Cognitive workload and sleep restriction interact to influence sleep homeostatic responses

Impact of one night of sleep restriction on sleepiness and cognitive function: A systematic review and meta-analysis

Detrimental consequences of chronic sleep restriction on cognitive function are well established in the literature. However, effects of a single night of sleep restriction remain equivocal. Therefore, we synthesized data from 44 studies to investigate effects of sleep restriction to 2-6 h sleep opportunity on sleepiness and cognition in this meta-analysis. We investigated subjective sleepiness, sustained attention, choice reaction time, cognitive throughput, working memory, and inhibitory control. Results revealed a significant increase in subjective sleepiness following one night of sleep restriction (Standardized Mean Difference (SMD) = 0.986, p < 0.001), while subjective sleepiness was not associated with sleep duration during sleep restriction (β = -0.214, p = 0.039, significance level 0.01). Sustained attention, assessed via common 10-min tasks, was impaired, as demonstrated through increased reaction times (SMD = 0.512, p < 0.001) and attentional lapses (SMD = 0.489, p < 0.001). However, the degree of impaired attention was not associated with sleep duration (ps > 0.090). We did not find significant effects on choice reaction time, cognitive throughput, working memory, or inhibitory control. Overall, results suggest that a single night of restricted sleep can increase subjective sleepiness and impair sustained attention, a cognitive function crucial for everyday tasks such as driving.

Brain stimulation techniques as novel treatment options for insomnia: A systematic review

Despite the success of cognitive behavioural therapy for insomnia and recent advances in pharmacotherapy, many patients with insomnia do not sufficiently respond to available treatments. This systematic review aims to present the state of science regarding the use of brain stimulation approaches in treating insomnia. To this end, we searched MEDLINE, Embase and PsycINFO from inception to 24 March 2023. We evaluated studies that compared conditions of active stimulation with a control condition or group. Outcome measures included standardized insomnia questionnaires and/or polysomnography in adults with a clinical diagnosis of insomnia. Our search identified 17 controlled trials that met inclusion criteria, and assessed a total of 967 participants using repetitive transcranial magnetic stimulation, transcranial electric stimulation, transcutaneous auricular vagus nerve stimulation or forehead cooling. No trials using other techniques such as deep brain stimulation, vestibular stimulation or auditory stimulation met the inclusion criteria. While several studies report improvements of subjective and objective sleep parameters for different repetitive transcranial magnetic stimulation and transcranial electric stimulation protocols, important methodological limitations and risk of bias limit their interpretability. A forehead cooling study found no significant group differences in the primary endpoints, but better sleep initiation in the active condition. Two transcutaneous auricular vagus nerve stimulation trials found no superiority of active stimulation for most outcome measures. Although modulating sleep through brain stimulation appears feasible, gaps in the prevailing models of sleep physiology and insomnia pathophysiology remain to be filled. Optimized stimulation protocols and proof of superiority over reliable sham conditions are indispensable before brain stimulation becomes a viable treatment option for insomnia.

Dynamic hippocampal functional connectivity responses to varying working memory loads following total sleep deprivation

Sleep loss with work overload can impact human cognitive performance. However, the brain's response to an increased working memory load following total sleep deprivation (TSD) remains unclear. In the present study, we focussed on the dynamic response of the hippocampus to increased working memory load before and after total sleep deprivation of 36 h. A total of 16 male participants completed a verbal working memory task under functional magnetic resonance imaging. After whole-brain activation analysis and region of interest analysis of the hippocampus, the generalised form of context-dependent psychophysiological interactions (gPPI) was used to analyse the hippocampal functional connectivity with the whole brain. The results revealed that as the working memory load increased within a small range, from 0-back to 1-back task, the left hippocampal functional connectivity decreased with the left supplementary motor area, left pars opercularis, left rolandic operculum, right superior frontal gyrus, bilateral precentral gyrus, and left middle cingulate cortex following total sleep deprivation compared with that observed in resting wakefulness. When the working memory load further increased from 1-back to 2-back task, the connectivity increased between the left hippocampus and the left superior parietal lobule as well as between the left hippocampus and right lingual gyrus after total sleep deprivation compared with that observed in resting wakefulness. Moreover, the left hippocampus gPPI effect on the left middle cingulate cortex and left superior parietal lobule could predict the behavioural test accuracy in 1-back and 2-back task, respectively, following total sleep deprivation. These findings indicated that increased working memory load after total sleep deprivation disrupts working memory processes. The brain reacts to these disruptions in a dynamic and flexible manner, involving not only brain activation but also hippocampus-related functional network connections.

Circadian acclimatization of performance, sleep, and 6-sulfatoxymelatonin using multiple phase shifting stimuli

Misalignment between the environment and one's circadian system is a common phenomenon (e.g., jet lag) which can have myriad negative effects on physical and mental health, mental and physiological performance, and sleep. Absent any intervention, the circadian system adjusts only 0.5-1.0 h per day to a shifted light-dark and sleep-wake schedule. Bright light facilitates circadian adjustment, but in field studies, bright light is only modestly better than no stimulus. Evidence indicates that exercise and melatonin can be combined with bright light to elicit larger shifts but no study has combined all of these stimuli or administered them at the times that are known to elicit the largest effects on the circadian system. The aims of this study are to compare the effects of different treatments on circadian adjustment to simulated jet lag in a laboratory. Following 2 weeks of home recording, 36 adults will spend 6.5 consecutive days in the laboratory. Following an 8 h period of baseline sleep recording on the participant's usual sleep schedule on Night 1 (e.g., 0000-0800 h), participants will undergo a 26 h circadian assessment protocol involving 2 h wake intervals in dim light and 1 h of sleep in darkness, repeated throughout the 26 h. During this protocol, all urine voidings will be collected; mood, sleepiness, psychomotor vigilance, and pain sensitivity will be assessed every 3 h, forehead temperature will be assessed every 90 min, and anaerobic performance (Wingate test) will be tested every 6 h. Following, the circadian assessment protocol, the participant's sleep-wake and light dark schedule will be delayed by 8 h compared with baseline (e.g., 0800-1400 h), analogous to travelling 8 times zones westward. This shifted schedule will be maintained for 3 days. During the 3 days on the delayed schedule, participants will be randomized to one of 3 treatments: (1) Dim Red Light + Placebo Capsules, (2) Bright Light Alone, (3) Bright Light + Exercise + Melatonin. During the final 26 h, all conditions and measures of the baseline circadian protocol will be repeated. Acclimatization will be defined by shifts in circadian rhythms of aMT6s, psychomotor vigilance, Wingate Anaerobic performance, mood, and sleepiness, and less impairments in these measures during the shifted schedule compared with baseline. We posit that Bright Light Alone and Bright Light + Exercise + Melatonin will elicit greater shifts in circadian rhythms and less impairments in sleep, mood, performance, and sleepiness compared with Dim Red Light + Placebo Capsules. We also posit that Bright Light + Exercise + Melatonin will elicit greater shifts and less impairments than Bright Light Alone.

Sleep Homeostasis and Night Work: A Polysomnographic Study of Daytime Sleep Following Three Consecutive Simulated Night Shifts

PURPOSE

Millions of people work at times that overlap with the habitual time for sleep. Consequently, sleep often occurs during the day. Daytime sleep is, however, characterized by reduced sleep duration. Despite preserved time spent in deep NREM sleep (stage N3), daytime sleep is subjectively rated as less restorative. Knowledge on how night work influences homeostatic sleep pressure is limited. Therefore, we aimed to explore the effect of three consecutive simulated night shifts on daytime sleep and markers of sleep homeostasis.

PATIENTS AND METHODS

We performed continuous EEG, EMG and EOG recordings in the subjects' home setting for one nighttime sleep opportunity, and for the daytime sleep opportunities following three consecutive simulated night shifts.

RESULTS

For all daytime sleep opportunities, total sleep time was reduced compared to nighttime sleep. While time spent in stage N3 was preserved, sleep pressure at sleep onset, measured by slow wave activity (1-4 Hz), was higher than nighttime sleep and higher on day 3 than on day 1 and 2. Elevated EEG power during daytime sleep was sustained through 6 h of time in bed. Slow wave energy was not significantly different from nighttime sleep after 6 h, reflecting a less efficient relief of sleep pressure.

CONCLUSION

Adaptation to daytime sleep following three consecutive simulated night shifts is limited. The increased homeostatic response and continuation of sleep pressure relief even after 6 h of sleep, are assumed to reflect a challenge for appropriate homeostatic reduction to occur.

Subtypes of nurses' mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis

BACKGROUND

Nurses play critical roles when providing health care in high-risk situations, such as during the COVID-19 outbreak. However, no previous study had systematically assessed nurses' mental workloads and its interaction patterns with fatigue, work engagement and COVID-19 exposure risk.

METHODS

A cross-sectional study was conducted via online questionnaire. The NASA Task Load Index, Fatigue Scale-14, and Utrecht Work Engagement Scale were used to assess nurses' mental workload, fatigue and work engagement, respectively. A total of 1337 valid questionnaires were received and analyzed. Nurses were categorized into different subgroups of mental workload via latent class analysis (LCA). Cross-sectional comparisons, analysis of covariance (ANCOVA), and multivariate (or logistic) regression were subsequently performed to examine how demographic variables, fatigue and work engagement differ among nurses belonging to different subgroups.

RESULTS

Three latent classes were identified based on the responses to mental workload assessment: Class 1 - low workload perception & high self-evaluation group (n = 41, 3.1%); Class 2 - medium workload perception & medium self-evaluation group (n = 455, 34.0%); and Class 3 - high workload perception & low self-evaluation group (n = 841, `62.9%). Nurses belonging into class 3 were most likely to be older and have longer professional years, and displayed higher scores of fatigue and work engagement compared with the other latent classes (p < 0.05). Multivariate analysis showed that high cognitive workload increased subjective fatigue, and mental workload may be positively associated with work engagement. Group comparison results indicated that COVID-19 exposure contributed to significantly higher mental workload levels.

CONCLUSIONS

The complex scenario for the care of patients with infectious diseases, especially during an epidemic, raises the need for improved consideration of nurses' perceived workload, as well as their physical fatigue, work engagement and personal safety when working in public health emergencies.

Assessment of effects of total sleep deprivation and subsequent recovery sleep: a methodological strategy feasible without sleep laboratory

Background

Sleep is critical for maintaining homeostasis in bodily and neurobehavioral functions. This homeostasis can be disturbed by sleep interruption and restored to normal by subsequent recovery sleep. Most research regarding recovery sleep (RS) effects has been conducted in specialized sleep laboratories, whereas small, less-well equipped research units may lack the possibilities to run studies in this area. Hence, the aims of the present study were to develop and validate an experimental protocol, which allows a thorough assessment of at-home recovery sleep after sleep deprivation.

Methods

The experimental protocol, comprising one night of baseline sleep (BL) at home, one night of monitored total sleep deprivation and a subsequent recovery night at home, was tested in a sample of 30 healthy participants. Subjects’ fatigue and alertness were assessed prior to and after each night. Sleep at home (BL, RS) was objectively assessed using portable polysomnography. To check whether our at-home sleep assessments yielded results that are comparable to those conducted in sleep laboratories, we compared the sleep data assessed in our study with sleep data assessed in laboratory studies.

Results

Sleep parameters assessed during RS exhibited changes as expected (prolonged total sleep time, better sleep efficiency, slow wave sleep rebound). Sleep parameters of BL and RS were in line with parameters assessed in previous studies examining sleep in a laboratory setting. Fatigue normalized after one night of RS; alertness partly recovered.

Conclusions

Our results suggest a successful implementation of our new experimental protocol, emphasizing it as a useful tool for future studies on RS outside of well-equipped sleep laboratories.

Raw scores on subjective sleepiness, fatigue, and vigor metrics consistently define resilience and vulnerability to sleep loss

STUDY OBJECTIVES

Although trait-like individual differences in subjective responses to sleep restriction (SR) and total sleep deprivation (TSD) exist, reliable characterizations remain elusive. We comprehensively compared multiple methods for defining resilience and vulnerability by subjective metrics.

METHODS

41 adults participated in a 13-day experiment:2 baseline, 5 SR, 4 recovery, and one 36h TSD night. The Karolinska Sleepiness Scale (KSS) and the Profile of Mood States Fatigue (POMS-F) and Vigor (POMS-V) were administered every 2h. Three approaches (Raw Score [average SR score], Change from Baseline [average SR minus average baseline score], and Variance [intraindividual SR score variance]), and six thresholds (±1 standard deviation, and the highest/lowest scoring 12.5%, 20%, 25%, 33%, 50%) categorized Resilient/Vulnerable groups. Kendall's tau-b correlations compared the group categorization's concordance within and between KSS, POMS-F, and POMS-V scores. Bias-corrected and accelerated bootstrapped t-tests compared group scores.

RESULTS

There were significant correlations between all approaches at all thresholds for POMS-F, between Raw Score and Change from Baseline approaches for KSS, and between Raw Score and Variance approaches for POMS-V. All Resilient groups defined by the Raw Score approach had significantly better scores throughout the study, notably including during baseline and recovery, whereas the two other approaches differed by measure, threshold, or day. Between-measure correlations varied in strength by measure, approach, or threshold.

CONCLUSION

Only the Raw Score approach consistently distinguished Resilient/Vulnerable groups at baseline, during sleep loss, and during recovery‒‒we recommend this approach as an effective method for subjective resilience/vulnerability categorization. All approaches created comparable categorizations for fatigue, some were comparable for sleepiness, and none were comparable for vigor. Fatigue and vigor captured resilience/vulnerability similarly to sleepiness but not each other.

Sleepiness is a signal to go to bed: data and model simulations

Study Objectives

Assess the validity of a subjective measure of sleepiness as an indicator of sleep drive by quantifying associations between intraindividual variation in evening sleepiness and bedtime, sleep duration, and next morning and subsequent evening sleepiness, in young adults.

Methods

Sleep timing and sleepiness were assessed in 19 students in late autumn and late spring on a total of 771 days. Karolinska Sleepiness Scales (KSS) were completed at half-hourly intervals at fixed clock times starting 4 h prior to participants’ habitual bedtime, and in the morning. Associations between sleepiness and sleep timing were evaluated by mixed model and nonparametric approaches and simulated with a mathematical model for the homeostatic and circadian regulation of sleepiness.

Results

Intraindividual variation in evening sleepiness was very large, covering four or five points on the 9-point KSS scale, and was significantly associated with subsequent sleep timing. On average, a one point higher KSS value was followed by 20 min earlier bedtime, which led to 11 min longer sleep, which correlated with lower sleepiness next morning and the following evening. Associations between sleepiness and sleep timing were stronger in early compared to late sleepers. Model simulations indicated that the directions of associations between sleepiness and sleep timing are in accordance with their homeostatic and circadian regulation, even though much of the variance in evening sleepiness and details of its time course remain unexplained by the model.

Conclusion

Subjective sleepiness is a valid indicator of the drive for sleep which, if acted upon, can reduce insufficient sleep.

Residual, differential neurobehavioral deficits linger after multiple recovery nights following chronic sleep restriction or acute total sleep deprivation

STUDY OBJECTIVES

The amount of recovery sleep needed to fully restore well-established neurobehavioral deficits from sleep loss remains unknown, as does whether the recovery pattern differs across measures after total sleep deprivation (TSD) and chronic sleep restriction (SR).

METHODS

In total, 83 adults received two baseline nights (10-12-hour time in bed [TIB]) followed by five 4-hour TIB SR nights or 36-hour TSD and four recovery nights (R1-R4; 12-hour TIB). Neurobehavioral tests were completed every 2 hours during wakefulness and a Maintenance of Wakefulness Test measured physiological sleepiness. Polysomnography was collected on B2, R1, and R4 nights.

RESULTS

TSD and SR produced significant deficits in cognitive performance, increases in self-reported sleepiness and fatigue, decreases in vigor, and increases in physiological sleepiness. Neurobehavioral recovery from SR occurred after R1 and was maintained for all measures except Psychomotor Vigilance Test (PVT) lapses and response speed, which failed to completely recover. Neurobehavioral recovery from TSD occurred after R1 and was maintained for all cognitive and self-reported measures, except for vigor. After TSD and SR, R1 recovery sleep was longer and of higher efficiency and better quality than R4 recovery sleep.

CONCLUSIONS

PVT impairments from SR failed to reverse completely; by contrast, vigor did not recover after TSD; all other deficits were reversed after sleep loss. These results suggest that TSD and SR induce sustained, differential biological, physiological, and/or neural changes, which remarkably are not reversed with chronic, long-duration recovery sleep. Our findings have critical implications for the population at large and for military and health professionals.

Homeostatic Response to Sleep Restriction in Adolescents

The high prevalence of chronic sleep restriction in adolescents underscores the importance of understanding how adolescent sleep is regulated under such conditions. One component of sleep regulation is a homeostatic process: if sleep is restricted, then sleep intensity increases. Our knowledge of this process is primarily informed by total sleep deprivation studies and has been incorporated in mathematical models of human sleep regulation. Several animal studies, however, suggest that adaptation occurs in chronic sleep restriction conditions, showing an attenuated or even decreased homeostatic response. We investigated the homeostatic response of adolescents to different sleep opportunities. Thirty-four participants were allocated to one of three groups with 5, 7.5 or 10 h of sleep opportunity per night for 5 nights. Each group underwent a protocol of 9 nights designed to mimic a school week between 2 weekends: 2 baseline nights (10 h sleep opportunity), 5 condition nights (5, 7.5 or 10 h), and two recovery nights (10 h). Measures of sleep homeostasis (slow-wave activity and slow-wave energy) were calculated from frontal and central EEG derivations and compared to predictions derived from simulations of the homeostatic process of the two-process model of sleep regulation. Only minor differences were found between empirical data and model predictions, indicating that sleep homeostasis is preserved under chronic sleep restriction in adolescents. These findings improve our understanding of effects of repetitive short sleep in adolescents.

Robust stability of trait-like vulnerability or resilience to common types of sleep deprivation in a large sample of adults

STUDY OBJECTIVES

Sleep loss produces large individual differences in neurobehavioral responses, with marked vulnerability or resilience among individuals. Such differences are stable with repeated exposures to acute total sleep deprivation (TSD) or chronic sleep restriction (SR) within short (weeks) and long (years) intervals. Whether trait-like responses are observed to commonly experienced types of sleep loss and across various demographically defined groups remains unknown.

METHODS

Eighty-three adults completed two baseline nights (10 h-12 h time-in-bed, TIB) followed by five 4 h TIB SR nights or 36 h TSD. Participants then received four 12-h TIB recovery nights followed by five SR nights or 36 h TSD, in counterbalanced order to the first sleep loss sequence. Neurobehavioral tests were completed every 2 h during wakefulness.

RESULTS

Participants who displayed neurobehavioral vulnerability to TSD displayed vulnerability to SR, evidenced by substantial to near perfect intraclass correlation coefficients (ICCs; 78%-91% across measures). Sex, race, age, body mass index (BMI), season, and sleep loss order did not impact ICCs significantly. Individuals exhibited significant consistency of responses within, but not between, performance and self-reported domains.

CONCLUSIONS

Using the largest, most diverse sample to date, we demonstrate for the first time the remarkable stability of phenotypic neurobehavioral responses to commonly experienced sleep loss types, across demographic variables and different performance and self-reported measures. Since sex, race, age, BMI, and season did not affect ICCs, these variables are not useful for determining stability of responses to sleep loss, underscoring the criticality of biological predictors. Our findings inform mathematical models and are relevant for the general population and military and health professions.

Caloric and Macronutrient Intake and Meal Timing Responses to Repeated Sleep Restriction Exposures Separated by Varying Intervening Recovery Nights in Healthy Adults

Sleep restriction (SR) reliably increases caloric intake. It remains unknown whether such intake cumulatively increases with repeated SR exposures and is impacted by the number of intervening recovery sleep opportunities. Healthy adults (33.9 ± 8.9y; 17 women, Body Mass Index: 24.8 ± 3.6) participated in a laboratory protocol. N = 35 participants experienced two baseline nights (10 h time-in-bed (TIB)/night; 22:00–08:00) followed by 10 SR nights (4 h TIB/night; 04:00–08:00), which were divided into two exposures of five nights each and separated by one (n = 13), three (n = 12), or five (n = 10) recovery nights (12 h TIB/night; 22:00–10:00). Control participants (n = 10) were permitted 10 h TIB (22:00–08:00) on all nights. Food and drink consumption were ad libitum and recorded daily. Compared to baseline, sleep-restricted participants increased daily caloric (+527 kcal) and saturated fat (+7 g) intake and decreased protein (−1.2% kcal) intake during both SR exposures; however, intake did not differ between exposures or recovery conditions. Similarly, although sleep-restricted participants exhibited substantial late-night caloric intake (671 kcal), such intake did not differ between exposures or recovery conditions. By contrast, control participants showed no changes in caloric intake across days. We found consistent caloric and macronutrient intake increases during two SR exposures despite varying intervening recovery nights. Thus, energy intake outcomes do not cumulatively increase with repeated restriction and are unaffected by recovery opportunities.

Distinct effects of orexin receptor antagonist and GABAA agonist on sleep and physical/cognitive functions after forced awakening

The majority of patients with insomnia are treated with hypnotic agents. In the present study, we evaluated the side-effect profile of an orexin receptor antagonist and γ-aminobutyric acid A (GABA_A) receptor agonist on physical/cognitive functions upon forced awakening. This double-blind, randomized, placebo-controlled, cross-over study was conducted on 30 healthy male subjects. Fifteen minutes before bedtime, the subjects took a pill of suvorexant (20 mg), brotizolam (0.25 mg), or placebo and were forced awake 90 min thereafter. Physical- and cognitive-function tests were performed before taking the pill, after forced awakening, and the next morning. Polysomnographic recordings revealed that the efficacies of the hypnotic agents in prolonging total sleep time (∼30 min) and increasing sleep efficiency (∼6%) were comparable. When the subjects were allowed to go back to sleep after the forced awakening, the sleep latency was shorter under the influence of hypnotic agents (∼2 min) compared to the placebo trial (24 min), and the rapid eye movement latency was significantly shorter under suvorexant (98.8, 81.7, and 48.8 min for placebo, brotizolam, and suvorexant, respectively). Although brotizolam significantly impaired the overall physical/cognitive performance (sum of z score) compared with placebo upon forced awakening, there was no significant difference in the total z score of performance between suvorexant and placebo. Notably, the score for static balance with the eyes open was higher under suvorexant compared to brotizolam administration. The energy expenditure was lower under suvorexant and brotizolam compared with the placebo. The effect size of brotizolam (d = 0.24) to reduce the energy expenditure was larger than that of suvorexant (d < 0.01).

Sleepiness as a Local Phenomenon

Sleep occupies a third of our life and is a primary need for all animal species studied so far. Nonetheless, chronic sleep restriction is a growing source of morbidity and mortality in both developed and developing countries. Sleep loss is associated with the subjective feeling of sleepiness and with decreased performance, as well as with detrimental effects on general health, cognition, and emotions. The ideas that small brain areas can be asleep while the rest of the brain is awake and that local sleep may account for at least some of the cognitive and behavioral manifestations of sleepiness are making their way into the scientific community. We herein clarify the different ways sleep can intrude into wakefulness, summarize recent scientific advances in the field, and offer some hypotheses that help framing sleepiness as a local phenomenon.

Evening electronic device use and sleep patterns in athletes

The present study aimed to investigate pre-sleep behaviours (including evening electronic device use) and sleep quantity in well-trained athletes. Seventy well-trained athletes (44 females, 26 males) aged 21 ± 4 y from a range of team and individual sports were asked to complete an online sleep diary for 7 days. The sleep diary included questions about pre-sleep behaviours (e.g. napping, caffeine intake), electronic device use in the 2 h prior to bedtime (e.g. type of device and duration of use) and sleep (e.g. time in bed, sleep onset latency). On average, athletes spent 8:20 ± 1:21 h in bed each night. Associations between age, time in bed and sleepiness suggested that younger athletes spent more time in bed (B = -0.05, p = 0.001) but felt sleepier (r = -0.32, p < 0.01) than older athletes. On average, athletes mostly used electronic devices for 0-30 min prior to sleep. The use of multiple devices in the evening was associated with more perceived difficulty in falling asleep (B = 0.22, p = 0.03), but no associations existed with other sleep variables. In summary, younger athletes may require later start times or improved sleep quality to resolve excessive sleepiness.

An improved model to predict performance under mental fatigue

Fatigue has become an increasing problem in our modern society. Using MATLAB as a generic modelling tool, a fatigue model was developed based on an existing one and compared with a commercial fatigue software for prediction of cognitive performance under total and partial sleep deprivation. The flexibility of our fatigue model allowed additions of new algorithms and mechanisms for non-sleep factors and countermeasures and thus improved model predictions and usability for both civilian and military applications. This was demonstrated by model simulations of various scenarios and comparison with experimental studies. Our future work will be focused on model validation and integration with other modelling tools. Practitioner Summary: Mental fatigue affects health, safety and quality of life in our modern society. In this paper, we reported a cognitive fatigue model based on existing models with newly incorporated components taking both the operator's state of alertness and task demand into account. The model provided the additional capability for prediction of cognitive performance in scenarios involving pharmaceutical countermeasures, different task demands and shift work.

Influence of new hire transition workload on insomnia in nurses

AIMS

In this study, we investigated the relationship of the prevalence and incidence of insomnia with the new hire transition workload in nurses.

METHODS

This retrospective study used the clinical diagnosis data of the entire nursing population in Taiwan for 2005 to 2008, drawn from the National Health Insurance Research Database. Adjusted logistic regression and Cox regression models were used to separately analyse factors related to the prevalence and incidence of insomnia.

RESULTS

During this period, the prevalence of insomnia increased, whereas its incidence remained stable. After adjustment for demographic variables in the logistic regression models, the higher prevalence of insomnia was associated with a longer employment duration and a higher new hire ratio. In the Cox regression models, a higher incidence of insomnia was associated with a shorter employment duration and a higher new hire ratio. Nurses with a longer employment duration had a higher prevalence, but lower incidence, of insomnia. A higher new hire ratio was associated with a higher prevalence and incidence of insomnia.

CONCLUSION

To mitigate the risk of insomnia, we suggest that additional support should be provided to non-new nurses to assist them in the new hire transition.

Intraindividual Increase of Homeostatic Sleep Pressure Across Acute and Chronic Sleep Loss: A High-Density EEG Study

Study Objectives

To compare intraindividually the effects of acute sleep deprivation (ASD) and chronic sleep restriction (CSR) on the homeostatic increase in slow wave activity (SWA) and to relate it to impairments in basic cognitive functioning, that is, vigilance.

Methods

The increase in SWA after ASD (40 hours of wakefulness) and after CSR (seven nights with time in bed restricted to 5 hours per night) relative to baseline sleep was assessed in nine healthy, male participants (age = 18-26 years) by high-density electroencephalography. The SWA increase during the initial part of sleep was compared between the two conditions of sleep loss. The increase in SWA was related to the increase in lapses of vigilance in the psychomotor vigilance task (PVT) during the preceding days.

Results

While ASD induced a stronger increase in initial SWA than CSR, the increase was globally correlated across the two conditions in most electrodes. The increase in initial SWA was positively associated with the increase in PVT lapses.

Conclusions

The individual homeostatic response in SWA is globally preserved across acute and chronic sleep loss, that is, individuals showing a larger increase after ASD also do so after CSR and vice versa. Furthermore, the increase in SWA is globally correlated to vigilance impairments after sleep loss over both conditions. Thus, the increase in SWA might therefore provide a physiological marker for individual differences in performance impairments after sleep loss.

Daytime microsleeps during 7 days of sleep restriction followed by 13 days of sleep recovery in healthy young adults

We investigated the consequences of sleep restriction (SR) on maintenance of wakefulness capacities and diurnal sleepiness through microsleeps monitoring. 12 healthy males (20-36 years old) were sleep restricted (4 h per night) during 7 nights followed by 13 nights of recovery sleep. Participants completed Karolinska Sleepiness Scale (KSS) and Maintenance of Wakefulness Test (MWT) at baseline (B), during SR (SR1, SR4 and SR7) and during recovery (R3 and R13), while continuously recorded for EEG analysis. During SR, MWT latencies decreased (SR7: -24.4%), whereas the number, the cumulative duration of microsleeps and KSS scores increased. Recovery nights allowed MWT latencies, KSS scores and all sleep values to return to baseline levels, while a rebound in N3, N3% and REM% sleep stages occurred. During SR, the maintenance of N3 sleep duration seems not sufficient to reduce daytime sleepiness and MWT results did not reflect the sleepiness levels characterized by persistent sleep attacks.

Healthy Adults Display Long-Term Trait-Like Neurobehavioral Resilience and Vulnerability to Sleep Loss

Sleep loss produces well-characterized cognitive deficits, although there are large individual differences, with marked vulnerability or resilience among individuals. Such differences are stable with repeated exposures to acute total sleep deprivation (TSD) within a short-time interval (weeks). Whether such stability occurs with chronic sleep restriction (SR) and whether it endures across months to years in TSD, indicating a true trait, remains unknown. In 23 healthy adults, neurobehavioral vulnerability to TSD exposures, separated by 27–2,091 days (mean: 444 days; median: 210 days), showed trait-like stability in performance and subjective measures (82–95% across measures). Similarly, in 24 healthy adults, neurobehavioral vulnerability to SR exposures, separated by 78–3,058 days (mean: 935 days; median: 741 days), also showed stability (72–92% across measures). Cognitive performance outcomes and subjective ratings showed consistency across objective measures, and consistency across subjective measures, but not between objective and subjective domains. We demonstrate for the first time the stability of phenotypic neurobehavioral responses in the same individuals to SR and to TSD over long-time intervals. Across multiple measures, prior sleep loss responses are strong predictors of individual responses to subsequent sleep loss exposures chronically or intermittently, across months and years, thus validating the need for biomarkers and predictors.

What drives slow wave activity during early non-REM sleep: Learning during prior wake or effort?

What is the function of sleep in humans? One claim is that sleep consolidates learning. Slow wave activity (SWA), i.e. slow oscillations of frequency < 4 Hz, has been observed in electroencephalograms (EEG) during sleep; it increases with prior wakefulness and decreases with sleep. Studies have claimed that increase in SWA in specific regions of the sleeping brain is correlated with overnight improved performance, i.e. overnight consolidation, on a demanding motor learning task. We wondered if SWA change during sleep is attributable to overnight consolidation or to metabolic demand. Participants executed out-and-back movements to a target using a pen-like cursor with their dominant hand while the target and cursor position were displayed on a screen. They trained on three different conditions on separate nights, differing in the amount and degree of rotation between the actual hand movement direction and displayed cursor movement direction. In the no-rotation (NR) condition, there was no rotation. In the single rotation (SR) condition, the amount of rotation remained the same throughout, and performance improved both across pre-sleep training and after sleep, i.e. overnight consolidation occurred; in the random rotation (RR) condition, the amount of rotation varied randomly from trial to trial, and no overnight consolidation occurred; SR and RR were cognitively demanding. The average EEG power density of SWA for the first 30 min. of non-rapid eye movement sleep after training was computed. Both SR and RR elicited increase in SWA in the parietal region; furthermore, the topographic distribution of SWA in each was remarkably similar. No correlation was found between the overnight performance improvement on SR and the SWA change in the parietal region on measures of learning. Our results argue that regulation of SWA in early sleep is associated with high levels of cognitive effort during prior wakefulness, and not just overnight consolidation.

Molecular Mechanisms of Sleep Homeostasis in Flies and Mammals

Sleep is homeostatically regulated with sleep pressure accumulating with the increasing duration of prior wakefulness. Yet, a clear understanding of the molecular components of the homeostat, as well as the molecular and cellular processes they sense and control to regulate sleep intensity and duration, remain a mystery. Here, we will discuss the cellular and molecular basis of sleep homeostasis, first focusing on the best homeostatic sleep marker in vertebrates, slow wave activity; second, moving to the molecular genetic analysis of sleep homeostasis in the fruit fly Drosophila; and, finally, discussing more systemic aspects of sleep homeostasis.

The neurocognitive consequences of sleep restriction: A meta-analytic review

The current meta-analytic review evaluated the effects of experimentally manipulated sleep restriction on neurocognitive functioning. Random-effects models were employed to estimate the overall effect size and the differential effect size across cognitive domains. Age, time of day, age-adjusted sleep deficit, cumulative days of restricted sleep, sleep latency, subjective sleepiness, and biological sex were examined as potential moderators of the effect. Based on a sample of 61 studies, from 71 different populations, findings revealed a significant negative effect of sleep restriction on cognitive processing across cognitive domains (g=-0.383, p<0.001). This effect held for executive functioning (g=-0.324, p<0.001), sustained attention (g=-0.409, p<0.001), and long-term memory (g=-0.192, p=0.002). There was insufficient evidence to detect an effect within the domains of attention, multitask, impulsive decision-making or intelligence. Age group, time of day, cumulative days of restricted sleep, sleep latency, subjective sleepiness, and biological sex were all significant moderators of the overall effect. In conclusion, the current meta-analysis is the first comprehensive review to provide evidence that short-term sleep restriction significantly impairs waking neurocognitive functioning.

Fatiguing effect of multiple take-offs and landings in regional airline operations

Fatigue is a risk factor for flight performance and safety in commercial aviation. In US commercial aviation, to help to curb fatigue, the maximum duration of flight duty periods is regulated based on the scheduled start time and the number of flight segments to be flown. There is scientific support for regulating maximum duty duration based on scheduled start time; fatigue is well established to be modulated by circadian rhythms. However, it has not been established scientifically whether the number of flight segments, per se, affects fatigue. To address this science gap, we conducted a randomized, counterbalanced, cross-over study with 24 active-duty regional airline pilots. Objective and subjective fatigue was compared between a 9-hour duty day with multiple take-offs and landings versus a duty day of equal duration with a single take-off and landing. To standardize experimental conditions and isolate the fatiguing effect of the number of segments flown, the entire duty schedules were carried out in a high-fidelity, moving-base, full-flight, regional jet flight simulator. Steps were taken to maintain operational realism, including simulated airplane inspections and acceptance checks, use of realistic dispatch releases and airport charts, real-world air traffic control interactions, etc. During each of the two duty days, 10 fatigue test bouts were administered, which included a 10-minute Psychomotor Vigilance Test (PVT) assessment of objective fatigue and Samn-Perelli (SP) and Karolinska Sleepiness Scale (KSS) assessments of subjective sleepiness/fatigue. Results showed a greater build-up of objective and subjective fatigue in the multi-segment duty day than in the single-segment duty day. With duty start time and duration and other variables that could impact fatigue levels held constant, the greater build-up of fatigue in the multi-segment duty day was attributable specifically to the difference in the number of flight segments flown. Compared to findings in previously published laboratory studies of simulated night shifts and nighttime sleep deprivation, the magnitude of the fatiguing effect of the multiple take-offs and landings was modest. Ratings of flight performance were not significantly reduced for the simulated multi-segment duty day. The US duty and flight time regulations for commercial aviation shorten the maximum duty duration in multi-segment operations by up to 25% depending on the duty start time. The present results represent an important first step in understanding fatigue in multi-segment operations, and provide support for the number of flight segments as a relevant factor in regulating maximum duty duration. Nonetheless, based on our fatigue results, a more moderate reduction in maximum duty duration as a function of the number of flight segments might be considered. However, further research is needed to include investigation of flight safety, and to extend our findings to nighttime operations.

Effects of partial sleep deprivation on slow waves during non-rapid eye movement sleep: A high density EEG investigation

OBJECTIVE

Changes in slow waves during non-rapid eye movement (NREM) sleep in response to acute total sleep deprivation are well-established measures of sleep homeostasis. This investigation utilized high-density electroencephalography (hdEEG) to examine topographic changes in slow waves during repeated partial sleep deprivation.

METHODS

Twenty-four participants underwent a 6-day sleep restriction protocol. Spectral and period-amplitude analyses of sleep hdEEG data were used to examine changes in slow wave energy, count, amplitude, and slope relative to baseline.

RESULTS

Changes in slow wave energy were dependent on the quantity of NREM sleep utilized for analysis, with widespread increases during sleep restriction and recovery when comparing data from the first portion of the sleep period, but restricted to recovery sleep if the entire sleep episode was considered. Period-amplitude analysis was less dependent on the quantity of NREM sleep utilized, and demonstrated topographic changes in the count, amplitude, and distribution of slow waves, with frontal increases in slow wave amplitude, numbers of high-amplitude waves, and amplitude/slopes of low amplitude waves resulting from partial sleep deprivation.

CONCLUSIONS

Topographic changes in slow waves occur across the course of partial sleep restriction and recovery.

SIGNIFICANCE

These results demonstrate a homeostatic response to partial sleep loss in humans.

Sleep restriction and delayed sleep associate with psychological health and biomarkers of stress and inflammation in women

STUDY OBJECTIVES

Despite strong associations between sleep duration and health, there is no clear understanding of how volitional chronic sleep restriction (CSR) alters the physiological processes that lead to poor health in women. We focused on biochemical and psychological factors that previous research suggests are essential to uncovering the role of sleep in health.

DESIGN

Cross-sectional study.

SETTING

University-based.

PARTICIPANTS

Sixty female participants (mean age, 19.3; SD, 2.1 years).

MEASUREMENTS

We analyzed the association between self-reported volitional CSR and time to go to sleep on a series of sleep and psychological health measures as well as biomarkers of immune functioning/inflammation (interleukin [IL]-1β), stress (cortisol), and sleep regulation (melatonin).

RESULTS

Across multiple measures, poor sleep was associated with decreased psychological health and a reduced perception of self-reported physical health. Volitional CSR was related to increased cortisol and increased IL-1β levels. We separately looked at individuals who experienced CSR with and without delayed sleep time and found that IL-1β levels were significantly elevated in CSR alone and in CSR combined with a late sleep time. Cortisol, however, was only elevated in those women who experienced CSR combined with a late sleep time. We did not observe any changes in melatonin across groups, and melatonin levels were not related to any sleep measures.

CONCLUSIONS

New to our study is the demonstration of how an increase in a proinflammatory process and an increase in hypothalamic-pituitary-adrenal axis activity both relate to volitional CSR, with and without a delayed sleep time. We further show how these mechanisms relate back to psychological and self-reported health in young adult women.

Digital media use in the 2 h before bedtime is associated with sleep variables in university students

Digital media use is widespread in University students, and use of digital media near bedtime has a broadly negative effect on sleep outcomes. Adequate and good quality sleep is important for physical and mental health, but few studies have rigorously measured both sleep and digital media use. In this study, we investigated whether self-reported sleep patterns were associated with digital media use in a first-year University student (N = 254, 48% male) population. Students tracked their sleep through daily online diaries and provided digital media use data in 15-min blocks for 2 h prior to bedtime on nine occasions. A longer duration of digital media use was associated with reduced total sleep time and later bedtime, while greater diversity of digital media use was associated with increased total sleep time and earlier bedtime. Analysis of activities in the last hour before bedtime indicated that activity type plays a role in digital media's effect on sleep, with computer work, surfing the Internet, and listening to music showing the strongest relationship to multiple sleep variables. These findings have implications for physical and mental health of University students and can inform design of devices to minimize negative effects of digital media on sleep.

Impact of sleep loss before learning on cortical dynamics during memory retrieval

Evidence shows that sleep loss before learning decreases activation of the hippocampus during encoding and promotes forgetting. But it remains to be determined which neural systems are functionally affected during memory retrieval after one night of recovery sleep. To investigate this issue, we evaluated memory for pairs of famous people's faces with the same or different profession (i.e., semantically congruent or incongruent faces) after one night of undisturbed sleep in subjects who either underwent 4hours of acute sleep restriction (ASR, N=20) or who slept 8hours the pre-training night (controls, N=20). EEG recordings were collected during the recognition memory task in both groups, and the cortical sources generating this activity localized by applying a spatial beamforming filter in the frequency domain. Even though sleep restriction did not affect accuracy of memory performance, controls showed a much larger decrease of alpha power relative to a baseline period when compared to sleep-deprived subjects. These group differences affected a widespread frontotemporoparietal network involved in retrieval of episodic/semantic memories. Regression analyses further revealed that associative memory in the ASR group was negatively correlated with alpha power in the occipital regions, whereas the benefit of congruency in the same group was positively correlated with delta power in the left lateral prefrontal cortex. Retrieval-related decreases of alpha power have been associated with the reactivation of material-specific memory representations, whereas increases of delta power have been related to inhibition of interferences that may affect the performance of the task. We can therefore draw the conclusion that a few hours of sleep loss in the pre-training night, though insufficient to change the memory performance, is sufficient to alter the processes involved in retrieving and manipulating episodic and semantic information.

Sleep and plasticity in schizophrenia

Schizophrenia is a devastating mental illness with a worldwide prevalence of approximately 1%. Although the clinical features of the disorder were described over one hundred years ago, its neurobiology is still largely elusive despite several decades of research. Schizophrenia is associated with marked sleep disturbances and memory impairment. Above and beyond altered sleep architecture, sleep rhythms including slow waves and spindles are disrupted in schizophrenia. In the healthy brain, these rhythms reflect and participate in plastic processes during sleep. This chapter discusses evidence that schizophrenia patients exhibit dysfunction of sleep-mediated plasticity on a behavioral, cellular, and molecular level and offers suggestions on how the study of sleeping brain activity can shed light on the pathophysiological mechanisms of the disorder.