Contact-free radar recordings of body movement can reflect ultradian dynamics of sleep.

This work aimed to evaluate if a contact-free radar sensor can be used to observe ultradian patterns in sleep physiology, by way of a data processing tool known as Locomotor Inactivity During Sleep (LIDS). LIDS was designed as a simple transformation of actigraphy recordings of wrist movement, meant to emphasise and enhance the contrast between movement and non-movement and to reveal patterns of low residual activity during sleep that correlate with ultradian REM/NREM cycles. We adapted the LIDS transformation for a radar that detects body movements without direct contact with the subject and applied it to a dataset of simultaneous recordings with polysomnography, actigraphy, and radar from healthy young adults (n = 12, four nights of polysomnography per participant). Radar and actigraphy-derived LIDS signals were highly correlated with each other (r > 0.84), and the LIDS signals were highly correlated with reduced-resolution polysomnographic hypnograms (rradars >0.80, ractigraph >0.76). Single-harmonic cosine models were fitted to LIDS signals and hypnograms; significant differences were not found between their amplitude, period, and phase parameters. Mixed model analysis revealed similar slopes of decline per cycle for radar-LIDS, actigraphy-LIDS, and hypnograms. Our results indicate that the LIDS technique can be adapted to work with contact-free radar measurements of body movement; it may also be generalisable to data from other body movement sensors. This novel metric could aid in improving sleep monitoring in clinical and real-life settings, by providing a simple and transparent way to study ultradian dynamics of sleep using nothing more than easily obtainable movement data.

Dysfunctional Overnight Memory Consolidation in Patients with Schizophrenia in Comparison to Healthy Controls: Disturbed Slow-Wave Sleep as Contributing Factor?

INTRODUCTION: Memory deficiency has been shown in schizophrenia patients, but results on the role of sleep parameters in overnight consolidation of associative verbal memory are still missing. Therefore, the aim of our study was to elucidate underlying processes of impaired sleep-related consolidation of associative word pairs in schizophrenia including standard sleep parameters as well as sleep spindle counts and spectral analysis. METHODS: Eighteen stably medicated schizophrenia patients and 24 healthy age-matched controls performed an associative declarative memory task before and after polysomnographic recordings. Part of the participants expected verbal associative memory testing in the morning, while the others did not. Furthermore, participants filled in self-rating questionnaires of schizophrenia-typical experiences (Eppendorf Schizophrenia Inventory [ESI] and Psychotic Symptom Rating Scale). RESULTS: Schizophrenia patients performed worse in verbal declarative memory in the evening as well as in overnight consolidation (morning compared to evening performance). While duration of slow-wave sleep was nearly comparable between groups, schizophrenia patients showed lower sleep spindle count, reduced delta power during slow-wave sleep, and reduced spindle power during the slow oscillation (SO) up-state. In healthy but not in schizophrenia patients, a linear relationship between overnight memory consolidation and slow-wave sleep duration as well as delta power was evident. No significant effect with respect to the expectation of memory retrieval was evident in our data. Additionally, we observed a negative linear relationship between total number of sleep spindles and ESI score in healthy participants. DISCUSSION/CONCLUSION: As expected, schizophrenia patients showed deficient overnight verbal declarative memory consolidation as compared to healthy controls. Reduced sleep spindles, delta power, and spindle power during the SO up-state may link sleep and memory deficiency in schizophrenia. Additionally, the absence of a linear relationship between sleep-related memory consolidation and slow-wave sleep as well as delta power suggests further functional impairments in schizophrenia. Note that this conclusion is based on observational data. Future studies should investigate if stimulation of delta waves during sleep could improve memory performance and thereby quality of life in schizophrenia.

Tracked and self-reported nighttime smartphone use, general health, and healthcare utilization: results from the SmartSleep Study.

STUDY OBJECTIVES: Nighttime smartphone use is an increasing public health concern. We investigated whether nighttime smartphone use is associated with general health and primary healthcare utilization. METHODS: Four thousand five hundred and twenty individuals (age 35.6 ±â€…9.7 years, 35% male) provided self-reported information on smartphone use frequency, symptoms of depression, and general health (one-item perceived health and cross-symptom composite score). A subset of the study sample (n = 3221) tracked their nighttime smartphone use. Primary healthcare utilization, i.e. the number of weeks in which at least one service from the patient's general practitioner (GP) was billed in 2020, was extracted from Danish population registries. Statistical analysis comprised logistic and multiple linear regression, controlling for sociodemographics. RESULTS: Three hundred and nineteen individuals (7%) reported using their smartphone almost every night or more. More frequent self-reported nighttime smartphone use was associated with poor general health across all measures. Using the smartphone almost every night or more was associated with 2.8 [95% CI: 1.9, 4.1] fold higher odds of reporting poor health and with an average of 1.4 [95% CI: 0.7, 2.1] additional GP utilizations per year compared to no use. Associations were also found for the cross-symptom composite score across all symptoms. Further adjustment for symptoms of depression attenuated some associations. Smartphone use towards the end of the sleep period (sleep-offset use) was associated with poorer self-reported general health, but not with healthcare utilization. CONCLUSIONS: Nighttime smartphone use frequency is associated with poor general health and healthcare utilization. Further studies should investigate the underlying causal structure and nighttime smartphone use as a transdiagnostic intervention target.

Using cross-recurrence quantification analysis to compute similarity measures for time series of unequal length with applications to sleep stage analysis.

Comparing time series of unequal length requires data processing procedures that may introduce biases. This article describes, validates, and applies Cross-Recurrence Quantification Analysis (CRQA) to detect and quantify correlation and coupling among time series of unequal length without prior data processing. We illustrate and validate this application using continuous and discrete data from a model system (study 1). Then we use the method to re-analyze the Sleep Heart Health Study (SHHS), a rare large dataset comprising detailed physiological sleep measurements acquired by in-home polysomnography. We investigate whether recurrence patterns of ultradian NREM/REM sleep cycles (USC) predict mortality (study 2). CRQA exhibits better performance compared with traditional approaches that require trimming, stretching or compression to bring two time series to the same length. Application to the SHHS indicates that recurrence patterns linked to stability of USCs are associated with all-cause mortality even after controlling for other sleep parameters, health, and sociodemographics. We suggest that CRQA is a useful tool for analyzing categorical time series, where the underlying structure of the data is unlikely to result in matching data points-such as ultradian sleep cycles.

Self-reported and tracked nighttime smartphone use and their association with overweight and cardiometabolic risk markers.

Nighttime smartphone use is associated with sleep problems, which in turn have a bidirectional association with overweight. We aim to investigate whether nighttime smartphone use and sleep are related to overweight and metabolic dysfunction in adult populations. We used data from three population samples (aged 16-89) from the SmartSleep Study, which included survey data (N = 29,838), high-resolution tracking data (N = 3446), follow-up data (N = 1768), and cardiometabolic risk markers (N = 242). Frequent self-reported nighttime smartphone use was associated with 51% higher odds (95% CI: 1.32; 1.70) of overweight compared with no use. Tracked nighttime smartphone use was also associated with overweight. Similar results were found for obesity as an outcome. No consistent associations were found between nighttime smartphone use and cardiometabolic risk markers in a small subsample of healthy young women. Poor sleep quality (vs. good sleep quality) was associated with overweight (OR = 1.19, 85% CI: 1.10; 1.28). Overall, frequent nighttime smartphone use was consistently associated with overweight and a higher BMI across diverse population samples. The bidirectional interplay between nighttime smartphone use, sleep, and overweight may create a vicious circle of metabolic dysfunction over time. Therefore, nighttime smartphone use may be a potential target point for public health interventions to reduce overweight at the population level.

Nighttime smartphone use, sleep quality, and mental health: investigating a complex relationship.

STUDY OBJECTIVES: This study investigated the complex relationship between nighttime smartphone use, sleep, and mental health among adult populations in Denmark. METHODS: Data from three interconnected samples (aged 16-89 years) from the SmartSleep Study included 5798 individuals with survey and register data; 4239 individuals also provided high-resolution smartphone tracking data. Logistic regression models and causal discovery algorithms, which suggest possible causal pathways consistent with the underlying data structure, were used to infer the relationship between self-reported and tracked nighttime smartphone use, self-reported sleep quality, mental health indicators, and register-based psychotropic medication use. RESULTS: Frequent self-reported nighttime smartphone use was associated with high perceived stress (OR: 2.24, 95% CI = 1.42 to 3.55) and severe depressive symptoms (OR: 2.96, 95% CI = 2.04 to 4.28). We found no clear associations between tracked nighttime smartphone use and mental health outcomes, except for the cluster that used their smartphones repeatedly during the sleep period, which was associated with severe depressive symptoms (OR = 1.69, 95% CI = 1.24 to 2.31). Poor sleep quality (vs. good sleep quality) was associated with high perceived stress (OR = 5.07, 95% CI = 3.72 to 6.90), severe depressive symptoms (OR = 9.67, 95% CI = 7.09 to 13.19), and psychotropic medication use (OR = 2.13, 95% CI = 1.36 to 3.35). The causal discovery models suggest that nighttime smartphone use affects mental health through both problematic smartphone use and poor sleep quality. CONCLUSION: The complex relationship between nighttime smartphone use, sleep, and poor mental health may create a vicious circle over time, and nighttime smartphone use may constitute a potential leverage point for public health interventions aimed at improving sleep and mental health.

Cohort profile: The SmartSleep Study, Denmark, combining evidence from survey, clinical and tracking data.

PURPOSE: The SmartSleep Study is established to comprehensively assess the impact of night-time smartphone use on sleep patterns and health. An innovative combination of large-scale repeated survey information, high-resolution sensor-driven smartphone data, in-depth clinical examination and registry linkage allows for detailed investigations into multisystem physiological dysregulation and long-term health consequences associated with night-time smartphone use and sleep impairment. PARTICIPANTS: The SmartSleep Study consists of three interconnected data samples, which combined include 30 673 individuals with information on smartphone use, sleep and health. Subsamples of the study population also include high-resolution tracking data (n=5927) collected via a customised app and deep clinical phenotypical data (n=245). A total of 7208 participants are followed in nationwide health registries with full data coverage and long-term follow-up. FINDINGS TO DATE: We highlight previous findings on the relation between smartphone use and sleep in the SmartSleep Study, and we evaluate the interventional potential of the citizen science approach used in one of the data samples. We also present new results from an analysis in which we use 803 000 data points from the high-resolution tracking data to identify clusters of temporal trajectories of night-time smartphone use that characterise distinct use patterns. Based on these objective tracking data, we characterise four clusters of night-time smartphone use. FUTURE PLANS: The unprecedented size and coverage of the SmartSleep Study allow for a comprehensive documentation of smartphone activity during the entire sleep span. The study has been expanded by linkage to nationwide registers, which allow for further investigations into the long-term health and social consequences of night-time smartphone use. We also plan new rounds of data collection in the coming years.

Couple Relationships Are Associated With Increased REM Sleep-A Proof-of-Concept Analysis of a Large Dataset Using Ambulatory Polysomnography.

Background/Objectives: Rapid Eye Movement (REM) sleep is associated with memory consolidation and several health effects including stress response, mental health, and longevity. Recently, it has been shown that regularly co-sleeping couples have increased and stabilized REM sleep when co-sleeping as compared to sleeping individually. However, it remained unclear whether this is due to a specific effect of altering the usual sleeping environment by partner deprivation or due to a generalizable REM-sleep promoting effect of couple relationships. The present study aims to clarify this ambiguity. Methods: Married or never married individuals were taken from the Sleep Heart Health Study (n = 5,804) and matched regarding sociodemographic and health parameters. Matching was done using propensity score matching (1:1, nearest neighbor) and resulted in two groups of n = 69 each (married vs. never married). After confirmation of successful matching, samples were compared regarding REM sleep and other polysomnographic parameters (paired Students t-tests or Wilcoxon signed-rank tests). Results: Married individuals showed significantly higher levels of total and relative REM sleep as compared to never married individuals (all p's ≤ 0.003). Neither other sleep stages nor REM-sleep fragmentation differed between groups (all p's ≥ 0.29). Results regarding number of sleep cycles were ambiguous. Conclusion: This is the first between-subjects study to show that couple relationships are associated with increased REM sleep. This finding represents a necessary (but not sufficient) condition for the previously hypothesized self-enhancing feedback loop of REM sleep and sociality as well as for REM-sleep promotion as a mechanism through which couple relationships prevent mental illness.

Self-control or social control - what determines sleep hygiene in bed-sharing couples?

OBJECTIVES: To investigate intimate partners' impact on sleep hygiene with focus on the temporal dimension and differential predictors of sleep hygiene in co-sleepers and individual sleepers. MATERIAL AND METHODS: Habitual co-sleepers and individual sleepers (n=102) completed a cross-sectional, self-report, in-lab, digital survey on sleep hygiene, habitual sleeping arrangement, self-control, depressiveness, and sociodemographic parameters. RESULTS: The relationship between sleeping arrangement and sleep hygiene in co-sleepers was time-dependent with an initial steep incline and a subsequent plateau at approximately one year of co-sleeping routine. Co-sleepers with more than one year of unaltered sleeping arrangement had significantly better sleep hygiene than co-sleepers with less than one-year or individual sleepers. More than one-year continuity of the sleeping arrangement moreover robustly predicted sleep hygiene in co-sleepers whereas self-control was the dominant predictor in individual sleepers. CONCLUSION: Amongst others, our findings support the idea that insomnia treatment could be improved by becoming sensitive to the habitual sleeping arrangement.

Psychotic-like experiences in patients with insomnia or sleep apnea: associations with sleep parameters.

OBJECTIVES: There are strong links between sleep and psychotic-like experiences (PLE), such as magical ideations or persecutory ideas. Sleep disturbances seem to play an important role in the occurrence of such symptoms, but studies investigating PLE in patients with sleep disorders are lacking. METHODS: We studied 24 subjects with insomnia disorder (41 ± 13 years) and 47 participants with obstructive sleep apnea (OSA, 47 ± 11 years) in the sleep laboratory and 33 healthy controls. Sleep in patients with sleep disorders was recorded and scored according to standard criteria of the American Academy of Sleep Medicine. PLE were measured by the Magical Ideation Scale (MIS, short form with 10 items) and by the Peters et al., Delusions Inventory (PDI, 21 items). Additionally, cognitive tests and further psychological self-rating tests such as the Beck Depression Inventory (BDI) and the Pittsburgh Sleep Quality Index (PSQI) were administered. RESULTS: Patients with insomnia had significantly higher scores of magical and delusional ideations compared to healthy controls. Sleep apnea patients showed a tendency of a higher score of delusional beliefs in comparison to controls. Magical ideations in insomnia subjects were significantly negatively correlated with the number of sleep spindles. In a subgroup of insomnia patients without antidepressants, delusional beliefs were negatively associated with rapid eye movement (REM)-sleep. CONCLUSIONS: As there are indications that diminutions of sleep spindles are a biomarker for dysfunctional thalamo-cortical circuits underlying the neuropathology of psychosis, we conclude that there might be a sub-group of insomnia patients with fewer sleep spindles which is more vulnerable to developing a psychotic disorder in the future.

REM density is associated with treatment response in major depression: Antidepressant pharmacotherapy vs. psychotherapy.

Major depression is one of the most common psychiatric illnesses. Interestingly, a few studies have indicated the existence of depression subgroups, which respond differently to the available treatment options. Previously, sleep abnormalities have been suggested to indicate amenability to different treatment regimens. Thereby, especially REM-sleep parameters seem to play a prominent role, and REM-sleep dysregulation has been repeatedly discussed as a potential endophenotype of depression. With that said, estimating therapy outcome in order to choose the best line of treatment is of utmost importance to patients suffering from depression. The present study looks deeper into these clues by investigating the capability of polysomnographic sleep parameters to predict treatment response in depressed patients to either pharmacotherapy or psychotherapy. Moderately to severely depressed patients (n = 38) were randomly assigned to either psychotherapy (i.e. interpersonal psychotherapy) or pharmacotherapy (i.e., monotherapy with selective serotonin reuptake inhibitors, SSRI, or selective serotonin noradrenalin reuptake inhibitors, SSNRI). Prior to treatment, all patients underwent polysomnography in the sleep laboratory. After treatment, responders and non-responders of both treatment groups were compared regarding their baseline sleep parameters. Higher baseline REM density, i.e. the amount of rapid eye movements during REM sleep, predicted better response to antidepressant pharmacotherapy. In the psychotherapy group, the effect seemed reversed but was not statistically significant. No other sleep parameter predicted treatment response. Our findings support the notion that REM-sleep dysregulation is indeed indicative of a distinct endophenotype of depression and that pharmacotherapy with SSRI/SSNRI might be superior to psychotherapy in these patients.

Losartan Improves Memory, Neurogenesis and Cell Motility in Transgenic Alzheimer's Mice.

Angiotensin receptor blockers (ARBs) have demonstrated multiple neuroprotective benefits in Alzheimer's disease (AD) models. However, their beneficial effects on memory deficits, cholinergic activity, neurogenesis and Amyloid beta (Aß) clearance reveal significant interstudy variability. The delivery route can impact not only delivery but also targeting and therapeutic efficacy of ARBs. Our previous findings on the beneficial effects of intranasally delivered losartan in the APP/PS1 model of AD prompted us to explore the influence of the delivery route by employing here the systemic administration of losartan. Consistent with our previous results with intranasal losartan, repeated intraperitoneal administration (10 mg/kg) resulted in a remarkable decrease in Aß plaques and soluble Aß42, as well as inflammatory cytokines (IL-2, IL-6 and TNFα). The Aß reduction can be ascribed to its facilitated degradation by neprilysin and diminished generation by BACE1. Losartan increased neurogenesis in vivo and in vitro and improved migratory properties of astrocytes isolated from adult transgenic AD mice. In summary, this data together with our previous results suggest therapeutic features of losartan which are independent of delivery route. The improvement of cell motility of Aß-affected astrocytes by losartan deserves further in vivo investigation, which may lead to new strategies for AD treatment.

Bed-Sharing in Couples Is Associated With Increased and Stabilized REM Sleep and Sleep-Stage Synchronization.

BACKGROUND/OBJECTIVES: Sharing the bed with a partner is common among adults and impacts sleep quality with potential implications for mental health. However, hitherto findings are contradictory and particularly polysomnographic data on co-sleeping couples are extremely rare. The present study aimed to investigate the effects of a bed partner's presence on individual and dyadic sleep neurophysiology. METHODS: Young healthy heterosexual couples underwent sleep-lab-based polysomnography of two sleeping arrangements: individual sleep and co-sleep. Individual and dyadic sleep parameters (i.e., synchronization of sleep stages) were collected. The latter were assessed using cross-recurrence quantification analysis. Additionally, subjective sleep quality, relationship characteristics, and chronotype were monitored. Data were analyzed comparing co-sleep vs. individual sleep. Interaction effects of the sleeping arrangement with gender, chronotype, or relationship characteristics were moreover tested. RESULTS: As compared to sleeping individually, co-sleeping was associated with about 10% more REM sleep, less fragmented REM sleep (p = 0.008), longer undisturbed REM fragments (p = 0.0006), and more limb movements (p = 0.007). None of the other sleep stages was significantly altered. Social support interacted with sleeping arrangement in a way that individuals with suboptimal social support showed the biggest impact of the sleeping arrangement on REM sleep. Sleep architectures were more synchronized between partners during co-sleep (p = 0.005) even if wake phases were excluded (p = 0.022). Moreover, sleep architectures are significantly coupled across a lag of ± 5min. Depth of relationship represented an additional significant main effect regarding synchronization, reflecting a positive association between the two. Neither REM sleep nor synchronization was influenced by gender, chronotype, or other relationship characteristics. CONCLUSION: Depending on the sleeping arrangement, couple's sleep architecture and synchronization show alterations that are modified by relationship characteristics. We discuss that these alterations could be part of a self-enhancing feedback loop of REM sleep and sociality and a mechanism through which sociality prevents mental illness.

Slow-wave sleep predicts long-term social functioning in severe mental illness.

Sleep's relevance for long-term social functioning in psychiatric disorders has been widely overlooked so far. Here, we investigate social functioning in a transdiagnostic sample of 31 patients with severe mental illness, namely schizophrenia (n = 15) or major depression (n = 16), in relation to their polysomnographic sleep characteristics 6 (± 2.4) years earlier. In addition, cognitive performance at follow-up and clinical characteristics (i.e., severity of disorder-related symptoms and number of hospitalizations between baseline and follow-up) are assessed. Multiple regression analysis results in a model with slow-wave sleep (SWS) and number of hospitalizations as significant predictors accounting for 50% (R2 = 0.507; p <0.001) of the variance in social functioning. SWS remains a significant predictor of long-term social functioning throughout a series of refining analyses which also identify baseline functioning as an additional significant predictor, whereas diagnosis is non-significant. Also, the effect of SWS on social functioning is not mediated by number of hospitalizations as assessed by a bootstrapped mediation analysis. We thus conclude that duration of slow-wave sleep is a powerful predictor of long-term social outcome in psychiatric disorders. Also, we discuss the relevance of verbal memory, symptom severity, and diagnostic category for social functioning. Future studies should test this finding by using a prospective design, a bigger sample, optimized predictor variables, and a more diverse set of diagnoses. Moreover, it should be explored whether or not treating sleep disturbances in psychiatric illnesses independently improves long-term social functioning.

"Are We in Sync with Each Other?" Exploring the Effects of Cosleeping on Heterosexual Couples' Sleep Using Simultaneous Polysomnography: A Pilot Study.

The present study aimed to explore dynamic and interactive aspects of cosleep in heterosexual couples. The sample consisted of eight young healthy adults who belonged to four heterosexual couples with a good relationship quality and a history of cosleeping. All individuals underwent simultaneous polysomnography in a sleep laboratory for four nights in which they slept individually and with their partner. Also, a sleep protocol of subjective sleep measures was completed. Statistical analyses included cross recurrence quantification analysis to assess synchronization during sleep. Cosleeping was associated with better subjective sleep quality, increased total sleep time, sleep efficiency, total slow wave sleep, and REM sleep. Sleep stages were more synchronized during cosleep independent of awakenings. Cardiorespiratory measures remained unchanged. The results indicate that young healthy couples in good relationships benefit from cosleeping on a subjective and objective level. Combining simultaneous polysomnography and cross recurrence quantification analysis is a promising method to study dynamic and interactive aspects of cosleep possibly leading to deeper understanding of the role of sleep for sociality, the nature of REM sleep, and the partner as a social zeitgeber. Moreover, clinical implications may arise from these findings.