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

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.

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.

Enhanced amygdala-cingulate connectivity associates with better mood in both healthy and depressive individuals after sleep deprivation

Sleep loss robustly disrupts mood and emotion regulation in healthy individuals but can have a transient antidepressant effect in a subset of patients with depression. The neural mechanisms underlying this paradoxical effect remain unclear. Previous studies suggest that the amygdala and dorsal nexus (DN) play key roles in depressive mood regulation. Here, we used functional MRI to examine associations between amygdala- and DN-related resting-state connectivity alterations and mood changes after one night of total sleep deprivation (TSD) in both healthy adults and patients with major depressive disorder using strictly controlled in-laboratory studies. Behavioral data showed that TSD increased negative mood in healthy participants but reduced depressive symptoms in 43% of patients. Imaging data showed that TSD enhanced both amygdala- and DN-related connectivity in healthy participants. Moreover, enhanced amygdala connectivity to the anterior cingulate cortex (ACC) after TSD associated with better mood in healthy participants and antidepressant effects in depressed patients. These findings support the key role of the amygdala-cingulate circuit in mood regulation in both healthy and depressed populations and suggest that rapid antidepressant treatment may target the enhancement of amygdala-ACC connectivity.

Concurrent behavioral and electrophysiological longitudinal recordings for in vivo assessment of aging

Electrophysiological and behavioral alterations, including sleep and cognitive impairments, are critical components of age-related decline and neurodegenerative diseases. In preclinical investigation, many refined techniques are employed to probe these phenotypes, but they are often conducted separately. Herein, we provide a protocol for one-time surgical implantation of EMG wires in the nuchal muscle and a skull-surface EEG headcap in mice, capable of 9-to-12-month recording longevity. All data acquisitions are wireless, making them compatible with simultaneous EEG recording coupled to multiple behavioral tasks, as we demonstrate with locomotion/sleep staging during home-cage video assessments, cognitive testing in the Barnes maze, and sleep disruption. Time-course EEG and EMG data can be accurately mapped to the behavioral phenotype and synchronized with neuronal frequencies for movement and the location to target in the Barnes maze. We discuss critical steps for optimizing headcap surgery and alternative approaches, including increasing the number of EEG channels or utilizing depth electrodes with the system. Combining electrophysiological and behavioral measurements in preclinical models of aging and neurodegeneration has great potential for improving mechanistic and therapeutic assessments and determining early markers of brain disorders.

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.

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.

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.