Daniel J. Mollicone

Mars 520-d mission simulation reveals protracted crew hypokinesis and alterations of sleep duration and timing

The success of interplanetary human spaceflight will depend on many factors, including the behavioral activity levels, sleep, and circadian timing of crews exposed to prolonged microgravity and confinement. To address the effects of the latter, we used a high-fidelity ground simulation of a Mars mission to objectively track sleep–wake dynamics in a multinational crew of six during 520 d of confined isolation. Measurements included continuous recordings of wrist actigraphy and light exposure (4.396 million min) and weekly computer-based neurobehavioral assessments (n = 888) to identify changes in the crews activity levels, sleep quantity and quality, sleep–wake periodicity, vigilance performance, and workload throughout the record-long 17 mo of mission confinement. Actigraphy revealed that crew sedentariness increased across the mission as evident in decreased waking movement (i.e., hypokinesis) and increased sleep and rest times. Light exposure decreased during the mission. The majority of crewmembers also experienced one or more disturbances of sleep quality, vigilance deficits, or altered sleep–wake periodicity and timing, suggesting inadequate circadian entrainment. The results point to the need to identify markers of differential vulnerability to hypokinesis and sleep–wake changes during the prolonged isolation of exploration spaceflight and the need to ensure maintenance of circadian entrainment, sleep quantity and quality, and optimal activity levels during exploration missions. Therefore, successful adaptation to such missions will require crew to transit in spacecraft and live in surface habitats that instantiate aspects of Earths geophysical signals (appropriately timed light exposure, food intake, exercise) required for temporal organization and maintenance of human behavior.

Time of Day Effects on Neurobehavioral Performance During Chronic Sleep Restriction

INTRODUCTION Chronic nocturnal sleep restriction results in accumulation of neurobehavioral impairment across days. The purpose of this study was to determine whether time of day modulates the effects of sleep restriction on objective daytime performance deficits and subjective sleepiness across days of chronic sleep restriction. METHODS There were N = 90 healthy adults (21-49 yr; 38 women) who participated in a 14-d laboratory protocol involving randomization to 1 of 18 schedules of restricted nocturnal sleep with and without a diurnal nap for 10 consecutive days. The total time available for daily sleep ranged from 4.2 h to 8.2 h across conditions. Performance lapses on the psychomotor vigilance test (PVT) and subjective sleepiness were measured each day every 2 h during scheduled wakefulness. Nonlinear mixed-effects regression was used to test the hypothesis that there would be an interaction between time of day and the accumulation (slope across days) of neurobehavioral sleepiness. RESULTS In agreement with earlier studies, less sleep time resulted in faster accumulation of deficits across days. Time of day significantly affected this relationship for both PVT lapses and subjective sleepiness. The build-up rate of cumulative neurobehavioral deficits across days was largest at 0800 and became progressively smaller across the hours of the day, especially between 1600 and 2000. Following 8 d of sleep restricted to 4 h/d, subjects averaged 8.3 more PVT performance lapses at 0800 than at 1800. DISCUSSION This study provides evidence that the circadian system has a substantial modulatory effect on cumulative impairment from chronic sleep restriction and that it facilitates a period of relatively protected alertness in the late afternoon/early evening hours when nocturnal sleep is chronically restricted.

Dynamic Circadian Modulation in a Biomathematical Model for the Effects of Sleep and Sleep Loss on Waking Neurobehavioral Performance

Recent experimental observations and theoretical advances have indicated that the homeostatic equilibrium for sleep/wake regulation--and thereby sensitivity to neurobehavioral impairment from sleep loss--is modulated by prior sleep/wake history. This phenomenon was predicted by a biomathematical model developed to explain changes in neurobehavioral performance across days in laboratory studies of total sleep deprivation and sustained sleep restriction. The present paper focuses on the dynamics of neurobehavioral performance within days in this biomathematical model of fatigue. Without increasing the number of model parameters, the model was updated by incorporating time-dependence in the amplitude of the circadian modulation of performance. The updated model was calibrated using a large dataset from three laboratory experiments on psychomotor vigilance test (PVT) performance, under conditions of sleep loss and circadian misalignment; and validated using another large dataset from three different laboratory experiments. The time-dependence of circadian amplitude resulted in improved goodness-of-fit in night shift schedules, nap sleep scenarios, and recovery from prior sleep loss. The updated model predicts that the homeostatic equilibrium for sleep/wake regulation--and thus sensitivity to sleep loss--depends not only on the duration but also on the circadian timing of prior sleep. This novel theoretical insight has important implications for predicting operator alertness during work schedules involving circadian misalignment such as night shift work.

Psychological and behavioral changes during confinement in a 520-day simulated interplanetary mission to mars.

Behavioral health risks are among the most serious and difficult to mitigate risks of confinement in space craft during long-duration space exploration missions. We report on behavioral and psychological reactions of a multinational crew of 6 healthy males confined in a 550 m3 chamber for 520 days during the first Earth-based, high-fidelity simulated mission to Mars. Rest-activity of crewmembers was objectively measured throughout the mission with wrist-worn actigraphs. Once weekly throughout the mission crewmembers completed the Beck Depression Inventory-II (BDI-II), Profile of Moods State short form (POMS), conflict questionnaire, the Psychomotor Vigilance Test (PVT-B), and series of visual analogue scales on stress and fatigue. We observed substantial inter-individual differences in the behavioral responses of crewmembers to the prolonged mission confinement and isolation. The crewmember with the highest average POMS total mood disturbance score throughout the mission also reported symptoms of depression in 93% of mission weeks, which reached mild-to-moderate levels in >10% of mission weeks. Conflicts with mission control were reported five times more often than conflicts among crewmembers. Two crewmembers who had the highest ratings of stress and physical exhaustion accounted for 85% of the perceived conflicts. One of them developed a persistent sleep onset insomnia with ratings of poor sleep quality, which resulted in chronic partial sleep deprivation, elevated ratings of daytime tiredness, and frequent deficits in behavioral alertness. Sleep-wake timing was altered in two other crewmembers, beginning in the first few months of the mission and persisting throughout. Two crewmembers showed neither behavioral disturbances nor reports of psychological distress during the 17-month period of mission confinement. These results highlight the importance of identifying behavioral, psychological, and biological markers of characteristics that predispose prospective crewmembers to both effective and ineffective behavioral reactions during the confinement of prolonged spaceflight, to inform crew selection, training, and individualized countermeasures.

Effect of a Protected Sleep Period on Hours Slept During Extended Overnight In-hospital Duty Hours Among Medical Interns: A Randomized Trial

CONTEXT A 2009 Institute of Medicine report recommended protected sleep periods for medicine trainees on extended overnight shifts, a position reinforced by new Accreditation Council for Graduate Medical Education requirements. OBJECTIVE To evaluate the feasibility and consequences of protected sleep periods during extended duty. DESIGN, SETTING, AND PARTICIPANTS Randomized controlled trial conducted at the Philadelphia VA Medical Center medical service and Oncology Unit of the Hospital of the University of Pennsylvania (2009-2010). Of the 106 interns and senior medical students who consented, 3 were not scheduled on any study rotations. Among the others, 44 worked at the VA center, 16 at the university hospital, and 43 at both. INTERVENTION Twelve 4-week blocks were randomly assigned to either a standard intern schedule (extended duty overnight shifts of up to 30 hours; equivalent to 1200 overnight intern shifts at each site), or a protected sleep period (protected time from 12:30 AM to 5:30 AM with handover of work cell phone; equivalent to 1200 overnight intern shifts at each site). Participants were asked to wear wrist actigraphs and complete sleep diaries. MAIN OUTCOME MEASURES Primary outcome was hours slept during the protected period on extended duty overnight shifts. Secondary outcome measures included hours slept during a 24-hour period (noon to noon) by day of call cycle and Karolinska sleepiness scale. RESULTS For 98.3% of on-call nights, cell phones were signed out as designed. At the VA center, participants with protected sleep had a mean 2.86 hours (95% CI, 2.57-3.10 hours) of sleep vs 1.98 hours (95% CI, 1.68-2.28 hours) among those who did not have protected hours of sleep (P < .001). At the university hospital, participants with protected sleep had a mean 3.04 hours (95% CI, 2.77-3.45 hours) of sleep vs 2.04 hours (95% CI, 1.79-2.24) among those who did not have protected sleep (P < .001). Participants with protected sleep were significantly less likely to have call nights with no sleep: 5.8% (95% CI, 3.0%-8.5%) vs 18.6% (95% CI, 13.9%-23.2%) at the VA center (P < .001) and 5.9% (95% CI, 3.1%-8.7%) vs 14.2% (95% CI, 9.9%-18.4%) at the university hospital (P = .001). Participants felt less sleepy after on-call nights in the intervention group, with Karolinska sleepiness scale scores of 6.65 (95% CI, 6.35-6.97) vs 7.10 (95% CI, 6.85-7.33; P = .01) at the VA center and 5.91 (95% CI, 5.64-6.16) vs 6.79 (95% CI, 6.57-7.04; P < .001) at the university hospital. CONCLUSIONS For internal medicine services at 2 hospitals, implementation of a protected sleep period while on call resulted in an increase in overnight sleep duration and improved alertness the next morning. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00874510.

Modifying the human circadian pacemaker using model based predictive control

The human circadian pacemaker is a biological timekeep ing mechanism that governs alertness as well as many other physiological processes of the human body. It is widely accepted that daytime alertness is maximized when an individuals sleepjwake schedule and circadian pacemaker are synchronized. Unfortunately todays world is characterized by widely distributed activity schedules which often make this difficult. However research in chronobiology indicates that ambient light stimulus can he used to phase advance or delay the human circadian pacemaker. To optimally control the human circadian pacemaker using light, the authors present a model based predictive control system. This ap proach readily facilitates closed-loop control and elegantly handles the constraints present in a typical human environment, thus has merit for a number of practical applications.

Naturalistic field study of the restart break in US commercial motor vehicle drivers: Truck driving, sleep, and fatigue.

Commercial motor vehicle (CMV) drivers in the US may start a new duty cycle after taking a 34-h restart break. A restart break provides an opportunity for sleep recuperation to help prevent the build-up of fatigue across duty cycles. However, the effectiveness of a restart break may depend on its timing, and on how many nighttime opportunities for sleep it contains. For daytime drivers, a 34-h restart break automatically includes two nighttime periods. For nighttime drivers, who are arguably at increased risk of fatigue, a 34-h restart break contains only one nighttime period. To what extent this is relevant for fatigue depends in part on whether nighttime drivers revert back to a nighttime-oriented sleep schedule during the restart break. We conducted a naturalistic field study with 106 CMV drivers working their normal schedules and performing their normal duties. These drivers were studied during two duty cycles and during the intervening restart break. They provided a total of 1260days of data and drove a total of 414,937 miles during the study. Their duty logs were used to identify the periods when they were on duty and when they were driving and to determine their duty cycles and restart breaks. Sleep/wake patterns were measured continuously by means of wrist actigraphy. Fatigue was assessed three times per day by means of a brief psychomotor vigilance test (PVT-B) and a subjective sleepiness scale. Data from a truck-based lane tracking and data acquisition system were used to compute lane deviation (variability in lateral lane position). Statistical analyses focused on 24-h patterns of duty, driving, sleep, PVT-B performance, subjective sleepiness, and lane deviation. Duty cycles preceded by a restart break containing only one nighttime period (defined as 01:00-05:00) were compared with duty cycles preceded by a restart break containing more than one nighttime period. During duty cycles preceded by a restart break with only one nighttime period, drivers showed more nighttime-oriented duty and driving patterns and more daytime-oriented sleep patterns than during duty cycles preceded by a restart break with more than one nighttime period. During duty cycles preceded by a restart break with only one nighttime period, drivers also experienced more lapses of attention on the PVT-B and increased lane deviation at night, and they reported greater subjective sleepiness. Importantly, drivers exhibited a predominantly nighttime-oriented sleep schedule during the restart break, regardless of whether the restart break contained only one or more than one nighttime period. Consistent with findings in laboratory-based studies of the restart break, the results of this naturalistic field study indicate that having at least two nighttime periods in the restart break provides greater opportunity for sleep recuperation and helps to mitigate fatigue.

Automated determination of wakefulness and sleep in rats based on non-invasively acquired measures of movement and respiratory activity

The current standard for monitoring sleep in rats requires labor intensive surgical procedures and the implantation of chronic electrodes which have the potential to impact behavior and sleep. With the goal of developing a non-invasive method to determine sleep and wakefulness, we constructed a non-contact monitoring system to measure movement and respiratory activity using signals acquired with pulse Doppler radar and from digitized video analysis. A set of 23 frequency and time-domain features were derived from these signals and were calculated in 10s epochs. Based on these features, a classification method for automated scoring of wakefulness, non-rapid eye movement sleep (NREM) and REM in rats was developed using a support vector machine (SVM). We then assessed the utility of the automated scoring system in discriminating wakefulness and sleep by comparing the results to standard scoring of wakefulness and sleep based on concurrently recorded EEG and EMG. Agreement between SVM automated scoring based on selected features and visual scores based on EEG and EMG were approximately 91% for wakefulness, 84% for NREM and 70% for REM. The results indicate that automated scoring based on non-invasively acquired movement and respiratory activity will be useful for studies requiring discrimination of wakefulness and sleep. However, additional information or signals will be needed to improve discrimination of NREM and REM episodes within sleep.

Model-Based Human Circadian Phase Estimation Using a Particle Filter

We present a method for tracking an individuals circadian phase that integrates dynamic models of circadian physiology with physiological measurements in a Bayesian statistical framework. A model of the circadian pacemakers response to light exposure is transformed into a nonlinear state-space model with a circadian phase state. The probability distribution of the circadian phase is estimated by a particle filter that predicts changes over time based on the model, and performs updates with information gained from physiological measurements. Simulations demonstrate how probability distributions allow flexible initialization of model states and enable statistical quantification of entrainment and divergence properties of the circadian pacemaker. The combined use of sleep-wake scheduling data and physiological measurements is demonstrated in a case study highlighting advantages for addressing the challenge of noninvasive ambulatory monitoring of circadian physiology.

Development and Validation of the Cognition Test Battery for Spaceflight.

BACKGROUND Sustained high-level cognitive performance is of paramount importance for the success of space missions, which involve environmental, physiological, and psychological stressors that may affect brain functions. Despite subjective symptom reports of cognitive fluctuations in spaceflight, the nature of neurobehavioral functioning in space has not been clarified. METHODS We developed a computerized cognitive test battery (Cognition) that has sensitivity to multiple cognitive domains and was specifically designed for the high-performing astronaut population. Cognition consists of 15 unique forms of 10 neuropsychological tests that cover a range of cognitive domains, including emotion processing, spatial orientation, and risk decision making. Cognition is based on tests known to engage specific brain regions as evidenced by functional neuroimaging. Here we describe the first normative and acute total sleep deprivation data on the Cognition test battery as well as several efforts underway to establish the validity, sensitivity, feasibility, and acceptability of Cognition. RESULTS Practice effects and test-retest variability differed substantially between the 10 Cognition tests, illustrating the importance of normative data that both reflect practice effects and differences in stimulus set difficulty in the population of interest. After one night without sleep, medium to large effect sizes were observed for 3 of the 10 tests addressing vigilant attention (Cohens d = 1.00), cognitive throughput (d = 0.68), and abstract reasoning (d = 0.65). CONCLUSIONS In addition to providing neuroimaging-based novel information on the effects of spaceflight on a range of cognitive functions, Cognition will facilitate comparing the effects of ground-based analogues to spaceflight, increase consistency across projects, and thus enable meta-analyses.