Total Sleep Deprivation Research Articles

Electrodermal Activity Is Sensitive to Sleep Deprivation but Does Not Moderate the Effect of Total Sleep Deprivation on Affect.

Emotion is characterized by dimensions of affective valence and arousal, either or both of which may be altered by sleep loss, thereby contributing to impaired regulatory functioning. Controlled laboratory studies of total sleep deprivation (TSD) generally show alterations in physiological arousal and affective state, but the relationship of affect and emotion with physiological arousal during TSD has not been well characterized. Established methods for examining physiological arousal include electrodermal activity (EDA) measures such as non-specific skin conductance responses (NSSCR) and skin conductance level (SCL). These measures are robust physiological markers of sympathetic arousal and have been linked to changes in experienced emotion. To explore the link between physiological arousal and affect during sleep deprivation, we investigated individuals’ EDA under TSD and its relationship to self-reported affect. We also investigated the relationship of EDA to two other measures known to be particularly sensitive to the arousal-decreasing effects of TSD, i.e., self-reported sleepiness and performance on a vigilant attention task. Data were drawn from three previously published laboratory experiments where participants were randomly assigned to either well-rested control (WRC) or 38 h of TSD. In this data set, comprising one of the largest samples ever used in an investigation of TSD and EDA (N = 193 with 74 WRC and 119 TSD), we found the expected impairing effects of TSD on self-reported affect and sleepiness and on vigilant attention. Furthermore, we found that NSSCR, but not SCL, were sensitive to TSD, with significant systematic inter-individual differences. Across individuals, the change in frequency of NSSCR during TSD was not predictive of the effect of TSD on affect, sleepiness, or vigilant attention, nor was it related to these outcomes during the rested baseline. Our findings indicate that while physiological arousal, as measured by EDA, may be useful for assessing TSD-related changes in non-specific arousal at the group level, it is not associated with individuals’ self-reported affect at rest nor their change in affect during TSD. This suggests that an essential aspect of the relationship between physiological arousal and self-reported affect is not well captured by EDA as measured by NSSCR.

Association Between Sleep Parameters and Postural Control: A Literature Review

Background and Objective The purpose of the review was to explore the association between sleep parameters and postural control.Methods The PubMed, Science Direct, and EBSCO were searched using the keywords ‘sleep’ including either sleep quality, sleep deprivation, poor sleep quality; and ‘postural control’ including either dynamic balance, static balance, postural balance, and balance control. Related studies published till December 2017 were selected.Results Acute sleep deprivation resulted in an impairment in postural control. Chronic sleep deprivation and postural control were also found to be related in a similar way to that of total sleep deprivation, thus affecting postural control negatively. Time of day was found to influence the postural control such that the postural control was better in the morning than in the latter part of the day. A study of the impact of aging on the effects of sleep deprivation on postural control revealed that loss of sleep had a more disturbing effect on postural control in the olderadult group than in younger participants, thus indicating a high risk of fall among the elderly.Conclusions Despite various limitations and methodological differences, this review has identified a negative influence on postural control due to impaired sleep in a wide range of populations, indicating the need for a more focused approach to sleep when assessing and measuring postural control.

One night of total sleep deprivation impairs decision-making skills, anaerobic performances, mood states, and perceptual responses in elite Kung-Fu athletes

ABSTRACT To explore how one night of total sleep deprivation (TSD) could affect cognitive and physical performances, as well as subjective experiences in 24 elite Kung-Fu athletes (age: 20.2 ± 1.76 years; body mass: 64.67 ± 6.52 kg; height: 1.71 ± 0.04 m). Participants completed, in a randomized counterbalanced order, two tests sessions in the late-afternoon (separated by 72-h recovery) under normal sleep (NS) and TSD conditions. Specific decision-making skills (decision accuracy (DA) and decision time (DT)), various anaerobic-exercises performance (i.e. seated medicine-ball throw (SMBT), horizontal jump (HJ), vertical jump (VJ), isometric back-muscles strength (IBMS), and isometric leg-muscles strength (ILMS)), mood states, and perceptual responses (attention and concentration) were assessed. The TSD was associated with lower values of vigor, and higher values of anxiety, depression, fatigue, anger, confusion, and total mood disturbance, compared to NS. The TSD resulted in lower attention and concentration, compared to NS. Similarly, lower performances of SMBT, HJ, VJ, and ILMS were recorded after TSD compared to NS. For cognitive performances, the TSD resulted in higher DA and lower DT, compared to NS. In summary, one night of TSD elicits negative effects on decision-making and anaerobic performance in Kung-Fu elites through disturbances in mood and attentional capacities.

Sex moderates the effects of total sleep deprivation and sleep restriction on risk preference.

Sleep loss has been shown to alter risk preference during decision-making. However, research in this area has largely focussed on the effects of total sleep deprivation (TSD), while evidence on the effects of sleep restriction (SR) or the potentially moderating role of sex on risk preference remains scarce and unclear. The present study investigated risky decision-making in 47 healthy young adults who were assigned to either of two counterbalanced protocols: well-rested (WR) and TSD, or WR and SR. Participants were assessed on the Lottery Choice Task (LCT), which requires a series of choices between two risky gambles with varying risk levels. Analyses on the pooled dataset indicated across all sleep conditions, participants were generally more risk-seeking when trying to minimise financial loss (LOSSES) than while trying to maximise financial gain (GAINS). On GAINS trials, female participants were more risk-averse during TSD and SR, whereas male participants remained unchanged. On LOSSES trials, female participants remained unchanged during TSD and SR, whereas male participants became more risk-seeking during TSD. Our findings suggest the relationship between sleep loss and risk preference is moderated by sex, whereby changes in risk preference after TSD or SR differ in men and women depending on whether the decision is framed in terms of gains or losses.

0125 Fluid Intelligence Does Not Mediate Cognitive Throughput Deficits during Total Sleep Deprivation

Abstract Introduction The Digit Symbol Substitution Test (DSST) has been used in sleep research to measure slowing of cognitive throughput. The task shows large aptitude differences in baseline performance and substantial inter-individual differences in vulnerability to performance deficits during total sleep deprivation (TSD). Fluid intelligence (Gf) is generally positively related to processing speed. However, DSST performance is typically found to be independent of Gf. The possible interaction of sleep loss with Gf on performance remains to be examined. Methods N=56 healthy adults (ages 22–37, 29 females) completed a 4-day/3-night in-laboratory study and were randomly assigned (2:1 ratio) to a TSD (n=37) or control (n=19) condition. Sleep opportunities were from 22:00–08:00 on the first (baseline) and last (recovery) night for the TSD group and on all three nights for the control group. Subjects completed a 4min, computerized DSST twice on day 2 (baseline) and twice on day 3 (TSD or control). At baseline, subjects also completed the Shipley Institute of Living Scale (SILS). The abstraction score was used to categorize fluid intelligence (Gf) as relatively high (≥34, n=36) or low (<34, n=20). Mean DSST throughput (number of correct responses in the 4min task) was analyzed using mixed-effects ANOVA with fixed effects for day (2, 3), condition (TSD, control), and their interaction, with and without Gf category (high, low) as a covariate. Results As expected, DSST throughput was significantly reduced by TSD (day by condition interaction: F[1,166]=27.99, p<0.001). Adding Gf had no effect on the day by condition interaction, and Gf category was not significant as a covariate (F[1,166]=1.67, p=0.20). Conclusion Our results indicate that the Gf measure from the SILS does not capture the aspects of cognition that are influenced by TSD and that lead to a decline in DSST throughput. This is consistent with findings that while the DSST has high sensitivity for cognitive dysfunction in clinical settings, it has low specificity in identifying components of cognition responsible for dysfunction. Support (If Any) ONR N00014-13-1-0302 and PRMRP W81XWH-20-1-0442.

0118 Performance on a Computerized Threat Elimination Task in an Animated Environment during Total Sleep Deprivation

Abstract Introduction Military and law enforcement operators must make split-second decisions on whether to shoot during confrontations. Quick responses are crucial when force is necessary, but accurate decision-making is also imperative. Often, decisions are made while fatigued, which could impair speed and/or accuracy. Furthermore, the reliability of background information may impact performance. We investigated performance on a computerized shooting task during a total sleep deprivation (TSD) study. Methods N=86 healthy adults (39 males, age 21-38) completed a 4-day/3-night in-laboratory study, randomly assigned to a TSD (n=56) or control (n=28) condition. A custom task was administered after 32h or 8h of wakefulness (TSD and control groups). Participants were to shoot enemy robots (press spacebar) and not shoot friendly robots (no response) within 500ms of each robot being revealed inside shipping crates (1-5s inter-trial-interval). The task introduction described which crates would contain enemies, but the intel’s accuracy varied across four phases: 100% (20 trials), 80% (120 trials), and 20% (40 trials), then irrelevant in a new environment (60 trials). Reaction time (RT) and accuracy (hits and false alarms (FAs)) were analyzed using 2x4 mixed-effects ANOVAs to determine the effects of condition, phase, and their interaction. Results There was a significant effect of phase on RT (p<0.001); in both conditions, participants reacted faster in phase 1 than all other phases. However, there was no effect of condition (p=0.20) or phase-condition interaction (p=0.080) on RT. There were significant effects of condition on hits (p<0.001) and FAs (p=0.004); TSD had fewer hits and more FAs than the control group. There was an effect of phase on hits (p=0.045), with fewer hits in phase 1, and a condition-phase interaction (p=0.026) showing that the TSD group experienced less improvement in hits. For FAs, there was no effect of phase (p=0.86) or phase-condition interaction (p=0.86). Conclusion The results suggest a speed/accuracy tradeoff during TSD, where relative to the control group, RTs remained equivalent, but accuracy was worse. In both groups, the RT slowing from phase 1 to subsequent phases, suggests that participants initially used the intel to facilitate quicker decision-making, but disregarded it once it was not completely reliable. Support (If Any) CDMRP grants W81XWH-16-1-0319 and W81XWH-20-1-0442

0234 Salivary α-Amylase Response to Repeated Exposure to Acute Stressors Is Altered by Sleep Deprivation

Abstract Introduction Salivary α-amylase (sAA), a biomarker of autonomic nervous system (ANS) activity, is believed to reflect physiological responsiveness to stressors. Although exposure to stressors often co-occurs with sleep deprivation, little is known about their combined effects. We investigated the sAA response following repeated exposure to acute stressors at well-rested baseline and during total sleep deprivation (TSD). Methods As part of a larger study, N=8 healthy subjects (ages 29.0±6.6; 4 females) participated in a 4-day/3-night laboratory-based experiment. Subjects had 38h TSD preceded and followed by 10h sleep opportunities (22:00–08:00). On days 2 (baseline) and 3 (TSD), subjects completed two (A, B) deadly-force decision-making simulations in a high-fidelity shooting simulator with 30min rest between sessions. During each simulation, subjects (who were civilians) acted as police officers while viewing interactive videos depicting stressful law enforcement emergency response scenarios involving deadly-force decision-making. In these scenarios, subjects attempted to de-escalate the situations in the scenarios using verbal commands. If unsuccessful, they were to determine if the use of (simulated) deadly force was necessary and respond accordingly. Saliva samples were collected immediately before the first simulation of the baseline and TSD days, and immediately, 15min, and 30min after each simulation. Samples were assayed in duplicate using a sAA kinetic enzyme assay; results were normalized against the first pre-stressor sample of the baseline day. Results Post-simulation sAA values normalized to reference were analyzed with mixed-effects ANOVA with fixed effects of day and sample and their interaction and a random effect over subjects on the intercept. There was a significant effect of sample (F[5,76]=3.38, p=0.008) indicating that sAA spiked immediately after each deadly-force decision-making simulation. Planned comparisons revealed significantly blunted sAA during TSD compared to baseline immediately after the second simulation of the day (t[76]=2.09, p=0.040). Conclusion In our sample of civilian subjects, the deadly-force decision-making simulations elicited a sAA response, which was blunted after the second simulation on the day subjects were sleep-deprived, suggesting that TSD mediates the biological response to repeated exposure to acute stressors. Whether this result generalizes to police officers and military personnel trained in deadly-force decision-making remains to be determined. Support (If Any) ONR grant N00014-13-1-0302

0296 Vigilant Attention Performance Advantage Conferred by TNFα G308A Polymorphism is Associated with Diminished Delta and Theta Power in the Non-REM Sleep EEG

Abstract Introduction Carriers of the A allele of a single nucleotide polymorphism of the TNFα gene (G308A, rs1800629) are relatively resilient to vigilant attention performance impairment from total sleep deprivation (TSD), as compared to G/G homozygotes, and even exhibit a small performance advantage at baseline. The mechanism underlying this effect remains unclear. As TNFα is a sleep regulatory substance, we investigated whether TNFα G308A genotype is associated with systematic differences in markers of sleep homeostasis. Methods N=168 healthy young adults (ages 27.4±5.4y; 86 women) participated in one of seven in-laboratory TSD studies. During TSD, performance was assessed every 2–3h using a psychomotor vigilance test (PVT). The TSD period was preceded and followed by nocturnal sleep opportunities (baseline and recovery, respectively), which were recorded polysomnographically and scored according to AASM criteria. The EEG (C3-M2 derivation) of stages N2 and N3 non-REM sleep was investigated using spectral analysis. Results The genotype distribution of the sample was 0.6% A/A, 26.8% A/G, 72.6% G/G, in Hardy-Weinberg equilibrium (P=0.14). As documented previously, A allele carriers, compared to G/G homozygotes, had fewer PVT lapses (RTs>500ms) at baseline and during TSD, indicating greater resilience to sleep deprivation. During both baseline and recovery sleep, A allele carriers, compared to G/G homozygotes, displayed reduced power in the delta (0.8–4.0Hz; P=0.017) and theta (4.2–8.0Hz; P=0.004) bands of the non-REM sleep EEG. Conclusion The performance advantage of the A allele carriers brings to mind the “banking sleep” phenomenon previously observed in sleep deprivation studies with prior sleep extension, suggesting that the A allele carriers gained this advantage by essentially being able to bank sleep. If this interpretation is correct, then the diminished power in the delta and theta bands of the non-REM sleep EEG in the A allele carriers, which suggests reduced homeostatic sleep pressure during both baseline and recovery sleep, may imply that the A allele carriers operate at a lower homeostatic setpoint due to an underlying advantage in the recuperative efficiency of sleep. Support (If Any) NIH R01HL070154, R21CA167691, R01HL105768; ONR N00014-13-C-0063, N00014-13-1-0302, FAA DTFAAC-11-A-00003, CDMRP W81XWH-16-1-0319, USAMRDC W81XWH-05-1-0099, and an SRS Elliot D. Weitzman, M.D. Research Grant.

0024 ARC Genotype Modulates EEG Spectral Power Following Total Sleep Deprivation

Abstract Introduction Sleep homeostasis is manifested by a robust increase in slow wave sleep (SWS) following acute total sleep deprivation (TSD), with concomitant changes in spectral power of the non-REM (NREM) sleep EEG marked by substantial interindividual differences. We previously found that a single nucleotide polymorphism of the activity-regulated cytoskeleton associated protein (ARC) gene modulates SWS rebound following TSD. Here we sought to determine whether ARC genotype is also associated with interindividual differences in spectral power of the NREM sleep EEG. Methods 50 healthy adults (27.3±4.9 years; 28 females) participated in one of two in-laboratory studies. Each participant had a 10h baseline sleep opportunity (22:00–08:00), 38h TSD, and a 10h recovery sleep opportunity (22:00–08:00). Sleep periods were recorded polysomnographically and visually scored according to AASM criteria. Genomic DNA was assayed for the ARC c.*742 + 58C>T non-coding SNP, rs35900184. Log-transformed NREM sleep EEG spectral power (C3-M3 derivation) over 0.2 Hz frequency bins in each of four frequency bands – delta (0.8–4.0 Hz), theta (4.2–8.0 Hz), alpha (8.2–12.0 Hz), and beta (12.2–16.0 Hz) – was analyzed by band using mixed-effects ANOVA with fixed effects for ARC genotype, night (baseline, recovery), frequency bin, and their interactions. Analyses included study and age as covariates and a random effect over subjects on the intercept. Results The genotype distribution in this sample was 33 C/C homozygotes, 11 C/T heterozygotes, and 6 T/T homozygotes. There was a significant ARC by night interaction in the theta (F2,1833=5.94, p=0.003) and alpha (F2,1833=8.58, p<0.001) bands. Compared to baseline sleep, during recovery sleep C/C homozygotes had 18.9% more theta power and 8.7% more alpha power, C/T heterozygotes had 17.9% more theta power and 7.6% more alpha power, and T/T homozygotes had 20.0% more theta power and 15.1% more alpha power. Conclusion Our results show that ARC genotype mediates the NREM sleep EEG response to TSD; compared to C allele carriers, homozygosity for the T allele is associated with a much more pronounced increase in alpha power, as well as a larger increase in theta power. The functional implications of this ARC effect remain to be determined. Support (If Any) ONR N00014-13-1-0302, NIH R21CA167691, and USAMRDC W81XWH-18-1-0100.

0119 Effects of Total Sleep Deprivation on Performance on a Continuous Performance Matching Task

Abstract Introduction Tasks requiring individuals to identify specific stimuli may create response/non-response conflict, which may impair performance depending on stimulus feature overlap. Whether sleep deprivation interacts with such impairment is unknown. We investigated the effects of total sleep deprivation (TSD) on stimulus identification in a continuous performance matching task (CPMT). Methods N=85 adults (ages 21–40; 50f) completed a 4-day laboratory study with 10h baseline sleep (22:00–08:00), a 38h acute TSD or 10h sleep opportunity (control condition), and 10h recovery sleep. The ~6min CPMT was administered every 2–4h during wakefulness. Participants completed 300 trials where a 3-digit number was flashed on the screen for 100ms. They were instructed to respond (mouse-click) within 900ms, but only if the number was the same as the preceding number (i.e., a repeat); for all other trials a response was to be withheld. The 5 daytime testing sessions (09:00–21:00) at baseline (day 2) and after TSD/control (day 3) were used for analysis. Trials were classified based on number of digits matching the preceding trial (stimulus feature overlap): none (180 trials), one (30 trials), two (near-repeat; 30 trials), or all (repeat; 60 trials). Hit and false alarm (FA) rates were analyzed with mixed-effects ANOVA for day, condition, trial type, and their interactions. Mean response time (MRT) was analyzed equivalently for repeat trials only. Results Hit rate declined from day 2 to day 3 in the TSD group (F[1,83]=0.15, p<0.001), but not the control group (F[1,83]=0.018, p=0.335). Though FA rate was low overall (<0.06), FA frequency was higher on trials with greater stimulus feature overlap. FA rate increased on day 3 for the TSD group (all p<0.004), especially for near-repeats (F[1,415]=-0.014, p<0.001). Changes in MRT were statistically significant, but negligible (<20ms). Conclusion Our results suggest that greater stimulus feature overlap on the CPMT was associated with greater costs required to resolve conflict. Sleep deprivation exacerbated these costs. Interpretation is limited however, because a response was not required for non-repeat trials. Implementing a two-alternative forced choice version of the task in future TSD studies would address this limitation. Support (If Any) PRMRP W81XWH-16-1-0319 and W81XWH-20-1-0442

0283 Neurobehavioral Resilience and Vulnerability to Sleep Loss Differs Between Objective and Self-Rated Metrics Regardless of Categorization Method Utilized

Abstract Introduction Trait-like individual differences in neurobehavioral responses to sleep restriction (SR) and total sleep deprivation (TSD) are robust and phenotypic. We investigated whether the concordance between multiple approaches for defining differential vulnerability depends on the methods and metrics utilized for categorization, including comparisons between objective and self-rated metrics. Trait-like individual differences in neurobehavioral responses to sleep restriction (SR) and total sleep deprivation (TSD) are robust and phenotypic. We investigated whether the concordance between multiple approaches for defining differential vulnerability depends on the methods and metrics utilized for categorization, including comparisons between objective and self-rated metrics. Methods Forty-one adults (33.9±8.9y; 18 females) participated in a 13-day experiment (two baseline nights [10h-12h time-in-bed, TIB], 5 SR nights [4h TIB], 4 recovery nights [12h TIB], and 36h TSD). The 10-minute Psychomotor Vigilance Test (PVT), Digit Symbol Substitution Test (DSST), Digit Span Task (DS), Karolinska Sleepiness Scale (KSS), Profile of Mood States Fatigue (POMS-F) and Vigor (POMS-V) were administered every 2h during wakefulness. 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 best and worst performing 12.5%, 20%, 25%, 33%, and 50%) categorized Resilient and Vulnerable groups. Kendall’s tau-b correlations assessed the group categorization’s concordance between pairings of PVT lapses (reaction time [RT]>500ms), PVT mean response speed (1/RT), DSST number correct, DS total number correct, KSS score, POMS-F score, and POMS-V score (tau-b=0.0: zero; 0.1: weak; 0.4: moderate; 0.70: strong; 1.0: perfect). Results Generally, tau-b correlations comparing Resilient and Vulnerable categorizations between two objective metrics (i.e., PVT, DSST, DS) revealed weak to moderate significant relationships (tau-b=0.29-0.53, p<0.001-0.049) between at least two of the approaches at most thresholds. However, comparisons between one objective (i.e., PVT, DSST, DS) and one self-rated metric (i.e., KSS, POMS) revealed a general lack of significant relationships (tau-b=-0.25-0.28, p=0.052-1.00), regardless of approach or threshold. Conclusion Comparisons between two objective metrics revealed significantly concordant Resilient and Vulnerable categorizations, whereas categorizations were generally not significantly correlated between one objective and one subjective metric, regardless of the method utilized. Our findings support and extend previous assertions that SR differentially impacts objective and subjective neurobehavioral domains and have important implications when assessing resilience and vulnerability to sleep loss in both laboratory and applied settings. Support (If Any) ONR Award No. N00014-11-1-0361; NIH UL1TR000003; NASA NNX14AN49G and 80NSSC20K0243; NIH R01DK117488

0293 The Effect of Sleep Loss on Divergent Thinking using a Remote Associates Task

Abstract Introduction Sleep loss-induced neurobehavioral deficits are a recognized threat to health, safety, and performance. Sleep loss has previously been shown to differentially impact distinct types of cognitive function, although less is known about the higher-order cognitive function, divergent thinking. Understanding the influence of sleep on divergent thinking can assist in developing targeted strategies to mitigate specific cognitive function impairments. Methods Eight participants (3M/5F), mean age 27.875y (± 5.5y SD) were studied over the course of 40 days in a crossover design. Participants were randomly assigned to one of two study schedules, with 4 participants in each that alternated the order of sleep restriction and total sleep deprivation. The schedules consisted of a baseline assessment and 6 study phases [sleep extension prior to sleep restriction (10h Time in Bed (TIB)), sleep restriction (6h TIB), recovery following sleep restriction, sleep extension prior to total sleep deprivation (10h TIB), total sleep deprivation (62h), and recovery following sleep restriction. The Remote Associates Task (RAT), a task to assess divergent thinking by presenting a triad of apparently unrelated words with the goal of identifying a unifying 4th word, was administered the evening of the last day of every phase. RAT performance metrics included number of triads attempted, correct responses, repeated trials, and mean correct and incorrect reaction times. Results No differences were found in total number of word triads attempted by participants (p=0.18). The number of correct responses during baseline was lower than during sleep restriction, recovery from sleep restriction, and total sleep restriction (p=0.00691), most likely reflecting a steep learning curve. No significant main effect of phase was found for any RAT metric. Conclusion These preliminary findings suggest divergent thought as measured by the RAT is conserved across a differential amounts of sleep. More studies are needed to better characterize the impact of sleep loss on divergent thinking as well as possible mediating effects of other higher-order cognitive functions. Support (If Any) Department of Defense Military Operational Medicine Research Program (MOMRP)

0259 Chronotype and affective response to sleep restriction, sleep deprivation, and circadian misalignment

Abstract Introduction Late chronotypes have been shown to have decreased positive affect during the day and during sleep loss. Findings for negative affect are inconsistent. The present analysis examined the effect of chronotype on positive and negative affect during two sleep and circadian challenges. Methods In both studies, chronotype was determined by habitual mid-sleep time. In Study 1, 10 healthy adults (5 early, 5 late chronotypes) completed a 10-day protocol of sleep restriction followed by total sleep deprivation. Participants maintained habitual 8h sleep schedules at home for 1 week, then completed a 2-day in-laboratory protocol: 4h of sleep restriction, followed by a 4h sleep opportunity, followed by 28h of sleep deprivation. Affect was assessed with the Positive and Negative Affect Schedule (PANAS) every hour during scheduled wakefulness. In Study 2, 14 healthy adults (7 early, 7 late chronotypes) completed a 39-day protocol of combined sleep restriction and circadian misalignment. Participants maintained habitual 8h sleep schedules at home for 2 weeks, then completed a 4-day in-laboratory protocol with the following sleep opportunities: 8h on night 1, 3h on night 2, and 3h on mornings 3 and 4. After 3 days of at-home unscheduled recovery sleep opportunities, the protocol was repeated. Affect was assessed with the PANAS every 3h during scheduled wakefulness. Data from each study were analyzed separately with mixed-model ANOVA. Results Positive affect decreased during sleep restriction+sleep deprivation and sleep restriction+circadian misalignment (p<.05), regardless of chronotype. However, late chronotypes reported lower positive affect than early chronotypes across both sleep/circadian challenges (p<.05), and this effect was accounted for by baseline positive affect. Negative affect was not consistently impacted by sleep/circadian challenges or chronotype, with or without considering baseline negative affect. In both studies, chronotype did not interact with sleep/circadian challenges. Conclusion These findings are consistent with prior work showing later chronotypes have lower positive affect. Chronotype and sleep loss/circadian misalignment may impact affect through independent mechanisms. Future work is needed to replicate these findings in larger samples with more extreme chronotypes. Support (If Any) Office of Naval Research MURI N00014-15-1-2809; CurAegis Technologies Inc. (formerly Torvec, Inc), NIH HL109706, NIH TR001082; Undergraduate Research Opportunities Grant University of Colorado Boulder.

0009 Interindividual variation and extended wakefulness in sleepiness after acute and chronic sleep deprivation

Abstract Introduction Sleepiness is a behavioural consequence of sleep pressure and is associated with negative outcomes with interindividual variation, possibly related to central sleep mechanisms. However, there is a lack of evidence linking progressive sleep need and sleepiness with factors of individual variability, which could be tested by total acute and chronic sleep deprivation. Thus, the objective of the study was to investigate the development of sleepiness in sleep deprived mice. Methods Male C57BL/6J mice were distributed in sleep deprivation, sleep rebound and control groups. Animals underwent acute sleep deprivation for 3, 6, 9 or 12 hours or chronic sleep deprivation for 6 hours for 5 consecutive days. Sleep rebound groups had a sleep opportunity for 1, 2, 3, or 4 hours after acute sleep deprivation or 24 hours after chronic sleep deprivation. During the protocols, sleep attempts were counted to calculate a sleepiness index. After euthanasia, blood was collected for corticosterone assessment. Results Using the average of group sleep attempts, it was possible to differentiate between sleepy (mean>group average) and resistant animals (mean<group average). Resistant mice were more frequent in all settings. Individual variation accounted for 52% of sleepiness variance during chronic sleep deprivation and extended wakefulness explained 68% of sleepiness variance during acute sleep deprivation. A normal corticosterone peak was observed at the start of the dark phase, independent of sleep deprivation. Conclusion Different profiles of sleepiness emerged in sleep deprived mice. Sleep deprivation was the main factor for sleepiness during acute sleep deprivation whereas in chronic deprivation individual variation was more relevant. Support (If Any) Our studies are supported by the following funding agencies: AFIP (Associação Fundo de Incentivo à Pesquisa), São Paulo Research Foundation (FAPESP #2017/18455-5 to GLF), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES - Finance Code 001 to GLF), and CNPq (fellowships to MLA and ST; #169040/2017-8, and #141445/2021-1 to GLF). This study received indirect funding from AFIP and CNPq, which support the department in which the project was conducted.

0658 Slow-Wave Sleep Disruption Decreases Ability to Recognize Certain Negative Emotions

Abstract Introduction Research has demonstrated that sleep deprivation may alter emotion recognition. Given that emotion recognition is critical for effective human communication, it is essential to understand how sleep is involved in this process. Slow-wave sleep (SWS) has been suggested to be important for the consolidation and processing of emotional memories and neuroplasticity. This study aimed to examine the impact of experimental disruption of SWS on emotion recognition to further understand the contribution of SWS. Methods 31 participants (20 individuals diagnosed with Major Depressive Disorder (MDD), 11 healthy controls (HC)) completed two overnight sleep studies spaced one week apart. One night served as baseline (BL) and on the other night participants underwent slow-wave disruption (SWD), where SWS was disrupted using auditory stimulation. In the morning following each overnight visit, participants completed an emotion recognition task. Accuracy scores were computed as the percentage correct in each of 10 categories of emotions (anger, contempt, disgust, embarrassment, fear, joy, neutral, pride, sadness, and surprise). Repeated measures ANOVA was used to assess the impact of SWD on emotion recognition with group (HC, MDD) as the between subjects factor and condition (BL, SWD) as the within subjects factor. Results Results revealed a significant main effect of condition for disgust (F=13.72, p< .001), embarrassment (F=6.23, p=.019), and surprise (F=8.06, p=.008), with follow-up t-tests demonstrating that accuracy for the recognition of disgust and embarrassment decreased following SWD and accuracy for surprise increasing following SWD. No significant interactions were found for group*condition (ps>.105). Conclusion These results suggest that while SWD decreases the ability to recognize certain negative emotions, it also increases the ability to recognize surprise, which is in line with previous research examining acute total sleep deprivation. Interestingly, there appears to be no difference in the ability to recognize emotions between individuals with and without depression. Slow-wave sleep deficits, common in disorders such as depression and schizophrenia, may therefore contribute to poor communication abilities through decreased ability to recognize emotions, increasing the risk of interpersonal distress and mental health problems. Support (If Any) Goldschmied: K23MH118580 (NIMH)

0291 Social Desirability Mediates Self-Reported Sleepiness during a Laboratory Total Sleep Deprivation Study

Abstract Introduction Total sleep deprivation (TSD) increases sleepiness and impairs vigilant attention. There are large individual differences in vulnerability to sleep loss, but individuals’ self-ratings of sleepiness often do not align with their objective performance impairment. Here we investigated whether the trait of social desirability – the desire to conform to social standards – plays a role. Methods N=39 healthy adults (ages 27.6±4.6y; 22 men) completed a 3-night/4-day in-laboratory study with 10h baseline and recovery sleep opportunities (22:00–08:00) preceding and following a 38h period of TSD. Every 2–4h during TSD, subjects completed the Karolinska Sleepiness Scale (KSS) and a 10min Psychomotor Vigilance Test (PVT) to assess subjective sleepiness and vigilant attention, respectively. Throughout the study, subjects were behaviorally monitored by the researchers. Prior to the study, subjects completed the Marlow-Crowne Social Desirability (MCSD) scale. Based on standard criteria, subjects were categorized post hoc into average (n=13) and high (n=26) social desirability groups (no subjects in the sample scored low on social desirability). Self-reported sleepiness scored on the KSS and lapses (reaction times ≥500ms) on the PVT were analyzed using mixed-effects ANOVA with fixed effects for time awake and MCSD group and their interaction. Results As expected, there was a main effect of time awake for KSS score (F[12,441]=31.48, p<0.001) and PVT lapses (F[12,441]=16.27, p<0.001), with sleepiness and lapses increasing during TSD. We found a main effect of MCSD group for KSS score (F[1,441]=4.56, p=0.033), with the high MCSD group reporting lower levels of sleepiness than the average MCSD group. However, there was no effect of MCSD group for PVT lapses (p=0.93) and no time awake by MCSD interaction for either KSS (p=0.86) or PVT (p=0.99). Conclusion Subjects high in social desirability reported less sleepiness during TSD than those with average social desirability yet their objective performance was equally degraded. This finding has implications for fatigue risk management because individuals with high social desirability may underreport their sleepiness. This may undermine the reliability of self-report assessments of sleepiness and ability to work safely. [ 1] Whether there is bias in self-reported sleepiness for individuals low in social desirability as well remains to be investigated. Support (If Any) Support: ONR N00014-13-1-0302 and PRMRP W81XWH-20-1-0442

0202 Predicting Sleep Inertia in a Biomathematical Model of Fatigue and Performance: A Novel Approach

Abstract Introduction Biomathematical models of fatigue typically include sleep inertia as an additive process during wakefulness. However, there is predictive information to be gained from tracking the propensity for sleep inertia through sleep periods. We propose a novel approach involving a neurobiological sleep inertia process with relatively fast dynamics (in the order of several minutes) interacting with the much slower dynamics of the established processes of sleep/wake regulation. This sleep inertia process is captured by the addition of two ordinary differential equations (ODEs) in the model framework of McCauley and colleagues (2009, 2013, 2021) – one for wakefulness to track impairment from sleep inertia, and one for sleep to track the propensity for sleep inertia upon awakening. A single time constant is introduced to control the dynamic behavior of these ODEs to capture the dynamics of sleep inertia. Methods 398 healthy young adults (ages 21–49 years) each participated in one of eight multi-day laboratory studies of total sleep deprivation, sustained sleep restriction, or simulated shift work. At 2–4 hour intervals while awake, participants performed a Psychomotor Vigilance Test (PVT), for which number of lapses (RT>500ms) was assessed, and rated their sleepiness on the Karolinska Sleepiness Scale (KSS). Sleep periods were recorded polysomnographically. Data were divided into a calibration set (five studies) used to estimate a single new model parameter capturing sleep inertia, and a validation set (three studies) used to independently verify model validity. Results Based on the calibration data set, the sleep inertia time constant estimate was 0.71h±0.01. Based on the validation data set, goodness-of-fit root-mean-square-error was 2.28 for PVT and 0.733 for KSS, indicating high predictive accuracy. A dynamic buildup and then decline of predicted propensity for sleep inertia during sleep emerged, peaking 2–3h into the sleep period. Conclusion The model expansion with a one-parameter sleep inertia process captured the transient effect of sleep inertia accurately across a range of sleep deprivation, sleep restriction, and simulated shift work scenarios. The emerging dynamic of sleep inertia propensity during sleep is consistent with findings on the magnitude of sleep inertia as a function of sleep duration and stage of awakening. Support (If Any) WSU HPC

Abnormal timing of slow wave synchronization processes in non-rapid eye movement sleep parasomnias.

Sleepwalking, confusional arousals, and sleep terrors are parasomnias occurring out of non-rapid eye movement (NREM) sleep. Several previous studies have described EEG changes associated with NREM parasomnia episodes, but it remains unclear whether these changes are specific to parasomnia episodes or whether they are part of the normal awakening process. Here we directly compared regional brain activity, measured with high-density (hd-) EEG, between parasomnia episodes and normal awakenings (without behavioral manifestations of parasomnia). Twenty adult patients with non-rapid eye movement parasomnias underwent a baseline hd-EEG recording (256 electrodes) followed by a recovery sleep recording after 25 h of total sleep deprivation, during which auditory stimuli were administered to provoke parasomnia episodes. Both normal awakenings (n = 25) and parasomnia episodes (n = 96) were preceded by large, steep, and "K-complex-like" slow waves in frontal and central brain regions, and by a concomitant increase in high-frequency EEG (beta) activity. Compared to normal awakenings, parasomnia episodes occurred on a less activated EEG background and displayed higher slow wave activity (SWA) and lower beta activity in frontal and central brain regions after movement onset. Our results suggest that non-rapid eye movement awakenings, irrespective of behavioral manifestations of parasomnia episodes, involve an arousal-related slow wave synchronization process that predominantly recruits frontal and central brain areas. In parasomnia episodes, this synchronization process comes into play abnormally during periods of high SWA and is associated with higher SWA after movement onset. Thus, an abnormal timing of arousal-related slow wave synchronization processes could underlie the occurrence of NREM parasomnias.

Recovery of Cognitive Performance Following Multi-Stressor Military Training.

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

How Sleep-Deprived People See and Evaluate Others' Faces: An Experimental Study.

BackgroundAcute sleep loss increases the brain’s reactivity toward positive and negative affective stimuli. Thus, despite well-known reduced attention due to acute sleep loss, we hypothesized that humans would gaze longer on happy, angry, and fearful faces than neutral faces when sleep-deprived. We also examined if facial expressions are differently perceived after acute sleep loss.MethodsIn the present, within-subjects study, 45 young adults participated in one night of total sleep deprivation and one night with an 8-hour sleep opportunity. On the morning after each night, an eye tracker was used to measure participants’ time spent fixating images of happy, angry, fearful, and neutral faces. Participants also evaluated faces’ attractiveness, trustworthiness, and healthiness on a 100-mm visual analog scale.ResultsFollowing sleep loss, participants struggled more fixating the faces than after sleep. The decrease in total fixation duration ranged from 6.3% to 10.6% after sleep loss (P<0.001). Contrary to our hypothesis, the reduction in total fixation duration occurred irrespective of the displayed emotion (P=0.235 for sleep*emotion interaction) and was also present for the upper (P<0.001) but not the lower part of the faces (except for the lower part of angry faces). Overall, faces were evaluated as less trustworthy (−2.6 mm) and attractive (−3.6 mm) after sleep loss (p<0.05).DiscussionFacial expressions are crucial for social interactions. Thus, spending less time fixating on faces after acute sleep loss may come along with several problems for social interactions, eg, inaccurate and delayed judgment of the emotional state of others. In addition, more negative social impressions of others may lead to social withdrawal in sleep-deprived humans.