Predictors for achieving optimal sleep in healthy children: Exploring sleep patterns in a sleep extension trial.

STUDY OBJECTIVES: Earlier bedtimes can help some children get more sleep, but we don't know which children, or what features of their usual sleep patterns could predict success with this approach. Using data from a randomized crossover trial of sleep manipulation, we sought to determine this. METHODS: Participants were 99 children aged 8-12years (49.5% female) with no sleep disturbances. Sleep was measured by actigraphy at baseline and over a restriction or extension week (1 hour later or earlier bedtime respectively), randomly allocated and separated by a washout week. Data were compared between baseline (week 1) and extension weeks only (week 3 or 5), using linear or logistic regression analyses as appropriate, controlling for randomization order. RESULTS: One hour less total sleep time than average at baseline predicted 29.7 minutes (95% CI: 19.4, 40.1) of sleep gained and 3.45 (95% CI: 1.74, 6.81) times higher odds of successfully extending sleep by >30 minutes. Per standardized variable, less total sleep time and a shorter sleep period time were the strongest predictors (significant odds ratios (ORs) of 2.51 and 2.28, respectively). Later sleep offset, more variability in sleep timing and lower sleep efficiency also predicted sleep gains. The sleep period time cut-point that optimized prediction of successful sleep gains was <8 hours 28 minutes with 75% of children's baseline sleep in that range. CONCLUSIONS: Children with a baseline sleep period time <8½ hours a night obtained the most sleep from earlier bedtimes maintained over a week, demonstrating experimentally the value of earlier bedtimes to improve sleep. CLINICAL TRIALS REGISTRY: Australian New Zealand Clinical Trial Registry, ACTRN12618001671257, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=367587&isReview=true.

Sleep need, the key regulator of sleep homeostasis, is indicated and controlled by phosphorylation of threonine 221 in salt-inducible kinase 3.

Sleep need drives sleep and plays a key role in homeostatic regulation of sleep. So far sleep need can only be inferred by animal behaviors and indicated by electroencephalography (EEG). Here we report that phosphorylation of threonine (T) 221 of the salt-inducible kinase 3 (SIK3) increased the catalytic activity and stability of SIK3. T221 phosphorylation in the mouse brain indicates sleep need: more sleep resulting in less phosphorylation and less sleep more phosphorylation during daily sleep/wake cycle and after sleep deprivation (SD). Sleep need was reduced in SIK3 loss of function (LOF) mutants and by T221 mutation to alanine (T221A). Rebound after SD was also decreased in SIK3 LOF and T221A mutant mice. By contrast, SIK1 and SIK2 do not satisfy criteria to be both an indicator and a controller of sleep need. Our results reveal SIK3-T221 phosphorylation as a chemical modification which indicates and controls sleep need.

Mitochondrial control of sleep.

The function of sleep remains one of biology's biggest mysteries. A solution to this problem is likely to come from a better understanding of sleep homeostasis, and in particular of the cellular and molecular processes that sense sleep need and settle sleep debt. Here, we highlight recent work in the fruit fly showing that changes in the mitochondrial redox state of sleep-promoting neurons lie at the heart of a homeostatic sleep-regulatory mechanism. Since the function of homeostatically controlled behaviours is often linked to the regulated variable itself, these findings corroborate with the hypothesis that sleep serves a metabolic function.

Perceived daily sleep need and sleep debt in adolescents: associations with daily affect over school and vacation periods.

STUDY OBJECTIVES: To describe trajectories of daily perceived sleep need and sleep debt, and examine if cumulative perceived sleep debt predicts next-day affect. METHODS: Daily sleep and affect were measured over two school weeks and two vacation weeks (N = 205, 54.1% females, M ± SDage = 16.9 ± 0.87 years). Each day, participants wore actigraphs and self-reported the amount of sleep needed to function well the next day (i.e. perceived sleep need), sleep duration, and high- and low-arousal positive and negative affect (PA, NA). Cumulative perceived sleep debt was calculated as the weighted average of the difference between perceived sleep need and sleep duration over the past 3 days. Cross-lagged, multilevel models were used to test cumulative sleep debt as a predictor of next-day affect. Lagged affect, day of the week, study day, and sociodemographics were controlled. RESULTS: Perceived sleep need was lower early in the school week, before increasing in the second half of the week. Adolescents accumulated perceived sleep debt across school days and reduced it during weekends. On weekends and vacations, adolescents self-reported meeting their sleep need, sleeping the amount, or more than the amount of sleep they perceived as needing. Higher cumulative actigraphy sleep debt predicted higher next-day high arousal NA; higher cumulative diary sleep debt predicted higher NA (regardless of arousal), and lower low arousal PA the following day. CONCLUSION: Adolescents experienced sustained, cumulative perceived sleep debt across school days. Weekends and vacations appeared to be opportunities for reducing sleep debt. Trajectories of sleep debt during vacation suggested recovery from school-related sleep restriction. Cumulative sleep debt was related to affect on a daily basis, highlighting the value of this measure for future research and interventions.

Accumulation of sleep loss among shift-working truck drivers.

Sleep loss is known to contribute to road traffic accidents. Professional drivers are vulnerable to curtailment of sleep due to long driving bouts and shift work. To fill in the gap in the literature related to the buildup of sleep loss in irregular shift systems, we recorded the sleep and working hours of 47 shift-working long-haul truck drivers during a two-week period. Sleep (time in bed) was verified by actigraphy and sleep logs. Sleepiness was measured using the Karolinska Sleepiness Scale (KSS). Individual sleep need was based on self-assessments. We examined the accumulated sleep versus self-reported sleep need across the study period, using midnights as points of observation, and the accumulated sleep loss within 72 h prior to shift end (sleep versus need, SVN72). Across the study period, the drivers' sleep was close to their self-reported sleep need, but 45% of the drivers showed accumulated sleep loss of >6 h at least once. SVN72 averaged -1.5 h and was 2.87 h shorter in connection with morning shifts compared to day or evening shifts. Night shifts showed no such difference. During days off, sleep exceeded sleep need by 1.13 h and was not dependent on the type of preceding work shift. SVN72 showed small-to-medium negative associations with on-duty KSS even after accounting for sleep within the 24 h prior to the shift end. Our results show that long-haul truck drivers are exposed to severe levels of accumulated sleep loss while working irregular shifts, but they can catch up on their lost sleep, especially during days off.

How Much Sleep Does an Elite Athlete Need?

PURPOSE: Anecdotal reports indicate that many elite athletes are dissatisfied with their sleep, but little is known about their actual sleep requirements. Therefore, the aim of this study was to compare the self-assessed sleep need of elite athletes with an objective measure of their habitual sleep duration. METHODS: Participants were 175 elite athletes (n = 30 females), age 22.2 (3.8) years (mean [SD]) from 12 individual and team sports. The athletes answered the question "how many hours of sleep do you need to feel rested?" and they kept a self-report sleep diary and wore a wrist activity monitor for ∼12 nights during a normal phase of training. For each athlete, a sleep deficit index was calculated by subtracting their average sleep duration from their self-assessed sleep need. RESULTS: The athletes needed 8.3 (0.9) hours of sleep to feel rested, their average sleep duration was 6.7 (0.8) hours, and they had a sleep deficit index of 96.0 (60.6) minutes. Only 3% of athletes obtained enough sleep to satisfy their self-assessed sleep need, and 71% of athletes fell short by an hour or more. Specifically, habitual sleep duration was shorter in athletes from individual sports than in athletes from team sports (F1,173 = 13.1, P < .001; d = 0.6, medium), despite their similar sleep need (F1,173 = 1.40, P = .24; d = 0.2, small). CONCLUSIONS: The majority of elite athletes obtain substantially less than their self-assessed sleep need. This is a critical finding, given that insufficient sleep may compromise an athlete's capacity to train effectively and/or compete optimally.

Self-Reported Sleep Need, Subjective Resilience, and Cognitive Performance Following Sleep Loss and Recovery Sleep.

OBJECTIVE: Individuals vary in response to sleep loss: some individuals are "vulnerable" and demonstrate cognitive decrements following insufficient sleep, while others are "resistant" and maintain baseline cognitive capability. Physiological markers (e.g., genetic polymorphisms) have been identified that can predict relative vulnerability. However, a quick, cost-effective, and feasible subjective predictor tool has not been developed. The objective of the present study was to determine whether two factors-"subjective sleep need" and "subjective resilience"-predict cognitive performance following sleep deprivation. METHODS: Twenty-seven healthy, sleep-satiated young adults participated. These individuals were screened for sleep disorders, comorbidities, and erratic sleep schedules. Prior to 40 hours of in-laboratory total sleep deprivation, participants were questioned on their subjective sleep need and completed a validated resilience scale. During and after sleep deprivation, participants completed a 5-minute psychomotor vigilance test every 2 hours. RESULTS: Both subjective resilience and subjective sleep need individually failed to predict performance during sleep loss. However, these two measures interacted to predict performance. Individuals with low resilience and low sleep need had poorer cognitive performance during sleep loss. However, in individuals with medium or high resilience, psychomotor vigilance test performance was not predicted by subjective sleep need. Higher resilience may be protective against sleep loss-related neurobehavioral impairments in the context of subjective sleep need. CONCLUSIONS: Following sleep loss (and recovery sleep), trait resilient individuals may outperform those with lower resiliency on real-world tasks that require continuous attention. Future studies should determine whether the present findings generalize to other, operationally relevant tasks and additional cognitive domains.

Changes in EEG permutation entropy in the evening and in the transition from wake to sleep.

Quantifying the complexity of the EEG signal during prolonged wakefulness and during sleep is gaining interest as an additional mean to characterize the mechanisms associated with sleep and wakefulness regulation. Here, we characterized how EEG complexity, as indexed by Multiscale Permutation Entropy (MSPE), changed progressively in the evening prior to light off and during the transition from wakefulness to sleep. We further explored whether MSPE was able to discriminate between wakefulness and sleep around sleep onset and whether MSPE changes were correlated with spectral measures of the EEG related to sleep need during concomitant wakefulness (theta power-Ptheta: 4-8 Hz). To address these questions, we took advantage of large datasets of several hundred of ambulatory EEG recordings of individual of both sexes aged 25-101 years. Results show that MSPE significantly decreases before light off (i.e. before sleep time) and in the transition from wakefulness to sleep onset. Furthermore, MSPE allows for an excellent discrimination between pre-sleep wakefulness and early sleep. Finally, we show that MSPE is correlated with concomitant Ptheta. Yet, the direction of the latter correlation changed from before light-off to the transition to sleep. Given the association between EEG complexity and consciousness, MSPE may track efficiently putative changes in consciousness preceding sleep onset. An MSPE stands as a comprehensive measure that is not limited to a given frequency band and reflects a progressive change brain state associated with sleep and wakefulness regulation. It may be an effective mean to detect when the brain is in a state close to sleep onset.

Sleep abnormalities across different clinical stages of Bipolar Disorder: A review of EEG studies.

Sleep disturbances are highly prevalent across all stages of Bipolar Disorder. Despite a wealth of research on the neurophysiological features of sleep in this population, progress in this field has been slow. We aimed to review the literature on sleep electroencephalography (EEG) studies in Bipolar Disorder, considering sleep architecture and microstructural oscillatory activity. We included a total of 22 studies: six on sleep during manic episodes, seven during depressive episodes, seven in euthymic patients and two in high-risk individuals. The most consistent findings were increased SOL and REM density across all stages of the disorder. Only two studies reported a reduced spindle count during bipolar depression and euthymia, respectively. Although not specific for Bipolar Disorder, SOL and REM density have been repeatedly found to be increased across all stages of illness in this population. Whereas the former reflects a difficulty initiating sleep, the latter can be considered a neurophysiological signature of patients' overall reduced sleep need, independent of illness stage.

Nonpharmacologic Management of Excessive Daytime Sleepiness.

Unlike other reviews written on this topic, the focus of this article is primarily on nonpharmacologic treatments for daytime sleepiness that is not secondary to other medical or psychological conditions. To provide an appropriate background on primary excessive daytime sleepiness, what is considered optimal sleep in terms of sleep duration, sleep insufficiency, and sleep need is discussed in detail. This discussion is followed by an examination of the behavioral strategy of banking sleep. After briefly discussing behavioral interventions for sleepiness associated with narcolepsy, a new behavioral method of treating daytime somnolence is proposed and described.

Presynaptic Active Zone Plasticity Encodes Sleep Need in Drosophila.

Sleep is universal across species and essential for quality of life and health, as evidenced by the consequences of sleep loss. Sleep might homeostatically normalize synaptic gains made over wake states in order to reset information processing and storage and support learning, and sleep-associated synaptic (ultra)structural changes have been demonstrated recently. However, causal relationships between the molecular and (ultra)structural status of synapses, sleep homeostatic regulation, and learning processes have yet to be established. We show here that the status of the presynaptic active zone can directly control sleep in Drosophila. Short sleep mutants showed a brain-wide upregulation of core presynaptic scaffold proteins and release factors. Increasing the gene copy number of ELKS-family scaffold master organizer Bruchpilot (BRP) not only mimicked changes in the active zone scaffold and release proteins but importantly provoked sleep in a dosage-dependent manner, qualitatively and quantitatively reminiscent of sleep deprivation effects. Conversely, reducing the brp copy number decreased sleep in short sleep mutant backgrounds, suggesting a specific role of the active zone plasticity in homeostatic sleep regulation. Finally, elimination of BRP specifically in the sleep-promoting R2 neurons of 4xBRP animals partially restored sleep patterns and rescued learning deficits. Our results suggest that the presynaptic active zone plasticity driven by BRP operates as a sleep homeostatic actuator that also restricts periods of effective learning.

The coupling of short sleep duration and high sleep need predicts riskier decision making.

Objective: To examine how risk-related decision making might be associated with habitual sleep variables, including sleep variability, sleep duration and perceived sleep need in young adults cross-sectionally and longitudinally. Design: 166 participants completed a 7-day protocol with sleep and risk-related decision-making measures at baseline (T1) and 12 months later (T2). Results: Habitual short sleep duration (averaging < 6 h nightly) was identified in 11.0% in our sample. After controlling for baseline demographic factors and risk-taking measures, self-reported sleep need at T1 interacted with habitual short sleep in predicting risk taking at follow-up (F8,139=9.575, adjusted R2=.431, p<.001). T1 greater perceived sleep need predicted more risk taking among short sleepers, but decreased risk taking among normal sleepers at T2. Variable sleep timing was cross-sectionally correlated with making more Risky choices at baseline and fewer Safe choices after loss at follow up. Conclusions: Young adults with variable sleep timing and those with short sleep duration coupled with high perceived sleep need were more likely to take risks. The moderating effects of perceived sleep need suggest that individual differences may alter the impact of sleep loss and hence should be measured and accounted for in future studies.

Acute Social Defeat Stress Increases Sleep in Mice.

Social conflict is a major source of stress in humans. Animals also experience social conflicts and cope with them by stress responses that facilitate arousal and activate sympathetic and neuroendocrine systems. The effect of acute social defeat (SoD) stress on the sleep/wake behavior of mice has been reported in several models based on a resident-intruder paradigm. However, the post-SoD stress sleep/wake effects vary between the studies and the contribution of specific effects in response to SoD or non-specific effects of the SoD procedure (e.g., sleep deprivation) is not well established. In this study, we established a mouse model of acute SoD stress based on strong aggressive mouse behavior toward unfamiliar intruders. In our model, we prevented severe attacks of resident mice on submissive intruder mice to minimize behavioral variations during SoD. In response to SoD, slow-wave sleep (SWS) strongly increased during 9 h. Although some sleep changes after SoD stress can be attributed to non-specific effects of the SoD procedure, most of the SWS increase is likely a specific response to SoD. Slow-wave activity was only enhanced for a short period after SoD and dissipated long before the SWS returned to baseline. Moreover, SoD evoked a strong corticosterone response that may indicate a high stress level in the intruder mice after SoD. Our SoD model may be useful for studying the mechanisms and functions of sleep in response to social stress.

Dose response of acute cocaine on sleep/waking behavior in mice.

Chronic cocaine use has been associated with sleep disturbances, both during active use periods and during withdrawal and abstinence. Acute cocaine also increases waking at the expense of slow wave sleep and Rapid Eye Movement in non-human subjects. However, the effects of acute cocaine on sleep/waking activity in mice, a rodent model commonly used in both sleep and addiction research due to its high genetic tractability, has yet to be investigated. Sleep/waking activity was measured via polysomnography following IP administration of three doses of cocaine (3.6, 9.6, 18 mg/kg) and vehicle control in male C57BL/6 mice. Cocaine dose-dependently increased sleep latency, increased waking time and increased fast EEG activity within waking. Increases in waking occurred primarily during the first hour following injection, followed by rebound SWS sleep. Sleep/waking activity normalized within a 24-hour period. As with humans and other rodents, cocaine dose dependently reduces sleep in a wildtype strain of mice commonly used in reward and addiction research.

Nonpharmacologic Management of Excessive Daytime Sleepiness.

Unlike other reviews written on this topic, the focus of this article is primarily on nonpharmacologic treatments for daytime sleepiness that is not secondary to other medical or psychological conditions. To provide an appropriate background on primary excessive daytime sleepiness, what is considered optimal sleep in terms of sleep duration, sleep insufficiency, and sleep need is discussed in detail. This discussion is followed by an examination of the behavioral strategy of banking sleep. After briefly discussing behavioral interventions for sleepiness associated with narcolepsy, a new behavioral method of treating daytime somnolence is proposed and described.

Excessive daytime sleepiness, sleep need and insomnia 3 years after Giardia infection: a cohort study.

OBJECTIVE: To investigate whether prior infection with Giardia lamblia is associated with excessive daytime sleepiness, insomnia, and level of sleep need. DESIGN: A questionnaire was sent to all confirmed cases of giardiasis 3 years after the outbreak and a control group matched on age and gender. Associations were evaluated by use of multiple regression analysis. RESULTS: Excessive daytime sleepiness (score ≥11 on the Epworth Sleepiness Scale) was reported by 31.5% of the Giardia-exposed and 14.1% of the controls. In multivariate analysis, excessive daytime sleepiness was independently associated with Giardia exposure, with an adjusted odds ratio of 1.40 (95% confidence interval [CI], 1.06-1.86). Insomnia was reported by 15.4% of Giardia-exposed and 8.8% of controls, adjusted odds ratio was 0.93 (95% CI, 0.65-1.35). Mean (SD) self-reported sleep need was 8 (1.4) hours among Giardia-exposed and 7.5 (1.1) hours in the control group (P < .001). The adjusted regression coefficient was 0.12 (95% CI, 0.01-0.24). CONCLUSION: Being exposed to Giardia was independently associated with excessive daytime sleepiness and larger sleep need, but not with insomnia.

Sleep-deprived motor vehicle operators are unfit to drive: a multidisciplinary expert consensus statement on drowsy driving.

OBJECTIVES: This article presents the consensus findings of the National Sleep Foundation Drowsy Driving Consensus Working Group, which was an expert panel assembled to establish a consensus statement regarding sleep-related driving impairment. METHODS: The National Sleep Foundation assembled a expert panel comprised of experts from the sleep community and experts appointed by stakeholder organizations. A systematic literature review identified 346 studies that were abstracted and provided to the panelists for review. A modified Delphi RAND/UCLA Appropriateness Method with 2 rounds of voting was used to reach consensus. RESULTS: A final consensus was reached that sleep deprivation renders motorists unfit to drive a motor vehicle. After reviewing growing evidence of impairment and increased crash risk among drivers who obtained less than optimal sleep duration in the preceding 24 hours, the panelists recognized the need for public policy guidance as to when it is certainly unsafe to drive. Toward this end, the panelists agreed upon the following expert consensus statement: "Drivers who have slept for two hours or less in the preceding 24 hours are not fit to operate a motor vehicle." Panelists further agreed that most healthy drivers would likely be impaired with only 3 to 5 hours of sleep during the prior 24 hours. CONCLUSIONS: There is consensus among experts that healthy individuals who have slept for 2 hours or less in the preceding 24 hours are too impaired to safely operate a motor vehicle. Prevention of drowsy driving will require sustained and collaborative effort from multiple stakeholders. Implications and limitations of the consensus recommendations are discussed.

Association between subjective actual sleep duration, subjective sleep need, age, body mass index, and gender in a large sample of young adults.

BACKGROUND: Poor sleep is a major health concern, and there is evidence that young adults are at increased risk of suffering from poor sleep. There is also evidence that sleep duration can vary as a function of gender and body mass index (BMI). We sought to replicate these findings in a large sample of young adults, and also tested the hypothesis that a smaller gap between subjective sleep duration and subjective sleep need is associated with a greater feeling of being restored. METHODS: A total of 2,929 university students (mean age 23.24±3.13 years, 69.1% female) took part in an Internet-based survey. They answered questions related to demographics and subjective sleep patterns. RESULTS: We found no gender differences in subjective sleep duration, subjective sleep need, BMI, age, or feeling of being restored. Nonlinear associations were observed between subjective sleep duration, BMI, and feeling of being restored. Moreover, a larger discrepancy between subjective actual sleep duration and subjective sleep need was associated with a lower feeling of being restored. CONCLUSION: The present pattern of results from a large sample of young adults suggests that males and females do not differ with respect to subjective sleep duration, BMI, or feeling of being restored. Moreover, nonlinear correlations seemed to provide a more accurate reflection of the relationship between subjective sleep and demographic variables.

The colony environment modulates sleep in honey bee workers.

One of the most important and evolutionarily conserved roles of sleep is the processing and consolidation of information acquired during wakefulness. In both insects and mammals, environmental and social stimuli can modify sleep physiology and behavior, yet relatively little is known about the specifics of the wake experiences and their relative contribution to experience-dependent modulation of sleep. Honey bees provide an excellent model system in this regard because their behavioral repertoire is well characterized and the environment they experience during the day can be manipulated while keeping an ecologically and sociobiologically relevant context. We examined whether social experience modulates sleep in honey bees, and evaluated the relative contribution of different social signals. We exposed newly emerged bees to different components of their natural social environment and then monitored their sleep behavior in individual cages in a constant lab environment. We found that rich waking experience modulates subsequent sleep. Bees that experienced the colony environment for 1 or 2 days slept more than same-age sister bees that were caged individually or in small groups in the lab. Furthermore, bees placed in mesh-enclosures in the colony, that prevented direct contact with nestmates, slept similarly to bees freely moving in the colony. These results suggest that social signals that do not require direct or close distance interactions between bees are sufficiently rich to encompass almost the entire effect of the colony on sleep. Our findings provide a remarkable example of social experience-dependent modulation of an essential biological process.