Sleep

Study ObjectivesIdiopathic hypersomnia (IH) is a central nervous system hypersomnia frequently accompanied by autonomic symptoms, yet objective physiological data are limited. We sought to characterize autonomic nervous system (ANS) dysfunction in IH using nocturnal heart rate variability (HRV) and diurnal autonomic reflex testing (ART), compared to individuals with type 1 narcolepsy (NT1) and healthy controls (HCs). MethodsTwenty-four adults with IH, 10 with NT1, and 14 HCs underwent overnight video polysomnography with HRV analyses in time and frequency domains during stable slow-wave sleep and REM sleep. Comprehensive ART included sympathetic adrenergic (head-up tilt (HUT), Valsalva BP responses), parasympathetic cardiovagal (HRV to deep breathing, Valsalva ratio), and sudomotor (Q-Sweat) measures. ResultsIH participants were predominantly female, with over half reporting long sleep duration. Compared to NT1 and HC, participants with IH demonstrated a greater magnitude of orthostatic tachycardia on tilt ({Delta}HR 41.0 {+/-} 16.3 vs. 26.3 {+/-} 9.3 vs. 30.8 {+/-} 9.3 bpm, p = 0.0086), as well as frequent sudomotor dysfunction (64.3%). IH participants demonstrated greater nocturnal and REM HR with reduced parasympathetic indices during REM, indicating diminished vagal modulation compared with HCs ConclusionsIH is characterized by a distinct pattern of autonomic dysfunction, including pronounced orthostatic tachycardia, frequent sudomotor abnormalities, and reduced parasympathetic activity during sleep. These findings provide objective physiological evidence of ANS involvement in IH and delineate features that distinguish IH from NT1 and HCs.

Actigraphy is widely used for long-term sleep monitoring, but established sleep-wake scoring algorithms often require parameter tuning, which is commonly performed manually and can reduce reproducibility. In this study, a grid-search-based calibration framework is presented for established actigraphy algorithms and evaluate whether it can serve as a practical alternative to manual tuning. The method was evaluated using two datasets: a multi-subject polysomnography-validated actigraphy dataset and a self-collected dual-device dataset. In the polysomnography-validated dataset, grid-search optimization produced performance patterns similar to manual parameter selection, while slightly improving detection of sleep onset and sleep offset and yielding modest gains in wake-sensitive metrics. In the dual-device dataset, consensus and majority voting were useful for reducing the influence of brief wake episodes occurring within the main sleep period, including micro-awakenings that can fragment sleep predictions across individual algorithms. Overall, these findings show that grid-search can replace manual parameter tuning with a more explicit and reproducible procedure while providing small improvements in sleep timing estimation and benefiting ensemble-based handling of within-sleep wakefulness.

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.

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.

Excessive daytime sleepiness (EDS) is a heterogeneous phenotype with little known of its genetic basis. Large-scale genome-wide association studies (GWAS) have reported genomic loci associated with EDS, though since most of these are non-coding, the causal gene(s) underlying the association are not known. Additionally, the cell types in which these genes exert their effects on sleep have not been functionally explored in vivo. Here, we employed a chromatin-based variant-to-gene mapping approach to first implicate candidate effector genes at EDS GWAS loci in human-derived neural and glial cell lines. Subsequent cell type-specific RNAi knockdown of orthologous genes using neural and glial GAL4 drivers in Drosophila confirmed cell-specific regulation of sleep by these GWAS-implicated effector genes. Among these, ruby (ortholog to AP3B2), a component of the AP-3 vesicular trafficking complex emerged as a robust sleep regulator. Targeted knockdown in flies localized ruby function to astrocyte-like glia, where loss of ruby increased sleep duration. The conserved role of ruby/ ap3b2 was validated in zebrafish where CRISPR-mediated loss increased daytime sleep. Together, these findings show that physical variant-to-gene mapping predicted cell-type-specific gene function for complex sleep traits and revealed ruby/AP3B2 as a conserved glial regulator of sleep and arousal. This work provides a generalizable framework for connecting non-coding GWAS variants and their corresponding effector genes to identify novel and highly conserved regulators of sleep.

ObjectiveIsolated rapid-eye-movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video-polysomnography. We assessed a two-stage screening strategy combining a brief questionnaire on rapid-eye-movement sleep behavior disorder symptoms and other prodromes with wrist actigraphy across multiple case-control cohorts. MethodsParticipants aged 40-80 without neurodegenerative disease were recruited from five cohorts; all cases were confirmed by video-polysomnography. The questionnaire was administered to 289 participants, and 236 underwent [&ge;]14 nights of home wrist actigraphy. The wearable-based algorithm was built on four movement features (mean motor activity, activity index, short or long immobile bouts, twitch activity). Models were trained with nested cross-validation using XGBoost. ResultsThe full retrospective cohort included 396 participants (99 cases, 297 controls; mean age 64 {+/-} 11; 55% male). The dream enactment question alone achieved an area under the curve of 0.85, which improved to 0.86 using the four-item questionnaire. Actigraphy alone achieved 82% sensitivity and 84% specificity. In the subgroup completing both assessments (75 cases, 54 controls), the two-stage protocol--questionnaire followed by actigraphy--yielded 68% sensitivity and 100% specificity using the dream-enactment question alone, and 73% sensitivity and 100% specificity using the four-item questionnaire. InterpretationA two-stage protocol combining questionnaire and actigraphy demonstrated high specificity and good sensitivity for detecting isolated rapid-eye-movement sleep behavior disorder in this multicenter cohort. This low-cost, scalable strategy is compatible with widely used wearable devices and warrants validation in community-based populations.

ObjectivesChronic insomnia (INS) is particularly prevalent in older adults and females. Sex-and age-related differences in neurophysiological markers of sleep quality (sleep spindles and slow-wave activity [SWA]) may underlie differential vulnerability to INS. This study investigated the effects of sex and insomnia on spindle and SWA beyond aging, to better understand the mechanistic differences contributing to the higher prevalence of INS in females. MethodsAfter a habituation night, one night of sleep assessed with polysomnography was analyzed in 222 adults (aged 18-82) including 119 INS (71% female) and 103 healthy sleepers (HS; 61% female). Spindle density, slow oscillation (SO) density, relative sigma power and SWA were derived during NREM sleep. Age, group, sex, and group-by-sex interactions were examined, with age as a covariate. ResultsAge, insomnia, and sex each contributed uniquely to NREM oscillatory activity. INS primarily reduced spindle and SO density, while sex accounted for differences in SWA. While SWA was higher in females overall, sex differences were not significant within the INS or HS groups. Female INS reported highest rates of insomnia severity as well as lower sigma power than males in the INS group. Spindle and SO density deficits were also present in female INS relative to female HS, as well as male INS relative to male HS. ConclusionsThe combination of reduced sigma power in females with insomnia relative to their male counterparts, as well as less spindle and SO density compared to female healthy sleepers may contribute to greater insomnia severity in females. Statement of SignificanceInsomnia is a growing public health concern that is more commonly reported in females, yet the neural mechanisms underlying this sex difference remain poorly understood. Our findings suggest that specific markers of sleep quality are disproportionately disrupted in females with insomnia, potentially contributing to greater vulnerability and symptom severity. These results provide new insight into how sex influences the neurophysiology of insomnia disorder and identify oscillatory markers that could serve as targets for personalized interventions. Future research should investigate whether these alterations represent persistent dysfunction or reversible changes, which could advance understanding of the biological basis of insomnia and inform strategies to improve sleep health in at-risk populations.

Background Narcolepsy is a rare, lifelong neurological disorder that often begins in childhood or adolescence. Diagnosis is frequently delayed because current diagnostic testing relies on specialist in-patient sleep investigations: overnight polysomnography (PSG) followed by a multiple sleep latency test (MSLT), interpreted according to International Classification of Sleep Disorders criteria (ICSD-3-TR). These investigations are expensive, labour intensive, and available in a limited number of centres, contributing to delays and inequity of access. Automated analysis of sleep-stage probabilities (hypnodensity) using neural networks has shown promising diagnostic performance in research cohorts but still requires hospital-based PSG acquisition. The Dreem 3 headband (DH) is a comfortable, dry-montage EEG device designed for home use. Combined with its proprietary machine learning classification of sleep stages, it may offer accurate ambulatory sleep physiology assessments and support clinical decision making. Methods This was a single-centre, prospective, observational study recruiting 60 participants aged 10 to 35 years undergoing investigation for hypersomnolence within GSTT sleep services and scheduled for PSG and MSLT as part of routine care. Exclusion criteria included physician-diagnosed medical or psychiatric disorder that could independently account for excessive daytime sleepiness; and/ or regular use of prescribed or recreational medication known to affect sleep architecture. Participants first wore the DH at home for five weeknights, followed by a continuous 48-hour weekend recording using two devices in rotation. They then underwent routine in-patient PSG and MSLT. PSG and MSLT were interpreted according to ICSD-3 by an experienced sleep physician and a final diagnosis determined by a sleep physiology consultant. The primary outcome is accuracy of ambulatory DH-based assessment of sleep physiology and subsequent diagnosis of sleep disorders. We evaluate proprietary and in-house developed machine learning methods to detect SOREM epochs and predict narcolepsy diagnosis from PSG, PSG+MSLT and DH data. All algorithmic outcomes will be compared to clinical outcomes derived from current clinical standard of care. Discussion This study will provide proof-of-concept evidence for a home-based wearable EEG approach to narcolepsy diagnosis. Patient and public involvement work with young people with confirmed narcolepsy indicates high acceptability of the DH protocol: in a survey of ten young people, eight reported they would be willing to wear a sleep headband nightly at home for five days (two were unsure), and seven reported they would be willing to wear it continuously for 48 hours over a weekend (two were unsure; one said no). These findings informed the decision to restrict continuous wear to the weekend, reflecting feedback that daytime wear during school or work hours would be unacceptable. If validated, this approach could reduce delays to diagnosis, improve equity of access, and support development of a subsequent multicentre study. Trial registration IRAS Project ID: 321547. Registered October 2022. Recruitment was completed on 30 January 2026.

IntroductionSleep spindles are electroencephalographic elements characteristic of non-rapid eye movement sleep generated by thalamo-cortical interactions. Spindles have been linked to some of the cognitive benefits afforded by sleep and high spindle activity is associated with increased arousal threshold. Here, we demonstrate that targeting the thalamus with Transcranial Electrical Stimulation with Temporal Interference (TES-TI) can enhance spindle activity. Methods46 participants (24 {+/-} 9.5 years; 58.7% F) underwent thalamic TES-TI stimulation during daytime naps. Three stimulation protocols with 15kHz carrier frequency were tested during stage 2 of non-rapid eye movement sleep (N2): fixed difference frequency of 10 Hz (TES15kHz-TI10Hz), difference frequency matched to individual spindle peak (TES15kHz-TIPeak), and no difference frequency (TES15kHz). Spectral power in the spindle (sigma) band and integrated spindle activity (ISA) were compared before and during the stimulation, and across stimulation protocols. ResultsTES15kHz-TI10Hz stimulation was associated with a significant increase in sigma band power ({Delta}[x]STIM-PRE = 0.46 log10{micro}V2, p = 0.0042) and ISA ({Delta}[x]STIM-PRE = 4.064 {micro}V/s, p = 0.030). Cluster-based analysis localized the increase in sigma power across the entire scalp (p = 0.008). Linear mixed effects models showed that both sigma band power and ISA during stimulation increased significantly more in TES15kHz-TI10Hz compared to the other experimental condition. ConclusionsThis study provides evidence supporting the successful use of TES-TI targeting the thalamus to enhance sleep spindle activity. Stimulation at a fixed difference frequency of 10 Hz increased sigma band power and ISA, whereas neither stimulation matched to individual sigma band peak nor TES alone produced comparable effects. These promising results warrant further investigations into the cognitive and clinical impact of TES-TI, a non-invasive neuromodulation tool that can reach deep brain regions. Statement of significanceThis study provides evidence that thalamo-cortical networks, which are central to many physiological and pathological brain activities, can be modulated non-invasively in humans. More specifically, the findings show that transcranial electrical stimulation with temporal interference targeting the thalamus can selectively enhance sleep spindle activity. This work introduces a new strategy for precisely targeting sleep-generating mechanisms regulated by deep brain circuits without surgery or medication. Key next steps include determining whether this increase in spindle activity can positively impact cognition and assessing the translational potential of this approach for clinical populations.

The transition from wake to stable sleep is characterized by multiple neural, physiological, and behavioral changes. How these changes may differ in individuals with difficulties falling asleep such as children with neurodevelopmental conditions is poorly understood. Here, we studied sleep initiation in >2000 nights recorded from 186 children who participated in the Simons Sleep Project (SSP). Data included simultaneous, synchronized recordings of actigraphy, electroencephalography (EEG), photoplethysmography (PPG), and skin temperature. We extracted multiple neural, physiological, and behavioral measures that are known to increase/decrease during the sleep initiation period including EEG delta (1-4Hz) power, movement counts, heart rate (HR), and skin temperature. Transitions from 20 minutes before sleep onset to 40 minutes after sleep onset were modeled with a sigmoid function enabling the quantification of transition timing, speed, and magnitude per measure. Individuals with longer sleep onset latencies (SOL) exhibited smaller increases in EEG delta power and skin temperature as well as smaller decreases in HR and activity counts. These findings indicate that difficulties falling asleep are associated with multiple forms of cortical, physiological, and behavioral hyperarousal that can be measured at home with wearable devices. Importantly, transition magnitudes were key to explaining differences in SOL across participants (26% explained variance) in contrast to transition speed or timing within the sleep initiation period (<13% explained variance). Longer SOL and weaker transitions were particularly prominent in children diagnosed with autism and/or attention deficit hyperactivity disorder (ADHD).

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.

Background: Circadian rest-activity rhythms weaken with age, but whether sleep disorders modify this trajectory is unknown. Methods: We analyzed wrist accelerometry data from 4,386 participants aged 6-80 years in the 2011-2012 National Health and Nutrition Examination Survey (NHANES). Circadian features were extracted using cosinor analysis and nonparametric methods; a Circadian Disruption Index (CDI) was constructed from five standardized components. Survey-weighted regression with natural cubic splines and Wald F-tests tested age-by-sleep-disorder interactions using Taylor series linearization for variance estimation. Results: Doctor-diagnosed sleep disorder (N = 360, 8.2%) was associated with significantly different age-related trajectories of amplitude (F(2,17) = 11.24, p = 0.0008) and MESOR (F(2,17) = 8.22, p = 0.0032), both surviving Bonferroni correction (p < 0.006). CDI was higher in those with a sleep disorder (0.290 vs. 0.131, p < 0.001) and was independently associated with higher BMI (beta = 1.33 kg/m2, p < 0.001), higher HbA1c (beta = 0.089%, p = 0.004), greater diabetes prevalence (beta = 3.8 percentage points, p < 0.001), and worse depressive symptoms (beta = 0.43 PHQ-9 points, p = 0.020). Sensitivity analyses using a broader sleep problem exposure did not replicate these interactions. Conclusions: Doctor-diagnosed sleep disorders are associated with an altered age-related decline in circadian amplitude and mean activity level. CDI was independently linked to cardiometabolic and depressive outcomes, supporting a mechanistic connection between clinically significant sleep pathology and circadian disruption across the lifespan.

Objective: The narcolepsy type 1 (NT1) phenotype severity is heterogeneous, and the disease course is largely unknown. The 2009-10 H1N1-(Pandemrix(R))-vaccinations were followed by increased numbers of possibly more severe post-H1N1 NT1 cases but long-term prospective data on large, vaccinated cohorts are missing. Methods: 130 consecutive post-H1N1 NT1 cases (113/130 Pandemrix(R) -vaccinated) were prospectively followed up after approximately 5.5 years. Epworth Sleepiness Scale (ESS), cataplexy, hypnagogic hallucinations, sleep paralysis, PSG, MSLT, and BMI were evaluated. Phenotype severity predictors (hypocretin-1 deficiency severity <40 vs. 40-150 pg/ml; Pandemrix(R)- vaccination; disease duration) were tested in age and sex-adjusted multivariable regressions. Results: From baseline to follow-up, phenotype severity overall improved (milder symptoms, higher mean MSLT sleep latency (SL) and fewer SOREMPs, all p<0.001). Follow-up phenotype severity was strongly predicted by the same baseline measures. Females had worse ESS and cataplexy, men had higher BMI, and young individuals had lower mean MSLT SL and more SOREMPs. Severe hypocretin deficiency (<40 pg/ml) predicted baseline PSG SOREMPs and lower MSLT SL. Vaccinated individuals had more severe baseline PSG/MSLT measures but greater long-term symptom improvement, and vaccination no longer predicted PSG/MSLT severity at follow-up. Conclusion: The best prognostic factor for long-term NT1 phenotype severity is the earlier phenotype severity. Hypocretin deficiency severity also predicts parts of short-term but not long-term phenotype severity. Pandemrix(R)-vaccination is associated with initially more severe phenotype but larger long-term improvement i.e. a different clinical course than in unvaccinated NT1, although medication effects cannot be excluded. Our findings underscore heterogeneity in NT1 phenotype and disease trajectories.

Chronic short sleep (CSS) is an emerging public health issue that frequently begins in adolescence and is common among healthcare professionals and others engaged in shift work. Epidemiological studies associate CSS and sleep disruption with metabolic disorders, cardiovascular disease, cognitive decline, and heightened Alzheimers disease risk. Building on our prior findings that sleep deprivation perturbs proteostasis and activates endoplasmic reticulum (ER) stress pathways, we investigated the long-term consequences of CSS in young adult wild-type mice over the course of one year. Mice exposed to CSS displayed impaired cognition in hippocampal dependent tasks by 28 weeks of age, indicating emerging memory deficits. At the molecular level, CSS disrupted hippocampal proteostasis--particularly protein folding processes--and triggered ER stress and activation of the unfolded protein response (UPR). Importantly, disrupted proteostasis preceded the behavioral decline, with diminution of the key chaperone and UPR regulator BiP occurring at 20-22 weeks of age. CSS also increased markers of cellular stress and neuroinflammation while reducing the expression of proteins associated with memory function. Age also seemed to be a cellular stressor, causing a longitudinal increase in UPR, ISR, and neuroinflammation markers. Together, these results indicate that both chronic short sleep and age compromise proteostasis and promote neuroinflammation, contributing to progressive cognitive dysfunction.

Cannabis use is an increasingly common therapeutic for a variety of chronic diseases. In addition, people with sleep problems may self-medicate using cannabis products. However, genetic architecture of cannabis use and its shared genetic predispositions with sleep traits has not been systematically examined. We performed a meta-analysis of cannabis use within the All of Us and UK Biobank cohorts, consisting of 152,807 cases and 220,272 controls. Our meta-analysis identified 39 independent loci, including the previously reported CADM2 locus associated with cannabis use and replicating previous work. Additionally our associations include neuronal and sleep-regulating genes such as HTR1A, RAI1, SLC39A8, and NCAM1. Moreover, tissue-specific analyses revealed that the genetic architecture of cannabis use is heavily enriched within the central nervous system and specific brain cell types. In addition, we observed significant positive genetic correlations with clinical insomnia, insomnia-related medication usage, and objectively measured nighttime physical activity, alongside negative correlations with morningness chronotype and daytime activity. Fine-mapping and colocalization analyses identified shared genetic signals between cannabis use and clinical insomnia including a near-perfect colocalization at SLC39A8 and CADM2. Together, these results highlight the shared genetic risk between cannabis use and sleep disorders. Additionally, our findings indicate the importance of investigating the genetic effects of cannabis use as its use becomes more widespread, both recreationally and medicinally.

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.

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.

2)BackgroundCircadian rhythm desynchrony (CD) occurs when there is a mismatch between the circadian clock and local time, such as shift work. Mouse models are commonly employed to study CD, but may have significant shortcomings such as environmental masking, a focus only on sleep physiology, and significant variability between study designs. ObjectiveThis study used in vivo telemetry for simultaneous, real-time monitoring of locomotor activity (LA), core body temperature (CBT), and brain activity (EEG) in freely moving C57BL/6J mice to assess CD effects. MethodsFour-month-old C57BL/6J mice (n=11) were surgically implanted with telemeters enabling simultaneous real-time recording of LA, CBT, EEG.: Mice were sequentially exposed to a control condition standard 12:12h light-dark cycle (T24) then 4, 8-day CD paradigms: 10:10 h short day (T20), social jet lag (SJL), repeated 6h phase advances (6A2), and a 3:3 h ultradian cycle (T6)For each paradigm, the final 48h of data (250 Hz) were analyzed. ResultsWe found clear differences in the severity of the effects of each CD paradigm on sleep and circadian fitness, where T20[~]T6>SJL>6A2. CBT revealed broader disruption, but EEG outputs proved the most sensitive indicators of internal desynchrony. ConclusionsEach CD paradigm produced a unique profile across behavioral, physiological, and neural domains. We have also identified Gamma CV as a novel, sensitive metric of CD. These results highlight the necessity of multimodal monitoring to accurately characterize the impact of ecologically relevant stressors on circadian and sleep physiology. Statement of SignificanceCircadian rhythm desynchrony (CD), driven by shift work, jet lag, and modern irregular light exposure, is a major health burden linked to metabolic, neurodegenerative, and neuropsychiatric diseases. However, standard methods for measuring CD in laboratory models often rely on simple locomotor activity, which can "mask" the true extent of internal circadian stress. In this study, we simultaneously monitored brain EEG activity, core body temperature, and motion across four distinct models of circadian stress. We discovered that locomotor activity is a deceptive indicator of health; while mice appeared to show no alterations under several stress paradigms, their brain waves and body temperatures revealed the underlying impact of CD. Specifically, we identified "Gamma CV" as a highly sensitive new brain-wave marker that detects early circuit instability even when behavior appears normal and sleep quantity is preserved. These findings provide a marker for identifying early neurological vulnerability to irregular light schedules, offering a potential bridge to understanding similar gamma brain-wave alterations seen in addiction, early-stage Alzheimers disease, and other disorders.

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.

We completed a video-based, four-night, in-home, level 3 sleep apnea study of healthy, low-risk pregnant participants and their bed partners in order to characterize sleep physiology in the third trimester of pregnancy. Demographic, anthropometric, and baseline sleep health characteristics were recorded, and the NightOwl home sleep apnea test device was used to measure sleep breathing, posture, and architecture parameters. Symptoms of restless legs syndrome were elicited in the exit interview. Forty-one pregnant participants and 36 bed partners completed the study. Bed partners had a significantly higher prevalence of sleep apnea than their pregnant co-sleepers (31% vs. 5.9%). Bed partners also had more severe sleep apnea than their pregnant co-sleepers, and this persisted on an adjusted analysis for baseline differences in factors known to increase risk of sleep apnea. In pregnant participants, increasing gestational age was found to be protective against mild respiratory events but not more severe events. While the correlation between STOP-Bang score and measures of sleep apnea severity was weak, an affirmative response to the "witnessed apneas" item on the STOP-Bang questionnaire was a strong predictor of more severe sleep apnea for all participants. Smoking history also increased sleep apnea risk. Pregnant participants had lower sleep efficiency and longer self-reported sleep onset latency. Restless legs syndrome was experienced by 39.5% of the pregnant participants but no bed partners. From a sleep breathing perspective, people with healthy, low-risk pregnancies have better sleep than their bed partners despite lower sleep efficiency and higher rates of restless legs syndrome. Clinical Study RegistrationSleep in Late Pregnancy - Artificial Intelligence Development for the Detection of Disturbances and Disorders (SLeeP AID4), https://clinicaltrials.gov/study/NCT05376475, registration ID NCT05376475. Statement of SignificancePregnancy negatively impacts sleep, and poor sleep in pregnancy negatively impacts maternal and fetal health. Pregnancy represents a unique challenge to sleep breathing physiology and, thus, an opportunity to test for sleep apnea. Sleep apnea however, while increased in pregnancy, is more common in males. This novel study tested healthy people with low-risk pregnancies and their bed partners for sleep apnea in the comfort of their home over four nights in late pregnancy. Sleep apnea was more common and worse in the bed partners. Advancing gestational age was protective against mild but not severe sleep apnea, and a critical remaining knowledge gap is this interplay in high-risk pregnancies. Future sleep in pregnancy research should make efforts to include high-risk pregnancies.