Mounting evidence shows sex-based differences in sleep experiences and outcomes, including the prevalence of insomnia disorder. However, the impact of biological sex on brain oscillations during sleep remains poorly understood, especially in the context of insomnia disorder. This is a notable gap, given that neurophysiological aspects of sleep are associated with brain health and overall sleep quality. We systematically reviewed and meta-analysed data from studies reporting spindle and slow wave activity in adults with and without insomnia disorder. We conducted systematic searches in PubMed, Embase, Scopus, and PsycInfo. Risk of bias was evaluated using the Newcastle Ottawa and the PEDro scales. Forty-three studies met our inclusion criteria, with thirteen studies of normal sleepers (N = 668) reporting sufficient data for random-effects meta-analyses. Compared with males, female normal sleepers had higher spindle density, sigma and delta power. Most studies recruited individuals with primary insomnia, and data pooling for insomnia and mixed groups was not possible due to insufficient statistical reporting. Moreover, group-by-sex interactions were limited, inconsistent, and varied across studies and sample characteristics. Further research is needed to explore sex-specific differences in sleep microarchitecture and their role in normal sleep and the manifestation of insomnia disorder.

Background:Sleep-dependent memory consolidation (SDMC), the process by which sleep supports the transfer of memories into long-term storage, declines with age but remains underexplored in older adults with subjective cognitive decline and mild cognitive impairment. Traditional SDMC assessments are typically conducted in lab settings, with limited evidence for feasibility to do these assessments at home for this clinical population. Objective:To address this, we co-designed the Sleep Memories app, which assesses overnight memory for a previously validated 32-item word-pairs task. This pilot study first explored the feasibility and acceptability of the app, including willingness to participate. Second, we explored various demographic, clinical, and subjective sleep factors associated with task completion and SDMC performance in a memory clinic sample. Methods:Within an 8-month period, we invited 141 older adults aged 50 years and above (mean 71.27, SD 7.51 y) from the Healthy Brain Ageing clinic, a specialist brain health and memory clinic in Sydney, to pilot the Sleep Memories app. Of these, 76 (mean 70.19, SD 7.75) agreed to participate. All participants underwent a full neuropsychological test battery, medical assessment, and mood assessment. Results:Sixty-eight participants completed at least 1 test of the word-pairs task. The word-pairs task completion rate for all trials was over 50%. There was 57% (39/68) completion of both evening and morning delayed recall tests. Lower willingness to participate was associated with lower global cognitive scores, poorer sleep behavior, and clinical factors. Higher task completion was associated with greater education and greater anxiety levels. User feedback indicated that the app was well-accepted and liked, although some participants reported minor technical difficulties. Conclusions:These findings support the feasibility of mobile app-based SDMC assessment in older adults at risk of cognitive decline and underscore the importance of considering individual characteristics (eg, subjective sleep factors, clinical characteristics, and education) when designing digital SDMC tools.

Emerging evidence suggests altered sleep neurophysiology may be an early marker of brain pathology. However, no studies have examined links between sleep neurophysiology and blood-based neurodegeneration biomarkers. We aimed to determine if blood-based Alzheimer's and neurodegeneration biomarkers are associated with sleep neurophysiology in older adults with subjective and objective cognitive impairment. We recruited adults aged 50+ with cognitive or mood concerns from a memory clinic. Cognitive status was classified as mild cognitive impairment (MCI) or subjective cognitive impairment (SCI) using neuropsychological test criteria. MCI required scores ≥1.5 SD below normative means on one or more tests, while SCI indicated no objective deficits. Participants completed a fasting blood test and overnight polysomnography. Plasma biomarkers (Aβ42/40, GFAP, NFL, pTau181) were measured on the Quanterix SIMOA HD-X platform using commercially available kits. Sleep measures included spindle density, relative theta/delta power, and REM slowing. Spindles were detected via a validated algorithm (C3), while power and REM slowing used Fz electrode data. Linear regressions assessed whether biomarkers predicted sleep neurophysiology metrics. Our sample included 116 participants (mean age=68.3 (SD=8.1), n = 40 males (34.5%)), with a mean Mini-Mental State Examination of 28.3 (SD=2.5). Of these, 56 (48.3%) had MCI, and 60 (51.7%) had SCI. Spindle density and relative delta power were higher in SCI than MCI ( p <0.05), whereas relative theta was lower in SCI ( p <0.05). No group differences were found in REM slowing ( p >0.05). As expected, Aβ42/40 was lower in MCI than SCI ( p <0.05), while GFAP, NFL, and pTau181 were higher in MCI ( p <0.05). Regression analyses showed Aβ42/40 was associated with spindle density (R 2 =0.03, t=-2.2, p <0.05) and REM slowing (R 2 =0.03, t=2.1, p <0.05). GFAP (R 2 =0.05, t=-2.5, p <0.05) was significantly linked to spindle density. After adjusting for clinical status and age, only REM slowing remained significant ( p <0.05). The findings suggest REM slowing is a robust marker linked to plasma Aβ42/40, highlighting its potential as an early indicator of neuropathological changes. Aligned with prior research, REM slowing may reflect pathological changes driven by amyloid accumulation, contributing to disrupted cholinergic signalling. Longitudinal studies are needed to determine the causal relationship between sleep neurophysiology and plasma biomarkers of AD and neurodegeneration.

There is growing evidence in humans linking the temporal coupling between spindles and slow oscillations during NREM sleep with the overnight stabilization of memories encoded from daytime experiences in humans. However, whether the type and strength of learning influence that relationship is still unknown. Here we tested whether the amount or type of verbal word-pair learning prior to sleep affects subsequent phase-amplitude coupling (PAC) between spindles and slow oscillations (SO). We measured the strength and preferred timing of such coupling in the EEG of 41 healthy human participants over a post-learning and control night to compare intra-individual changes with inter-individual differences. We leveraged learning paradigms of varying word-pair (WP) load: 40 WP learned to a minimum criterion of 60% correct (n = 11); 40 WP presented twice (n = 15); 120 WP presented twice (n = 15). There were no significant differences in the preferred phase or strength between the control and post-learning nights, in all learning conditions. We observed an overnight consolidation effect (improved performance at delayed recall) for the criterion learning condition only, and only in this condition was the overnight change in memory performance significantly positively correlated with the phase of SO-spindle coupling. These results suggest that the coupling of brain oscillations during human NREM sleep is stable traits that are not modulated by the amount of pre-sleep learning, yet are implicated in the sleep-dependent consolidation of memory-especially when overnight gains in memory are observed.

Objectives Our objective was to assess the effect of cognitive-behavioral therapy for insomnia (CBTi) on subjective and objective sleep quality (including sleep spindles) and cognition during a sedative-hypnotics withdrawal program in older adults with insomnia disorder. Methods We performed a two-arm randomized controlled trial (RCT) of a sedative-hypnotic withdrawal plan alone (WPo group) or combined with CBTi (WP + CBTi group) in 47 older adults with insomnia disorder over a sixteen-week period. Our primary outcomes were change in self-reported insomnia severity (Insomnia Severity Index (ISI)), sleep efficiency (SE) from sleep diaries, and change in SE and spindle density from polysomnographic (PSG) recordings collected at baseline and at post-intervention (16 weeks). Secondary outcomes included other sleep changes from PSG, actigraphy and sleep diaries, sleep and mood questionnaires and neuropsychological assessments (manual dexterity, attention/concentration, verbal inhibition, visuo-spatial abilities). Results The withdrawal program was effective in achieving discontinuation and reducing insomnia severity, with similar success with and without CBTi. The combined intervention additionally improved subjective sleep quality and prevented the decrease in subjective sleep duration induced by sedative-hypnotic discontinuation. Neither intervention significantly impacted objective sleep architecture or cognitive performance. Furthermore, reduction in sleep spindle density was observed with combined CBTi and withdrawal, but not with withdrawal alone. Conclusions Both withdrawal alone and sedative-hypnotic withdrawal combined with CBTi effectively facilitated discontinuation and reduced insomnia severity, with the combined intervention further enhancing subjective sleep quality and preserving sleep duration. Although neither approach significantly impacted objective sleep architecture or cognitive performance, the potential reduction in sleep spindle density linked to the combined intervention warrants further investigation.

While sleep disturbances are prevalent in older people and are linked with poor health and cognitive outcomes, screening for the range of sleep disturbances is inefficient and therefore not ideal nor routine in memory and cognition clinic settings. We aimed to develop and validate a new brief self-report questionnaire for easy use within memory and cognition clinics. The design for this study was cross-sectional. Older adults (aged ≥50 in Sydney, Australia) were recruited from a memory and cognition research clinic. Participants (N = 497, mean age 67.7 years, range 50-86, 65.0% female) completed a comprehensive medical, neuropsychological, and mental health assessment, alongside self-report instruments, including existing sleep questionnaires and a new 10-item sleep questionnaire, the CogSleep Screener. We examined the factor structure, convergent validity, internal consistency, and discriminant validity of this novel questionnaire. Using exploratory factor analysis, a 3-factor solution was generated highlighting the factors of Insomnia, Rapid Eye Movement (REM) Symptoms and Daytime Sleepiness. Each factor was significantly correlated with currently used sleep questionnaires for each subdomain (all Spearman rho >0.3, all p < 0.001), suggesting good convergent validity. Internal consistency was also good (Revelle's ω = .74). Receiver operating characteristic curves showed good discriminative ability between participants with and without sleep disturbances (all area under curve >0.7, all p < 0.01). The CogSleep Screener has good psychometric properties in older to elderly adults attending a memory and cognition clinic. The instrument has the potential to be used in memory clinics and other clinical settings to provide quick and accurate screening of sleep disturbances. [Correction added on April 2025, after first publication: The number of participants has been updated and associated statistics have been updated].

This systematic scoping review examines evidence from the last five years on sleep interventions in cognitive healthy older adults and those with mild cognitive impairment. Sleep disturbance has been identified as a potential early, modifiable risk factor for dementia, making it crucial to investigate if these interventions also enhance cognitive function and neurodegenerative biomarkers. Since 2019, research on sleep interventions in older adults with or without cognitive impairment has gradually expanded, especially on non-pharmacological treatments including CBT-I, exercise, and multi-modal interventions, which show promise but require further study to confirm cognitive benefits. Pharmacological interventions have primarily focused on melatonin and orexin antagonists, with long-term safety remaining a concern. Tailored, clinically effective interventions that consider the presence of Alzheimer’s disease biomarkers, such as amyloid, tau, cerebrovascular disease, or alpha-synuclein in key sleep-related circuits, are essential to developing feasible, cost-effective, and scalable treatments for older adults with or without cognitive impairment.

Decrease in cognitive performance after sleep deprivation followed by recovery after sleep suggests its key role, and especially non-rapid eye movement (NREM) sleep, in the maintenance of cognition. It remains unknown whether brain network reorganization in NREM sleep stages N2 and N3 can uniquely be mapped onto individual differences in cognitive performance after a recovery nap following sleep deprivation. Using resting state functional magnetic resonance imaging (fMRI), we quantified the integration and segregation of brain networks during NREM sleep stages N2 and N3 while participants took a 1-hour nap following 24-hour sleep deprivation, compared to well-rested wakefulness. Here, we advance a new analytic framework called the hierarchical segregation index (HSI) to quantify network segregation across spatial scales, from whole-brain to the voxel level, by identifying spatio-temporally overlapping large-scale networks and the corresponding voxel-to-region hierarchy. Our results show that network segregation increased in the default mode, dorsal attention and somatomotor networks during NREM sleep compared to wakefulness. Segregation within the visual, limbic, and executive control networks exhibited N2 versus N3 sleep-specific voxel-level patterns. More segregation during N3 was associated with worse recovery of working memory, executive attention, and psychomotor vigilance after the nap. The level of spatial resolution of network segregation varied among brain regions and was associated with the recovery of performance in distinct cognitive tasks. We demonstrated the sensitivity and reliability of voxel-level HSI to provide key insights into within-region variation, suggesting a mechanistic understanding of how NREM sleep replenishes cognition after sleep deprivation.

Study objectiveTo provide a comprehensive assessment of sleep state misperception in insomnia disorder (INS) and good sleepers (GS) by comparing recordings performed for one night in-lab (PSG and night review) and during several nights at-home (actigraphy and sleep diaries).MethodsFifty-seven INS and 29 GS wore an actigraphy device and filled a sleep diary for two weeks at-home. They subsequently completed a PSG recording and filled a night review in-lab. Sleep perception index (subjective/objective × 100) of sleep onset latency (SOL), sleep duration (TST) and wake duration (TST) were computed and compared between methods and groups.ResultsGS displayed a tendency to overestimate TST and WASO but correctly perceived SOL. The degree of misperception was similar across methods within the GS group. In contrast, INS underestimated their TST and overestimated their SOL both in-lab and at-home, yet the severity of misperception of SOL was larger at-home than in-lab. Finally, INS overestimated WASO only in-lab while correctly perceiving it at-home. While only the degree of TST misperception was stable across methods in INS, misperception of SOL and WASO were dependent on the method used.ConclusionsWe found that GS and INS exhibit opposite patterns and severity of sleep misperception. While the degree of misperception in GS was similar across methods, only sleep duration misperception was reliably detected by both in-lab and at-home methods in INS. Our results highlight that, when assessing sleep misperception in insomnia disorder, the environment and method of data collection should be carefully considered.

Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a widely used non-invasive neuroimaging technique in sleep studies. However, EEG data are strongly influenced by two types of MRI-related artefacts: gradient artefacts (GA) and ballistocardiogram artefacts (BCG). If artefacts correction is suboptimal, the BCG obscures the EEG signals below 20Hz and could make it difficult to investigate sleep oscillations, especially sleep spindles, sleep specific oscillations occurring within 11-16Hz frequency band. We previously demonstrated the utility of beamforming spatial filtering in correcting MRI-related artefacts on EEG. Here, we investigated the use of beamforming spatial filtering for improving the detection of EEG oscillations during sleep, in particular, 1) to accurately estimate single-event spindle EEG power changes, and 2) to demonstrate the potential improvement of fMRI general linear model (GLM) analysis when involving such additional EEG information. We analysed EEG-fMRI data acquired during a recovery nap after sleep deprivation in 20 young healthy participants (12 females, 8 males, age=21.3+/-2.5 years). Based on spindle events (onset and duration) detected by trained sleep scorers on BCG corrected EEG signals through a conventional average artefact subtraction (AAS) method, we compared four different EEG processing steps: non-BCG corrected; AAS BCG corrected; beamforming BCG corrected; beamforming+AAS BCG corrected. These processing steps consist of non-BCG corrected and AAS BCG corrected considered either at the sensor level or at the source-level (after beamformer localization) to evaluate the impact of the BCG artefact on the detection of spindle activity. Then we further investigated four different fMRI GLM approaches using 1) the spindle onset and duration (GLM1), 2) spindle onset, duration, and parametric modulation of single-spindle power change from the Cz electrode of the AAS BCG corrected data (GLM2), 3) spindle onset, duration, and parametric modulation of single-spindle power change from the beamforming+AAS BCG corrected (GLM3) and 4) spindle onset, duration, and parametric modulation of single-spindle power change from the beamforming BCG corrected data (GLM4). We found that the beamforming approach did not only attenuate the BCG artefacts, but also recovered sleep spindle activity occurring during NREM sleep. Furthermore, this beamforming approach allowed us to accurately estimate single-event power change of each spindle in the source space when compared to the channel level analysis, and therefore to further improve the specificity of fMRI GLM analysis, better localizing the recruited brain regions during spindles. Our findings show the benefit of applying beamforming source imaging technique to EEG-fMRI acquired during sleep. We demonstrate that this approach would be beneficial especially for long EEG-fMRI data acquisitions (i.e., sleep, resting-state), when the BCG correction becomes problematic due to inherent dynamic changes of heart rates. Our findings extend previous work regarding the application of the source imaging to the sleep EEG-fMRI. Combining with this advanced methodology and analysis, sleep EEG-fMRI will help us better understand the functional roles of human sleep. ### Competing Interest Statement The authors have declared no competing interest.

Sleep is essential for optimal functioning and health. Interconnected to multiple biological, psychological and socio-environmental factors (i.e., biopsychosocial factors), the multidimensional nature of sleep is rarely capitalized on in research. Here, we deployed a data-driven approach to identify sleep-biopsychosocial profiles that linked self-reported sleep patterns to inter-individual variability in health, cognition, and lifestyle factors in 770 healthy young adults. We uncovered five profiles, including two profiles reflecting general psychopathology associated with either reports of general poor sleep or an absence of sleep complaints (i.e., sleep resilience) respectively. The three other profiles were driven by sedative-hypnotics-use and social satisfaction, sleep duration and cognitive performance, and sleep disturbance linked to cognition and mental health. Furthermore, identified sleep-biopsychosocial profiles displayed unique patterns of brain network organization. In particular, somatomotor network connectivity alterations were involved in the relationships between sleep and biopsychosocial factors. These profiles can potentially untangle the interplay between individuals' variability in sleep, health, cognition and lifestyle — equipping research and clinical settings to better support individual’s well-being.

Rationale: High rates of insomnia in older adults lead to widespread benzodiazepine (BZD) and benzodiazepine receptor agonist (BZRA) use, even though chronic use has been shown to disrupt sleep regulation and impact cognition. Little is known about sedative-hypnotic effects on NREM slow oscillations (SO) and spindles, including their coupling, which is crucial for memory, especially in the elderly. Objectives: Our objective was to investigate the effect of chronic sedative-hypnotic use on sleep macro-architecture, EEG relative power, as well as SO and spindle characteristics and coupling. Methods: One hundred and one individuals (66.05 +/- 5.84 years, 73% female) completed a one-night study and were categorized into three groups: good sleepers (GS, n=28), individuals with insomnia (INS, n=26) or individuals with insomnia who chronically use either BZD or BZRA to manage their insomnia difficulties (MED, n=47; dose equivalent in Diazepam: 6.1 +/- 3.8 mg/week). We performed a comprehensive comparison of sleep architecture, EEG relative spectrum, and associated brain oscillatory activities, focusing on NREM brain oscillations crucial for sleep-dependent memory consolidation (i.e., SO and spindles) and their temporal coupling. Results: Chronic use of BZD/BZRA worsened sleep architecture and spectral activity compared to older adults with and without insomnia disorder. The use of BZD/BZRAs also altered the characteristics of sleep-related brain oscillations and their synchrony. An exploratory interaction model suggested that BZD use exacerbated sleep alterations compared to BZRA, and higher BZD/BZRA dosage worsened alteration in sleep micro-architecture and EEG spectrum. Conclusions: Our results suggest that chronic use of sedative-hypnotics is detrimental to sleep when compared to drug-free GS and INS. Such alteration of sleep regulation; at the macro and micro-architectural levels; may contribute to the reported association between sedative-hypnotic use and cognitive impairment in older adults. Keywords: benzodiazepine, sleep, brain oscillation, ageing ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by grants from the Canadian Institutes of Health Research (MOP 142191/ PJT 153115) to TDV and JPG, from the Natural Sciences and Engineering Research Council of Canada to TDV, from the Centre de Recherche de l Institut Universitaire de Geriatrie de Montreal and from Concordia University to TDV. LB has been supported by the CIHR-SPOR Chair in Innovative, Patient-Oriented, Behavioural Clinical Trials, Concordia University. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: the Concordia University Human Research Ethics Committee of Concordia University gave ethical approval for this work the Comite d Ethique de la Recherche of the Institut Universitaire de Geriatrie de Montreal gave ethical approval for this work I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors