster 6, characterized by elevated alpha, sigma, and beta power and peaking in the latter half of the light phase (ZT6-12). TRF increases the frequency of both NREM substates, particularly within longer uninterrupted sleep episodes during the light phases. These findings introduce an objective framework for quantifying murine sleep microarchitecture and show that aligning caloric intake with the circadian active window mitigates HFD-induced macro-level sleep disruption while selectively enhancing two physiologically distinct NREM substates. Significance StatementTime-restricted eating - targeting food intake to a defined window during the circadian active phase - confers well-established metabolic benefits, but its impact on sleep is largely underexplored. Using continuous EEG/EMG recordings, we show that an active- phase eating window mitigates high-fat-diet-induced sleep disruption in mice. We employed a novel machine-learning pipeline, further revealing that timed eating selectively increases distinct NREM substates, demonstrating that "when we eat" fine-tunes the macro- and microarchitecture of sleep. These insights lay the foundation for future translational studies and clinical trials aimed at harnessing timed eating to enhance both metabolic and sleep health.

Isolated rapid eye movement sleep behavior disorder is a strong clinical marker of future alpha-synucleinopathy, but earlier stages of this risk pathway remain insufficiently characterized. Rapid eye movement sleep without atonia is the polysomnographic substrate of this disorder and may also be detected in individuals without clinical dream-enactment behavior. Whether isolated rapid eye movement sleep without atonia is a benign finding or an early risk state for future rapid eye movement sleep behavior disorder and neurodegeneration remains unknown. DREAMER is a multicenter, prospective, observational cohort protocol designed to identify adults without clinical rapid eye movement sleep behavior disorder who show isolated rapid eye movement sleep without atonia during full-night laboratory video-polysomnography. Four Italian sleep centers will use harmonized eligibility criteria, standardized clinical and sleep assessment, quantitative REM Atonia Index scoring, secure web-based data capture, and planned longitudinal follow-up. Adults aged 40 years or older undergoing video-polysomnography will be screened. Participants with prior rapid eye movement sleep behavior disorder or technically inadequate REM sleep/chin electromyographic data will be excluded. Isolated rapid eye movement sleep without atonia will be defined in participants without clinical rapid eye movement sleep behavior disorder using a REM Atonia Index threshold of <0.85. The target recruitment is more than 500 participants over 18 months, with an expected enriched subgroup of approximately 85 individuals with isolated rapid eye movement sleep without atonia. Ancillary neurophysiological assessments and blood sampling for future biomarker studies will be obtained when feasible. DREAMER is intended to create a harmonized, trial-ready cohort for evaluating isolated rapid eye movement sleep without atonia as a potential early risk marker for incident rapid eye movement sleep behavior disorder and subsequent neurodegenerative outcomes. The study is registered at ClinicalTrials.gov as DREAMER, ClinicalTrials.gov Identifier NCT06140511.

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.

Objectives: Self-applied, low-density EEG offers opportunities to examine sleep in the home environment, yet its feasibility during behavioural sleep interventions remains unexplored. This pilot study aimed to evaluate the feasibility and acceptability of a self-applied, low-density EEG device during sleep restriction therapy (SRT) and explore effects on sleep and affect. Methods: Seventeen adults with insomnia and depressive symptoms completed a 2-week baseline and 4 weeks of SRT. The primary outcome was the proportion of expected EEG recordings completed and scoreable. Secondary outcomes included clinical measures, sleep continuity (sleep diary, actigraphy), sleep architecture (low-density EEG for 9 nights), power spectral density, and affect. Data were analysed with linear mixed models. Cohen's d and 95% confidence intervals were reported. Results: Feasibility was demonstrated (92% of expected EEG nights completed). SRT was associated with reductions in insomnia severity, depressive symptoms, negative affect, and increases in positive affect. Robust improvements were observed across treatment in sleep continuity (SOL, WASO, SE) from diary, which were paralleled by actigraphy. EEG revealed reduced TIB, TST, N1, N2, REM sleep, and REM latency during week one. Reductions in EEG-derived TIB and N1 sleep were maintained at night 28. There were no reliable differences for spectral or spindle measures. Conclusions: These findings suggest that self-applied, low-density EEG during SRT is feasible, acceptable, and may capture sleep changes during treatment. They highlight the potential for multi-night monitoring of sleep interventions at home and elucidating mechanisms underlying therapeutic change.

Background Insomnia symptoms are common in older adults. While observational studies suggest physical activity (PA) timing affects health outcomes, its effect on sleep remains unclear. We compared morning versus evening PA effects on insomnia severity and sleep quality in older adults with insomnia symptoms. Methods Eligible participants were aged 60 to 80 years with (sub)clinical insomnia (Insomnia Severity Index [ISI] score [&ge;]10). In a randomized cross-over trial, participants engaged in coached PA in the morning (10:00 - 11:00) or evening (19:30 - 20:30) for 14 days each. ISI scores were assessed post-intervention. Objective sleep parameters; duration, latency, efficiency, and timing, were assessed with a Withings Sleep Analyzer under the mattress. Subjective sleep quality was reported daily via smartphone app. Salivary dim light melatonin onset (DLMO) was measured on the final day of each intervention. Results Of 37 participants (mean ISI 14.3 {+/-} 3.3), 27 completed the study (mean age 69.8 {+/-} 5; 63% women). ISI scores improved after both morning ({Delta} - 2.5; 95% CI: - 1.14, - 3.83) and evening ({Delta} - 2.0; 95% CI: - 0.63, - 3.38) activity relative to baseline, but were not different between interventions. Compared to evening activity, sleep midpoint occurred earlier with morning activity (03:40 vs 04:00; {Delta} - 20 min; 95% CI: - 31, - 8). No differences in subjective sleep quality or DLMO were found. Exploratory analyses suggested insomnia scores improved specifically in late chronotypes following morning activity. Conclusions While morning vs. evening PA timing did not impact most sleep quality measures, it influenced sleep timing. Larger studies are needed to define optimal and personalized PA timing for improving sleep.

ObjectiveK-complexes (KCs) are large-amplitude EEG events that represent N2 sleep stage and have been linked to sensory gating, sleep protection, and memory consolidation. Their detection remains limited by inter-rater variability in visual scoring and by the reliance of detectors on features that discard temporal information. We propose a two-stage detector that combines a rule-based candidate localization algorithm with a Support Vector Machine (SVM) classifier operating directly on the raw 2-seconds waveform, and we evaluate it against an adjudicated expert consensus of two different datasets. MethodsPolysomnographic recordings from 10 healthy adults (Dataset 1) were independently annotated by two human scorers; discordant events were adjudicated by a senior expert, yielding 240 consensus KCs. The automatic classifier was evaluated using subject-level 10-fold Group K-Fold cross-validation and compared directly against the two human scorers under identical conditions. Cross-dataset generalization was further assessed on the public DREAMS database (Dataset 2) under both external and internal training criteria. ResultsThe SVM classifier achieved the highest F1-score (79.4%) and accuracy (78.8%) among all scorers, with balanced recall (81.7%) and specificity (75.8%). Of the 58 false positives, 42 originated from events both experts had rejected yet displayed canonical KC morphology and received high classifier confidence (P(KC)>0.7 in 45.2% of cases). This pattern was replicated on Dataset 2. ConclusionA waveform-based classifier matches expert performance and systematically flags morphologically valid KCs that fall outside conventional visual-scoring criteria. SignificanceThese findings question the existence of an unambiguous ground truth for KC detection and support a data-driven redefinition of the event boundary, with implications for sleep staging and memory-consolidation research.

Sleep-wake regulation arises from the interaction between homeostatic sleep pressure and circadian timing, yet current assessments evaluate these processes independently and fail to capture their dynamic modulation by environmental pressures. This limitation is particularly relevant in adolescents with attention-deficit/hyperactivity disorder (ADHD), who are at increased risk of circadian delay and sleep disruption. Here, we combined month-long wearable-based physiological monitoring with ecological behavioral assessments in adolescents with ADHD to characterize circadian and homeostatic processes dynamically in real-world settings. Using continuous skin temperature recordings, we derived individualized and day-specific estimates of circadian phase through hierarchical modelling, and integrated these measures with actigraphy-based sleep estimates and daily assessments of neurocognitive functioning and functional impairment. Temperature-derived circadian phase correlated with questionnaire-based chronotype but more accurately predicted sleep patterns. Delayed circadian phase was associated with later sleep onset and greater weekday-weekend variability. Importantly, circadian phase exhibited significant day-to-day fluctuations, particularly in individuals with delayed phase, reflecting interactions with environmental constraints. Sleep latency was jointly determined by homeostatic sleep pressure and day-specific circadian phase, with combined models outperforming either process alone. Crucially, both sleep deprivation and day-specific circadian misalignment independently predicted fluctuations in ADHD symptom severity, perceived stress, and neurocognitive impulsivity. In contrast, mean circadian phase alone did not explain behavioral variability. These findings demonstrate that circadian regulation is a dynamic, environmentally sensitive process rather than a fixed trait. Wearable-based estimation of circadian phase provides a scalable approach to capture these dynamics and may enable personalized interventions targeting sleep and circadian dysregulation.

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.

Sleep is fundamental to metabolic regulation, cognitive performance, immune function, and cardiovascular health, and evening screen exposure is widely proposed as a behavioural contributor whose adult evidence base remains thin. Here we analyze 350,600 paired screen-day and following-night observations from 3,086 Ultrahuman Ring AIR adult users. Sleep quality was assessed via the rings composite sleep score, derived from heart-rate variability, nightly movement, and skin temperature. At the user level, users in the highest screen-time quintile had lower sleep scores (Cohens d = -0.30), shorter sleep duration (d = -0.25), and lower sleep efficiency (d = -0.14) than the lowest screen-time quintile (all q [&le;] 0.005). Further, 45+ min of screen use in the last hour before bed was associated with mean sleep scores at the bottom of the cohort range, whereas the same dose 4-5 hours earlier showed no detectable cost, so the timing of screen use, not just its total, mattered. We next asked whether the way users distribute their screen time across the 24 hours, independent of total dose, separates users by sleep outcome. K-means clustering on 24-hour screen-use profiles identified three phenotypes: Daytime Peakers (DP), Late-Night Users (LNU), and Round-the-Clock Users (RCU), distinguished primarily by their nighttime share of 24-h screen use (DP 8.2%, LNU 16.9%, RCU 29.3%). Despite comparable total daily screen time, the phenotype gap in mean sleep score between DP (75.2 {+/-} 0.3 SEM) and RCU (66.7 {+/-} 0.6) was 8.5 points. We further identified users who transitioned phenotypes across four sequential quarters of follow-up; in this longitudinal subcohort, the magnitude of sleep-score change tracked the magnitude of the behavioural shift, with DP [-&gt;] LNU transitioners declining by 5.16 {+/-} 0.94 points and LNU [-&gt;] RCU transitioners by 4.79 {+/-} 1.87 points (both p < 0.05). Together, these findings position the temporal distribution of screen use, alongside its daily total and its concentration immediately before bed, as a behavioural correlate of objectively measured sleep quality in adults.

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.

BackgroundSleep-onset insomnia (SOI) is characterized by difficulty initiating sleep and is frequently associated with psycho-affective disorders. Despite its high prevalence and clinical impact, pathophysiological biomarkers and clear nosological frameworks remain lacking. Conventional polysomnographic (PSG) measures provide limited insight into the continuous dynamics of vigilance during the transition from wakefulness to sleep and across the night. MethodsWe retrospectively analyzed PSG recordings from 2 952 individuals using fine-grained EEG markers of vigilance, including theta/alpha ratio dynamics, micro-sleep episodes, and probability-of-wakefulness metrics. Individuals with and without SOI were compared, and SOI subgroups with and without depressive or anxiety symptoms were further examined. ResultsIndividuals with SOI exhibited a persistent state of elevated EEG-defined vigilance extending from wakefulness through the sleep onset period (SOP) and across all sleep stages, including N2, N3, and REM sleep. This hypervigilance was associated with vigilance instability during the SOP and a delayed accumulation of deep sleep over the night. Importantly, hypervigilance was more pronounced in isolated SOI than in SOI comorbid with psycho-affective symptoms, particularly depressive symptoms, and remained largely undetected by conventional PSG macrostructure measures. ConclusionsThese findings support a reconceptualization of SOI as a disorder of sustained vigilance dysregulation and reveal heterogeneity in hypervigilance across insomnia phenotypes. This dissociation from psycho-affective symptoms challenges current nosological frameworks at the interface of sleep and psychiatric disorders. By capturing microstructural alterations in vigilance invisible to standard scoring, continuous EEG-based markers provide mechanistic insight into insomnia heterogeneity and may enable biologically informed phenotyping across psychiatric conditions.

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.

Young people with major depressive disorder (MDD) exhibit altered thermoregulation, which has also been linked to vigilance and sustained attention. However, whether peripheral skin temperature is associated with cognitive vulnerability around sleep onset is unknown. We examined the relationship between the distal-proximal skin temperature gradient (DPG) and vigilance in 38 young people with MDD (20.1{+/-}3.7 years, 65.9% female) using an in-laboratory protocol spanning 4h before, to 2h after, habitual sleep time. Participants were classified into DPGwarm and DPGcold subgroups based on being above or below median DPG before sleep onset. Linear mixed models adjusted for age and sex examined psychomotor vigilance task performance across timepoints. The DPGwarm subgroup (n=19) showed significantly worse performance than DPGcold (n=19) across the evening for mean reaction time (RT), reciprocal reaction time, number of lapses, and fastest 10% of RT (all p[&le;]0.003). Significant GroupxTime interactions were observed for mean RT (F(3,90.4)=5.00, p=0.003) and lapses (F(3,93.6)=6.73, p<0.001), with DPGwarm participants showing progressively worse performance approaching sleep onset. At 2h post-habitual sleep onset, DPGwarm participants exhibited slower RT ({Delta}=129ms, p<0.001) and nearly four times more lapses (14.9 vs 4.1, p<0.001). Performance decrements were not accompanied by differences in melatonin timing, subjective sleepiness or mood, suggesting DPG may index cognitive vulnerability independently. Of note, younger age was associated with greater vigilance decrements. These findings demonstrate that elevated peripheral skin temperature before sleep onset is associated with reduced vigilance in young people with MDD, and may therefore have potential utility as a non-invasive thermoregulatory biomarker of cognitive vulnerability.

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.

Motor memory retention is impaired in Parkinsons disease (PD), affecting long-term rehabilitation outcomes. It appears that NREM sleep could be beneficial for consolidation processes in PD, and could be leveraged with non-invasive sleep interventions. This study examined the effect of auditory targeted memory reactivation (TMR) during NREM sleep on the retention of a motor sequence learning finger tapping task in 20 PD and 20 healthy older adults (HOA). TMR was applied during a 2-hour nap and its effect on motor retention was post-nap, after 24-hours and with a dual-task. The impact of TMR on sleep electrophysiology was also evaluated. Results showed no effect of TMR on motor retention or dual-tasking, with no difference between the groups. However, the TMR intervention did increase slow-wave density and decreased spindle density in both groups, and slow-wave amplitude during the presentation of the auditory cues was positively associated with performance in HOA. In conclusion, TMR applied during a 2 hour nap did not enhance motor retention, but the changes in sleep physiological features could be linked to a possible underlying effect on memory processing that warrants further investigation.

Prader-Willi syndrome (PWS) is a neurodevelopmental disorder caused by the loss of paternally expressed genes within the imprinted 15q11-q13 locus, which includes clusters of box C/D small nucleolar RNAs (SNORDs), notably the SNORD115 and SNORD116 gene families. Although paternally inherited SNORD116 deletions have been associated with sleep disturbances in patients and mouse models, the respective and combined contributions of SNORD115 and SNORD116 to sleep regulation remain unclear. Here, we combined polysomnographic recordings with quantitative analysis of hypothalamic neuronal populations to assess sleep-wake architecture, sleep homeostasis, and underlying circuit alterations in mice carrying paternal deletions of SNORD115, SNORD116, or both clusters. SNORD116 deletion was associated with a selective increase in REM sleep, particularly during the light phase and during recovery following sleep deprivation, without affecting slow-wave sleep or REM-associated theta activity. In contrast, SNORD115 deletion did not alter sleep. Unexpectedly, combined deletion of SNORD115 and SNORD116 did not reproduce the REM sleep phenotype observed in SNORD116-deficient mice, indicating that SNORD115 loss attenuates SNORD116-dependent REM sleep alterations. At the cellular level, melanin-concentrating hormone (MCH) neuron density was reduced in both SNORD116-KO and double SNORD116/115-KO mice, whereas hypocretin (Hcrt) neurons were preserved across genotypes. Notably, REM sleep alterations did not parallel MCH loss, as increased REM sleep was absent in double-KO animals despite comparable reduction in MCH neuron density. Transcriptomic analyses at ZT0 further revealed only limited changes in hypothalamic gene expression across models. Together, these findings reveal an unanticipated interaction between SNORD115 and SNORD116 in the regulation of REM sleep and uncover a dissociation between genetic alterations, neuronal circuit organization, and sleep phenotype. More broadly, they caution against inferring physiological functions or disease-relevant mechanisms from single SNORD deletions within complex imprinted loci, and indicate that current mouse models may not faithfully capture sleep alterations associated with PWS.