Macro and micro sleep architecture and cognitive performance in older adults

Day-night hyperarousal in tinnitus patients

Tinnitus, which affects 12-30 % of the population, is associated with sleep disturbances and daytime dysfunction, yet the neural mechanisms that link wake-up states remain unclear. This study investigated electroencephalographic (EEG) characteristics of 51 tinnitus patients and 51 controls across wakefulness (eyes-open, eyes-closed, mental arithmetic) and sleep stages (N1, N2, N3, REM) to clarify day-night pathological mechanisms. The key findings showed persistent hyperarousal in tinnitus: wakefulness revealed enhanced gamma power (30-45 Hz) in eyes-closed and task states, while sleep demonstrated elevated gamma/beta power across all stages accompanied by reduced delta/theta power in deep sleep (N2/N3).). An analysis of sleep structure indicates impaired stability in maintaining the N2 stage among tinnitus patients, corroborating a reduction in N3 duration and an increased proportion of the N2 stage. From the wake states to the sleep stages, group × state interactions for the delta/theta power suggest an impaired state regulation capacity in tinnitus patients. Correlation clustering further revealed aberrant integration of wake-related gamma/beta activity into non-rapid eye movement sleep, indicating neuroplastic overgeneralization of wake hyperarousal into sleep. These results extend the so-called loss-of-inhibition theory to sleep, proposing that deficient low-frequency oscillations fail to suppress hyperarousal, impairing sleep-dependent neuroplasticity, and perpetuating daytime symptoms. Furthermore, this study establishes sleep as a critical therapeutic target to interrupt the 24-h dysfunctional cycle of tinnitus.

Association between objectively measured, multidimensional sleep health and cognitive function in older adults: cross-sectional wearable tracker study

Both sleep and cognition are multidimensional constructs. Using univariate methods to examine associations between sleep and cognition may inadequately characterize the association between these arrays of variables. The current study used a multivariate approach to identify key sleep metrics and cognitive domains contributing to the maximum sleep-cognition covariance in healthy older adults. In 773 community-dwelling older adults of ages 65-80 years, sleep was assessed using the Oura Ring worn for 15-28 days. Cognition performance in seven domains was assessed using standardized tests. The overall covariance between sleep and cognition was examined by a partial least square correlation (PLSC) analysis. Sleep metrics and cognitive domains contributing to significant PLSC components were identified by bootstrapping. PLSC analysis identified a component that explained 82 % of covariance between sleep and cognition matrices (r = 0.2, p < 0.001). Bootstrapping tests further identified 11 sleep continuity and regularity metrics and 3 corresponding cognitive domains that contributed significantly to the observed covariance. Post-hoc univariate analyses showed that sleep continuity metrics correlated with speed of processing, while sleep regularity metrics correlated with verbal memory, executive functions, and speed of processing. Our results suggest that sleep continuity and regularity may be more sensitive markers of impairments across multiple cognitive domains in healthy aging compared to sleep duration and timing.

Sleep timing, sleep timing regularity, and cognitive performance in women entering late adulthood: the Study of Women's Health Across the Nation (SWAN)

STUDY OBJECTIVES

This study examined whether sleep timing and its regularity are associated with cognitive performance in older women and whether associations vary based on cardiometabolic risk factors.

METHODS

The cross-sectional analysis included 1177 community-dwelling females (mean age 65 years) from the observational Study of Women's Health Across the Nation (SWAN) annual visit 15. Sleep timing (mean midpoint from sleep onset to wake-up) and its regularity (standard deviation of midpoint) were assessed using actigraphy. Cognitive measures included immediate and delayed verbal memory, working memory, and processing speed. Cardiometabolic risk measures included central obesity, hypertension, diabetes, and the Atherosclerotic Cardiovascular Disease (ASCVD) risk score. Linear regression models, adjusted for covariates, tested associations between sleep and cognitive measures.

RESULTS

After covariate adjustment, early sleep timing was associated with worse delayed verbal memory (β = -0.37; p = .047) and late sleep timing was associated with worse processing speed (β = -1.80; p = .008). Irregular sleep timing was associated with worse immediate (β = -0.29; p = .020) and delayed verbal memory (β = -0.36; p = .006), and better working memory (β = 0.50; p = .004). Associations between early sleep timing and delayed verbal memory strengthened as ASCVD risk increased (interaction β = -8.83, p = .026), and sleep timing irregularity's effect on working memory was stronger among women with hypertension (interaction β = -3.35, p = .039).

CONCLUSIONS

Sleep timing and its regularity are concurrently associated with cognitive performance in older women. Cardiovascular disease risk may modify some of these associations. Future longitudinal studies are needed to clarify these relationships.

Threshold Values of Sleep Spindles Features in Healthy Adults Using Scalp-EEG and Associations With Sleep Parameters

OBJECTIVE

Sleep spindles are an electrophysiological fingerprint of the sleeping human brain. They can be described in terms of duration, frequency, amplitude, and density, and vary widely according to age and sex. Spindles play a role in sleep and wake functions and are altered in several neurological and psychiatric disorders. This study established the first threshold values for sleep spindles in healthy adults using scalp-EEG and explored their associations with other sleep parameters.

METHODS

This observational prospective study was conducted with 80 healthy participants stratified by age and sex (40.9 years, range 19-74, 50% females). All participants underwent in-laboratory polysomnography. Sleep spindles during N2 were analyzed using an automated procedure and categorized as fast (> 13 Hz) or slow (≤ 13 Hz).

RESULTS

For fast spindles, the threshold values were duration (0.80-1.11 s), frequency (13.4-14.3 Hz), amplitude (5.2-15.2 μV), and density (1.0-5.8 spindles/min). For slow spindles, the values were duration (0.79-1.17 s), frequency (12.3-12.9 Hz), amplitude (4.1-13.2 μV), and density (0.03-3.15 spindles/min). From age 40 onwards, the density, amplitude, and duration of both types of spindles decreased; the amplitudes of both types of spindles were higher in females. Higher amplitude in fast spindles was associated with increased excessive daytime sleepiness and an increased proportion of slow-wave sleep.

INTERPRETATION

This study provides the first threshold values for sleep spindle characteristics in healthy adults. The findings emphasize the importance of investigating spindles to develop innovative biomarkers for neurological and psychiatric disorders and to gain deeper insights into the functioning of the sleeping brain.

Influence of sleep and cardiovascular health on cognitive trajectories in older adults

Age-related changes in sleep have been associated with cognitive decline, yet causal pathways have not been identified. Evidence suggests reduced cardiovascular health may be a consequence of poor sleep and a precursor to cognitive decline. This observational cohort study used path analyses to determine whether cardiovascular disease risk mediated or moderated effects of sleep on yearly longitudinal change in cognition, estimated with linear growth models. Total sleep time (TST), sleep efficiency (SE), and relative spectral power of slow wave activity (SWA; 1-4 Hz) and slow oscillations (SO; 0.5-1 Hz), were measured with single-channel home EEG. Cardiovascular disease risk (CVR) was estimated as 10-year Framingham Risk Score 1-year post-sleep. Outcomes were yearly change in executive function (EF), episodic memory (EM), and processing speed (PS) over 2-5 years post-sleep. 342 participants (mean age 73.5 +/- 5.6 years, 51 % female) were included. Shorter TST was linearly associated with increased CVR across all models (βs = -0.18(0.058) - -0.19(0.059), ps< 0.002). TST was indirectly associated with EF and PS decline through CVR, such that associations between short TST and cognitive decline were partially due to higher CVR. All other mediating and moderating effects were nonsignificant after multiple comparisons. Indirect associations between short sleep duration and greater decline in executive function and processing speed were found through higher CVR, suggesting a potential mechanism by which sleep leads to cognitive decline. Findings support the prioritization of adequate sleep duration to preserve both cardiovascular and cognitive health in later life.

Mapping the Relationships Between Structural Brain MRI Characteristics and Sleep EEG Patterns: The Multi-Ethnic Study of Atherosclerosis

While brain morphology is well-established as a key factor influencing overall brain function, little is known about how brain structural properties are associated with oscillatory activity, particularly during sleep. In this study, we analyzed whole-night sleep EEG and brain structural MRI data from a subset of 621 individuals in the Multi-Ethnic Study of Atherosclerosis to explore the relationship between brain structure and sleep EEG properties. We found that larger total white matter (WM) volume was associated with higher absolute broad-band power, regardless of sleep stage, likely reflecting WM contribution to enhanced synchronization across cortical regions and reduced activation attenuation via long-range myelinated fibers. Additionally, both WM fractional anisotropy and thalamus volume showed negative association with relative slow power and positive association with delta power during non-rapid eye movement sleep. This was mirrored in the duration of slow oscillations (SOs), both overall and when divided into slow-switching and fast-switching types, with their ratio additionally linked to total WM volume. Furthermore, we observed strong but largely independent effects of age and sex on sleep EEG and structural MRI metrics, suggesting that sleep EEG captures aging processes and sex-specific features that extend beyond the macro-scale brain morphology changes examined here. Overall, these findings deepen our understanding of how structural brain properties influence sleep-related oscillatory activity.

Impact of spindle-inspired transcranial alternating current stimulation during a nap on sleep-dependent motor memory consolidation in healthy older adults

With the increase in life expectancy and the rapid evolution of daily life technologies, older adults must constantly learn new skills to adapt to society. Sleep reinforces skills acquired during the day and is associated with the occurrence of specific oscillations such as spindles. However, with age, spindles deteriorate and thus likely contribute to memory impairments observed in older adults. The application of electric currents by means of transcranial alternating current stimulation (tACS) with spindle-like waveform, applied during the night, was found to enhance spindles and motor memory consolidation in young adults. Here, we tested whether tACS bursts inspired by spindles applied during daytime naps may (i) increase spindle density and (ii) foster motor memory consolidation in older adults. Twenty-six healthy older participants performed a force modulation task at 10:00, were retested at 16:30, and the day after the initial training. They had 90-minute opportunity to take a nap while verum or placebo spindle-inspired tACS bursts were applied with similar temporal parameters to those observed in young adults and independently of natural spindles, which are reduced in the elderly. We show that the density of natural spindles correlates with the magnitude of memory consolidation, thus confirming that spindles are promising physiological targets for enhancing memory consolidation in older adults. However, spindle-inspired tACS, as used in the present study, did not enhance either spindles or memory consolidation. We therefore suggest that applying tACS time-locked to natural spindles might be required to entrain them and improve their related functions.

Mechanistic insights into the interaction between epilepsy and sleep

Epidemiological evidence has demonstrated associations between sleep and epilepsy, but we lack a mechanistic understanding of these associations. If sleep affects the pathophysiology of epilepsy and the risk of seizures, as suggested by correlative evidence, then understanding these effects could provide crucial insight into the basic mechanisms that underlie the development of epilepsy and the generation of seizures. In this Review, we provide in-depth discussion of the associations between epilepsy and sleep at the cellular, network and system levels and consider the mechanistic underpinnings of these associations. We also discuss the clinical relevance of these associations, highlighting how they could contribute to improvements in the management of epilepsy. A better understanding of the mechanisms that govern the interactions between epilepsy and sleep could guide further research and the development of novel approaches to the management of epilepsy.

Artificial Intelligence Can Drive Sleep Medicine

This article explores the transformative role of artificial intelligence (AI) in sleep medicine, highlighting its applications in detecting sleep microstructure patterns and integrating novel metrics. AI enhances diagnostic accuracy and objectivity, addressing inter-rater variability. AI also facilitates the classification of sleep disorders and the prediction of health outcomes. AI can drive sleep medicine to achieve deeper insights into sleep's impact on health, leading to personalized treatment strategies and improved patient care.

The prevalence and risk factors of sleep disturbances in community-dwelling older adults: a systematic review and meta-analysis

PURPOSE

Sleep disturbance is one of the most prevalent health issues among community-dwelling older adults. This systematic review aims to assess the prevalence of sleep disturbances among these adults living in the community and identify associated risk factors.

METHODS

A comprehensive literature search was performed using PubMed, Web of Science, Embase, and the Cochrane Library databases. We screened studies focusing on the prevalence of sleep disturbances in community-dwelling older adults (≥ 60 years). A random-effects model was used to calculate the pooled prevalence of sleep disturbances. Sensitivity and subgroup analyses were conducted to investigate sources of heterogeneity, and funnel plots were used to assess publication bias.

RESULTS

Our systematic review included 41 articles, encompassing a total sample of 71,607 participants from 13 countries. The pooled prevalence of sleep disturbances, measured by PSQI, was found to be 45% (95% CI: 40-50%). Notably, the prevalence of sleep disturbances was significantly higher among individuals aged 70 years and older (48%) compared to those aged 60 years and older (41%). Common risk factors for sleep disturbances included depression, advanced age, females, chronic diseases (hypertension, coronary heart disease, chronic obstructive pulmonary disease) and poor external support (poor social support and poor family relationships).

CONCLUSION

The findings highlight the necessity for comprehensive assessments and management strategies targeting this population with depression, advanced age, females, hypertension, coronary heart disease, chronic obstructive pulmonary disease, and poor external support while also underscoring the significance of healthcare planners and policymakers in enhancing sleep quality for older adults.

Comparing Manual and Automatic Artifact Detection in Sleep EEG Recordings

Sleep electroencephalogram (EEG) recordings can be contaminated by artifacts. Visual and automatic methods have been developed to mark such erroneous segments of EEG data. Here, we systematically explored the effect of artifacts on the sleep EEG power spectrum density (PSD), and we compared gold-standard visual detections to a simple automatic detector using Hjorth parameters to identify artifacts. We found that most distortions in the all-night average PSD occur because of a small minority of highly anomalous artifacts, which mainly affect the beta and gamma frequency ranges and NREM delta. Visual and automatic detections only showed moderate agreement in which data segments are artifactual. However, the resulting all-night average PSD is highly similar across all methods, and PSDs calculated with all methods successfully recover the known correlations of PSD with age and sex. No parameter settings of the automatic detector clearly outperformed others. Additionally, we showed that accurate average PSD estimates can be recovered from just a fraction of available data epochs. Our results suggest that artifacts represent a minor and easily solvable problem in sleep EEG recordings. Most visually identified artifacts do not seriously distort estimates of mid-frequency activity in the sleep EEG spectrum, and distortions to low and high frequencies can be eliminated using a simple automatic detection method nearly as well as with visual detections. These findings show that the visual inspection of EEG data is not necessary to eliminate the effects of artifacts, which is encouraging for the expected performance of automatic preprocessing in large sleep EEG databases.

Hyperarousal features in the sleep architecture of individuals with and without insomnia

Sleep architecture encodes relevant information on the structure of sleep and has been used to assess hyperarousal in insomnia. This study investigated whether polysomnography-derived sleep architecture displays signs of hyperarousal in individuals with insomnia compared with individuals without insomnia. Data from Phase 3 clinical trials, private clinics and a cohort study were analysed. A comprehensive set of sleep architecture features previously associated with hyperarousal were retrospectively analysed focusing on sleep-wake transition probabilities, electroencephalographic spectra and sleep spindles, and enriched with a novel machine learning algorithm called the Wake Electroencephalographic Similarity Index. This analysis included 1710 individuals with insomnia and 1455 individuals without insomnia. Results indicate that individuals with insomnia had a higher likelihood of waking from all sleep stages, and showed increased relative alpha during Wake and N1 sleep and increased theta power during Wake when compared with individuals without insomnia. Relative delta power was decreased and Wake Electroencephalographic Similarity Index scores were elevated across all sleep stages except N3, suggesting more wake-like activity during these stages in individuals with insomnia. Additionally, sleep spindle density was decreased, and spindle dispersion was increased in individuals with insomnia. These findings suggest that insomnia is characterized by a dysfunction in sleep quality with a continuous hyperarousal, evidenced by changes in sleep-wake architecture.

Association between sleep microarchitecture and cognition in obstructive sleep apnea

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) increases the risk of cognitive impairment. Measures of sleep microarchitecture from EEG may help identify patients at risk of this complication.

METHODS

Participants with suspected OSA (n = 1142) underwent in-laboratory polysomnography and completed sleep and medical history questionnaires, and tests of global cognition (Montreal Cognitive Assessment, MoCA), memory (Rey Auditory Verbal Learning Test, RAVLT) and information processing speed (Digit-Symbol Coding, DSC). Associations between cognitive scores and stage 2 non-rapid eye movement (NREM) sleep spindle density, power, frequency and %-fast (12-16Hz), odds-ratio product (ORP), normalized EEG power (EEGNP), and the delta:alpha ratio were assessed using multivariable linear regression (MLR) adjusted for age, sex, education, and total sleep time. Mediation analyses were performed to determine if sleep microarchitecture indices mediate the negative effect of OSA on cognition.

RESULTS

All spindle characteristics were lower in participants with moderate and severe OSA (p ≤ .001, vs. no/mild OSA) and positively associated with MoCA, RAVLT, and DSC scores (false discovery rate corrected p-value, q ≤ 0.026), except spindle power which was not associated with RAVLT (q = 0.185). ORP during NREM sleep (ORPNREM) was highest in severe OSA participants (p ≤ .001) but neither ORPNREM (q ≥ 0.230) nor the delta:alpha ratio were associated with cognitive scores in MLR analyses (q ≥ 0.166). In mediation analyses, spindle density and EEGNP (p ≥ .048) mediated moderate-to-severe OSA's negative effect on MoCA scores while ORPNREM, spindle power, and %-fast spindles mediated OSA's negative effect on DSC scores (p ≤ .018).

CONCLUSIONS

Altered spindle activity, ORP and normalized EEG power may be important contributors to cognitive deficits in patients with OSA.

The effectiveness of exercise interventions targeting sleep in older adults with cognitive impairment or Alzheimer's disease and related dementias (AD/ADRD): A systematic review and meta-analysis

Sleep loss is associated with reduced health and quality of life, and increased risk of Alzheimer's disease and related dementias. Up to 66% of persons with Alzheimer's disease and related dementias experience poor sleep, which can predict or accelerate the progression of cognitive decline. Exercise is a widely accessible intervention for poor sleep that can protect against functional and cognitive decline. No previous systematic reviews have investigated the effectiveness of exercise for sleep in older adults with mild cognitive impairment or Alzheimer's disease and related dementias. We systematically reviewed controlled interventional studies of exercise targeting subjectively or objectively (polysomnography/actigraphy) assessed sleep in persons with mild cognitive impairment or Alzheimer's disease and related dementias. We conducted searches in PubMed, Embase, Scopus and Cochrane-Library (n = 6745). Nineteen randomised and one non-randomised controlled interventional trials were included, representing the experiences of 3278 persons with mild cognitive impairment or Alzheimer's disease and related dementias. Ten had low-risk, nine moderate-risk, and one high-risk of bias. Six studies with subjective and eight with objective sleep outcomes were meta-analysed (random-effects model). We found moderate- to high-quality evidence for the beneficial effects of exercise on self-reported and objectively-measured sleep outcomes in persons with mild cognitive impairment or Alzheimer's disease and related dementias. However, no studies examined key potential moderators of these effects, such as sex, napping or medication use. Our results have important implications for clinical practice. Sleep may be one of the most important modifiable risk factors for a range of health conditions, including cognitive decline and the progression of Alzheimer's disease and related dementias. Given our findings, clinicians may consider adding exercise as an effective intervention or adjuvant strategy for improving sleep in older persons with mild cognitive impairment or Alzheimer's disease and related dementias.

Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography

Objective.Obstructive sleep apnea (OSA) is associated with deficits in vigilance. This work explored the temporal patterns of OSA-related events during sleep and vigilance levels measured by the psychomotor vigilance test (PVT) in patients undergoing polysomnography (PSG) for suspected OSA.Approach.The PVT was conducted prior to in-laboratory PSG for 80 patients suspected of having OSA. Three groups were formed based on PVT-RT-outcomes and participants were randomly allocated into Training (n= 55) and Test (n= 25) samples. Sleep epochs of non-rapid-eye movement (NREM) electroencephalographic (EEG) asynchrony data, and REM and NREM data for respiratory, arousal, limb movement and desaturation events were analysed. The data were segmented by sleep stage, by sleep blocks (SB) of stable Stage N2, Stage N3, mixed-stage NREM sleep (NXL), and, by Time of Night (TN) across sleep. Models associating this data with PVT groups were developed and tested.Main Results.Amodel using NREM EEG asynchrony data segmented by SB and TN achieved 81.9% accuracy in the Test Cohort. Models based on interhemispheric asynchrony SB data and OSA data segmented by TN achieved 80.6% and 79.5% respectively.Significance.Novel data segmentation methods via blocks of NXL and TN have improved our understanding of the relationship between sleep, OSA and vigilance.

Sleep macro-architecture and dementia risk in adults: Meta-analysis of 5 cohorts from the Sleep and Dementia Consortium

Study objectives

Poor sleep may play a role in the risk of dementia. However, few studies have investigated the association between polysomnography (PSG)-derived sleep architecture and dementia incidence. We examined the relationship between sleep macro-architecture and dementia incidence across five US-based cohort studies from the Sleep and Dementia Consortium (SDC).

Methods

Percent of time spent in stages of sleep (N1, N2, N3, REM sleep), wake after sleep onset and sleep maintenance efficiency were derived from a single night home-based PSG. Dementia was ascertained in each cohort using its cohort-specific criteria. Each cohort performed Cox proportional hazard regressions for each sleep exposure and incident dementia, adjusting for age, sex, body mass index, anti-depressant use, sedative use, and APOE e4 status. Results were then pooled in random effects meta-analyses.

Results

The pooled sample comprised 4,657 participants (30% women) aged ≥60 years (mean age was 74 years at sleep assessment). There were 998 (21.4%) dementia cases (median follow-up time of 5 to 19 years). Pooled effects of the five cohorts showed no association between sleep architecture and incident dementia. When meta-analyses were restricted to the three cohorts which had dementia case ascertainment based on DSM-IV/V criteria (n=2,374), higher N3% was marginally associated with an increased risk of dementia (HR: 1.06; 95%CI: 1.00-1.12, per percent increase N3, p=0.050).

Conclusions

There were no consistent associations between sleep macro-architecture measured and the risk of incident dementia. Implementing more nuanced sleep metrics remains an important next step for uncovering more about sleep-dementia associations.

Associations between longitudinal changes in sleep stages and risk of cognitive decline in older men

STUDY OBJECTIVES

To investigate the relationships between longitudinal changes in sleep stages and the risk of cognitive decline in older men.

METHODS

This study included 978 community-dwelling older men who participated in the first (2003-2005) and second (2009-2012) sleep ancillary study visits of the Osteoporotic Fractures in Men Study. We examined the longitudinal changes in sleep stages at the initial and follow-up visits, and the association with concurrent clinically relevant cognitive decline during the 6.5-year follow-up.

RESULTS

Men with low to moderate (quartile 2, Q2) and moderate increase (Q3) in N1 sleep percentage had a reduced risk of cognitive decline on the modified mini-mental state examination compared to those with a substantial increase (Q4) in N1 sleep percentage. Additionally, men who experienced a low to moderate (Q2) increase in N1 sleep percentage had a lower risk of cognitive decline on the Trails B compared with men in the reference group (Q4). Furthermore, men with the most pronounced reduction (Q1) in N2 sleep percentage had a significantly higher risk of cognitive decline on the Trails B compared to those in the reference group (Q4). No significant association was found between changes in N3 and rapid eye movement sleep and the risk of cognitive decline.

CONCLUSIONS

Our results suggested that a relatively lower increase in N1 sleep showed a reduced risk of cognitive decline. However, a pronounced decrease in N2 sleep was associated with concurrent cognitive decline. These findings may help identify older men at risk of clinically relevant cognitive decline.

Louis EK, McCarter SJ, Bukartyk J, Przybelski SA, Kamykowski MG, Spychalla AJ, Machulda MM, Boeve BF, Petersen RC, Jack CR, Lowe VJ, Graff-Radford J, Worrell GA, Somers VK, Varga AW, Vemuri P. Non-rapid eye movement sleep slow-wave activity features are associated with amyloid accumulation in older adults with obstructive sleep apnoea

Obstructive sleep apnoea (OSA) is associated with an increased risk for cognitive impairment and dementia, which likely involves Alzheimer's disease pathology. Non-rapid eye movement slow-wave activity (SWA) has been implicated in amyloid clearance, but it has not been studied in the context of longitudinal amyloid accumulation in OSA. This longitudinal retrospective study aims to investigate the relationship between polysomnographic and electrophysiological SWA features and amyloid accumulation. From the Mayo Clinic Study of Aging cohort, we identified 71 participants ≥60 years old with OSA (mean baseline age = 72.9 ± 7.5 years, 60.6% male, 93% cognitively unimpaired) who had at least 2 consecutive Amyloid Pittsburgh Compound B (PiB)-PET scans and a polysomnographic study within 5 years of the baseline scan and before the second scan. Annualized PiB-PET accumulation [global ΔPiB(log)/year] was estimated by the difference between the second and first log-transformed global PiB-PET uptake estimations divided by the interval between scans (years). Sixty-four participants were included in SWA analysis. SWA was characterized by the mean relative spectral power density (%) in slow oscillation (SO: 0.5-0.9 Hz) and delta (1-3.9 Hz) frequency bands and by their downslopes (SO-slope and delta-slope, respectively) during the diagnostic portion of polysomnography. We fit linear regression models to test for associations among global ΔPiB(log)/year, SWA features (mean SO% and delta% or mean SO-slope and delta-slope), and OSA severity markers, after adjusting for age at baseline PiB-PET, APOE ɛ4 and baseline amyloid positivity. For 1 SD increase in SO% and SO-slope, global ΔPiB(log)/year increased by 0.0033 (95% CI: 0.0001; 0.0064, P = 0.042) and 0.0069 (95% CI: 0.0009; 0.0129, P = 0.026), which were comparable to 32% and 59% of the effect size associated with baseline amyloid positivity, respectively. Delta-slope was associated with a reduction in global ΔPiB(log)/year by -0.0082 (95% CI: -0.0143; -0.0021, P = 0.009). Sleep apnoea severity was not associated with amyloid accumulation. Regional associations were stronger in the pre-frontal region. Both slow-wave slopes had more significant and widespread regional associations. Annualized PiB-PET accumulation was positively associated with SO and SO-slope, which may reflect altered sleep homeostasis due to increased homeostatic pressure in the setting of unmet sleep needs, increased synaptic strength, and/or hyper-excitability in OSA. Delta-slope was inversely associated with PiB-PET accumulation, suggesting it may represent residual physiological activity. Further investigation of SWA dynamics in the presence of sleep disorders before and after treatment is necessary for understanding the relationship between amyloid accumulation and SWA physiology.

Attention and executive function impairments in obstructive sleep apnea are associated with decreased sleep spindles

INTRODUCTION

Sleep spindles play a key role in sleep-mediated cognitive processes. Cognitive functions are well-known to be affected in obstructive sleep apnea (OSA). Here, we analyzed attention and executive functions in patients with OSA and investigated the relationship between sleep spindles and cognitive abilities.

METHODS

Sixty patients with OSA (18-65 years, 19 females and 41 males) and a control group (n = 41) including age-and sex-matched healthy individuals were consecutively and prospectively enrolled. All participants had a full-night polysomnography, and sleep spindles were analyzed using a semi-automated program. For the evaluation of short-term memory, attention and executive functions, Stroop test, forward and backward digit span tests were applied to all participants upon awakening following polysomnography.

RESULTS

Scores of forward and backward digit span and Stroop tests were worse in OSA patients in compared to those in controls. Mean density of sleep spindles was decreased in OSA patients than those in controls (p = 0.044). A positive correlation was found between fast sleep spindle frequency and forward digit span (r = 2.222; p = 0.038) and backward digit span test scores (r = 2,157; p = 0.042) in OSA patients. In patients with moderate to severe OSA, sleep spindle density was positively correlated with forward (r = 2.323, p = 0.029) and backward (r = 2.500, p = 0.016) DSTs, and the duration of sleep spindles had positive correlation with backward DST (r = 2.452, p = 0.010).

CONCLUSION

Our findings demonstrated that the disturbances in sleep spindle characteristics in OSA are associated with the cognitive impairments in attention, short-term memory, and executive functions, especially in patients with moderate to severe OSA.

Age-related changes in sleep spindle characteristics in individuals over 75 years of age: a retrospective and comparative study

BACKGROUND

Sleep and its architecture are affected and changing through the whole lifespan. We know main modifications of the macro-architecture with a shorter sleep, occurring earlier and being more fragmented. We have been studying sleep micro-architecture through its pathological modification in sleep, psychiatric or neurocognitive disorders whereas we are still unable to say if the sleep micro-architecture of an old and very old person is rather normal, under physiological changes, or a concern for a future disorder to appear. We wanted to evaluate age-related changes in sleep spindle characteristics in individuals over 75 years of age compared with younger individuals.

METHODS

This was an exploratory study based on retrospective and comparative laboratory-based polysomnography data registered in the normal care routine for people over 75 years of age compared to people aged 65-74 years. We were studying their sleep spindle characteristics (localization, density, frequency, amplitude, and duration) in the N2 and N3 sleep stages. ANOVA and ANCOVA using age, sex and OSA were applied.

RESULTS

We included 36 participants aged > 75 years and 57 participants aged between 65 and 74 years. An OSA diagnosis was most common in both groups. Older adults receive more medication to modify their sleep. Spindle localization becomes more central after 75 years of age. Changes in the other sleep spindle characteristics between the N2 and N3 sleep stages and between the slow and fast spindles were conformed to literature data, but age was a relevant modifier only for density and duration.

CONCLUSION

We observed the same sleep spindle characteristics in both age groups except for localization. We built our study on a short sample, and participants were not free of all sleep disorders. We could establish normative values through further studies with larger samples of people without any sleep disorders to understand the modifications in normal aging and pathological conditions and to reveal the predictive biomarker function of sleep spindles.

Development and validation of a novel sleep health score in the sleep heart health study

BACKGROUND

There is a lack of consensus in evaluating multidimensional sleep health, especially concerning its implication for mortality. A validated multidimensional sleep health score is the foundation of effective interventions.

METHODS

We obtained data from 5706 participants in the Sleep Heart Health Study. First, random forest-recursive feature elimination algorithm was used to select potential predictive variables. Second, a sleep composite score was developed based on the regression coefficients from a Cox proportional hazards model evaluating the associations between selected sleep-related variables and mortality. Last, we validated the score by constructing Cox proportional hazards models to assess its association with mortality.

RESULTS

The mean age of participants was 63.2 years old, and 47.6% (2715/5706) were male. Six sleep variables, including average oxygen saturation (%), spindle density (C3), sleep efficiency (%), spindle density (C4), percentage of fast spindles (%) and percentage of rapid eye movement (%) were selected to construct this multidimensional sleep health score. The average sleep composite score in participants was 6.8 of 22 (lower is better). Participants with a one-point increase in sleep composite score had an 10% higher risk of death (hazard ratio = 1.10, 95% confidence interval: 1.08-1.12).

CONCLUSIONS

This study constructed and validated a novel multidimensional sleep health score to better predict death based on sleep, with significant associations between sleep composite score and all-cause mortality. Integrating questionnaire information and sleep microstructures, our sleep composite score is more appropriately applied for mortality risk stratification.

Associations between sleep duration trajectories and cognitive decline: A longitudinal cohort study in China

OBJECT

The relationship between sleep duration trajectories and cognitive decline remains uncertain. This study aims to examine the connections between various patterns of sleep duration and cognitive function.

METHODS

Group-based trajectory modeling (GBTM) was employed to identify longitudinal trajectories of sleep duration over four-year follow-up period, while considering age, sex and nap duration as adjustments. Logistic regression was utilized to analyze the association between sleep trajectories and cognition, with odds ratios (OR) and 95 % confidence intervals (CI) reported. Subgroup analyses based on various demographic characteristics were conducted to explore potential differences in sleep trajectories and cognitive decline across different population subgroups.

RESULTS

A total of 5061 participants were followed for four years, and three sleep duration trajectories were identified: high increasing (n = 2101, 41.6 %), stable increasing (n = 2087, 40.7 %), and low decreasing (n = 873, 17.7 %). After adjustment for basic demographic information, health status, and baseline cognition, the high increasing trajectory was found to be associated with cognitive decline in terms of global cognition (OR:1.52,95 %CI:1.18-1.96), mental intactness (OR:1.36,95 %CI:1.07-1.73) and episodic memory (OR:1.33, 95 %CI:1.05-1.67), as compared to stable increasing trajectory. These associations were particularly prominent among the non-elderly population (≤65 years) and those without depressive symptoms.

CONCLUSION

This study suggests that both high increasing and low decreasing sleep duration trajectories are linked to cognitive decline, as compared to the stable increasing trajectory. Long-term attention to changes in sleep duration facilitates early prevention of cognitive decline.

ANPHY-Sleep: an Open Sleep Database from Healthy Adults Using High-Density Scalp Electroencephalogram

Well-documented sleep datasets from healthy adults are important for sleep pattern analysis and comparison with a wide range of neuropsychiatric disorders. Currently, available sleep datasets from healthy adults are acquired using low-density arrays with a minimum of four electrodes in a typical sleep montage. The low spatial resolution is thus prohibitive for the analysis of the spatial structure of sleep. Here we introduce an open-access sleep dataset from 29 healthy adults (13 female, aged 32.17 ± 6.30 years) acquired at the Montreal Neurological Institute. The dataset includes overnight polysomnograms with high-density scalp electroencephalograms incorporating 83 electrodes, electrocardiogram, electromyogram, electrooculogram, and an average of electrode positions using manual co-registrations and sleep scoring annotations. Data characteristics and group-level analysis of sleep properties were assessed. The database can be accessed through ( https://doi.org/10.17605/OSF.IO/R26FH ). This is the first high-density electroencephalogram open sleep database from healthy adults, allowing researchers to investigate sleep physiology at high spatial resolution. We expect that this database will serve as a valuable resource for studying sleep physiology and for benchmarking sleep pathology.

Biomarkers of sleep-wake disturbance as predictors of cognitive decline and accelerated disease progression

INTRODUCTION

In older adults, where sleep disturbances and cognitive impairment are common, mounting evidence suggests a potential connection between sleep and cognitive function, highlighting the significance of utilizing sleep as a biomarker for early detection of cognitive impairment to improve clinical outcomes in a noninvasive, cost-effective manner.

AREAS COVERED

This review describes the relationship between sleep and cognitive function in older adults, encompassing both subjective and objective measures of sleep quality, duration, architecture, and sleep-disordered breathing. The authors consider the directionality of the associations observed in prospective and cross-sectional studies, exploring whether sleep disturbances precede cognitive decline or vice versa. Furthermore, they discuss the potential bidirectional relationships between sleep and Alzheimer's disease (AD) risks in older adults while also examining the neurodegenerative pathways of this relationship.

EXPERT OPINION

Routine sleep monitoring in primary care settings has the potential to bolster early detection and treatment of sleep disturbance, and by extension, reduce the risk of dementia. Improving sleep assessment tools, such as wearables, provide scalable alternatives to traditional methods like polysomnography, potentially enabling widespread monitoring of sleep characteristics. Standardized measurement and inclusive participant recruitment are needed to enhance generalizability, while longitudinal studies are essential to understand the interaction between sleep and AD pathology.

Spindle chirp and other sleep oscillatory features in young children with autism

OBJECTIVES

To determine whether spindle chirp and other sleep oscillatory features differ in young children with and without autism.

METHODS

Automated processing software was used to re-assess an extant set of polysomnograms representing 121 children (91 with autism [ASD], 30 typically-developing [TD]), with an age range of 1.35-8.23 years. Spindle metrics, including chirp, and slow oscillation (SO) characteristics were compared between groups. SO and fast and slow spindle (FS, SS) interactions were also investigated. Secondary analyses were performed assessing behavioural data associations, as well as exploratory cohort comparisons to children with non-autism developmental delay (DD).

RESULTS

Posterior FS and SS chirp was significantly more negative in ASD than TD. Both groups had comparable intra-spindle frequency range and variance. Frontal and central SO amplitude were decreased in ASD. In contrast to previous manual findings, no differences were detected in other spindle or SO metrics. The ASD group displayed a higher parietal coupling angle. No differences were observed in phase-frequency coupling. The DD group demonstrated lower FS chirp and higher coupling angle than TD. Parietal SS chirp was positively associated with full developmental quotient.

CONCLUSIONS

For the first time spindle chirp was investigated in autism and was found to be significantly more negative than in TD in this large cohort of young children. This finding strengthens previous reports of spindle and SO abnormalities in ASD. Further investigation of spindle chirp in healthy and clinical populations across development will help elucidate the significance of this difference and better understand this novel metric.

Subjective sleep more predictive of global cognitive function than objective sleep in older adults: A specification curve analysis

OBJECTIVES

Sleep is associated with cognitive function in older adults. In the current study, we examined this relationship from subjective and objective perspectives, and determined the robustness and dimensional specificity of the associations using a comprehensive modelling approach.

METHODS

Multiple dimensions of subjective (sleep quality and daytime sleepiness) and objective sleep (sleep stages, sleep parameters, sleep spindles, and slow oscillations), as well as subjectively reported and objectively measured cognitive function were collected from 55 older adults. Specification curve analysis was used to examine the robustness of correlations for the effects of sleep on cognitive function.

RESULTS

Robust associations were found between sleep and objectively measured cognitive function, but not with subjective cognitive complaints. In addition, subjective sleep showed robust and consistent associations with global cognitive function, whereas objective sleep showed a more domain-specific association with episodic memory. Specifically, subjective sleep quality and daytime sleepiness correlated with global cognitive function, and objective sleep parameters correlated with episodic memory.

CONCLUSIONS

Overall, associations between sleep and cognitive function in older adults depend on how they are measured and which specific dimensions of sleep and domains of cognitive function are considered. It highlights the importance of focusing on specific associations to ameliorate the detrimental effects of sleep disturbance on cognitive function in later life.

Novel Electrophysiological Signatures of Learning and Forgetting in Human Rapid Eye Movement Sleep

Despite the known behavioral benefits of rapid eye movement (REM) sleep, discrete neural oscillatory events in human scalp electroencephalography (EEG) linked with behavior have not been discovered. This knowledge gap hinders mechanistic understanding of the function of sleep, as well as the development of biophysical models and REM-based causal interventions. We designed a detection algorithm to identify bursts of activity in high-density, scalp EEG within theta (4-8 Hz) and alpha (8-13 Hz) bands during REM sleep. Across 38 nights of sleep, we characterized the burst events (i.e., count, duration, density, peak frequency, amplitude) in healthy, young male and female human participants (38; 21F) and investigated burst activity in relation to sleep-dependent memory tasks: hippocampal-dependent episodic verbal memory and nonhippocampal visual perceptual learning. We found greater burst count during the more REM-intensive second half of the night (p < 0.05), longer burst duration during the first half of the night (p < 0.05), but no differences across the night in density or power (p > 0.05). Moreover, increased alpha burst power was associated with increased overnight forgetting for episodic memory (p < 0.05). Furthermore, we show that increased REM theta burst activity in retinotopically specific regions was associated with better visual perceptual performance. Our work provides a critical bridge between discrete REM sleep events in human scalp EEG that support cognitive processes and the identification of similar activity patterns in animal models that allow for further mechanistic characterization.

The Association of Upper Airway Anatomy with Brain Structure: The Multi-Ethnic Study of Atherosclerosis

Sleep apnea, affecting an estimated 1 in 4 American adults, has been reported to be associated with both brain structural abnormality and impaired cognitive function. Obstructive sleep apnea is known to be affected by upper airway anatomy. To better understand the contribution of upper airway anatomy to pathways linking sleep apnea with impaired cognitive function, we investigated the association of upper airway anatomy with structural brain abnormalities. Based in the Multi-Ethnic Study of Atherosclerosis, a longitudinal cohort study of community-dwelling adults, a comprehensive sleep study and an MRI of the upper airway and brain were performed on 578 participants. Machine learning models were used to select from 74 upper airway measures those measures most associated with selected regional brain volumes and white matter hyperintensity volume. Linear regression assessed associations between the selected upper airway measures, sleep measures, and brain structure. Maxillary divergence was positively associated with hippocampus volume, and mandible length was negatively associated with total white and gray matter volume. Both coefficients were small (coefficients per standard deviation 0.063 mL, p = 0.04, and - 7.0 mL, p < 0.001 respectively), and not affected by adjustment for sleep study measures. Self-reported snoring >2 times per week was associated with larger hippocampus volume (coefficient 0.164 mL, p = 0.007), and higher percentage of time in the N3 sleep stage was associated with larger total white and gray matter volume (4.8 mL, p = 0.004). Despite associations of two upper airway anatomy measures with brain volume, the evidence did not suggest that these upper airway and brain structure associations were acting primarily through the pathway of sleep disturbance.

The impacts of intra-individual daily sleep variability on daytime functioning and sleep architecture in healthy young adults: An experimental study

Sleep variability is commonly seen in the young populations. This study aimed to examine the impacts of experimentally induced sleep variability on sleepiness, mood, cognitive performance and sleep architectures among young adults. Thirty-six healthy individuals (aged 18-22 years) were randomly assigned to either variable sleep schedule (n = 20) or control (n = 16) groups. The protocol involved 1 week of regular sleep (time in bed = 7.5 hr) in the home setting, followed by one adaptation night (time in bed = 7.5 hr), one baseline night (time in bed = 7.5 hr), and 6 nights of sleep manipulation in the laboratory monitored by polysomnography (three cycles of variable sleep schedule by changing daily time in bed alternating between 6 hr and 9 hr for variable sleep schedule group versus fixed sleep schedule with daily time in bed for 7.5 hr for control group). Sleepiness, mood, sustained attention, processing speed, response inhibition and working memory were measured every morning and evening. The variable sleep schedule group reported a higher level of sleepiness, especially in the mornings, and increased negative mood in the evenings. There were no significant differences in positive mood, cognitive performance and sleep macro- and micro-structures. Our results showed the negative effects of sleep variability on daytime functioning especially sleepiness and negative mood, suggesting the need to address variable sleep schedules through sleep intervention.

All Obstructive Sleep Apnea Events Are Not Created Equal: The Relationship between Event-related Hypoxemia and Physiologic Response

Rationale: Obstructive sleep apnea (OSA) severity is typically assessed by the apnea-hypopnea index (AHI), a frequency-based metric that allocates equal weight to all respiratory events. However, more severe events may have a greater physiologic impact. Objectives: The purpose of this study was to determine whether the degree of event-related hypoxemia would be associated with the postevent physiologic response. Methods: Patients with OSA (AHI, ⩾5/h) from the multicenter Canadian Sleep and Circadian Network cohort were studied. Using mixed-effect linear regression, we examined associations between event-related hypoxic burden (HBev) assessed by the area under the event-related oxygen saturation recording with heart rate changes (ΔHRev), vasoconstriction (vasoconstriction burden [VCBev] assessed with photoplethysmography), and electroencephalographic responses (power ratio before and after events). Results: Polysomnographic recordings from 658 patients (median [interquartile range] age, 55.00 [45.00, 64.00] yr; AHI, 27.15 [14.90, 64.05] events/h; 42% female) were included in the analyses. HBev was associated with an increase in all physiologic responses after controlling for age, sex, body mass index, sleep stage, total sleep time, and study centers; for example, 1 standard deviation increase in HBev was associated with 0.21 [95% confidence interval, 0.2, 0.22], 0.08 [0.08, 0.09], and 0.22 [0.21, 0.23] standard deviation increases in ΔHRev, VCBev, and β-power ratio, respectively. Conclusions: Increased event-related hypoxic burden was associated with greater responses across a broad range of physiologic signals. Future metrics that incorporate information about the variability of these physiologic responses may have promise in providing a more nuanced assessment of OSA severity.

Sleep alterations as a function of 88 health indicators

BACKGROUND

Alterations in sleep have been described in multiple health conditions and as a function of several medication effects. However, evidence generally stems from small univariate studies. Here, we apply a large-sample, data-driven approach to investigate patterns between in sleep macrostructure, quantitative sleep EEG, and health.

METHODS

We use data from the MrOS Sleep Study, containing polysomnography and health data from a large sample (N = 3086) of elderly American men to establish associations between sleep macrostructure, the spectral composition of the electroencephalogram, 38 medical disorders, 2 health behaviors, and the use of 48 medications.

RESULTS

Of sleep macrostructure variables, increased REM latency and reduced REM duration were the most common findings across health indicators, along with increased sleep latency and reduced sleep efficiency. We found that the majority of health indicators were not associated with objective EEG power spectral density (PSD) alterations. Associations with the rest were highly stereotypical, with two principal components accounting for 85-95% of the PSD-health association. PC1 consists of a decrease of slow and an increase of fast PSD components, mainly in NREM. This pattern was most strongly associated with depression/SSRI medication use and age-related disorders. PC2 consists of changes in mid-frequency activity. Increased mid-frequency activity was associated with benzodiazepine use, while decreases were associated with cardiovascular problems and associated medications, in line with a recently proposed hypothesis of immune-mediated circadian demodulation in these disorders. Specific increases in sleep spindle frequency activity were associated with taking benzodiazepines and zolpidem. Sensitivity analyses supported the presence of both disorder and medication effects.

CONCLUSIONS

Sleep alterations are present in various health conditions.

Linking brain structure, cognition, and sleep: insights from clinical data

STUDY OBJECTIVES

To use relatively noisy routinely collected clinical data (brain magnetic resonance imaging (MRI) data, clinical polysomnography (PSG) recordings, and neuropsychological testing), to investigate hypothesis-driven and data-driven relationships between brain physiology, structure, and cognition.

METHODS

We analyzed data from patients with clinical PSG, brain MRI, and neuropsychological evaluations. SynthSeg, a neural network-based tool, provided high-quality segmentations despite noise. A priori hypotheses explored associations between brain function (measured by PSG) and brain structure (measured by MRI). Associations with cognitive scores and dementia status were studied. An exploratory data-driven approach investigated age-structure-physiology-cognition links.

RESULTS

Six hundred and twenty-three patients with sleep PSG and brain MRI data were included in this study; 160 with cognitive evaluations. Three hundred and forty-two participants (55%) were female, and age interquartile range was 52 to 69 years. Thirty-six individuals were diagnosed with dementia, 71 with mild cognitive impairment, and 326 with major depression. One hundred and fifteen individuals were evaluated for insomnia and 138 participants had an apnea-hypopnea index equal to or greater than 15. Total PSG delta power correlated positively with frontal lobe/thalamic volumes, and sleep spindle density with thalamic volume. rapid eye movement (REM) duration and amygdala volume were positively associated with cognition. Patients with dementia showed significant differences in five brain structure volumes. REM duration, spindle, and slow-oscillation features had strong associations with cognition and brain structure volumes. PSG and MRI features in combination predicted chronological age (R2 = 0.67) and cognition (R2 = 0.40).

CONCLUSIONS

Routine clinical data holds extended value in understanding and even clinically using brain-sleep-cognition relationships.

Gender differences in the relationship between sleep and age in a Brazilian cohort: the Baependi Heart Study

Gender and age are well-established determinants of health and sleep health that influence overall health, which also often varies by gender and age. Sleep architecture is an important component of sleep health. The goal of this analysis was to examine whether associations between age and sleep stages differ by gender in the absence of moderate-severe obstructive sleep apnea (OSA) in a rural setting in Brazil. This study conducted polysomnography recordings in the Baependi Heart Study, a cohort of Brazilian adults. Our sample included 584 women and 309 men whose apnea-hypopnea index was ≤15 events/h. We used splines to distinguish non-linear associations between age, total sleep time, wake after sleep onset (WASO), N2, N3, and rapid-eye-movement sleep. The mean (standard deviation; range) age was 47 (14; 18-89) years. All sleep outcomes were associated with age. Compared to men, women had more N3 sleep and less WASO after adjusting for age. Model-based comparisons between genders at specific ages showed statistically higher mean WASO for men at ages 60 (+13.6 min) and 70 years (+19.5 min) and less N3 for men at ages 50 (-13.2 min), 60 (-19.0 min), and 70 years (-19.5 min) but no differences at 20, 30, 40 or 80 years. The other sleep measures did not differ by gender at any age. Thus, even in the absence of moderate-severe OSA, sleep architecture was associated with age across adulthood, and there were gender differences in WASO and N3 at older ages in this rural community.

Associations Between Sleep Spindle Metrics, Age, Education and Executive Function in Young Adult and Middle-Aged Patients with Obstructive Sleep Apnea

Purpose

This study aimed to investigate the association between sleep spindle metrics and executive function in individuals with obstructive sleep apnea (OSA). Furthermore, we examined the association of age and education on executive function.

Patients and Methods

A total of 230 (40.90 ± 8.83 years, F/M = 45/185) participants were enrolled. Overnight electroencephalogram (C3-M2) recording detected sleep spindles by a novel U-Net-type neural network that integrates temporal information with time-frequency images. Sleep spindle metrics, including frequency (Hz), overall density (events/min), fast density (events/min), slow density (events/min), duration (sec) and amplitude (µV), were measured. Executive function was assessed using standardized neuropsychological tests. Associations between sleep spindle metrics, executive function, and demographic factors were analyzed using multivariate linear regression.

Results

In fully adjusted linear regression models, higher overall sleep spindle density (TMT-A, B=-1.279, p=0.009; TMT-B, B=-1.813, p=0.008), fast sleep spindle density (TMT-A, B=-1.542, p=0.048; TMT-B, B=-2.187, p=0.036) and slow sleep spindle density (TMT-A, B=-1.731, p=0.037; TMT-B, B=-2.449, p=0.034) were associated with better executive function. And the sleep spindle duration both during N2 sleep time (TMT-A, B=-13.932, p=0.027; TMT-B, B=-19.001, p=0.034) and N3 sleep time (TMT-B, B=-29.916, p=0.009; Stroop-incongruous, B=-21.303, p=0.035) was independently associated with better executive function in this population. Additionally, age and education were found to be highly associated with executive function.

Conclusion

Specific sleep spindle metrics, higher overall density, fast density and slow density during N2 sleep time, and longer duration during N2 and N3 sleep time, are independent and sensitive indicators of better executive function in young adult and middle-aged patients with OSA. Further research is needed to explore the underlying mechanisms and clinical implications of these findings.

Altered Sleep Microarchitecture and Cognitive Impairment in Patients With Temporal Lobe Epilepsy

BACKGROUND AND OBJECTIVES

To investigate the spatiotemporal characteristics of sleep waveforms in temporal lobe epilepsy (TLE) and examine their association with cognition.

METHODS

In this retrospective, cross-sectional study, we examined overnight EEG data from adult patients with TLE and nonepilepsy comparisons (NECs) admitted to the epilepsy monitoring unit at Mass General Brigham hospitals. Automated algorithms were used to characterize sleep macroarchitecture (sleep stages) and microarchitecture (spindles, slow oscillations [SOs]) on scalp EEG and to detect hippocampal interictal epileptiform discharges (hIEDs) from foramen ovale electrodes simultaneously recorded in a subset of patients with TLE. We examined the association of sleep features and hIEDs with memory and executive function from clinical neuropsychological evaluations.

RESULTS

A total of 81 adult patients with TLE and 28 NEC adult patients were included with similar mean ages. There were no significant differences in sleep macroarchitecture between groups, including relative time spent in each sleep stage, sleep efficiency, and sleep fragmentation. By contrast, the spatiotemporal characteristics of sleep microarchitecture were altered in TLE compared with NEC and were associated with cognitive impairments. Specifically, we observed a ∼30% reduction in spindle density in patients with TLE compared with NEC, which was significantly associated with worse memory performance. Spindle-SO coupling strength was also reduced in TLE and, in contrast to spindles, was associated with diminished executive function. We found no significant association between sleep macroarchitectural and microarchitectural parameters and hIEDs.

DISCUSSION

There is a fundamental alteration of sleep microarchitecture in TLE, characterized by a reduction in spindle density and spindle-SO coupling, and these changes may contribute to neurocognitive comorbidity in this disorder.

Sleep-EEG in comorbid pain and insomnia: implications for the treatment of pain disorders

INTRODUCTION

Patients with chronic pain experience a high prevalence of comorbid insomnia, which is associated with functional impairment. Recent advances in sleep electroencephalography (sleep-EEG) may clarify the mechanisms that link sleep and chronic pain. In this clinical update, we outline current advancements in sleep-EEG assessments for pain and provide research recommendations.

RESULTS

Promising preliminary work suggests that sleep-EEG spectral bands, particularly beta, gamma, alpha, and delta power, may create candidate neurophysiological signatures of pain, and macro-architectural parameters (e.g., total sleep time, arousals, and sleep continuity) may facilitate EEG-derived sleep phenotyping and may enable future stratification in the treatment of pain.

CONCLUSION

Integration of measures obtained through sleep-EEG represent feasible and scalable approaches that could be adopted in the future. We provide research recommendations to progress the field towards a deeper understanding of their utility and potential future applications in clinical practice.

The association of upper airway anatomy with cognitive test performance: the Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Numerous upper airway anatomy characteristics are risk factors for sleep apnea, which affects 26% of older Americans, and more severe sleep apnea is associated with cognitive impairment. This study explores the pathophysiology and links between upper airway anatomy, sleep, and cognition.

METHODS

Participants in the Multi-Ethnic Study of Atherosclerosis underwent an upper airway MRI, polysomnography to assess sleep measures including the apnea-hypopnea index (AHI) and completed the Cognitive Abilities Screening Instrument (CASI). Two model selection techniques selected from among 67 upper airway measures those that are most strongly associated with CASI score. The associations of selected upper airway measures with AHI, AHI with CASI score, and selected upper airway anatomy measures with CASI score, both alone and after adjustment for AHI, were assessed using linear regression.

RESULTS

Soft palate volume, maxillary divergence, and upper facial height were significantly positively associated with higher CASI score, indicating better cognition. The coefficients were small, with a 1 standard deviation (SD) increase in these variables being associated with a 0.83, 0.75, and 0.70 point higher CASI score, respectively. Additional adjustment for AHI very slightly attenuated these associations. Larger soft palate volume was significantly associated with higher AHI (15% higher AHI (95% CI 2%,28%) per SD). Higher AHI was marginally associated with higher CASI score (0.43 (95% CI 0.01,0.85) per AHI doubling).

CONCLUSIONS

Three upper airway measures were weakly but significantly associated with higher global cognitive test performance. Sleep apnea did not appear to be the mechanism through which these upper airway and cognition associations were acting. Further research on the selected upper airway measures is recommended.

Long-term associations between objective sleep quality and quantity and verbal memory performance in normal cognition and mild cognitive impairment

Introduction

Although the link between sleep and memory function is well established, associations between sleep macrostructure and memory function in normal cognition and Mild Cognitive Impairment remain unclear. We aimed to investigate the longitudinal associations of baseline objectively assessed sleep quality and duration, as well as time in bed, with verbal memory capacity over a 7-9 year period. Participants are a well-characterized subsample of 148 persons (mean age at baseline: 72.8 ± 6.7 years) from the Cretan Aging Cohort. Based on comprehensive neuropsychiatric and neuropsychological evaluation at baseline, participants were diagnosed with Mild Cognitive Impairment (MCI; n = 79) or found to be cognitively unimpaired (CNI; n = 69). Sleep quality/quantity was estimated from a 3-day consecutive actigraphy recording, whereas verbal memory capacity was examined using the Rey Auditory Verbal Learning Test (RAVLT) and the Greek Passage Memory Test at baseline and follow-up. Panel models were applied to the data using AMOS including several sociodemographic and clinical covariates.

Results

Sleep efficiency at baseline directly predicted subsequent memory performance in the total group (immediate passage recall: β = 0.266, p = 0.001; immediate word list recall: β = 0.172, p = 0.01; delayed passage retrieval: β = 0.214, p = 0.002) with the effects in Passage Memory reaching significance in both clinical groups. Wake after sleep onset time directly predicted follow-up immediate passage recall in the total sample (β = -0.211, p = 0.001) and in the MCI group (β = -0.235, p = 0.02). In the total sample, longer 24-h sleep duration was associated with reduced memory performance indirectly through increased sleep duration at follow-up (immediate passage recall: β = -0.045, p = 0.01; passage retention index: β = -0.051, p = 0.01; RAVLT-delayed recall: β = -0.048, p = 0.009; RAVLT-retention index:β = -0.066, p = 0.004). Similar indirect effects were found for baseline 24-h time in bed. Indirect effects of sleep duration/time in bed were found predominantly in the MCI group.

Discussion

Findings corroborate and expand previous work suggesting that poor sleep quality and long sleep duration predict worse memory function in elderly. Timely interventions to improve sleep could help prevent or delay age-related memory decline among non-demented elderly.

The association between sleep spindles and cognitive function in middle-aged and older men from a community-based cohort study

OBJECTIVES

Previous studies examining associations between sleep spindles and cognitive function attempted to account for obstructive sleep apnea without consideration for potential moderating effects. To elucidate associations between sleep spindles, cognitive function, and obstructive sleep apnea, this study of community-dwelling men examined cross-sectional associations between sleep spindle metrics and daytime cognitive function outcomes following adjustment for obstructive sleep apnea and potential obstructive sleep apnea moderating effects.

METHODS

Florey Adelaide Male Ageing Study participants (n = 477, 41-87 years) reporting no previous obstructive sleep apnea diagnosis underwent home-based polysomnography (2010-2011). Cognitive testing (2007-2010) included the inspection time task (processing speed), trail-making tests A (TMT-A) (visual attention) and B (trail-making test-B) (executive function), and Fuld object memory evaluation (episodic memory). Frontal spindle metrics (F4-M1) included occurrence (count), average frequency (Hz), amplitude (µV), and overall (11-16 Hz), slow (11-13 Hz), and fast (13-16 Hz) spindle density (number/minute during N2 and N3 sleep).

RESULTS

In fully adjusted linear regression models, lower N2 sleep spindle occurrence was associated with longer inspection times (milliseconds) (B = -0.43, 95% confidence interval [-0.74, -0.12], p = .006), whereas higher N3 sleep fast spindle density was associated with worse TMT-B performance (seconds) (B = 18.4, 95% confidence interval [1.62, 35.2], p = .032). Effect moderator analysis revealed that in men with severe obstructive sleep apnea (apnea-hypopnea index ≥30/hour), slower N2 sleep spindle frequency was associated with worse TMT-A performance (χ2 = 12.5, p = .006).

CONCLUSIONS

Specific sleep spindle metrics were associated with cognitive function, and obstructive sleep apnea severity moderated these associations. These observations support the utility of sleep spindles as useful cognitive function markers in obstructive sleep apnea, which warrants further longitudinal investigation.

Multivariate prediction of cognitive performance from the sleep electroencephalogram

Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5-10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics account for more covariance between sleep EEG and cognition than health variables, and consequently reduce this association by a greater degree, but even with the strictest covariate sets a statistically significant association is present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r = 0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r = 0.186) and health variables (r = 0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.

Associations of Slow-Wave Sleep With Prevalent and Incident Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis

CONTEXT

N3 sleep (i.e., slow-wave sleep), a marker of deep restorative sleep, is implicated in hormonal and blood pressure regulation and may impact cardiometabolic health.

OBJECTIVE

We conducted cross-sectional and prospective analyses to test whether a higher proportion and longer duration of N3 sleep are associated with reduced type 2 diabetes risk.

METHODS

A subsample of participants from the Multi-Ethnic Study of Atherosclerosis completed 1-night polysomnography at Exam 5 (2010-2013) and were prospectively followed until Exam 6 (2016-2018). We used modified Poisson regression to examine the cross-sectional associations of N3 proportion and duration with prevalent diabetes and Cox proportional hazards models to estimate risk of diabetes according to N3 measures.

RESULTS

In cross-sectional analyses (n = 2026, mean age: 69 years), diabetes prevalence was 28% (n = 572). Compared with the first quartile (Q1) of the N3 proportion (<2.0%), participants in Q4 (≥15.4%) were 29% (95% CI 0.58, 0.87) less likely to have prevalent diabetes (P trend = .0016). The association attenuated after adjustment for demographics, lifestyles, and sleep-related factors (P trend = .3322). In prospective analyses of 1251 participants and 129 incident cases over 6346 person-years of follow-up, a curvilinear relationship was observed between N3 proportion and incident diabetes risk. In the fully adjusted model, the hazard ratio (95% CI) of developing diabetes vs Q1 was 0.47 (0.26, 0.87) for Q2, 0.34 (0.15, 0.77) for Q3, and 0.32 (0.10, 0.97) for Q4 (P nonlinearity = .0213). The results were similar for N3 duration.

CONCLUSION

Higher N3 proportion and longer N3 duration were prospectively associated with lower type 2 diabetes risk in a nonlinear fashion among older American adults.

Effects of Early Adverse Life Events on Depression and Cognitive Performance from the Perspective of the Heart-Brain Axis

Early adverse life events (EALs) increase susceptibility to depression and impair cognitive performance, but the physiological mechanisms are still unclear. The target of this article is to clarify the impact of adverse childhood experiences on emotional and cognitive performance from the perspective of the heart-brain axis. We used the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) to test cognitive function and the Childhood Trauma Questionnaire (CTQ) to assess adverse childhood experiences. Heart rate variability (HRV) and electroencephalograms (EEG) were acquired at rest. We observed that subjects with depression had experienced more traumatic events during their childhood. Furthermore, they exhibited lower heart rate variability and higher power in the delta, theta, and alpha frequency bands. Moreover, heart rate variability partially mediated the association between childhood trauma exposure and depressive symptoms. Our findings suggested that adverse life events in childhood could influence the development of depression in adulthood, which might be linked to cardiac autonomic dysfunction and altered brain function.

Decoding information about cognitive health from the brainwaves of sleep

Sleep electroencephalogram (EEG) signals likely encode brain health information that may identify individuals at high risk for age-related brain diseases. Here, we evaluate the correlation of a previously proposed brain age biomarker, the "brain age index" (BAI), with cognitive test scores and use machine learning to develop and validate a series of new sleep EEG-based indices, termed "sleep cognitive indices" (SCIs), that are directly optimized to correlate with specific cognitive scores. Three overarching cognitive processes were examined: total, fluid (a measure of cognitive processes involved in reasoning-based problem solving and susceptible to aging and neuropathology), and crystallized cognition (a measure of cognitive processes involved in applying acquired knowledge toward problem-solving). We show that SCI decoded information about total cognition (Pearson's r = 0.37) and fluid cognition (Pearson's r = 0.56), while BAI correlated only with crystallized cognition (Pearson's r = - 0.25). Overall, these sleep EEG-derived biomarkers may provide accessible and clinically meaningful indicators of neurocognitive health.

Sleep Architecture, Obstructive Sleep Apnea, and Cognitive Function in Adults

Importance

Good sleep is essential for health, yet associations between sleep and dementia risk remain incompletely understood. The Sleep and Dementia Consortium was established to study associations between polysomnography (PSG)-derived sleep and the risk of dementia and related cognitive and brain magnetic resonance imaging endophenotypes.

Objective

To investigate association of sleep architecture and obstructive sleep apnea (OSA) with cognitive function in the Sleep and Dementia Consortium.

Design, Setting, and Participants

The Sleep and Dementia Consortium curated data from 5 population-based cohorts across the US with methodologically consistent, overnight, home-based type II PSG and neuropsychological assessments over 5 years of follow-up: the Atherosclerosis Risk in Communities study, Cardiovascular Health Study, Framingham Heart Study (FHS), Osteoporotic Fractures in Men Study, and Study of Osteoporotic Fractures. Sleep metrics were harmonized centrally and then distributed to participating cohorts for cohort-specific analysis using linear regression; study-level estimates were pooled in random effects meta-analyses. Results were adjusted for demographic variables, the time between PSG and neuropsychological assessment (0-5 years), body mass index, antidepressant use, and sedative use. There were 5946 participants included in the pooled analyses without stroke or dementia. Data were analyzed from March 2020 to June 2023.

Exposures

Measures of sleep architecture and OSA derived from in-home PSG.

Main Outcomes and Measures

The main outcomes were global cognitive composite z scores derived from principal component analysis, with cognitive domains investigated as secondary outcomes. Higher scores indicated better performance.

Results

Across cohorts, 5946 adults (1875 females [31.5%]; mean age range, 58-89 years) were included. The median (IQR) wake after sleep onset time ranged from 44 (27-73) to 101 (66-147) minutes, and the prevalence of moderate to severe OSA ranged from 16.9% to 28.9%. Across cohorts, higher sleep maintenance efficiency (pooled β per 1% increase, 0.08; 95% CI, 0.03 to 0.14; P < .01) and lower wake after sleep onset (pooled β per 1-min increase, -0.07; 95% CI, -0.13 to -0.01 per 1-min increase; P = .02) were associated with better global cognition. Mild to severe OSA (apnea-hypopnea index [AHI] ≥5) was associated with poorer global cognition (pooled β, -0.06; 95% CI, -0.11 to -0.01; P = .01) vs AHI less than 5; comparable results were found for moderate to severe OSA (pooled β, -0.06; 95% CI, -0.11 to -0.01; P = .02) vs AHI less than 5. Differences in sleep stages were not associated with cognition.

Conclusions and Relevance

This study found that better sleep consolidation and the absence of OSA were associated with better global cognition over 5 years of follow-up. These findings suggest that the role of interventions to improve sleep for maintaining cognitive function requires investigation.

Associations of Baseline Sleep Microarchitecture with Cognitive Function After 8 Years in Middle-Aged and Older Men from a Community-Based Cohort Study

Purpose

Prospective studies examining associations between baseline sleep microarchitecture and future cognitive function recruited from small samples with predominantly short follow-up. This study examined sleep microarchitecture predictors of cognitive function (visual attention, processing speed, and executive function) after 8 years in community-dwelling men.

Patients and Methods

Florey Adelaide Male Ageing Study participants (n=477) underwent home-based polysomnography (2010-2011), with 157 completing baseline (2007-2010) and follow-up (2018-2019) cognitive assessments (trail-making tests A [TMT-A] and B [TMT-B] and the standardized mini-mental state examination [SMMSE]). Whole-night F4-M1 sleep EEG recordings were processed following artifact exclusion, and quantitative EEG characteristics were obtained using validated algorithms. Associations between baseline sleep microarchitecture and future cognitive function (visual attention, processing speed, and executive function) were examined using linear regression models adjusted for baseline obstructive sleep apnoea, other risk factors, and cognition.

Results

The final sample included men aged (mean [SD]) 58.9 (8.9) years at baseline, overweight (BMI 28.5 [4.2] kg/m²), and well educated (75.2% ≥Bachelor, Certificate, or Trade), with majorly normal baseline cognition. Median (IQR) follow-up was 8.3 (7.9, 8.6) years. In adjusted analyses, NREM and REM sleep EEG spectral power was not associated with TMT-A, TMT-B, or SMMSE performance (all p>0.05). A significant association of higher N3 sleep fast spindle density with worse TMT-B performance (B=1.06, 95% CI [0.13, 2.00], p=0.026) did not persist following adjustment for baseline TMT-B performance.

Conclusion

In this sample of community-dwelling men, sleep microarchitecture was not independently associated with visual attention, processing speed, or executive function after 8 years.

AI-Driven sleep staging from actigraphy and heart rate

Sleep is an important indicator of a person's health, and its accurate and cost-effective quantification is of great value in healthcare. The gold standard for sleep assessment and the clinical diagnosis of sleep disorders is polysomnography (PSG). However, PSG requires an overnight clinic visit and trained technicians to score the obtained multimodality data. Wrist-worn consumer devices, such as smartwatches, are a promising alternative to PSG because of their small form factor, continuous monitoring capability, and popularity. Unlike PSG, however, wearables-derived data are noisier and far less information-rich because of the fewer number of modalities and less accurate measurements due to their small form factor. Given these challenges, most consumer devices perform two-stage (i.e., sleep-wake) classification, which is inadequate for deep insights into a person's sleep health. The challenging multi-class (three, four, or five-class) staging of sleep using data from wrist-worn wearables remains unresolved. The difference in the data quality between consumer-grade wearables and lab-grade clinical equipment is the motivation behind this study. In this paper, we present an artificial intelligence (AI) technique termed sequence-to-sequence LSTM for automated mobile sleep staging (SLAMSS), which can perform three-class (wake, NREM, REM) and four-class (wake, light, deep, REM) sleep classification from activity (i.e., wrist-accelerometry-derived locomotion) and two coarse heart rate measures-both of which can be reliably obtained from a consumer-grade wrist-wearable device. Our method relies on raw time-series datasets and obviates the need for manual feature selection. We validated our model using actigraphy and coarse heart rate data from two independent study populations: the Multi-Ethnic Study of Atherosclerosis (MESA; N = 808) cohort and the Osteoporotic Fractures in Men (MrOS; N = 817) cohort. SLAMSS achieves an overall accuracy of 79%, weighted F1 score of 0.80, 77% sensitivity, and 89% specificity for three-class sleep staging and an overall accuracy of 70-72%, weighted F1 score of 0.72-0.73, 64-66% sensitivity, and 89-90% specificity for four-class sleep staging in the MESA cohort. It yielded an overall accuracy of 77%, weighted F1 score of 0.77, 74% sensitivity, and 88% specificity for three-class sleep staging and an overall accuracy of 68-69%, weighted F1 score of 0.68-0.69, 60-63% sensitivity, and 88-89% specificity for four-class sleep staging in the MrOS cohort. These results were achieved with feature-poor inputs with a low temporal resolution. In addition, we extended our three-class staging model to an unrelated Apple Watch dataset. Importantly, SLAMSS predicts the duration of each sleep stage with high accuracy. This is especially significant for four-class sleep staging, where deep sleep is severely underrepresented. We show that, by appropriately choosing the loss function to address the inherent class imbalance, our method can accurately estimate deep sleep time (SLAMSS/MESA: 0.61±0.69 hours, PSG/MESA ground truth: 0.60±0.60 hours; SLAMSS/MrOS: 0.53±0.66 hours, PSG/MrOS ground truth: 0.55±0.57 hours;). Deep sleep quality and quantity are vital metrics and early indicators for a number of diseases. Our method, which enables accurate deep sleep estimation from wearables-derived data, is therefore promising for a variety of clinical applications requiring long-term deep sleep monitoring.

Sex differences in the effects of sleep disorders on cognitive dysfunction

Sleep is an essential physiological function that sustains human life. Sleep disorders involve problems with the quality, duration, and abnormal behaviour of sleep. Insomnia is the most common sleep disorder, followed by sleep-disordered breathing (SDB). Sleep disorders often occur along with medical conditions or other mental health conditions. Of particular interest to researchers is the role of sleep disorders in cognitive dysfunction. Sleep disorder is a risk factor for cognitive dysfunction, yet the exact pathogenesis is still far from agreement. Little is known about how sex differences influence the changes in cognitive functions caused by sleep disorders. This narrative review examines how sleep disorders might affect cognitive impairment, and then explores the sex-specific consequences of sleep disorders as a risk factor for dementia and the potential underlying mechanisms. Some insights on the direction of further research are also presented.

A Novel In-Home Sleep Monitoring System Based on Fully Integrated Multichannel Front-End Chip and Its Multilevel Analyses

OBJECTIVE

A novel in-home sleep monitoring system with an 8-channel biopotential acquisition front-end chip is presented and validated via multilevel data analyses and comparision with advanced polysomnography.

METHODS AND PROCEDURES

The chip includes a cascaded low-noise programmable gain amplifier (PGA) and 24-bit [Formula: see text]-[Formula: see text] analog-to-digital converter (ADC). The PGA is based on three op-amp structure while the ADC adopts cascade of integrator feedforward and feedback (CIFF-B) architecture. An innovative chopper-modulated input-scaling-down technique enhances the dynamic range. The proposed system and commercial polysomnography were used for in-home sleep monitoring of 20 healthy participants. The consistency and significance of the two groups' data were analyzed.

RESULTS

Fabricated in 180 nm BCD technology, the input-referred noise, input impedance, common-mode rejection ratio, and dynamic range of the acquisition front-end chip were [Formula: see text]Vpp, 1.25 GN), 113.9 dB, and 119.8 dB. The kappa coefficients between the sleep stage labels of the three scorers were 0.80, 0.76, and 0.79. The consistency of the slowing index, multiscale entropy, and percentile features between the two devices reached 0.958, 0.885, and 0.834. The macro sleep architecture characteristics of the two devices were not significantly different (all p [Formula: see text] 0.05).

CONCLUSION

The proposed chip was applied to develop an in-home sleep monitoring system with significantly reduced size, power, and cost. Multilevel analyses demonstrated that this system collects stable and accurate in-home sleep data.

CLINICAL IMPACT

The proposed system can be applied for long-term in-home sleep monitoring outside of laboratory environments and sleep disorders screening that with low cost.