The interactive effect of sustained sleep restriction and resistance exercise on skeletal muscle transcriptomics in young females.

Both sleep loss and exercise regulate gene expression in skeletal muscle, yet little is known about how the interaction of these stressors affects the transcriptome. The aim of this study was to investigate the effect of nine nights of sleep restriction (SR), with repeated resistance exercise (REx) sessions, on the skeletal muscle transcriptome of young, trained females. Ten healthy females aged 18-35 yr old undertook a randomized cross-over study of nine nights of SR (5 h time in bed) and normal sleep (NS; ≥7 h time in bed) with a minimum 6-wk washout. Participants completed four REx sessions per condition (days 3, 5, 7, and 9). Muscle biopsies were collected both pre- and post-REx on days 3 and 9. Gene and protein expression were assessed by RNA sequencing and Western blot, respectively. Three or nine nights of SR had no effect on the muscle transcriptome independently of exercise. However, close to 3,000 transcripts were differentially regulated (false discovery rate < 0.05) 48 h after the completion of three resistance exercise sessions in both NS and SR conditions. Only 39% of downregulated genes and 18% of upregulated genes were common between both conditions, indicating a moderating effect of SR on the response to exercise. SR and REx interacted to alter the enrichment of skeletal muscle transcriptomic pathways in young, resistance-trained females. Performing exercise when sleep restricted may not provide the same adaptive response for individuals as if they were fully rested.NEW & NOTEWORTHY This study investigated the effect of nine nights of sleep restriction, with repeated resistance exercise sessions, on the skeletal muscle transcriptome of young, trained females. Sleep restriction and resistance exercise interacted to alter the enrichment of skeletal muscle transcriptomic pathways in young, resistance-trained females. Performing exercise when sleep restricted may not provide the same adaptive response for individuals as if they were fully rested.

Subjective awareness of sleepiness while driving in younger and older adults.

Understanding whether drivers can accurately assess sleepiness is essential for educational campaigns advising drivers to stop driving when feeling sleepy. However, few studies have examined this in real-world driving environments, particularly among older drivers who comprise a large proportion of all road users. To examine the accuracy of subjective sleepiness ratings in predicting subsequent driving impairment and physiological drowsiness, 16 younger (21-33 years) and 17 older (50-65 years) adults drove an instrumented vehicle for 2 h on closed loop under two conditions: well-rested and 29 h sleep deprivation. Sleepiness ratings (Karolinska Sleepiness Scale, Likelihood of Falling Asleep scale, Sleepiness Symptoms Questionnaire) were obtained every 15min, alongside lane deviations, near crash events, and ocular indices of drowsiness. All subjective sleepiness measures increased with sleep deprivation for both age groups (p < 0.013). While most subjective sleepiness ratings significantly predicted driving impairment and drowsiness in younger adults (OR: 1.7-15.6, p < 0.02), this was only apparent for KSS, likelihood of falling asleep, and "difficulty staying in the lane for the older adults" (OR: 2.76-2.86, p = 0.02). This may be due to an altered perception of sleepiness in older adults, or due to lowered objective signs of impairment in the older group. Our data suggest that (i) younger and older drivers are aware of sleepiness; (ii) the best subjective scale may differ across age groups; and (iii) future research should expand on the best subjective measures to inform of crash risk in older adults to inform tailored educational road safety campaigns on signs of sleepiness.

Individualised prediction of resilience and vulnerability to sleep loss using EEG features.

It is well established that individuals differ in their response to sleep loss. However, existing methods to predict an individual's sleep-loss phenotype are not scalable or involve effort-dependent neurobehavioural tests. To overcome these limitations, we sought to predict an individual's level of resilience or vulnerability to sleep loss using electroencephalographic (EEG) features obtained from routine night sleep. To this end, we retrospectively analysed five studies in which 96 healthy young adults (41 women) completed a laboratory baseline-sleep phase followed by a sleep-loss challenge. After classifying subjects into sleep-loss phenotypic groups, we extracted two EEG features from the first sleep cycle (median duration: 1.6 h), slow-wave activity (SWA) power and SWA rise rate, from four channels during the baseline nights. Using these data, we developed two sets of logistic regression classifiers (resilient versus not-resilient and vulnerable versus not-vulnerable) to predict the probability of sleep-loss resilience or vulnerability, respectively, and evaluated model performance using test datasets not used in model development. Consistently, the most predictive features came from the left cerebral hemisphere. For the resilient versus not-resilient classifiers, we obtained an average testing performance of 0.68 for the area under the receiver operating characteristic curve, 0.72 for accuracy, 0.50 for sensitivity, 0.84 for specificity, 0.61 for positive predictive value, and 3.59 for likelihood ratio. We obtained similar performance for the vulnerable versus not-vulnerable classifiers. These results indicate that logistic regression classifiers based on SWA power and SWA rise rate from routine night sleep can largely predict an individual's sleep-loss phenotype.

Sleep restriction alters the integration of multiple information sources in probabilistic decision-making.

The detrimental effects of sleep loss on overall decision-making have been well described. Due to the complex nature of decisions, there remains a need for studies to identify specific mechanisms of decision-making vulnerable to sleep loss. Bayesian perspectives of decision-making posit judgement formation during decision-making occurs via a process of integrating knowledge gleaned from past experiences (priors) with new information from current observations (likelihoods). We investigated the effects of sleep loss on the ability to integrate multiple sources of information during decision-making by reporting results from two experiments: the first implementing both sleep restriction (SR) and total sleep deprivation (TSD) protocols, and the second implementing an SR protocol. In both experiments, participants were administered the Bayes Decisions Task on which optimal performance requires the integration of Bayesian prior and likelihood information. Participants in Experiment 1 showed reduced reliance on both information sources after SR, while no significant change was observed after TSD. Participants in Experiment 2 showed reduced reliance on likelihood after SR, especially during morning testing sessions. No accuracy-related impairments resulting from SR and TSD were observed in both experiments. Our findings show SR affects decision-making through altering the way individuals integrate available sources of information. Additionally, the ability to integrate information during SR may be influenced by time of day. Broadly, our findings carry implications for working professionals who are required to make high-stakes decisions on the job, yet consistently receive insufficient sleep due to work schedule demands.

Insufficient Sleep and Behavioral Health in the Military: A 5-Country Perspective.

PURPOSE OF REVIEW: The goal of this paper was to highlight the degree to which sleep, behavioral health, and leader involvement were interrelated using data from militaries in five English-speaking countries: Australia, Canada, New Zealand, the UK, and the United States. RECENT FINDINGS: Many service members reported sleeping fewer than the recommended 7 h/night: 34.9%, 67.2%, and 77.2% of respondents from New Zealand, Canada, and the United States, respectively. Countries reporting shorter sleep duration also reported fewer insomnia-related difficulties, likely reflecting higher sleep pressure from chronic sleep loss. Across all countries, sleep problems were positively correlated with behavioral health symptoms. Importantly, leader promotion of healthy sleep was positively correlated with more sleep and negatively correlated with sleep problems and behavioral health symptoms. Insufficient sleep in the military is ubiquitous, with serious implications for the behavioral health and functioning of service members. Leaders should attend to these risks and examine ways to promote healthy sleep in service members.

An in-depth analysis of postoperative insomnia in elderly patients and its implications on rehabilitation.

OBJECTIVES: (1) Assess the prevalence of postoperative insomnia; (2) identify the risk factors for postoperative insomnia before exposure to surgery; (3) explore the impact of postoperative insomnia on rehabilitation. METHODS: A study was conducted with 132 participants aged ≥ 65 undergoing spine interbody fusion. We collected the basic demographic data, Numeric Rating Scales (NRS), Pittsburgh Sleep Quality Index (PSQI), Geriatric Depression Scale (GDS), and Beck Anxiety Inventory (BAI). We measured Quality of Recovery 40 (QoR-40), GDS, BAI, NRS, and PSQI on the first and third nights post-surgery, followed by QoR-40 and NRS assessments two weeks after surgery. RESULTS: The cases of postoperative insomnia on the first and third nights and after two weeks were 81 (61.36%), 72 (54.55%), and 64 (48.48%), respectively, and the type of insomnia was not significantly different (P = 0.138). Sleep efficiency on the first night was 49.96% ± 23.51. On the first night of postoperative insomnia, 54 (66.67%) cases were depression or anxiety, and the PSQI was higher in this group than in the group without anxiety or depression (P < 0.001). PSQI, GDS, and the time of surgery were related factors for postoperative insomnia (PPSQI < 0.001, PGDS = 0.008, and PTime = 0.040). Postoperative rehabilitation showed differences between the insomnia and non-insomnia groups (P < 0.001). CONCLUSIONS: The prevalence of postoperative insomnia in the elderly was high, and postoperative insomnia had a significant correlation with postoperative rehabilitation. Interventions that target risk factors may reduce the prevalence of postoperative insomnia and warrant further research. CLINICAL TRIAL REGISTRATION: Multivariate analysis of postoperative insomnia in elderly patients with spinal surgery and its correlation with postoperative rehabilitation ( https://www.chictr.org.cn/bin/project/edit?pid=170201 ; #ChiCTR2200059827).

The Combination of Quantitative Proteomics and Systems Genetics Analysis Reveals that PTN Is Associated with Sleep-Loss-Induced Cognitive Impairment.

Sleep loss is associated with cognitive dysfunction. However, the detailed mechanisms remain unclear. In this study, we established a para-chlorophenylalanine (PCPA)-induced insomniac mouse model with impaired cognitive function. Mass-spectrometry-based proteomics showed that the expression of 164 proteins was significantly altered in the hippocampus of the PCPA mice. To identify critical regulators among the potential markers, a transcriptome-wide association screening was performed in the BXD mice panel. Among the candidates, the expression of pleiotrophin (Ptn) was significantly associated with cognitive functions, indicating that Ptn-mediates sleep-loss-induced cognitive impairment. Gene co-expression analysis further revealed the potential mechanism by which Ptn mediates insomnia-induced cognitive impairment via the MAPK signaling pathway; that is, the decreased secretion of Ptn induced by insomnia leads to reduced binding to Ptprz1 on the postsynaptic membrane with the activation of the MAPK pathway via Fos and Nr4a1, further leading to the apoptosis of neurons. In addition, Ptn is genetically trans-regulated in the mouse hippocampus and implicated in neurodegenerative diseases in human genome-wide association studies. Our study provides a novel biomarker for insomnia-induced cognitive impairment and a new strategy for seeking neurological biomarkers by the integration of proteomics and systems genetics.

Starvation-induced sleep suppression requires the Drosophila brain nutrient sensor.

Animals increase their locomotion activity and reduce sleep duration under starved conditions. This suggests that sleep and metabolic status are closely interconnected. The nutrient and hunger sensors in the Drosophila brain, including diuretic hormone 44 (DH44)-, CN-, and cupcake-expressing neurons, detect circulating glucose levels in the internal milieu, regulate the insulin and glucagon secretion and promote food consumption. Food deprivation is known to reduce sleep duration, but a potential role mediated by the nutrient and hunger sensors in regulating sleep and locomotion activity remains unclear. Here, we show that DH44 neurons are involved in regulating starvation-induced sleep suppression, but CN neurons or cupcake neurons may not be involved in regulating starvation-induced sleep suppression or baseline sleep patterns. Inactivation of DH44 neurons resulted in normal daily sleep durations and patterns under fed conditions, whereas it ablated sleep reduction under starved conditions. Inactivation of CN neurons or cupcake neurons, which were proposed to be nutrient and hunger sensors in the fly brain, did not affect sleep patterns under both fed and starved conditions. We propose that the glucose-sensing DH44 neurons play an important role in mediating starvation-induced sleep reduction.

Sleep restriction between consecutive days of exercise impairs sprint and endurance cycling performance.

The study aim was to determine the effect of sleep restriction (3 h) between consecutive days of exercise on sprint and endurance cycling performance, wellness, and mood. A total of 10 well-trained males performed 2 consecutive-day trials separated by a normal night sleep (control [CONT]; mean [SD] sleep duration 3.0 [0.2] h) or sleep restriction (RES; mean [SD] sleep duration 3.0 [0.2] h). Experimental trials included a 90-min fixed-paced cycling bout and the respective sleep conditions on Day 1, followed by two 6-s peak power (6-s PP) tests, a 4- and 20-min time trial (TT) on Day 2. Profile of Mood States (POMS) and wellness questionnaires were recorded on Day 1 and Day 2. Blood lactate and glucose, heart rate (HR), and rating of perceived exertion were recorded throughout Day 2. Power output (PO) was significantly reduced for RES in the 6-s PP trial (mean [SD] 1159 [127] W for RES versus 1250 [186] W for CONT; p = 0.04) and mean PO during the 20-min TT (mean [SD] 237 [59] W for RES versus 255 [58] W for CONT; p = 0.03). There were no differences for HR, lactate and glucose, or POMS between CONT and RES in all experimental trials (p = 0.05-0.89). Participants reported a reduction in overall wellness prior to exercise on Day 2 following RES (mean [SD] 14.5 [1.6] au) compared to CONT (mean [SD] 16 [3.0] au; p = 0.034). Sleep restriction and the associated reductions in wellness, reduce cycling performance during consecutive days of exercise in a range of cycling tests that are relevant to both track and road cyclists.

Electroencephalographic markers from routine sleep discriminate individuals who are vulnerable or resilient to sleep loss.

Sleep loss impairs cognition; however, individuals differ in their response to sleep loss. Current methods to identify an individual's vulnerability to sleep loss involve time-consuming sleep-loss challenges and neurobehavioural tests. Here, we sought to identify electroencephalographic markers of sleep-loss vulnerability obtained from routine night sleep. We retrospectively analysed four studies in which 50 healthy young adults (21 women) completed a laboratory baseline-sleep phase followed by a sleep-loss challenge. After classifying subjects as resilient or vulnerable to sleep loss, we extracted three electroencephalographic features from four channels during the baseline nights, evaluated the discriminatory power of these features using the first two studies (discovery), and assessed reproducibility of the results using the remaining two studies (reproducibility). In the discovery analysis, we found that, compared to resilient subjects, vulnerable subjects exhibited: (1) higher slow-wave activity power in channel O1 (p < 0.0042, corrected for multiple comparisons) and in channels O2 and C3 (p < 0.05, uncorrected); (2) higher slow-wave activity rise rate in channels O1 and O2 (p < 0.05, uncorrected); and (3) lower sleep spindle frequency in channels C3 and C4 (p < 0.05, uncorrected). Our reproducibility analysis confirmed the discovery results on slow-wave activity power and slow-wave activity rise rate, and for these two electroencephalographic features we observed consistent group-difference trends across all four channels in both analyses. The higher slow-wave activity power and slow-wave activity rise rate in vulnerable individuals suggest that they have a persistently higher sleep pressure under normal rested conditions.

Long-term influence of sleep/wake history on the dynamic neurobehavioural response to sustained sleep restriction.

Chronic sleep restriction, common in today's 24/7 society, causes cumulative neurobehavioural impairment, but the dynamics of the build-up and dissipation of this impairment have not been fully elucidated. We addressed this knowledge gap in a laboratory study involving two, 5-day periods of sleep restriction to 4 hr per day, separated by a 1-day dose-response intervention sleep opportunity. We measured sleep physiological and waking neurobehavioural responses in 70 healthy adults, each randomized to one of seven dose-response intervention sleep doses ranging from 0 to 12 hr, or a non-sleep-restricted control group. As anticipated, sleep physiological markers showed homeostatic dynamics throughout the study, and waking neurobehavioural impairment accumulated across the two sleep restriction periods. Unexpectedly, there was only a slight and short-lived effect of the 1-day dose-response intervention sleep opportunity. Whether the dose-response intervention sleep opportunity involved extension, further restriction or total deprivation of sleep, neurobehavioural functioning during the subsequent second sleep restriction period was dominated by prior sleep-wake history. Our findings revealed a profound and enduring influence of long-term sleep-wake history as a fundamental aspect of the dynamic regulation of the neurobehavioural response to sleep loss.

Sleep Immune Cross Talk and Insomnia.

Sleep and immunity have bidirectional relationships. In this chapter, we review the links between sleep and immunity, focusing on immune changes occurring in the insomnia disorder. During physiological sleep, there is a decrease of pro-inflammatory cytokines (IL-1, IL-6 and TNF-α) and a decrease of anti-inflammatory cytokines (IL-4, IL-10). Examinations of ratios of pro-inflammatory and anti-inflammatory cytokines allow to identify rather a pro-inflammatory activity at the beginning of the night and confirm then anti-inflammatory during the second part of the night. Immune cells, as NK-cells, decrease in the blood, due to their migration to secondary lymphoid organs, but their activity increases. Inversely, a short sleep duration appears associated with increased inflammatory processes and increased risk of infection.Only few studies have investigated changes in immunity in patients with insomnia disorder. These studies suggest that insomnia disorder is related to deregulation of the immune system, with an increase in the level of pro-inflammatory cytokines and change in rate of secretion and a decrease in the level of lymphocyte. Insomnia treatments, particularly cognitive behavioral therapy (CBT-I), seems to have a restorative effect not only on sleep, but also on the associated inflammation. Melatonin also seems to reduce inflammation in patients suffering from insomnia disorder.More studies are necessary to better understand the pathophysiology of changes in immune system in patients suffering from insomnia disorders and their clinical implications.

The impact of self-selected short sleep on monetary risk taking.

Risky choice has been widely studied in experimental settings, but there is a paucity of research examining the effects of self-selected sleep schedules on risky choices. The current study examined incentivised risky choices of 100 young, healthy adults whose self-selected (at-home) sleep schedules were tracked via actigraphy for 1 week prior to decision making. Average nightly sleep was 6.43 h/night. On each trial of the decision task, individuals chose between two monetary gambles, with separate blocks of trials presenting amounts to gain versus amounts to lose for each paired gamble choice. In general, participants were risk-averse when trying to maximise gains (GAINS) and risk-seeking when trying to minimise losses (LOSSES). These tendencies were amplified in trials where gambles differed more (vs less) in their riskiness. Response times were longer for real choices (vs. dummy trials of random choice), LOSS versus GAINS trials, and when gambles were more similar versus different in risk. Gamble choices were not impacted by actigraphy measured average sleep levels, which suggests self-selected moderate sleep deprivation does not affect risky monetary choices, as has been found in studies of experimentally induced sleep deprivation. However, our data showed that sleep variability increased risk-taking behaviour in the LOSS condition. Thus, risky decision-making may relate more to variability in sleep efficiency than to overall sleep duration or quality in naturalistic settings. The current study gives insight into how decision making in experimental sleep settings may or may not translate to more ecologically valid settings of self-directed sleep.

Understanding the association between sleep, shift work and COVID-19 vaccine immune response efficacy: Protocol of the S-CORE study.

This protocol describes an innovative study to investigate the relationship between sleep, shift work and the immune response to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2; coronavirus disease 2019 [COVID-19]) vaccination. As the COVID-19 pandemic is a global crisis with devastating health, social and economic impacts, there is a pressing need for effective vaccination programmes. Previous influenza and hepatitis vaccination studies suggest that lack of sleep can negatively alter immune responsiveness, while circadian misalignment most likely may also play an important role in the immune response to vaccination. Our present study will be the first to address this question in actual shift workers and in relation to COVID-19 vaccination. We hypothesise that the occurrence of recent night shifts and diminished sleep will negatively alter the immune response to vaccination in shift workers compared to dayworkers. We aim to recruit 50 shift workers and 50 dayworkers. Participants will receive an mRNA-based vaccination, through the Dutch vaccination programme. To assess immune responsiveness, blood will be drawn at baseline (before first vaccination), 10 days after first vaccination, the day prior to the second vaccination; and 28 days, 6 and 12 months after the second vaccination. Actigraphy and daily sleep e-diaries will be implemented for 7 days around each vaccination to assess sleep. The Pittsburgh Sleep Quality Index will be used to monitor sleep in the long term. Optimising the efficacy of the COVID-19 vaccines is of outmost importance and results of this study could provide insights to develop sleep and circadian-based interventions to enhance vaccination immunity, and thereby improve global health.

Insomnia, sleep loss, and circadian sleep disturbances in mood disorders: a pathway toward neurodegeneration and neuroprogression? A theoretical review.

The present paper aims at reviewing and commenting on the relationships between sleep and circadian phasing alterations and neurodegenerative/neuroprogressive processes in mood disorder. We carried out a systematic review, according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, in PubMed, PsycINFO, and Embase electronic databases for literature related to mood disorders, sleep disturbances, and neurodegenerative/neuroprogressive processes in relation to (1) neuroinflammation, (2) activation of the stress system, (3) oxidative stress, (4) accumulation of neurotoxic proteins, and (5) neuroprotection deficit. Seventy articles were collectively selected and analyzed. Experimental and clinical studies revealed that insomnia, conditions of sleep loss, and altered circadian sleep may favor neurodegeneration and neuroprogression in mood disorders. These sleep disturbances may induce a state of chronic inflammation by enhancing neuroinflammation, both directly and indirectly, via microglia and astrocytes activation. They may act as neurobiological stressors that by over-activating the stress system may negatively influence neural plasticity causing neuronal damage. In addition, sleep disturbances may favor the accumulation of neurotoxic proteins, favor oxidative stress, and a deficit in neuroprotection hence contributing to neurodegeneration and neuroprogression. Targeting sleep disturbances in the clinical practice may hold a neuroprotective value for mood disorders.

2B-Alert Web 2.0, an Open-Access Tool for Predicting Alertness and Optimizing the Benefits of Caffeine: Utility Study.

BACKGROUND: One-third of the US population experiences sleep loss, with the potential to impair physical and cognitive performance, reduce productivity, and imperil safety during work and daily activities. Computer-based fatigue-management systems with the ability to predict the effects of sleep schedules on alertness and identify safe and effective caffeine interventions that maximize its stimulating benefits could help mitigate cognitive impairment due to limited sleep. To provide these capabilities to broad communities, we previously released 2B-Alert Web, a publicly available tool for predicting the average alertness level of a group of individuals as a function of time of day, sleep history, and caffeine consumption. OBJECTIVE: In this study, we aim to enhance the capability of the 2B-Alert Web tool by providing the means for it to automatically recommend safe and effective caffeine interventions (time and dose) that lead to optimal alertness levels at user-specified times under any sleep-loss condition. METHODS: We incorporated a recently developed caffeine-optimization algorithm into the predictive models of the original 2B-Alert Web tool, allowing the system to search for and identify viable caffeine interventions that result in user-specified alertness levels at desired times of the day. To assess the potential benefits of this new capability, we simulated four sleep-deprivation conditions (sustained operations, restricted sleep with morning or evening shift, and night shift with daytime sleep) and compared the alertness levels resulting from the algorithm's recommendations with those based on the US Army caffeine-countermeasure guidelines. In addition, we enhanced the usability of the tool by adopting a drag-and-drop graphical interface for the creation of sleep and caffeine schedules. RESULTS: For the 4 simulated conditions, the 2B-Alert Web-proposed interventions increased mean alertness by 36% to 94% and decreased peak alertness impairment by 31% to 71% while using equivalent or smaller doses of caffeine as the corresponding US Army guidelines. CONCLUSIONS: The enhanced capability of this evidence-based, publicly available tool increases the efficiency by which diverse communities of users can identify safe and effective caffeine interventions to mitigate the effects of sleep loss in the design of research studies and work and rest schedules.

Recovery of Cognitive Performance Following Multi-Stressor Military Training.

OBJECTIVE: This project aimed to assess the impact of an 8-day military training exercise on cognitive performance, and track its recovery in periods of reduced training load and partially restored sleep. BACKGROUND: Military personnel often work in challenging multi-stressor environments, where sleep loss is inevitable. Sleep loss can impair multiple cognitive domains, which can have disastrous consequences in military contexts. METHOD: A total of 57 male and female soldiers undergoing the Australian Army combat engineer Initial Employment Training course were recruited and tracked over a 16-day study period which included an 8-day field-based military training exercise. Cognitive performance was assessed via a computerised battery at seven time points across four sequential study periods; 1) baseline (PRE), 2) military field training exercise which included total sleep deprivation (EX-FIELD), 3) training exercise at simulated base with restricted sleep opportunities (EX-BASE), and 4) a 3-day recovery period (REC). Subjective load, fatigue, and sleep were evaluated continuously via questionnaire and actigraphy. RESULTS: Psychomotor speed, reaction time, visual tracking and vigilance were impaired following the EX-FIELD period (p < 0.05). The majority of affected measures recovered 2 days following EX-FIELD, being no different in EX-BASE compared to PRE. CONCLUSION: The sensitivity of the cognitive tests to sleep restriction, and recovery, indicates they can help assess operational readiness in military personnel. Future studies should explore other indicators of, and strategies to preserve, operational readiness in military personnel. APPLICATION: This study highlights the impact of work-induced fatigue on cognitive performance, and would interest authorities seeking to preserve operational readiness.

Natural sleep loss is associated with lower mPFC activity during negative distracter processing.

Previous research has demonstrated that loss of sleep has a negative impact on both emotional and cognitive functioning. We examined whether subjectively reported natural sleep loss is associated with the interplay between emotion and cognition, as was probed by brain activity in response to emotional distraction during a working memory task. Forty-six healthy male adults reported their typical weekly sleep pattern using the Munich Chronotype Questionnaire (MCTQ), while recent sleep loss was enquired using a sleep diary in the 7 days preceding scanning. Participants performed a delayed match-to-sample task with negative and neutral distracters during the delay period inside the MRI scanner. Activity differences between negative and neutral distracters were associated to both sleep loss measures across participants. The amount of typically encountered sleep loss indicated by the MCTQ, but not sleep diary, was negatively associated with activity in the rostral anterior cingulate cortex and dorsomedial prefrontal cortex during emotionally negative compared to neutral distraction (p < 0.025, whole brain corrected). Participants showed less distracter-related activity in the ACC and dorsomedial PFC with increasing sleep loss, which, in the long run, might contribute to less adaptive emotional processing, and therefore a greater vulnerability to develop affective disorders.

An ensemble mixed effects model of sleep loss and performance.

Sleep loss causes decrements in cognitive performance, which increases risks to those in safety-sensitive fields, including medicine and aviation. Mathematical models can be formulated to predict performance decrement in response to sleep loss, with the goal of identifying when an individual may be at highest risk for an accident. This work produces an Ensemble Mixed Effects Model that combines a traditional Linear Mixed Effects (LME) model with a semi-parametric, nonlinear model called Mixed Effects Random Forest (MERF). Using this model, we predict performance on the Psychomotor Vigilance Task (PVT), a test of sustained attention, using biologically motivated features extracted from a dataset containing demographic, sleep, and cognitive test data from 44 healthy participants studied during inpatient sleep loss laboratory experiments. Our Ensemble Mixed Effects Model accurately predicts an individual's trend in PVT performance, and fits the data better than prior published models. The ensemble successfully combines MERF's high rate of peak identification with LME's conservative predictions. We investigate two questions relevant to this model's potential use in operational settings: the tradeoff between additional model features versus ease of collecting these features in real-world settings, and how recent a cognitive task must have been administered to produce strong predictions. This work addresses limitations of previous approaches by developing a predictive model that accounts for interindividual differences and utilizes a nonlinear, semi-parametric method called MERF. We methodologically address the modeling decisions required for this prediction problem, including the choice of cross-validation method. This work is novel in its use of data from a highly-controlled inpatient study protocol that uncouples the influence of the sleep-wake cycle from the endogenous circadian rhythm on the cognitive task being modeled. This uncoupling provides a clearer picture of the model's real-world predictive ability for situations in which people work at different circadian times (e.g., night- or shift-work).

The effect of 5 nights of sleep restriction on empathic propensity.

Literature supports the existence of a significant relationship between sleep quality/quantity and empathy. However, empathic ability and empathic propensity are distinct constructs. Expression of empathic propensity depends on the subjective cognitive costs attributed to the empathic experience. Studies on the effects of the experimental reduction in sleep duration on empathic behaviour are still lacking. Therefore, we investigated the consequences of 5 consecutive nights of sleep restriction on empathic propensity. A total of 42 university students (mean [SEM] age 24.09 [0.65] years; 22 females) underwent a cross-over design consisting of 5 consecutive nights of regular sleep and 5 consecutive nights of sleep restriction with a maximum of 5 hr sleep/night. After each condition, all participants were evaluated using the Empathy Selection Task, a new test assessing the motivated avoidance of empathy for its associated cognitive costs. The results showed different effects of sleep restriction depending on the habitual way of responding in the empathic context. Participants with baseline high levels of empathic propensity reduced their empathic propensity after prolonged sleep restriction. Differently, participants who tended to avoid empathising already in the habitual sleep condition maintained their empathic behaviour unchanged after sleep curtailment. In conclusion, inter-individual variability should be taken into account when evaluating the effects of sleep restriction on empathic propensity. People with habitual higher tendency to empathise could choose to avoid empathic experience following several consecutive nights of inadequate sleep.