Tau and ß-Amyloid Burden Predict Actigraphy-Measured and Self-Reported Impairment and Misperception of Human Sleep.

Alzheimer's disease is associated with poor sleep, but the impact of tau and ß-amyloid (Aß) pathology on sleep remains largely unknown. Here, we test the hypothesis that tau and Aß predict unique impairments in objective and self-perceived human sleep under real-life, free-living conditions. Eighty-nine male and female cognitively healthy older adults received 18F-FTP-tau and 11C-PIB-Aß PET imaging, 7 nights of sleep actigraphy and questionnaire measures, and neurocognitive assessment. Tau burden, but not Aß, was associated with markedly worse objective sleep. In contrast, Aß and tau were associated with worse self-reported sleep quality. Of clinical relevance, Aß burden predicted a unique perceptual mismatch between objective and subject sleep evaluation, with individuals underestimating their sleep. The magnitude of this mismatch was further predicted by worse executive function. Thus, early-stage tau and Aß deposition are linked with distinct phenotypes of real-world sleep impairment, one that includes a cognitive misperception of their own sleep health.SIGNIFICANCE STATEMENT Alzheimer's disease is associated with sleep disruption, often before significant memory decline. Thus, real-life patterns of sleep behavior have the potential to serve as a window into early disease progression. In 89 cognitive healthy older adults, we found that tau burden was associated with worse wristwatch actigraphy-measured sleep quality, and that both tau and ß-amyloid were independently predictive of self-reported sleep quality. Furthermore, individuals with greater ß-amyloid deposition were more likely to underestimate their sleep quality, and sleep quality underestimation was associated with worse executive function. These data support the role of sleep impairment as a key marker of early Alzheimer's disease, and offer the possibility that actigraphy may be an affordable and scalable tool in quantifying Alzheimer's disease-related behavioral changes.

Can stimulants make you smarter, despite stealing your sleep?

Nonmedical use of psychostimulants for cognitive enhancement is widespread and growing in neurotypical individuals, despite mixed scientific evidence of their effectiveness. Sleep benefits cognition, yet the interaction between stimulants, sleep, and cognition in neurotypical adults has received little attention. We propose that one effect of psychostimulants, namely decreased sleep, may play an important and unconsidered role in the effect of stimulants on cognition. We discuss the role of sleep in cognition, the alerting effects of stimulants in the context of sleep loss, and the conflicting findings of stimulants for complex cognitive processes. Finally, we hypothesize that sleep may be one unconsidered factor in the mythology of stimulants as cognitive enhancers and propose a methodological approach to systematically assess this relation.

Heart Rate Variability During REM Sleep is Associated with Reduced Negative Memory Bias.

Emotional memories change over time, but the mechanisms supporting this change are not well understood. Memory consolidation during sleep has been shown to selectively prioritize negative experiences while forgetting neutral memories. Whereas studies examining the role of vagal heart rate variability (HRV) during waking in memory consolidation have shown that vagal HRV is associated with enhanced memory of positive experiences at the expense of negative ones. However, no studies have explored how HRV during sleep contributes to emotional memory processing. Accordingly, we aimed to investigate the neural and vagal contributions during sleep to the processing of neutral and negative memories. To do so, we examined the impact of pharmacological vagal suppression, using zolpidem, on overnight emotional memory consolidation in a double-blind, placebo-controlled, within-subject, cross-over design. Thirty-two participants encoded neutral and negative pictures in the morning, then were tested on picture recognition before and after a night of sleep. Zolpidem or a placebo drug were administered in the evening before overnight sleep, monitored with electroencephalography and electrocardiography. Results showed that higher vagal HRV in Non-Rapid Eye Movement Sleep slow wave sleep (NREM SWS) and Rapid Eye Movement Sleep (REM) was associated with greater overnight improvement for neutral pictures in the placebo condition. Additionally, higher vagal HRV during REM was associated with an emotional memory tradeoff (i.e., greater memory for neutral at the expense of negative images), indicating a potential role for REM vagal HRV in forming a positive memory bias overnight. As previously reported, zolpidem reduced vagal HRV during SWS and increased NREM sigma power, and this vagal suppression eliminated the positive memory bias. Lastly, we used a stepwise linear mixed effects regression framework to investigate how NREM sigma power and vagal HRV during REM independently explained the variance in the emotional memory tradeoff effect and found that including vagal HRV significantly improved the model's fit. Overall, these results suggest that neural and vagal signals synergistically interact in the processing of emotional memories, with REM vagal HRV playing a specific role in contributing to the positive memory bias.

Using Wearable Skin Temperature Data to Advance Tracking and Characterization of the Menstrual Cycle in a Real-World Setting.

The menstrual cycle is a loop involving the interplay of different organs and hormones, with the capacity to impact numerous physiological processes, including body temperature and heart rate, which in turn display menstrual rhythms. The advent of wearable devices that can continuously track physiological data opens the possibility of using these prolonged time series of skin temperature data to noninvasively detect the temperature variations that occur in ovulatory menstrual cycles. Here, we show that the menstrual skin temperature variation is better represented by a model of oscillation, the cosinor, than by a biphasic square wave model. We describe how applying a cosinor model to a menstrual cycle of distal skin temperature data can be used to assess whether the data oscillate or not, and in cases of oscillation, rhythm metrics for the cycle, including mesor, amplitude, and acrophase, can be obtained. We apply the method to wearable temperature data collected at a minute resolution each day from 120 female individuals over a menstrual cycle to illustrate how the method can be used to derive and present menstrual cycle characteristics, which can be used in other analyses examining indicators of female health. The cosinor method, frequently used in circadian rhythms studies, can be employed in research to facilitate the assessment of menstrual cycle effects on physiological parameters, and in clinical settings to use the characteristics of the menstrual cycles as health markers or to facilitate menstrual chronotherapy.

Menstrual Cycle Variations in Wearable-Detected Finger Temperature and Heart Rate, But Not in Sleep Metrics, in Young and Midlife Individuals.

Most studies about the menstrual cycle are laboratory-based, in small samples, with infrequent sampling, and limited to young individuals. Here, we use wearable and diary-based data to investigate menstrual phase and age effects on finger temperature, sleep, heart rate (HR), physical activity, physical symptoms, and mood. A total of 116 healthy females, without menstrual disorders, were enrolled: 67 young (18-35 years, reproductive stage) and 53 midlife (42-55 years, late reproductive to menopause transition). Over one menstrual cycle, participants wore Oura ring Gen2 to detect finger temperature, HR, heart rate variability (root mean square of successive differences between normal heartbeats [RMSSD]), steps, and sleep. They used luteinizing hormone (LH) kits and daily rated sleep, mood, and physical symptoms. A cosinor rhythm analysis was applied to detect menstrual oscillations in temperature. The effect of menstrual cycle phase and group on all other variables was assessed using hierarchical linear models. Finger temperature followed an oscillatory trend indicative of ovulatory cycles in 96 participants. In the midlife group, the temperature rhythm's mesor was higher, but period, amplitude, and number of days between menses and acrophase were similar in both groups. In those with oscillatory temperatures, HR was lowest during menses in both groups. In the young group only, RMSSD was lower in the late-luteal phase than during menses. Overall, RMSSD was lower, and number of daily steps was higher, in the midlife group. No significant menstrual cycle changes were detected in wearable-derived or self-reported measures of sleep efficiency, duration, wake-after-sleep onset, sleep onset latency, or sleep quality. Mood positivity was higher around ovulation, and physical symptoms manifested during menses. Temperature and HR changed across the menstrual cycle; however, sleep measures remained stable in these healthy young and midlife individuals. Further work should investigate over longer periods whether individual- or cluster-specific sleep changes exist, and if a buffering mechanism protects sleep from physiological changes across the menstrual cycle.

Viability of an Early Sleep Intervention to Mitigate Poor Sleep and Improve Well-being in the COVID-19 Pandemic: Protocol for a Feasibility Randomized Controlled Trial.

BACKGROUND: The COVID-19 pandemic has led to drastic increases in the prevalence and severity of insomnia symptoms. These increases in insomnia complaints have been paralleled by significant decreases in well-being, including increased symptoms of depression, anxiety, and suicidality and decreased quality of life. However, the efficacy and impact of early treatment of insomnia symptoms on future sleep and well-being remain unknown. OBJECTIVE: Here, we present the framework and protocol for a novel feasibility, pilot study that aims to investigate whether a brief telehealth insomnia intervention targeting new insomnia that developed during the pandemic prevents deterioration of well-being, including symptoms of insomnia, depression, anxiety, suicidality, and quality of life. METHODS: The protocol details a 2-arm randomized controlled feasibility trial to investigate the efficacy of a brief, telehealth-delivered, early treatment of insomnia and evaluate its potential to prevent deterioration of well-being. Participants with clinically significant insomnia symptoms that began during the pandemic were randomized to either a treatment group or a 28-week waitlist control group. Treatment consists of 4 telehealth sessions of cognitive behavioral therapy for insomnia (CBT-I) delivered over 5 weeks. All participants will complete assessments of insomnia symptom severity, well-being, and daily habits checklist at baseline (week 0) and at weeks 1-6, 12, 28, and 56. RESULTS: The trial began enrollment on June 3, 2020 and closed enrollment on June 17, 2021. As of October 2021, 49 participants had been randomized to either immediate treatment or a 28-week waitlist; 23 participants were still active in the protocol. CONCLUSIONS: To our knowledge, this protocol would represent the first study to test an early sleep intervention for improving insomnia that emerged during the COVID-19 pandemic. The findings of this feasibility study could provide information about the utility of CBT-I for symptoms that emerge in the context of other stressors before they develop a chronic course and deepen understanding of the relationship between sleep and well-being. TRIAL REGISTRATION: ClinicalTrials.gov NCT04409743; https://clinicaltrials.gov/ct2/show/NCT04409743. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34409.