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

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.

Effects of total sleep deprivation on performance in a manual spacecraft docking task

Sleep deprivation and circadian rhythm disruptions are highly prevalent in shift workers, and also among astronauts. Resulting sleepiness can reduce cognitive performance, lead to catastrophic occupational events, and jeopardize space missions. We investigated whether 24 hours of total sleep deprivation would affect performance not only in the Psychomotor Vigilance Task (PVT), but also in a complex operational task, i.e. simulated manual spacecraft docking. Sixty-two healthy participants completed the manual docking simulation 6df and the PVT once after a night of total sleep deprivation and once after eight hours of scheduled sleep in a counterbalanced order. We assessed the impact of sleep deprivation on docking as well as PVT performance and investigated if sustained attention is an essential component of operational performance after sleep loss. The results showed that docking accuracy decreased significantly after sleep deprivation in comparison to the control condition, but only at difficult task levels. PVT performance deteriorated under sleep deprivation. Participants with larger impairments in PVT response speed after sleep deprivation also showed larger impairments in docking accuracy. In conclusion, sleep deprivation led to impaired 6df performance, which was partly explained by impairments in sustained attention. Elevated motivation levels due to the novelty and attractiveness of the task may have helped participants to compensate for the effects of sleepiness at easier task levels. Continued testing of manual docking skills could be a useful tool both to detect sleep loss-related impairments and assess astronauts' readiness for duty during long-duration missions.

Bright Light Therapy for Major Depressive Disorder in Adolescent Outpatients: A Preliminary Study

BACKGROUND

Bright light therapy (BLT) has not been well-studied in adolescents with major depressive disorder, particularly in outpatient settings.

METHODS

We conducted an 8-week clinical trial of BLT in adolescents recruited from a primary care practice with moderate to severe major depression. Acceptability and feasibility were defined by daily use of the light box and integration into daily routines. To assess treatment effects, we utilized the Short Mood and Feelings Questionnaire (SMFQ) and actigraphic sleep variables.

RESULTS

Of the nine enrolled adolescents, the rate of daily use of the light therapy box was 100% at week 2, 78% at week 4 (n = 7), and 67% at weeks 6 and 8 (n = 6). Participants were better able to integrate midday BLT compared to morning BLT into their day-to-day routines. Mean depression scores improved during the 2-week placebo lead-in (dim red light-DRL) and continued to show significant improvement through 6 weeks of BLT. Sleep efficiency increased significantly (p = 0.046), and sleep onset latency showed a trend toward a significant decrease (p = 0.075) in the BLT phase compared to the DRL phase.

CONCLUSION

Bright light treatment that was self-administered at home was feasible, acceptable, and effective for adolescent outpatients with depression. Findings support the development of larger, well-powered, controlled clinical trials of BLT in coordination with primary care.

Short-term and long-term phenotypic stability of actigraphic sleep metrics involving repeated sleep loss and recovery

For the first time, we determined whether actigraphic-assessed sleep measures show inter-individual differences and intra-individual stability during baseline (BL) and recovery (REC) phases surrounding repeated total sleep deprivation (TSD). We conducted a 5-day experiment at Months 2 and 4 in two separate studies (N = 11). During each experiment, sleep measures were collected via wrist actigraphy during two BL 8 h time-in-bed (TIB) nights (B1, B2) and during two REC 8-10 h TIB nights (R1, R2). Intraclass correlation coefficients (ICCs) assessed actigraphic measure long-term stability between 2 and 4 months for (1) the pre-experimental phase before BL; and (2) the BL (B1 + B2), REC (R1 + R2), and BL and REC average (BL + REC) phases; and short-term stability at Month 2 and at Month 4; and (3) between B1 versus B2 and R1 versus R2 in each 5-day experiment. Nearly all ICCs during the pre-experimental, BL, REC, and BL + REC phases were moderate to almost perfect (0.446-0.970) between Months 2 and 4. B1 versus B2 ICCs were more stable (0.440-0.899) than almost all R1 versus R2 ICCs (-0.696 to 0.588) at Month 2 and 4. Actigraphic sleep measures show phenotypic long-term stability during BL and REC surrounding repeated TSD between 2 and 4 months. Furthermore, within each 5-day experiment at Month 2 and 4, the two BL nights before TSD were more stable than the two REC nights following TSD, likely due to increased R1 homeostatic pressure. Given the consistency of actigraphic measures across the short-term and long-term, they can serve as biomarkers to predict physiological and neurobehavioral responses to sleep loss.

Comparison of effects of modafinil and caffeine on fatigue-vulnerable and fatigue-resistant aircrew after a limited period of sleep deprivation

Introduction: Literature suggests pilots experience fatigue differently. So-called fatigue-resistant or -vulnerable individuals might also respond differently to countermeasures or stimulants. This study, which is part of a larger randomized controlled clinical trial, aims to investigate the effect of caffeine and modafinil on fatigue-resistant and -vulnerable pilots. Methods: This study included 32 healthy employees of the Royal Netherlands Air Force, who completed three test days, separated by at least 7 days. After a regular work day, the subjects were randomly administered either 300 mg caffeine, 200 mg modafinil or placebo at midnight. Hereafter the subjects performed the psychomotor vigilance test (PVT), vigilance and tracking test (VigTrack) and Stanford sleepiness scale (SSS) six times until 8 a.m. the next day. Subjects were ranked on the average number of lapses on the PVT during the placebo night and divided into three groups: fatigue-vulnerable (FVUL), -intermediate (FINT) and -resistant (FRES), with 11, 10 and 11 subjects in each group, respectively. Area under the curve (AUC) of the PVT, VigTrack and SSS during the test nights were calculated, which were used in univariate factorial analysis of variance (ANOVA). Tukey's HSD post hoc tests were used to differentiate between the groups. Results: A significant effect of treatment was found in the ANOVA of both PVT parameters, VigTrack mean reaction time and SSS. There was a statistically significant effect of fatigue group on all PVT parameters and VigTrack mean percentage omissions, where FINT and FRES scored better than FVUL. There was a significant interaction effect between treatment and fatigue group for PVT number of lapses. This is congruent for the AUC analyses in which for all parameters (except for the SSS) the performance of the FVUL group was consistently worse than that of the FINT and FRES groups. Discussion: This study demonstrates that the performance of individuals with different fatigue tolerances are differently affected by simulants after a limited period of sleep deprivation. The classification of fatigue tolerance through PVT lapses when sleep deprived seems to be able to predict this.

Poor sleep is associated with deficits of attention in COPD patients

BACKGROUND

Poor sleep and attention deficits are common in COPD.

OBJECTIVES

To assess the relationship between self-reported poor sleep and attention deficits in COPD. We also studied the association between self-reported sleep and the attention tests with the objective characteristics of sleep.

METHODS

Fifty-nine COPD patients were prospectively studied. Self-reported sleep quality was assessed using the Pittsburgh sleep quality index (PSQI). Objective characteristics of sleep were assessed by actigraphy and polysomnography. Attention was evaluated with the Oxford sleep resistance test (OSLER) and the Psychomotor vigilance test (PVT).

RESULTS

28 (47 %) patients referred poor sleep (PSQI >5). In the OSLER test they showed earlier sleep onset than patients with good sleep, median (Interquartil range): 31.2 min (25.4-40) vs 40 min (28.5-40), p: 0.048. They also spent more time making errors: 4.5 % (0.6-7.6) of total test time vs 0.7 % (0.2-5.3), p: 0.048. In PVT, patients with poor sleep presented a greater dispersion of the reaction time values with a higher value in the slowest 10 % of the reactions, 828 (609-1667) msec. vs 708 (601-993) msec, p: 0.028. No association was found between self-reported poor sleep and objective sleep variables. We found no correlation between OSLER and PVT results and polysomnographic variables except between sleep efficiency and PVT response speed (β: 0.309, p: 0.018).

CONCLUSION

Self-reported poor sleep in COPD is associated with attention deficits. Sleep quality should be included in future studies of this facet of cognition in COPD, as well as to assess its potential usefulness as a therapeutic target.

The role of the fronto-parietal network in modulating sustained attention under sleep deprivation: an functional magnetic resonance imaging study

Objective

The intricate relationship between sleep deprivation (SD) and cognitive performance has long been a subject of research. Our study offers a novel angle by closely examining the neurobiological underpinnings of sustained attention deficits through the lens of the fronto-parietal network (FPN). Using state-of-the-art imaging techniques, we delve into the changes in spontaneous brain activity after SD and explore their associations with performance on the psychomotor vigilance task (PVT).

Methods

We conducted an elaborate investigation involving 64 healthy, right-handed participants who underwent resting-state functional MRI scans before and after experiencing 24 h of sleep deprivation. Employing sophisticated statistical analyses, we scrutinized the changes in fractional amplitude of low-frequency fluctuations (fALFF) through paired t-tests. Pearson correlation analyses were then applied to dissect the associations between these neurobiological shifts and behavioral outcomes in PVT.

Results

The study yielded remarkable findings, revealing a dramatic decrease in fALFF values within critical areas of the FPN following SD. These alterations predominantly occurred in the frontal and parietal gyri and were inversely correlated with PVT performance metrics. Furthermore, we discovered that baseline fALFF values in the left dorsolateral prefrontal cortex (DLPFC) have the potential to serve as compelling neurobiological markers, with high discriminatory power in identifying individual responses to the adverse effects of SD on cognitive performance.

Conclusion

Our groundbreaking research underscores the pivotal role that the FPN plays in modulating attention and executive function, especially under the challenging conditions brought about by sleep deprivation. The findings offer critical insights that could shape the way we understand, assess, and potentially mitigate the cognitive impacts of SD, setting the stage for future research in this riveting domain.

Impact of bimonthly repeated total sleep deprivation and recovery sleep on cardiovascular indices

Since short sleep duration adversely affects cardiovascular (CV) health, we investigated the effects of exposures to total sleep deprivation (TSD), and baseline (BL) and recovery (REC) sleep on CV measures. We conducted a 5-day experiment at months 2 and 4 in two separate studies (N = 11 healthy adults; 5 females). During these repeated experiments, CV measures [stroke volume (SV), cardiac index (CI), systemic vascular resistance index (SVRI), left ventricular ejection time, heart rate (HR), systolic and diastolic blood pressure (SBP and DBP) and mean arterial pressure (MAP)] were collected at three assessment time points after: (1) two BL 8 h time-in-bed (TIB) sleep opportunity nights; (2) a TSD night; and (3) two REC 8-10 h TIB nights. CV measures were also collected pre-study. TSD significantly increased SV and CI, and decreased SVRI, with large effect sizes, which importantly were reversed with recovery, indicating these measures are possible novel biomarkers for assessing the adverse consequences of TSD. Pre-study SV, CI, SVRI, HR, SBP, and MAP measures also significantly associated with TSD CV responses at months 2 and 4 [Pearson's r: 0.615-0.862; r2 : 0.378-0.743], indicating they are robust correlates of future TSD CV responses. Our novel findings highlight the critical impact of sleep on CV health across time.

Cardiovascular measures display robust phenotypic stability across long-duration intervals involving repeated sleep deprivation and recovery

Introduction

We determined whether cardiovascular (CV) measures show trait-like responses after repeated total sleep deprivation (TSD), baseline (BL) and recovery (REC) exposures in two long-duration studies (total N = 11 adults).

Methods

A 5-day experiment was conducted twice at months 2 and 4 in a 4-month study (N = 6 healthy adults; 3 females; mean age ± SD, 34.3 ± 5.7 years; mean BMI ± SD, 22.5 ± 3.2 kg/m2), and three times at months 2, 4, and 8 in an 8-month study (N = 5 healthy adults; 2 females; mean age ± SD, 33.6 ± 5.17 years; mean BMI ± SD, 27.1 ± 4.9 kg/m2). Participants were not shift workers or exposed to TSD in their professions. During each experiment, various seated and standing CV measures were collected via echocardiography [stroke volume (SV), heart rate (HR), cardiac index (CI), left ventricular ejection time (LVET), and systemic vascular resistance index (SVRI)] or blood pressure monitor [systolic blood pressure (SBP)] after (1) two BL 8h time in bed (TIB) nights; (2) an acute TSD night; and (3) two REC 8-10 h TIB nights. Intraclass correlation coefficients (ICCs) assessed CV measure stability during BL, TSD, and REC and for the BL and REC average (BL + REC) across months 2, 4, and 8; Spearman's rho assessed the relative rank of individuals' CV responses across measures.

Results

Seated BL (0.693-0.944), TSD (0.643-0.962) and REC (0.735-0.960) CV ICCs showed substantial to almost perfect stability and seated BL + REC CV ICCs (0.552-0.965) showed moderate to almost perfect stability across months 2, 4, and 8. Individuals also exhibited significant, consistent responses within seated CV measures during BL, TSD, and REC. Standing CV measures showed similar ICCs for BL, TSD, and REC and similar response consistency.

Discussion

This is the first demonstration of remarkably robust phenotypic stability of a number of CV measures in healthy adults during repeated TSD, BL and REC exposures across 2, 4, and 8 months, with significant consistency of responses within CV measures. The cardiovascular measures examined in our studies, including SV, HR, CI, LVET, SVRI, and SBP, are useful biomarkers that effectively track physiology consistently across long durations and repeated sleep deprivation and recovery.

Sleep loss suicidal ideation: the role of trait extraversion

Background: It is known that sleep disturbance is associated with increased suicidal thinking. Moreover, completed suicides, when adjusted for the proportion of the populace that is awake at a given time, are more probable during the late night/early morning hours. Despite these concerns, no studies have examined the role of trait-like individual differences in vulnerability to suicidal ideation during sleep deprivation or insomnia. In two separate studies, we examined whether the trait of extraversion is predictive of changes in suicidal thinking following two nights of sleep deprivation and among individuals meeting the criteria for insomnia.

Methods:Study 1: Twenty-five healthy military personnel (20 males), ages 20–35 completed the NEO-PI-R Extraversion scale and the Suicidal Ideation (SUI) scale of the Personality Assessment Inventory (PAI). Participants completed 77 h of continuous sleep deprivation. After 56 h of sleep deprivation, participants completed the SUI scale a second time. We predicted a change in SUI scores from baseline extraversion. Study 2: 2,061 adults aged 18–79 (900 males) were divided into two groups based on the clinical threshold (≥ 10) on the Insomnia Severity Index (ISI) and completed measures of extraversion and depression, including the suicide item of the Patient Health Questionnaire-9 (PHQ9).

Results:Study 1: After controlling for the caffeine group and changes in PAI Depression, Extraversion scores were used to predict changes in SUI scores using stepwise multiple linear regression. Higher Extraversion was significantly associated with increased non-clinical suicidal ideation following sleep loss, β = 0.463, partial r = 0.512, p = 0.013. Study 2: After controlling for depression, the effect of insomnia on suicidal ideation was moderated by trait extraversion (p < 0.0001). Overall, the presence or absence of insomnia had little effect on individuals low in trait extraversion (i.e., introverts), but insomnia was associated with significantly higher suicidal ideation among high trait extraverted individuals.

Conclusions: Higher trait extraversion was associated with increased vulnerability to suicidal ideation between rested baseline and total sleep deprivation and was associated with greater suicidal ideation among those meeting criteria for clinically severe insomnia. These findings point to a potential trait-like vulnerability factor that may further our understanding of sleep disruption in the phenomenology of suicide.

Identification of ultrastructural signatures of sleep and wake in the fly brain

The cellular consequences of sleep loss are poorly characterized. In the pyramidal neurons of mouse frontal cortex, we found that mitochondria and secondary lysosomes occupy a larger proportion of the cytoplasm after chronic sleep restriction compared to sleep, consistent with increased cellular burden due to extended wake. For each morphological parameter, the within-animal variance was high, suggesting that the effects of sleep and sleep loss vary greatly among neurons. However, the analysis was based on 4-5 mice/group and a single section/cell. Here, we applied serial block-face scanning electron microscopy to identify signatures of sleep and sleep loss in the Drosophila brain. Stacks of images were acquired and used to obtain full 3D reconstructions of the cytoplasm and nucleus of 263 Kenyon cells from adult flies collected after a night of sleep (S) or after 11 h (SD11) or 35 h (SD35) of sleep deprivation (9 flies/group). Relative to S flies, SD35 flies showed increased density of dark clusters of chromatin and Golgi apparata and a trend increase in the percent of cell volume occupied by mitochondria, consistent with increased need for energy and protein supply during extended wake. Logistic regression models could assign each neuron to the correct experimental group with good accuracy, but in each cell, nuclear and cytoplasmic changes were poorly correlated, and within-fly variance was substantial in all experimental groups. Together, these results support the presence of ultrastructural signatures of sleep and sleep loss but underscore the complexity of their effects at the single-cell level.

The 3-Minute Psychomotor Vigilance Test Demonstrates Inadequate Convergent Validity Relative to the 10-Minute Psychomotor Vigilance Test Across Sleep Loss and Recovery

The Psychomotor Vigilance Test (PVT) is a widely used behavioral attention measure, with the 10-min (PVT-10) and 3-min (PVT-3) as two commonly used versions. The PVT-3 may be comparable to the PVT-10, though its convergent validity relative to the PVT-10 has not been explicitly assessed. For the first time, we utilized repeated measures correlation (rmcorr) to evaluate intra-individual associations between PVT-10 and PVT-3 versions across total sleep deprivation (TSD), chronic sleep restriction (SR) and multiple consecutive days of recovery. Eighty-three healthy adults (mean ± SD, 34.7 ± 8.9 years; 36 females) received two baseline nights (B1-B2), five SR nights (SR1-SR5), 36 h TSD, and four recovery nights (R1-R4) between sleep loss conditions. The PVT-10 and PVT-3 were completed every 2 h during wakefulness. Rmcorr compared responses on two frequently used, sensitive PVT metrics: reaction time (RT) via response speed (1/RT) and lapses (RT > 500 ms on the PVT-10 and > 355 ms on the PVT-3) by day (e.g., B2), by study phase (e.g., SR1-SR5), and by time point (1000-2000 h). PVT 1/RT correlations were generally stronger than those for lapses. The majority of correlations (48/50 [96%] for PVT lapses and 38/50 [76%] for PVT 1/RT) were values below 0.70, indicating validity issues. Overall, the PVT-3 demonstrated inadequate convergent validity with the "gold standard" PVT-10 across two different types of sleep loss and across extended recovery. Thus, the PVT-3 is not interchangeable with the PVT-10 for assessing behavioral attention performance during sleep loss based on the design of our study and the metrics we evaluated. Our results have substantial implications for design and measure selection in laboratory and applied settings, including those involving sleep deprivation.

Roles for Sleep in Neural and Behavioral Plasticity: Reviewing Variation in the Consequences of Sleep Loss

Sleep is a vital physiological state that has been broadly conserved across the evolution of animal species. While the precise functions of sleep remain poorly understood, a large body of research has examined the negative consequences of sleep loss on neural and behavioral plasticity. While sleep disruption generally results in degraded neural plasticity and cognitive function, the impact of sleep loss can vary widely with age, between individuals, and across physiological contexts. Additionally, several recent studies indicate that sleep loss differentially impacts distinct neuronal populations within memory-encoding circuitry. These findings indicate that the negative consequences of sleep loss are not universally shared, and that identifying conditions that influence the resilience of an organism (or neuron type) to sleep loss might open future opportunities to examine sleep's core functions in the brain. Here, we discuss the functional roles for sleep in adaptive plasticity and review factors that can contribute to individual variations in sleep behavior and responses to sleep loss.

Left Ventricular Ejection Time Measured by Echocardiography Differentiates Neurobehavioral Resilience and Vulnerability to Sleep Loss and Stress

There are substantial individual differences (resilience and vulnerability) in performance resulting from sleep loss and psychosocial stress, but predictive potential biomarkers remain elusive. Similarly, marked changes in the cardiovascular system from sleep loss and stress include an increased risk for cardiovascular disease. It remains unknown whether key hemodynamic markers, including left ventricular ejection time (LVET), stroke volume (SV), heart rate (HR), cardiac index (CI), blood pressure (BP), and systemic vascular resistance index (SVRI), differ in resilient vs. vulnerable individuals and predict differential performance resilience with sleep loss and stress. We investigated for the first time whether the combination of total sleep deprivation (TSD) and psychological stress affected a comprehensive set of hemodynamic measures in healthy adults, and whether these measures differentiated neurobehavioral performance in resilient and vulnerable individuals. Thirty-two healthy adults (ages 27-53; 14 females) participated in a 5-day experiment in the Human Exploration Research Analog (HERA), a high-fidelity National Aeronautics and Space Administration (NASA) space analog isolation facility, consisting of two baseline nights, 39 h TSD, and two recovery nights. A modified Trier Social Stress Test induced psychological stress during TSD. Cardiovascular measure collection [SV, HR, CI, LVET, BP, and SVRI] and neurobehavioral performance testing (including a behavioral attention task and a rating of subjective sleepiness) occurred at six and 11 timepoints, respectively. Individuals with longer pre-study LVET (determined by a median split on pre-study LVET) tended to have poorer performance during TSD and stress. Resilient and vulnerable groups (determined by a median split on average TSD performance) showed significantly different profiles of SV, HR, CI, and LVET. Importantly, LVET at pre-study, but not other hemodynamic measures, reliably differentiated neurobehavioral performance during TSD and stress, and therefore may be a biomarker. Future studies should investigate whether the non-invasive marker, LVET, determines risk for adverse health outcomes.

Predicting Attentional Vulnerability to Sleep Deprivation: A Multivariate Pattern Analysis of DTI Data

BACKGROUND

Large individual differences exist in sleep deprivation (SD) induced sustained attention deterioration. Several brain imaging studies have suggested that the activities within frontal-parietal network, cortico-thalamic connections, and inter-hemispheric connectivity might underlie the neural correlates of vulnerability/resistance to SD. However, those traditional approaches are based on average estimates of differences at the group level. Currently, a neuroimaging marker that can reliably predict this vulnerability at the individual level is lacking.

METHODS

Efficient transfer of information relies on the integrity of white matter (WM) tracts in the human brain, we therefore applied machine learning approach to investigate whether the WM diffusion metrics can predict vulnerability to SD. Forty-nine participants completed the psychomotor vigilance task (PVT) both after resting wakefulness (RW) and after 24 h of sleep deprivation (SD). The number of PVT lapse (reaction time > 500 ms) was calculated for both RW condition and SD condition and participants were categorized as vulnerable (24 participants) or resistant (25 participants) to SD according to the change in the number of PVT lapses between the two conditions. Diffusion tensor imaging were acquired to extract four multitype WM features at a regional level: fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. A linear support vector machine (LSVM) learning approach using leave-one-out cross-validation (LOOCV) was performed to assess the discriminative power of WM features in SD-vulnerable and SD-resistant participants.

RESULTS

LSVM analysis achieved a correct classification rate of 83.67% (sensitivity: 87.50%; specificity: 80.00%; and area under the receiver operating characteristic curve: 0.85) for differentiating SD-vulnerable from SD-resistant participants. WM fiber tracts that contributed most to the classification model were primarily commissural pathways (superior longitudinal fasciculus), projection pathways (posterior corona radiata, anterior limb of internal capsule) and association pathways (body and genu of corpus callosum). Furthermore, we found a significantly negative correlation between changes in PVT lapses and the LSVM decision value.

CONCLUSION

These findings suggest that WM fibers connecting (1) regions within frontal-parietal attention network, (2) the thalamus to the prefrontal cortex, and (3) the left and right hemispheres contributed the most to classification accuracy.

Cortisol and C-Reactive Protein Vary During Sleep Loss and Recovery but Are Not Markers of Neurobehavioral Resilience

Cortisol and C-reactive protein (CRP) typically change during total sleep deprivation (TSD) and psychological stress; however, it remains unknown whether these biological markers can differentiate robust individual differences in neurobehavioral performance and self-rated sleepiness resulting from these stressors. Additionally, little is known about cortisol and CRP recovery after TSD. In our study, 32 healthy adults (ages 27-53; mean ± SD, 35.1 ± 7.1 years; 14 females) participated in a highly controlled 5-day experiment in the Human Exploration Research Analog (HERA), a high-fidelity National Aeronautics and Space Administration (NASA) space analog isolation facility, consisting of two baseline nights, 39 h TSD, and two recovery nights. Psychological stress was induced by a modified Trier Social Stress Test (TSST) on the afternoon of TSD. Salivary cortisol and plasma CRP were obtained at six time points, before (pre-study), during [baseline, the morning of TSD (TSD AM), the afternoon of TSD (TSD PM), and recovery], and after (post-study) the experiment. A neurobehavioral test battery, including measures of behavioral attention and cognitive throughput, and a self-report measure of sleepiness, was administered 11 times. Resilient and vulnerable groups were defined by a median split on the average TSD performance or sleepiness score. Low and high pre-study cortisol and CRP were defined by a median split on respective values at pre-study. Cortisol and CRP both changed significantly across the study, with cortisol, but not CRP, increasing during TSD. During recovery, cortisol levels did not return to pre-TSD levels, whereas CRP levels did not differ from baseline. When sex was added as a between-subject factor, the time × sex interaction was significant for cortisol. Resilient and vulnerable groups did not differ in cortisol and CRP, and low and high pre-study cortisol/CRP groups did not differ on performance tasks or self-reported sleepiness. Thus, both cortisol and CRP reliably changed in a normal, healthy population as a result of sleep loss; however, cortisol and CRP were not markers of neurobehavioral resilience to TSD and stress in this study.

Concordance of multiple methods to define resiliency and vulnerability to sleep loss depends on Psychomotor Vigilance Test metric

STUDY OBJECTIVES

Sleep restriction (SR) and total sleep deprivation (TSD) reveal well-established individual differences in Psychomotor Vigilance Test (PVT) performance. While prior studies have used different methods to categorize such resiliency/vulnerability, none have systematically investigated whether these methods categorize individuals similarly.

METHODS

41 adults participated in a 13-day laboratory study consisting of 2 baseline, 5 SR, 4 recovery, and one 36h TSD night. The PVT was administered every 2h during wakefulness. Three approaches (Raw Score [average SR performance], Change from Baseline [average SR minus average baseline performance], and Variance [intraindividual variance of SR performance]), and within each approach, six thresholds (±1 standard deviation and the best/worst performing 12.5%, 20%, 25%, 33%, and 50%) classified Resilient/Vulnerable groups. Kendall's tau-b correlations examined the concordance of group categorizations of approaches within and between PVT lapses and 1/reaction time (RT). Bias-corrected and accelerated bootstrapped t-tests compared group performance.

RESULTS

Correlations comparing the approaches ranged from moderate to perfect for lapses and zero to moderate for 1/RT. Defined by all approaches, the Resilient groups had significantly fewer lapses on nearly all study days. Defined by the Raw Score approach only, the Resilient groups had significantly faster 1/RT on all study days. Between-measures comparisons revealed significant correlations between the Raw Score approach for 1/RT and all approaches for lapses.

CONCLUSION

The three approaches defining vigilant attention resiliency/vulnerability to sleep loss resulted in groups comprised of similar individuals for PVT lapses but not for 1/RT. Thus, both method and metric selection for defining vigilant attention resiliency/vulnerability to sleep loss is critical.

Impaired Vigilant Attention Partly Accounts for Inhibition Control Deficits After Total Sleep Deprivation and Partial Sleep Restriction

PURPOSE

Sleep loss impairs a range of neurobehavioral functions, particularly vigilant attention and arousal. However, the detrimental effects of sleep deprivation on inhibition control and its relationship to vigilant attention impairments remain unclear. This study examined the extent to which vigilant attention deficits contribute to inhibition control performance after one night of total sleep deprivation (TSD) and two nights of partial sleep restriction (PSR).

PARTICIPANTS AND METHODS

We analyzed data from N = 49 participants in a one-night of TSD experiment, N=16 participants in a control experiment without sleep loss, and N = 16 participants in a two-nights of PSR experiment (time in bed, TIB = 6 h for each night). Throughout waking periods in each condition, participants completed the psychomotor vigilance test (PVT), which measures vigilant attention, and the Go/No-Go task, which measures inhibition control.

RESULTS

After TSD and PSR, participants displayed significantly slower reaction times (RT) and more lapses in PVT performance, as well as slower Go RT and more errors of omission during the Go/No-Go task. PVT deficits accounted for 18.0% of the change in Go RT and 12.4% of the change in errors of omission in the TSD study, and 23.7% of the change in Go RT and 20.3% of the change in errors of omission in the PSR study.

CONCLUSION

Both TSD and PSR impaired inhibition control during the Go/No-Go task, which can be partly accounted for by vigilant attention deficits during the PVT. These findings support the key role of vigilant attention in maintaining overall neurobehavioral function after sleep loss.

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.

Genetic Markers of Differential Vulnerability to Sleep Loss in Adults

In this review, we discuss reports of genotype-dependent interindividual differences in phenotypic neurobehavioral responses to total sleep deprivation or sleep restriction. We highlight the importance of using the candidate gene approach to further elucidate differential resilience and vulnerability to sleep deprivation in humans, although we acknowledge that other omics techniques and genome-wide association studies can also offer insights into biomarkers of such vulnerability. Specifically, we discuss polymorphisms in adenosinergic genes (ADA and ADORA2A), core circadian clock genes (BHLHE41/DEC2 and PER3), genes related to cognitive development and functioning (BDNF and COMT), dopaminergic genes (DRD2 and DAT), and immune and clearance genes (AQP4, DQB1*0602, and TNFα) as potential genetic indicators of differential vulnerability to deficits induced by sleep loss. Additionally, we review the efficacy of several countermeasures for the neurobehavioral impairments induced by sleep loss, including banking sleep, recovery sleep, caffeine, and naps. The discovery of reliable, novel genetic markers of differential vulnerability to sleep loss has critical implications for future research involving predictors, countermeasures, and treatments in the field of sleep and circadian science.

Cognitive throughput and working memory raw scores consistently differentiate resilient and vulnerable groups to sleep loss

STUDY OBJECTIVES

Substantial individual differences exist in cognitive deficits due to sleep restriction (SR) and total sleep deprivation (TSD), with various methods used to define such neurobehavioral differences. We comprehensively compared numerous methods for defining cognitive throughput and working memory resiliency and vulnerability.

METHODS

41 adults participated in a 13-day experiment: 2 baseline, 5 SR, 4 recovery, and one 36h TSD night. The Digit Symbol Substitution Test (DSST) and Digit Span Test (DS) were administered every 2h. Three approaches (Raw Score [average SR performance], Change from Baseline [average SR minus average baseline performance], and Variance [intraindividual variance of SR performance]), and six thresholds (±1 standard deviation, and the best/worst performing 12.5%, 20%, 25%, 33%, 50%) classified Resilient/Vulnerable groups. Kendall's tau-b correlations compared the group categorizations' concordance within and between DSST number correct and DS total number correct. Bias-corrected and accelerated bootstrapped t-tests compared group performance. .

RESULTS

The approaches generally did not categorize the same participants into Resilient/Vulnerable groups within or between measures. The Resilient groups categorized by the Raw Score approach had significantly better DSST and DS performance across all thresholds on all study days, while the Resilient groups categorized by the Change from Baseline approach had significantly better DSST and DS performance for several thresholds on most study days. By contrast, the Variance approach showed no significant DSST and DS performance group differences.

CONCLUSION

Various approaches to define cognitive throughput and working memory resilience/vulnerability to sleep loss are not synonymous. The Raw Score approach can be reliably used to differentiate resilient and vulnerable groups using DSST and DS performance during sleep loss.

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.

Emotional Vulnerability to Short Sleep Predicts Increases in Chronic Health Conditions Across 8 Years

BACKGROUND

Sleep is a robust determinant of next-day emotions, but people vary in the extent that their emotions fluctuate on days following short sleep duration. These individual differences in day-to-day sleep and emotion dynamics may have long-term health implications.

PURPOSE

To evaluate emotional vulnerability to short sleep (within-person associations between sleep duration and next-day emotions) as a risk factor for future chronic conditions.

METHODS

Adults aged 33-84 (N = 1,426; 57% female) in the Midlife in the United States Study reported sleep duration and emotions by telephone for eight consecutive days. Chronic conditions were assessed via checklist at baseline and at a median follow-up of eight years (range: 5-10 years). Short sleep was examined in three ways: person-centered continuous variable, ≤6 hr, and <7 hr; long sleep was defined as ≥9 hr.

RESULTS

Multilevel structural equation models revealed that people with greater negative emotions following nights of sleep ≤6 hr (vs. their negative emotions after longer sleep) had increased chronic conditions at follow-up, compared to people who were less emotionally vulnerable to short sleep (Est. = 1.04, SE = .51, p < .028). Smaller declines in positive emotions following ≤6 hr of sleep were marginally predictive of lower risk for chronic conditions (Est. = -.77, SE = .44, p = .054). Emotional vulnerability to <7, ≥9, and continuous sleep hours were not associated with subsequent chronic conditions.

CONCLUSIONS

Emotional vulnerability to short sleep is a unique risk factor for the development of chronic conditions, independent of mean-level sleep duration and emotions.

Effects of six weeks of chronic sleep restriction with weekend recovery on cognitive performance and wellbeing in high-performing adults

Chronic sleep loss is associated with escalating declines in vigilant attention across days of sleep restriction. However, studies exceeding two weeks of chronic sleep loss are scarce, and the cognitive performance outcomes assessed are limited. We assessed the effects of six weeks of chronic sleep restriction on a range of cognitive domains in 15 high-performing individuals (38.5±8.2 years, 6 women) confined to small space in groups of four. Sleep opportunities were limited to 5h on weekdays and 8h on weekends. Individual sleep/wake patterns were recorded with actigraphy. Neurobehavioral performance was assessed in evenings with Cognition, a computerized battery of ten tests assessing a range of cognitive domains. There were some small to moderate effects of increasing sleep debt relative to pre-mission baseline, with decreases in accuracy across cognitive domains (standardized β=0.121, p=0.001), specifically on tests of spatial orientation (β=0.289, p=0.011) and vigilant attention (β=0.688, p<0.001), which were not restored by two nights of weekend recovery sleep. Cognitive and subjective decrements occurred despite occasional daytime napping in breach of study protocol, evening testing around the circadian peak, and access to caffeine before 14:00. Sensorimotor speed, spatial learning and memory, working memory, abstraction and mental flexibility, emotion identification, abstract reasoning, cognitive throughput and risk decision making were not significantly affected by sleep debt. Taken together with modest lower subjective ratings of happiness and healthiness, these findings underline the importance of sufficient sleep, on both an acute and chronic basis, for performance in selected cognitive domains and subjective wellbeing in operationally-relevant environments.

Changes in Subjective Motivation and Effort During Sleep Restriction Moderate Interindividual Differences in Attentional Performance in Healthy Young Men

PURPOSE

The effects of sleep restriction on subjective alertness, motivation, and effort vary among individuals and may explain interindividual differences in attention during sleep restriction. We investigated whether individuals with a greater decrease in subjective alertness or motivation, or a greater increase in subjective effort (versus other participants), demonstrated poorer attention when sleep restricted.

PARTICIPANTS AND METHODS

Fifteen healthy men (M±SD, 22.3±2.8 years) completed a study with three nights of 10-hour time in bed (baseline), five nights of 5-hour time in bed (sleep restriction), and two nights of 10-hour time in bed (recovery). Participants completed a 10-minute psychomotor vigilance task (PVT) of sustained attention and rated alertness, motivation, and effort every two hours during wake (range: 3-9 administrations on a given day). Analyses examined performance across the study (first two days excluded) moderated by per-participant change in subjective alertness, motivation, or effort from baseline to sleep restriction. For significant interactions, we investigated the effect of study day² (day*day) on the outcome at low (mean-1 SD) and high (mean+1 SD) levels of the moderator (N = 15, all analyses).

RESULTS

False starts increased across sleep restriction in participants who reported lower (mean-1 SD) but not preserved (mean+1 SD) motivation during sleep restriction. Lapses increased across sleep restriction regardless of change in subjective motivation, with a more pronounced increase in participants who reported lower versus preserved motivation. Lapses increased across sleep restriction in participants who reported higher (mean+1 SD) but not preserved (mean-1 SD) effort during sleep restriction. Change in subjective alertness did not moderate the effects of sleep restriction on attention.

CONCLUSION

Vigilance declines during sleep restriction regardless of change in subjective alertness or motivation, but individuals with reduced motivation exhibit poorer inhibition. Individuals with preserved subjective alertness still perform poorly during sleep restriction, while those reporting additional effort demonstrate impaired vigilance.

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.