Sleep Stages Research Articles

Ontogenetic development of ponto-geniculo-occipital waves during paradoxical sleep in kittens.

Ponto-geniculo-occipital (PGO) waves are a hallmark feature of paradoxical sleep (PS), emerging just before PS onset during the transition from slow wave sleep (SWS) to PS (TSWS-PS) and persisting throughout the PS phase in adult cats. These waves are considered a biomarker for the maturation of PS. However, their developmental trajectory in mammals remains poorly understood. This study investigated the emergence and maturation of PGO waves during PS in developing kittens. Electrodes were stereotaxically implanted into the lateral geniculate nucleus, accurately localized using magnetic resonance imaging (MRI). Recording included cortical electroencephalogram, nuchal muscle activity, PGO waves and rapid eye movements (REMs). Despite the presence of abundant PS and frequent muscle twitches accompanied by REMs in neonatal kittens, PGO spikes were first detected at postnatal day (PND) 16, with an average onset at PND 19. Initially, these waves appeared with lower density and amplitude during the TSWS-PS and PS phases. Over the following weeks, PGO wave density and amplitude increased, along with prolonged durations during both TSWS-PS and PS. Type I waves (singlet and bigeminy) predominated during TSWS-PS, while type II waves (clusters) were more frequent during PS. The proportion of type II waves and their co-occurrence with REMs increased with age. The adult-like pattern of PGO waves was fully established by PND 50. The emergence and maturation of PGO waves during PS are closely linked to the development of the sleep-wake cycle and may play a role in learning and memory processes.

The interaction between comorbidities and sleep stages influences oxygen re-saturation characteristics.

Sleep stages exhibit differing patterns of cardiac, respiratory and nervous system activation. Rapid eye movement (REM) sleep is associated with deeper oxygen desaturation events in obstructive sleep apnea. However, no studies have looked to the effect of sleep staging on re-saturation characteristics. Polysomnographic data from the Sleep Heart Health Study were utilised to derive oxygen saturation parameters from events having both desaturation and re-saturation parts. Sleep stages were described as non-REM (NREM) 1 or 2 (combined), 3 and REM. Sleep stage effects on desaturation and re-saturation characteristics were investigated in a healthy subgroup (n = 759) and participants with hypertension (n = 2534), lung disease (n = 715), heart failure (n = 199) and myocardial infarction (n = 713). A total of 3793 participants (48.3% female) were included for analysis (171,976 saturation events; median 20 per participant). Events during REM had the longest duration, deepest nadirs and greatest area for desaturations and re-saturations. Sleep stage effected re-saturation parameters more than desaturation parameters, with a relative difference from NREM 1/2 to REM in duration of 16.7% and 29.8%, in rate of 0.2% and 4.5% and in area of 36.1% and 48.0% for desaturation and re-saturation, respectively, among healthy participants. Similarly, the effect of comorbidities was greater upon re-saturations than desaturations, as participants with heart failure recorded a relative difference to healthy participants of 10.3% and 24.4% for desaturation and re-saturation duration, respectively, 12.8% and 15.0% for rate and 6.4% and 16.4% for area. Sleep stages and comorbidities have significant effects upon nocturnal oxygen re-saturation parameters. Cardiorespiratory comorbidities elicit greater degradations in oxygen re-saturations than they do desaturations.

Interactions Between Anesthesia and Sleep: Optimizing Perioperative Care to Improve Sleep Quality and Surgical Recovery Outcomes.

Sleep is a fundamental physiological process that supports immunity, cognition, memory, and metabolism, making it essential for overall health and well-being. Poor-quality sleep is associated with the onset of many diseases, including cardiovascular and mental health disorders. When using anesthesia, it is essential to have a thorough understanding of the metabolic dysfunction and immunosuppression linked to sleep loss to ensure appropriate perioperative management. Commonly used agents like propofol, sevoflurane, and ketamine affect consciousness, pain levels, and autonomic responses. Inhaled anesthetics (e.g., sevoflurane and isoflurane) and intravenous anesthetics (propofol) act on gamma-aminobutyric acid (GABA) receptors and influence stages of sleep and circadian rhythms. Ketamine may uniquely preserve some aspects of restorative sleep, while most anesthetics affect rapid eye movement (REM) and slow wave sleep (SWS), altering cognitive and physical recovery. Modifying anesthetic regimes depending on the patient's sleep history and risk factors can maximize sleep health and postoperative patient outcomes. The physiological effects of anesthesia on the central nervous system persist beyond the perioperative period by influencing sleep quality, circadian regulation, and postoperative outcomes. Effective pain management is a significant component in addressing sleep quality. Opioids, while effective for pain relief, disrupt sleep architecture by reducing REM and SWS, increasing awakening frequency, and potentially causing respiratory depression. Multimodal pain therapy, including non-opioid analgesics, can reduce dependence, improve sleep quality, and lower adverse effects. Anesthetic agents can influence the body's internal clock, leading to mood changes, fatigue, and cognitive deficits. This review exploits the relationship between sleep and anesthesia, detailing the effect of anesthetic agents on the quality, architecture, and recovery of sleep patterns post-surgery. It also explores how these agents influence sleep stages, such as REM and non-REM sleep, and their implications for patient outcomes. Incorporating sleep optimization techniques can enhance recovery timelines and patient well-being. Researching anesthetic techniques that support postoperative sleep health is essential for further improving patient outcomes.

Reduction of orexin-expressing neurons and a unique sleep phenotype in the Tg-SwDI mouse model of Alzheimer’s disease

Sleep disturbances are common in Alzheimer’s disease (AD) and AD-related dementia (ADRD). We performed a sleep study on Tg-SwDI mice, a cerebral amyloid angiopathy (CAA) model, and age-matched wild-type (WT) control mice. The results showed that at 12 months of age, the hemizygous Tg-SwDI mice spent significantly more time in non-rapid eye movement (NREM) sleep (44.6 ± 2.4% in Tg-SwDI versus 35.9 ± 2.5% in WT) and had a much shorter average length of wake bout during the dark (active) phase (148.5 ± 8.7 s in the Tg-SwDI versus 203.6 ± 13.0 s in WT). Histological analysis revealed stark decreases of orexin immunoreactive (orexin-IR) neuron number and soma size in these Tg-SwDI mice (cell number: 2187 ± 97.1 in Tg-SwDI versus 3318 ± 137.9 in WT. soma size: 109.1 ± 8.1 μm2 in Tg-SwDI versus 160.4 ± 6.6 μm2 in WT), while the number and size of melanin-concentrating hormone (MCH) immunoreactive (MCH-IR) neurons remained unchanged (cell number: 4256 ± 273.3 in Tg-SwDI versus 4494 ± 326.8 in WT. soma size: 220.1 ± 13.6 μm2 in Tg-SwDI versus 202.0 ± 7.8 μm2 in WT). The apoptotic cell death marker cleaved caspase-3 immunoreactive (Caspase-3-IR) percentage in orexin-IR neurons was significantly higher in Tg-SwDI mice than in WT controls. This selective loss of orexin-IR neurons could be associated with the abnormal sleep phenotype in these Tg-SwDI mice. Further studies are needed to determine the cause of the selective death of orexin-IR cells and relevant effects on cognition impairments in this mouse model of microvascular amyloidosis.

Longer respiratory events in childhood obstructive sleep apnea syndrome constitute a trait of older children with excessive daytime sleepiness.

The objective was to evaluate the determinants of desaturation during apnea and apnea-hypopnea duration's links with the endotypes (pharyngeal compliance, loop gain) of obstructive sleep apnea (OSA) and with heart rate variability (HRV) indices. We retrospectively selected 35 otherwise healthy children (median age: 10.6 years, 16 females) with moderate to severe OSA who had measurements of pharyngeal compliance (acoustic pharyngometry), loop gain (awake tidal ventilation with calculation of controller and plant gains), and respiratory system impedance (impulse oscillometry system). HRV indices were obtained from the whole-night ECG of polysomnography. The slope of desaturation (0.64%.s-1) during apnea was related to baseline end-tidal PO2 (r2 = 0.74; p < 0.001), which is influenced by small airway disease (reactance at 5Hz and its area). The mean durations of apnea and hypopnea in NREM and REM sleep were combined into the mean apnea-hypopnea duration (MAD4), which positively correlated with age, sleepiness, and HRV indices. The MAD4 correlated with two endotypic traits, controller and plant gains. In conclusion, arterial desaturation during apnea is related to alveolar PO2. Longer respiratory events constitute a trait of older children with excessive daytime sleepiness, higher HRV, and adaptive responses of ventilatory control to maintain its stability.

Mettl3-m6A-NPY axis governing neuron-microglia interaction regulates sleep amount of mice.

Sleep behavior is regulated by diverse mechanisms including genetics, neuromodulation and environmental signals. However, it remains completely unknown regarding the roles of epitranscriptomics in regulating sleep behavior. In the present study, we showed that the deficiency of RNA m6A methyltransferase Mettl3 in excitatory neurons specifically induces microglia activation, neuroinflammation and neuronal loss in thalamus of mice. Mettl3 deficiency remarkably disrupts sleep rhythm and reduces the amount of non-rapid eye movement sleep. We also showed that Mettl3 regulates neuropeptide Y (NPY) via m6A modification and Mettl3 conditional knockout (cKO) mice displayed significantly decreased expression of NPY in thalamus. In addition, the dynamic distribution pattern of NPY is observed during wake-sleep cycle in cKO mice. Ectopic expression of Mettl3 and NPY significantly inhibits microglia activation and neuronal loss in thalamus, and restores the disrupted sleep behavior of cKO mice. Collectively, our study has revealed the critical function of Mettl3-m6A-NPY axis in regulating sleep behavior.

Sleep microstructure in patients with systemic sclerosis: A cyclic alternating pattern analysis study.

The cyclic alternating pattern (CAP) is a cyclic variation of sleep electroencephalogram activity within non-rapid eye movement (non-REM) sleep and increased CAP is the marker of sleep instability. The present study aimed to examine the expression of cyclic alternating pattern in non-REM sleep in patients with systemic sclerosis (SSc) and to compare these findings with the control group. Thirty-one patients with SSc were compared with matched controls by age, gender, body mass index, and apnea-hypopnea index (AHI). Sleep measurements were obtained by standard polysomnography with conventional sleep scoring. A CAP analysis was performed and verified by certified somnologists. The sleep parameters of the SSc and control groups were similar for sleep efficiency, sleep stage percents N1, N2, N3, sleep latency, and minimum oxygen saturation (p = 0.627, p = 0.693, p = 0.530, p = 0.736, p = 0.772, and p = 0.693, respectively). The SSc patients presented a higher arousal and periodic limb movement index. The CAP analyses showed that SSc patients had higher CAP numbers, phase A2 index, A3 duration, and lower A1 duration (p = 0.032, p = 0.016, p = 0.016, and p = 0.016, respectively). Overall the phase A2 index, A2 total time during non-REM sleep were significantly higher and the A1 duration was significantly lower in SSc patients, although sleep efficiency and the distribution of sleep macro-structure seem to be similar to the control group. This study emphasises that microstructure analysis performed with CAP provides information that would otherwise be lost if only macrostructure analysis were considered.

Characterisation of nocturnal arrhythmia avalanche dynamics: Insights from generalised linear model analysis.

Nocturnal arrhythmia avalanche (NAA) episodes, characterised by transient non-sustained cardiac arrhythmias during sleep, have been demonstrated as a predictor of adverse cardiovascular events. However, their dynamics and association with sleep architecture and events remain unclear. While generalised linear models (GLM) have captured sleep-disordered breathing (SDB) dynamics, their application to NAA remains underexplored. This study explored whether changes in sleep architecture contribute to nocturnal arrhythmias and if the impact of sleep stages, SDB, and arousal events on these arrhythmias varies by demographic factors. We analysed 7341 ECG recordings from the multi-ethnic study of atherosclerosis (MESA) and the sleep heart health study (SHHS) datasets. R-R intervals were divided into 10-min periods to detect NAA, defined as a 30% drop from baseline followed by recovery to 90% of baseline. A GLM framework was developed to characterise NAA episodes as functions of SDB, sleep arousal events, sleep stages, and prior NAA episodes. The GLM analysis revealed that NAA occurrence was 18% and 30% higher during non-rapid eye movement (NREM) light sleep compared with deep sleep in SHHS (p < 0.001) and MESA (p < 0.001), respectively. SDB events increased the NAA risk in 34% of participants, and arousals in 29%. In SHHS, the impact of SDB on NAA was 5% greater in men (p = 0.018), while the arousal effects were more pronounced in those over 75, highlighting the role of demographic factors in modulating arrhythmia risk. These findings demonstrate the utility of the GLM framework in modelling the dynamics of nocturnal arrhythmias and their associations with sleep disruptions and architecture.

Open-Source Algorithm for Automated Vigilance State Classification Using Single-Channel Electroencephalogram in Rodents

Accurate identification of sleep stages is essential for understanding sleep physiology and its role in neurological and behavioral research. Manual scoring of polysomnographic data, while reliable, is time-intensive and prone to variability. This study presents a novel Python-based algorithm for automated vigilance state scoring using single-channel electroencephalogram (EEG) recordings from rats and mice. The algorithm employs artifact processing, multi-band frequency analysis, and Gaussian mixture model (GMM)-based clustering to classify wakefulness, non-rapid, and rapid eye movement sleep (NREM and REM sleep, respectively). Combining narrow and broad frequency bands across the delta, theta, and sigma ranges, it uses a majority voting system to enhance accuracy, with tailored preprocessing and voting criteria improving REM detection. Validation on datasets from 10 rats and 10 mice under standard conditions showed sleep–wake state detection accuracies of 92% and 93%, respectively, closely matching manual scoring and comparable to existing methods. REM sleep detection accuracies of 89% (mice) and 91% (rats) align with previously reported (85–90%). Processing a full day of EEG data within several minutes, the algorithm is advantageous for large-scale and longitudinal studies. Its open-source design, flexibility, and scalability make it a robust, efficient tool for automated rodent sleep scoring, advancing research in standard experimental conditions, including aging and sleep deprivation.

Modulation of cardiac autonomic activity across consciousness states and levels of sleep depth in individuals with sleep complaints and bipolar disorder or unipolar depressive disorders

ObjectiveAutonomic nervous system dysfunction and reduced heart rate variability (HRV) often co-exist with mood disorders, a phenomenon likely influenced by sleep disturbances. This study investigated heart rate (HR) and HRV across wake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep in individuals with sleep complaints and bipolar or unipolar depressive disorder. MethodsPolysomnographic data was retrospectively collated for 120 adult patients with sleep complaints and depressive symptoms [60 diagnosed with bipolar disorder, 60 diagnosed with a unipolar depressive disorder], and 60 healthy controls. HR and time-based HRV variables were computed on 30-s segments and averaged across the night for wake, NREM and REM sleep. ResultsSignificant group by consciousness state interactions showed that the unipolar and bipolar groups had lower standard deviation of normal-to-normal intervals root mean square of successive R-R interval differences compared to controls during NREM and REM sleep, but not during wake (SDNN: F(4, 330) = 3.0, p = .021, np2 = 0.035; RMSSD: F(4, 332) = 5.8, p < .001, np2 = 0.065). The magnitude of these group differences did not vary significantly between NREM 1, NREM 2 and NREM 3 sleep. These interactions persisted after excluding individuals taking 3rd generation antipsychotic, lithium, anticonvulsant, and cardiovascular medications. ConclusionAlthough further work is required to account for the impact of psychotropic and cardiac medications, as well as manic and euthymic states, these findings suggest that the sleep-based autonomic signature of depressive states differs across different types of mood disorders and could potentially inform the development of biomarkers and therapeutic targets.

Energy expenditure and slow-wave sleep in runners: Focusing on reproductive function, chronic training, and sex.

This comparative study focused on chronic exercise training, menstrual cycle, menstruation, and sex related with slow-wave sleep and energy expenditure (EE) during sleep in runners and controls. Participants included 26 highly trained runners (9 males, 8 amenorrheic females, and 9 menstruating females) and 20 controls (10males and 10 menstruating females) aged 21± 2 years. Sleeping metabolic rate and EE during slow-wave sleep were 2.7% and 3.9% higher in the luteal than the follicular phase for female runners. Significant interactions were found between the 8-h time course adjusted EE and menstruation, exercise training, and sex. Sleep stage durations did not differ between groups. Interestingly, amenorrheic runners did not suppress sleeping and overnight metabolic rates, suggesting that EE in sleep may not be a causative factor for amenorrhea in runners. This study highlights the complex relationship between chronic exercise, menstrual cycle, and sex on EE during sleep.

The daily reciprocal associations between electroencephalography measured sleep and affect.

Self-report studies show that sleep and positive and negative affect are closely and bidirectionally linked. However, studies assessing sleep objectively yield more inconsistent results. This study assessed the reciprocal, daily relationship between sleep as measured with electroencephalography (EEG) and affect (measured in the evening) in a natural setting. We assessed sleep both on the macrolevel (i.e., rapid eye movement [REM] sleep and slow-wave sleep [SWS] duration) and on the microlevel (i.e., REM sleep fragmentation). In this study, 33 participants (i.e., healthy college students, mean [standard deviation] age 21.55 [3.73] years, 67% female) were followed for 2 weeks. Each participant wore an EEG headband for 15 nights and had polysomnography during 3 of the 15 nights providing 72 analysable nights of polysomnography and 271 analysable nights with the EEG headband. Every evening participants reported their momentary negative and positive affect. We examined the relationship between pre-sleep affect and the sleep variables, as well as the reverse relationship, with sleep variables predicting evening affect the next day. We detected that higher negative affect in the evening was related to more fragmented REM sleep. However, this result was only found with polysomnography and not with the EEG headband. No significant associations were found between affect and time spent in REM sleep and SWS. Overall, no support was found for the reciprocal association between negative and positive affect and EEG measured sleep. Only limited support was found for an association in one direction (i.e., evening negative affect was associated with more REM sleep fragmentation at night).

The influence of transcranial alternating current stimulation on EEG spectral power during subsequent sleep: A randomized crossover study.

To evaluate the instant impact of transcranial alternating current stimulation (tACS) on sleep brain oscillations. Thirty-six healthy subjects were randomly assigned to receive tACS and sham stimulation in a crossover design separated by a one-week washout period. After stimulation, a 2-h nap polysomnography (PSG) was performed to obtain Electroencephalogram (EEG) data and objective sleep variables, and self-reported subjective sleep parameters were collected at the end of the nap. EEG spectral analyses were conducted on the EEG data to obtain the absolute and relative power for each sleep stage during the nap. The associations between power values and objective and subjective measurements were analyzed using Spearman or Pearson correlation coefficients. The tACS group presented higher power in slow wave activity (SWA) and delta frequency bands and lower alpha, sigma and beta power values compared to the sham group during the N2 and N3 sleep stages. SWA and delta power were positively associated with sleep duration and sleep efficiency relevant parameters; while alpha, sigma and beta power were positively associated with prolonged sleep latency and wakefulness related variables. PSG, self-reported and sleep diary measured objective and subjective sleep parameters were comparable between the tACS and the sham groups. Our results support that tACS could promote sleep depth in microstructure of sleep EEG, manifesting as an increase in EEG spectral power in low frequency bands and a decrease in high frequency bands. The registration number of this study is ChiCTR2200063729.

Prolactin in sleep and EEG regulation: New mechanisms and sleep-related brain targets complement classical data.

The role of prolactin in sleep regulation has been the subject of extensive research over the past 50 years, resulting in the identification of multiple, disparate functions for the hormone. Prolactin demonstrated a characteristic circadian release pattern with elevation during dark and diminution during light. High prolactin levels were linked to non-rapid eye movement sleep and electroencephalogram delta activity in humans. Conversely, hyperprolactinemia showed strong correlation with REM sleep in rodent studies. Prolactin may be implicated in the alterations in female sleep patterns observed during the reproductive cycle, it may play a role in the REM sleep enhancement following stress and in sleep-related immunological processes. In conclusion, prolactin appears to have a sleep-promoting role, particularly during the dark phase. However, it does not appear to play a central and coherent role in sleep regulation, as observed in some neuropeptides such as orexin. Conversely, its principal function may be to facilitate situational, yet adaptive, changes in sleep patterns in response to challenging physiological phases, such as those associated with stress, immunological challenges, or the reproductive cycle. Neuronal substrates for prolactin-mediated sleep effects remain unknown; however, recent rodent sleep studies may provide insights into the potential sites of these effects.

An EEG-based single-channel dual-stream automatic sleep staging network with transfer learning

An EEG-based single-channel dual-stream automatic sleep staging network with transfer learning

Temporal Association Cortex Gates Sound-Evoked Arousal from NREM Sleep.

Sound-evoked wakefulness from sleep is crucial in daily life, yet its neural mechanisms remain poorly understood. It is found that CaMKIIα+ neurons in the temporal association cortex (TeA) of mice are not essential for natural awakening from sleep. However, optogenetic activation of these neurons reliably induces wakefulness from non-rapid eye movement (NREM) sleep but not from rapid eye movement (REM) sleep. In vivo electrophysiological and calcium recordings further demonstrated that TeA neurons are monotonically tuned to sound intensity but not frequency. More importantly, it is found that the activity of CaMKIIα+ neurons in TeA can gate sound-evoked arousal from NREM sleep, which is further confirmed by optogenetic manipulations. Further investigation reveals that the baseline excitability of TeA CaMKIIα+ neurons and the delta oscillations in the electroencephalogramare particularly important in regulating the evoked activity of TeA neurons. Anatomical and functional screening of downstream targets of TeA reveals that excitatory projections from TeA glutamatergic neurons to glutamatergic neurons in the basolateral/lateral amygdala are critical for modulating sound-evoked arousal from NREM sleep. These findings uncover a top-down regulatory circuit that selectively governs sound-evoked arousal from NREM sleep, with the TeA functioning as a key connecting cortex to subcortical regions.

Association of Novel EEG Biomarkers of Sleep Depth and Cortical Arousability with Cardiac Autonomic Modulation in Adolescents.

To examine the developmental association of the odds ratio product (ORP), an electroencephalographic measure of sleep depth, during non-rapid eye movement (NREM) sleep with 24-hour heart rate variability (HRV), an electrocardiographic measure of cardiac autonomic modulation (CAM), in the transition to adolescence. Leveraging data from the Penn State Child Cohort, we performed longitudinal analyses on 313 children (median [Md] age 9 years) followed-up after Md=7.4y and cross-sectional analyses on 344 adolescents (Md=16y). We extracted ORP during NREM sleep and in the 9 seconds following cortical arousals (ORP-9) from 9-hour, in-lab polysomnography, and frequency- and time-domain HRV indices from 24-h Holter ECG monitoring. Longitudinal and cross-sectional, multivariable-adjusted, regression models examined the association between ORP and ORP-9 with adolescent 24-h HRV indices. Longitudinally, a greater increase in ORP-9 since childhood was associated with lower daytime Log-LF, SDNN, RMSSD and higher HR in adolescence (p<0.05). A greater increase in ORP since childhood was associated with lower nighttime Log-LF and SDNN (p<0.05). Cross-sectionally, higher ORP and ORP-9 were associated with lower daytime and nighttime Log-LF, SDNN or RMSSD and higher HR within adolescence (p<0.05). A greater increase in cortical arousability since childhood is a strong developmental predictor of daytime cardiac autonomic imbalance in adolescence. Shallower sleep depth additionally arises as a proximal determinant of both daytime and nighttime cardiac autonomic imbalance within adolescence. These data suggest a coupling between fine-grained spectral measures of the sleeping brain and those of CAM, which may inform sleep-related cardiovascular risk early in life.

Sleep stage, sleep fragmentation and heart rate variability during the initial 3-h sleep period in patients with obstructive sleep apnea syndrome

Sleep stage, sleep fragmentation and heart rate variability during the initial 3-h sleep period in patients with obstructive sleep apnea syndrome

Associations between objectively measured sleep characteristics and 6-minute walk distance in older adults: the Disparities in Sleep and Cognitive Outcomes (DISCO) study.

Decline in physical functioning in older adults has been associated with higher risk of chronic diseases. Subjective sleep disturbances have been associated with declines in physical functioning with aging. We examined the association between objectively measured sleep characteristics and 6-minute walk distance, a marker of functional capacity, in a sample of older adults. This analysis included 199 participants who were enrolled in the Disparities in Sleep and Cognitive Outcomes (DISCO) study, a longitudinal cohort of older adults aged ≥55 years. Exposures included: sleep duration, sleep percentage, sleep fragmentation, and sleep regularity index measured using 7 days of wrist actigraphy; sleep stages including non-REM stage 3 (N3) and REM, and apnea-hypopnea index (AHI) measured using an overnight type 2 home polysomnography. The primary outcome was the total distance walked in 6-minutes (6MWD). Multiple linear regression was used for analysis. Mean age of participants was 67.6 (SD=6.3) years (range 55-84 years), 69.3% were women, 62.3% were White and 84.4% were non-Hispanic. The average 6MWD was 476.0 (SD=95.6) meters. In adjusted models (B [95% CI]), higher sleep percentage (2.65 [0.22,5.08] percent) and greater sleep regularity (1.03 [0.0047, 2.05] units) were associated with higher 6MWD. Greater sleep fragmentation was associated with lower 6MWD (-2.56 [-4.02, -1.10] percent). Sleep duration, N3, REM, and AHI were not associated with 6MWD. Poorer objective sleep quality and irregular sleep were associated with poorer functional capacity in older adults. Future work should test whether improving sleep quality and regularity improves physical functioning and overall health in older adults.

The UNICA sleep HRV analysis tool: an integrated open-source tool for heart rate variability analysis during sleep

Heart rate variability (HRV) analysis during sleep plays a key role for understanding autonomic nervous system function and assessing cardiovascular health. The UNICA Sleep HRV analysis (UNICA-HRV) tool is a novel, open-source MATLAB tool designed to fill the gap in current HRV analysis tools. In particular, the integration of ECG and HRV data with hypnogram information, which illustrates the progression through the different sleep stages, eases the computation of HRV metrics in polysomnographic recordings. This integration is crucial for accurate phase-specific analysis, as autonomic regulation changes markedly across different sleep stages. The tool supports single- and multiple-subject analyses and is tailored to enhance usability and accessibility for researchers and clinicians without requiring extensive technical expertise. It implements and supports a variety of data inputs and configurations, allowing for flexible, detailed HRV analyses across sleep stages, employing classical and advanced metrics, such as time-domain, frequency-domain, non-linear, complexity, and Poincaré plot indexes. Validation of the tool against established tools like Kubios and PhysioZoo indicates its robustness and precision in generating reliable HRV metrics, that are essential not only for sleep research, but also for clinical diagnostics. The introduction of UNICA-HRV represents a significant simplification for sleep studies, and its open-source nature (licensed under a Creative Commons Attribution 4.0 International License) allows to easily extend the functionality to other needs.