From trenches to technology: a narrative review of sleep medicine in the military.

Diagnoses of military-relevant sleep disorders have increased substantially since the terrorist attacks of 9-11. The cause of this increase appears to be complicated and multifactorial, with military and civilian populations clearly differing with respect to both the nature and distribution of sleep disorders diagnoses. In part, these differences may be attributable to the fact that a majority of service members (SMs) are chronically sleep restricted - an unavoidable consequence of continuous and sustained military operations that 'set the stage' for development of specific sleep disorders. The purpose of this narrative review is to describe the military relevance of several common sleep disorders, assess the extent to which these disorders currently constitute a burden on the military healthcare system, and suggest strategies to alleviate that burden. The military healthcare system does not have enough sleep providers to address the immediate and long-term consequences of sleep disorders in military personnel. Digital technologies and education packages can be leveraged to improve access to care.

Increased rates of brain protein synthesis during [N1,N2] sleep: L-[1-11C]leucine PET studies in human subjects.

During sleep, reduced brain energy demands provide an opportunity for biosynthetic processes like protein synthesis. Sleep is required for some forms of memory consolidation which requires de novo protein synthesis. We measured regional cerebral protein synthesis rates (rCPS) in human subjects to ascertain how rCPS is affected during sleep. Subjects underwent three consecutive L-[1-11C]leucine PET scans with simultaneous polysomnography: 1. rested awake, 2. sleep-deprived awake, 3. sleep. Measured rCPS were similar across the three conditions. Variations in sleep stage times during sleep scans were used to estimate rCPS in sleep stages under the assumption that measured rCPS is the weighted sum of rCPS in each stage, with weights reflecting time and availability of [11C]leucine in that stage. During sleep scans, subjects spent most of the time in N2, N3, and awake and very little time in N1 and REM; rCPS in N1 and REM could not be reliably estimated. When stages N1 and N2 were combined [N1,N2], estimates of rCPS were more robust. In selective regions, estimated rCPS were statistically significantly higher (30-39%) in [N1,N2] compared with N3; estimated rCPS in N3 were similar to values measured in sleep-deprived awake scans. Results indicate increased rates of protein synthesis linked to [N1,N2] sleep.

Acute sleep interventions as an avenue for treatment of trauma-associated disorders.

Scientific evidence that acute, posttrauma sleep disturbances (eg, nightmares and insomnia) can contribute significantly to the pathogenesis of trauma-induced disorders is compelling. Sleep disturbances precipitating from trauma are uniquely predictive of daytime posttrauma symptom occurrence and severity, as well as subsequent onset of mental health disorders, including post-traumatic stress disorder. Conversely, adequate sleep during the acute posttrauma period is associated with reduced likelihood of adverse mental health outcomes. These findings, which are broadly consistent with what is known about the role of sleep in the regulation of emotion, suggest that the acute posttrauma period constitutes a "window of opportunity" during which treatment of sleep disturbances may be especially effective for preventing or mitigating progression of aberrant psychophysiological processes. At this point, the weight of the scientific evidence supporting this possibility warrants initiation of clinical trials to confirm the benefits of targeted prophylactic sleep enhancement, and to establish treatment guidelines as appropriate. CITATION: Swift KM, Thomas CL, Balkin TJ, Lowery-Gionta EG, Matson LM. Acute sleep interventions as an avenue for treatment of trauma-associated disorders. J Clin Sleep Med. 2022;18(9):2291-2312.

2B-Alert Web 2.0, an Open-Access Tool for Predicting Alertness and Optimizing the Benefits of Caffeine: Utility Study.

BACKGROUND: One-third of the US population experiences sleep loss, with the potential to impair physical and cognitive performance, reduce productivity, and imperil safety during work and daily activities. Computer-based fatigue-management systems with the ability to predict the effects of sleep schedules on alertness and identify safe and effective caffeine interventions that maximize its stimulating benefits could help mitigate cognitive impairment due to limited sleep. To provide these capabilities to broad communities, we previously released 2B-Alert Web, a publicly available tool for predicting the average alertness level of a group of individuals as a function of time of day, sleep history, and caffeine consumption. OBJECTIVE: In this study, we aim to enhance the capability of the 2B-Alert Web tool by providing the means for it to automatically recommend safe and effective caffeine interventions (time and dose) that lead to optimal alertness levels at user-specified times under any sleep-loss condition. METHODS: We incorporated a recently developed caffeine-optimization algorithm into the predictive models of the original 2B-Alert Web tool, allowing the system to search for and identify viable caffeine interventions that result in user-specified alertness levels at desired times of the day. To assess the potential benefits of this new capability, we simulated four sleep-deprivation conditions (sustained operations, restricted sleep with morning or evening shift, and night shift with daytime sleep) and compared the alertness levels resulting from the algorithm's recommendations with those based on the US Army caffeine-countermeasure guidelines. In addition, we enhanced the usability of the tool by adopting a drag-and-drop graphical interface for the creation of sleep and caffeine schedules. RESULTS: For the 4 simulated conditions, the 2B-Alert Web-proposed interventions increased mean alertness by 36% to 94% and decreased peak alertness impairment by 31% to 71% while using equivalent or smaller doses of caffeine as the corresponding US Army guidelines. CONCLUSIONS: The enhanced capability of this evidence-based, publicly available tool increases the efficiency by which diverse communities of users can identify safe and effective caffeine interventions to mitigate the effects of sleep loss in the design of research studies and work and rest schedules.

Quantifying the effects of sleep loss: relative effect sizes of the psychomotor vigilance test, multiple sleep latency test, and maintenance of wakefulness test.

The psychomotor vigilance test (PVT) is a widely-used, minimally invasive, inexpensive, portable, and easy to administer behavioral measure of vigilance that is sensitive to sleep loss. We conducted analyses to determine the relative sensitivity of the PVT vs. the multiple sleep latency test (MSLT) and the maintenance of wakefulness test (MWT) during acute total sleep deprivation (TSD) and multiple days of sleep restriction (SR) in studies of healthy adults. Twenty-four studies met the criteria for inclusion. Since sleepiness countermeasures were administered in some of these studies, the relative sensitivity of the three measures to these interventions was also assessed. The difference in weighted effect size (eta-squared) was computed for each pair of sleepiness measures based on available raw test data (such as average PVT reaction time). Analyses revealed that the sleep measures were differentially sensitive to various types of sleep loss over time, with MSLT and MWT more sensitive to TSD than the PVT. However, sensitivity to SR was comparable for all three measures. The PVT and MSLT were found to be differentially sensitive to the administration of sleepiness countermeasures (drugs, sleep loss, etc.), but PVT and MWT were found to be comparably sensitive to these interventions. These findings suggest the potential utility of the PVT as a component of next-generation fatigue risk management systems.

Self-Reported Sleep Need, Subjective Resilience, and Cognitive Performance Following Sleep Loss and Recovery Sleep.

OBJECTIVE: Individuals vary in response to sleep loss: some individuals are "vulnerable" and demonstrate cognitive decrements following insufficient sleep, while others are "resistant" and maintain baseline cognitive capability. Physiological markers (e.g., genetic polymorphisms) have been identified that can predict relative vulnerability. However, a quick, cost-effective, and feasible subjective predictor tool has not been developed. The objective of the present study was to determine whether two factors-"subjective sleep need" and "subjective resilience"-predict cognitive performance following sleep deprivation. METHODS: Twenty-seven healthy, sleep-satiated young adults participated. These individuals were screened for sleep disorders, comorbidities, and erratic sleep schedules. Prior to 40 hours of in-laboratory total sleep deprivation, participants were questioned on their subjective sleep need and completed a validated resilience scale. During and after sleep deprivation, participants completed a 5-minute psychomotor vigilance test every 2 hours. RESULTS: Both subjective resilience and subjective sleep need individually failed to predict performance during sleep loss. However, these two measures interacted to predict performance. Individuals with low resilience and low sleep need had poorer cognitive performance during sleep loss. However, in individuals with medium or high resilience, psychomotor vigilance test performance was not predicted by subjective sleep need. Higher resilience may be protective against sleep loss-related neurobehavioral impairments in the context of subjective sleep need. CONCLUSIONS: Following sleep loss (and recovery sleep), trait resilient individuals may outperform those with lower resiliency on real-world tasks that require continuous attention. Future studies should determine whether the present findings generalize to other, operationally relevant tasks and additional cognitive domains.

Models for predicting sleep latency and sleep duration.

STUDY OBJECTIVES: Planning effective sleep-wake schedules for civilian and military settings depends on the ability to predict the extent to which restorative sleep is likely for a specified sleep period. Here, we developed and validated two mathematical models, one for predicting sleep latency and a second for predicting sleep duration, as decision aids to predict efficacious sleep periods. METHODS: We extended the Unified Model of Performance (UMP), a well-validated mathematical model of neurobehavioral performance, to predict sleep latency and sleep duration, which vary nonlinearly as a function of the homeostatic sleep pressure and the circadian rhythm. To this end, we used the UMP to predict the time course of neurobehavioral performance under different conditions. We developed and validated the models using experimental data from 317 unique subjects from 24 different studies, which included sleep conditions spanning the entire circadian cycle. RESULTS: The sleep-latency and sleep-duration models accounted for 42% and 84% of the variance in the data, respectively, and yielded acceptable average prediction errors for planning sleep schedules (4.0 min for sleep latency and 0.8 h for sleep duration). Importantly, we identified conditions under which small shifts in sleep onset timing result in disproportionately large differences in sleep duration-knowledge that may be applied to improve performance, safety, and sustainability in civilian and military operations. CONCLUSIONS: These models extend the capabilities of existing predictive fatigue-management tools, allowing users to anticipate the most opportune times to schedule sleep periods.

TNFα G308A genotype, resilience to sleep deprivation, and the effect of caffeine on psychomotor vigilance performance in a randomized, double-blind, placebo-controlled, crossover study.

The TNFα G308A gene polymorphism has been reported to influence performance impairment during total sleep deprivation (TSD). We investigated this effect in a randomized, double-blind, crossover laboratory study of repeated exposure to 48 h TSD with caffeine administration at different doses. In a retrospective analysis, we replicated the finding that the A allele of TNFα G308A, found in 4 of 12 study participants, confers resilience to performance impairment during TSD. There was no evidence of an interaction of TNFα genotype with the beneficial effect of caffeine (200 or 300 mg) on performance during TSD, suggesting distinct underlying mechanisms.

Effect of cognitive load and emotional valence of distractors on performance during sleep extension and subsequent sleep deprivation.

STUDY OBJECTIVES: The purpose of the present study was to assess the extent to which sleep extension followed by sleep deprivation impacts performance on an attentional task with varying cognitive and attentional demands that influence decisions. METHODS: Task performance was assessed at baseline, after 1 week of sleep extension, and after 40 h of total sleep deprivation. RESULTS: One week of sleep extension resulted in improved performance, particularly for high cognitive load decisions regardless of the emotional salience of attentional distractors. Those who extended sleep the most relative to their habitual sleep duration showed the greatest improvement in general performance during sleep extension. However, a higher percentage of time spent in slow-wave sleep (SWS) on the last night of the sleep extension phase was negatively correlated with performance on more difficult high cognitive load items, possibly reflecting a relatively higher level of residual sleep need. Sleep deprivation generally resulted in impaired performance, with a nonsignificant trend toward greater performance decrements in the presence of emotionally salient distractors. Performance overall, but specifically for high cognitive load decisions, during total sleep deprivation was negatively correlated with longer sleep and higher SWS percentage during subsequent recovery sleep. CONCLUSIONS: The present findings suggest two possibilities: those who performed relatively poorly during sleep deprivation were more vulnerable because (1) they utilized mental resources (i.e. accrued sleep debt) at a relatively faster rate during wakefulness, and/or (2) they failed to "pay down" pre-study sleep debt to the same extent as better-performing participants during the preceding sleep extension phase.

Precision Medicine for Sleep Loss and Fatigue Management.

Sleep loss is a widespread phenomenon and a public health threat. Sleep disorders, medical conditions, lifestyles, and occupational factors all contribute to insufficient sleep. Regardless of the underlying cause, insufficient sleep has well-defined consequences and the severity of said consequences partially influenced by individual characteristics. It is here where precision medicine needs to understand and define sleep insufficiency in hopes for personalizing medical approach to improve patient outcomes. Following a discussion on causes and consequences of sleep loss, this article discusses tools for assessing sleep sufficiency, mitigating strategies to sleep loss, and sleep loss in the context of fatigue management.

Objective changes in activity levels following sleep extension as measured by wrist actigraphy.

OBJECTIVE/BACKGROUND: It is widely established that insufficient sleep can lead to adverse health outcomes. Paradoxically, epidemiologic research suggests that individuals who report habitual nightly sleep greater than 9 h also are at risk for adverse health outcomes. Further, studies have shown that long sleepers have decreased activity levels, which may partially explain the relationship between long sleep duration and mortality. The influence of sleep extension (longer time in bed) on levels of daily activity has not yet been established. The current study examined whether a week of sleep extension altered activity levels within the subsequent daily waking active and sleep period in order to determine whether increased time in bed indeed is related to decreased activity levels. METHODS: A total of 26 healthy volunteers wore wrist accelerometer devices (Actiwatch 2.0, Philips) in order to objectively measure sleep and activity for six days during their normal schedules and for six days during a sleep extension (10 h time in bed) intervention. RESULTS: There were no significant or clinically-relevant differences in 24-h activity or activity during the active or sleep period between baseline and sleep extension conditions. There were no main or interaction effects of day and condition when daily activity counts were compared between baseline and sleep extension conditions for the 24 h period (Day: F(5, 21) = 1.92, p = 0.12; Condition: F(1,25) = 2.93, p = 0.09; Day by Condition: F(5,21) = 0.32, p = 0.83), Active Waking Period (Day: F(5,25) = 1.53, p = 0.18; Condition: F(1,25) = 0.26, p = 0.61; Day by Condition: F(5,21) = 0.55, p = 0.74) or Nightly Sleep (Day: F(5,21) = 0.86, p = 0.51; Condition: F(1,25) = 1.78, p = 0.19; Day by Condition: F(5,21) = 0.79, p = 0.56) periods. In contrast, there was a main effect of condition when examining sleep duration by day between conditions (Day: F(5,21) = 1.60, p = 0.16; Condition: F(1,25) = 167.31, p < 0.001; Day by Condition: F(5,21) = 2.31, p = 0.07), such that sleep duration was longer during the sleep extension condition. DISCUSSION: Sleep duration increased during six days of a sleep extension protocol but activity levels remained similar to their baseline (normal) sleep schedule. The current findings suggest that extending time in bed alone does not alter waking activity counts in young healthy adults. The link between extended sleep and adverse health outcomes may be attributable to other phenotypic factors, or other biological correlates of extended sleep and poor health.

Sleep health and its association with performance and motivation in tactical athletes enrolled in the Reserve Officers' Training Corps.

OBJECTIVE: To examine habitual sleep health and investigate how habitual sleep duration impacts performance and motivation in Reserve Officers' Training Corps (ROTC) tactical athletes. DESIGN: Observational. SETTING: A large, state university. PARTICIPANTS: Fifty-four young tactical athletes enrolled in ROTC. MEASUREMENTS: Participants wore wrist actigraph devices and completed sleep diaries for 7 days prior to completing a cognitive/motor test battery. RESULTS: The mean objective total sleep time of the participants was 6.17 ±â€¯0.69 hours, with only 7.4% of participants averaging ≥7 hours of sleep per day. A mean sleep quality rating between "Poor" and "Fair" was reported by 22.2% of participants. The mean Epworth Sleepiness Scale rating was 8.80 ±â€¯3.24, with 27.8% of participants reporting scores >10. Controlling for age and gender, the average objective total sleep duration was significantly associated with performance on the Symbol Digit Modalities Test (P = .026) and with motivation levels to perform the cognitive/motor battery (P = .016), but not with performance on the Psychomotor Vigilance Test, Flanker task, Trail Making Test, or Standing Broad Jump. CONCLUSIONS: ROTC tactical athletes habitually sleep less than the recommended 7 hours per day with roughly one-fourth reporting excessive daytime sleepiness and one-fifth reporting poor sleep quality, which may increase their risk for future adverse health outcomes. Longer sleep durations were associated with higher motivation levels and better cognitive processing speed performance; however, they were not associated with executive function, psychomotor vigilance, or broad jump performance.

Sleep extension reduces fatigue in healthy, normally-sleeping young adults.

OBJECTIVE: To assess the effects of one week of sleep extension on mood, fatigue and subjective sleepiness in normal-sleeping young adults. METHODS: Twenty-seven adults (age 24.4±5.4 years, 11 female) participated. At-home baseline sleep/wake patterns were recorded with wrist actigraphy for 14 days. This was followed by two nights of in-lab baseline sleep with 8 hours time in bed (TIB), then 7 nights with TIB extended to 10 hours (2100-0700 hours). Fatigue, mood, and sleepiness were assessed following the 2nd and 9th nights of in-laboratory sleep (i.e., 2 nights with 8hTIB and 7 nights with 10 hours TIB, respectively) using the Automated Neuropsychological Assessment Metric and Karolinska Sleepiness Scale. Paired t-tests were used to compare mood, fatigue, and sleepiness ratings between conditions. RESULTS: At-home wrist actigraphy revealed a mean nightly total sleep time (TST) of 7.53 +/- 0.88 hours of sleep per night. Mean in-lab baseline sleep duration (7.76 +/- 0.59) did not differ from at-home sleep. However, during sleep extension, mean TST was 9.36 +/- 0.37 hours per night, significantly more than during the in-lab baseline (p < .001). Following sleep extension, fatigue ratings were significantly reduced, relative to baseline (p = .03). However, sleep extension had no other significant effects on subjective ratings of mood or sleepiness. CONCLUSIONS: Sleep extension resulted in reduced fatigue in healthy, normal-sleeping young adults, although subjective sleepiness and mood were not improved. Implications include the possibility that (a) the effects of sleep extension on various aspects of mood depend upon the extent to which those aspects of mood are made salient by the study design and methodology; and (b) sleep extension may prove beneficial to fatigue-related conditions such as "burnout."

Effects of sleep extension on cognitive/motor performance and motivation in military tactical athletes.

OBJECTIVE: Investigate the immediate and residual impacts of sleep extension in tactical athletes. METHODS: A randomized controlled trial (Sleep extension = EXT vs Control = CON) was conducted on 50 (EXT: 20.12 ± 2.01 years vs CON: 19.76 ± 1.09 years) tactical athletes enrolled in the Reserve Officers' Training Corps (ROTC). Participants wore actigraphs for 15 consecutive nights and completed a cognitive/motor battery after seven habitual sleep nights, after four sleep extension nights, and after the resumption of habitual sleep for four nights. The CON group remained on habitual sleep schedules for the entire study. RESULTS: During the intervention, the EXT group significantly increased mean sleep time (1.36 ± 0.71 h, p < 0.001). After sleep extension, there were significant between-group differences on the mean score change since baseline in Psychomotor Vigilance Test (PVT) reaction time (p = 0.026), Trail Making Test (TMT) - B time (p = 0.027), standing broad jump (SBJ) distance (p < 0.001), and motivation levels [to perform the cognitive tasks (p = 0.003) and the SBJ (p = 0.009)]; with the EXT group showing a greater enhancement in performance/motivation. After resuming habitual sleep schedules, significant between-group differences on the mean score change since baseline persisted on SBJ distance (p = 0.001) and motivation to perform the SBJ (p = 0.035), with the EXT showing greater enhancement in performance/motivation. CONCLUSION: Increasing sleep duration in military tactical athletes resulted in immediate performance benefits in psychomotor vigilance, executive functioning, standing broad jump distance, and motivation levels. Benefits on motor performance were evident four days after resumption of habitual sleep schedules. Military tactical athletes aiming to optimize their overall performance should consider the impact of longer sleep durations when feasible.

Optimizing Sleep in the Military: Challenges and Opportunities.

Historically, scientific knowledge gaps-including a lack of information regarding the minimum amount of sleep needed to sustain nominally adequate, militarily relevant performance, and nescience of the potential impact of chronic sleep restriction on health and psychological well-being-have hindered decision-making vis-à-vis sleep/alertness management in operational environments. However, against a backdrop of increasing awareness of the importance of sleep for sustaining both performance and health, military researchers are currently doing the following: (1) developing a comprehensive, individualized sleep/alertness management system to optimize the general effectiveness of military personnel (ie, without regard to the potential relationship between sleep and specific aspects of military performance, thus sidestepping what has historically been an impediment to development of such a system); and (2) investigating the prevalence, potentially unique etiology (eg, resulting from the interaction of long-term exposure to combat-related stressors and sleep restriction), and treatment of sleep disorders and comorbidities in the military population.

2B-Alert App: A mobile application for real-time individualized prediction of alertness.

Knowing how an individual responds to sleep deprivation is a requirement for developing personalized fatigue management strategies. Here we describe and validate the 2B-Alert App, the first mobile application that progressively learns an individual's trait-like response to sleep deprivation in real time, to generate increasingly more accurate individualized predictions of alertness. We incorporated a Bayesian learning algorithm within the validated Unified Model of Performance to automatically and gradually adapt the model parameters to an individual after each psychomotor vigilance test. We implemented the resulting model and the psychomotor vigilance test as a smartphone application (2B-Alert App), and prospectively validated its performance in a 62-hr total sleep deprivation study in which 21 participants used the app to perform psychomotor vigilance tests every 3 hr and obtain real-time individualized predictions after each test. The temporal profiles of reaction times on the app-conducted psychomotor vigilance tests were well correlated with and as sensitive as those obtained with a previously characterized psychomotor vigilance test device. The app progressively learned each individual's trait-like response to sleep deprivation throughout the study, yielding increasingly more accurate predictions of alertness for the last 24 hr of total sleep deprivation as the number of psychomotor vigilance tests increased. After only 12 psychomotor vigilance tests, the accuracy of the model predictions was comparable to the peak accuracy obtained using all psychomotor vigilance tests. With the ability to make real-time individualized predictions of the effects of sleep deprivation on future alertness, the 2B-Alert App can be used to tailor personalized fatigue management strategies, facilitating self-management of alertness and safety in operational and non-operational settings.

Sleep extension reduces pain sensitivity.

INTRODUCTION: Insufficient sleep increases pain sensitivity in healthy individuals. Additionally, extending sleep (eg, increasing nocturnal sleep time or adding a mid-day nap) has been shown to restore pain sensitivity to baseline levels in sleep deprived/restricted individuals. Whether sleep extension can reduce pain sensitivity beyond baseline levels in non-sleep restricted/deprived individuals remains unknown. METHODS: In a sample of 27 healthy, pain-free, normally-sleeping individuals (17 males, mean age ∼24 yrs), we examined the impact of five nights of sleep extension on pain sensitivity. Pain threshold (elapsed time until the participant reported pain) and pain tolerance (total time the participant kept the hand submerged in the cold water) were measured using the Cold Pressor Task. Furthermore, we assessed the extent to which self-reported sleep amount in relation to the minimal subjective sleep requirement for adequate performance (sleep credit) was associated with pain sensitivity changes. RESULTS: On average individuals slept almost 2 extra hours per night. Our results indicate that sleep extension increases pain tolerance beyond baseline levels. However, sleep extension did not impact pain threshold. We also found that individuals with a smaller sleep credit (ie, those who habitually obtain less sleep than they feel they need) experienced greater increases in pain tolerance after extending sleep. CONCLUSIONS: The present findings suggest that sleep extension may increase pain tolerance but not pain threshold in healthy individuals who normally sleep the recommended amount. Our findings also support the idea that sleep credit may be a strong indicator of sleep debt in the context of pain sensitivity.

Rates of cerebral protein synthesis in primary visual cortex during sleep-dependent memory consolidation, a study in human subjects.

If protein synthesis during sleep is required for sleep-dependent memory consolidation, we might expect rates of cerebral protein synthesis (rCPS) to increase during sleep in the local brain circuits that support performance on a particular task following training on that task. To measure circuit-specific brain protein synthesis during a daytime nap opportunity, we used the L-[1-(11)C]leucine positron emission tomography (PET) method with simultaneous polysomnography. We trained subjects on the visual texture discrimination task (TDT). This was followed by a nap opportunity during the PET scan, and we retested them later in the day after the scan. The TDT is considered retinotopically specific, so we hypothesized that higher rCPS in primary visual cortex would be observed in the trained hemisphere compared to the untrained hemisphere in subjects who were randomized to a sleep condition. Our results indicate that the changes in rCPS in primary visual cortex depended on whether subjects were in the wakefulness or sleep condition but were independent of the side of the visual field trained. That is, only in the subjects randomized to sleep, rCPS in the right primary visual cortex was higher than the left regardless of side trained. Other brain regions examined were not so affected. In the subjects who slept, performance on the TDT improved similarly regardless of the side trained. Results indicate a regionally selective and sleep-dependent effect that occurs with improved performance on the TDT.

Caffeine dosing strategies to optimize alertness during sleep loss.

Sleep loss, which affects about one-third of the US population, can severely impair physical and neurobehavioural performance. Although caffeine, the most widely used stimulant in the world, can mitigate these effects, currently there are no tools to guide the timing and amount of caffeine consumption to optimize its benefits. In this work, we provide an optimization algorithm, suited for mobile computing platforms, to determine when and how much caffeine to consume, so as to safely maximize neurobehavioural performance at the desired time of the day, under any sleep-loss condition. The algorithm is based on our previously validated Unified Model of Performance, which predicts the effect of caffeine consumption on a psychomotor vigilance task. We assessed the algorithm by comparing the caffeine-dosing strategies (timing and amount) it identified with the dosing strategies used in four experimental studies, involving total and partial sleep loss. Through computer simulations, we showed that the algorithm yielded caffeine-dosing strategies that enhanced performance of the predicted psychomotor vigilance task by up to 64% while using the same total amount of caffeine as in the original studies. In addition, the algorithm identified strategies that resulted in equivalent performance to that in the experimental studies while reducing caffeine consumption by up to 65%. Our work provides the first quantitative caffeine optimization tool for designing effective strategies to maximize neurobehavioural performance and to avoid excessive caffeine consumption during any arbitrary sleep-loss condition.

A systematic review and meta-analysis of sleep architecture and chronic traumatic brain injury.

Sleep quality appears to be altered by traumatic brain injury (TBI). However, whether persistent post-injury changes in sleep architecture are present is unknown and relatively unexplored. We conducted a systematic review and meta-analysis to assess the extent to which chronic TBI (>6 months since injury) is characterized by changes to sleep architecture. We also explored the relationship between sleep architecture and TBI severity. In the fourteen included studies, sleep was assessed with at least one night of polysomnography in both chronic TBI participants and controls. Statistical analyses, performed using Comprehensive Meta-Analysis software, revealed that chronic TBI is characterized by relatively increased slow wave sleep (SWS). A meta-regression showed moderate-severe TBI is associated with elevated SWS, reduced stage 2, and reduced sleep efficiency. In contrast, mild TBI was not associated with any significant alteration of sleep architecture. The present findings are consistent with the hypothesis that increased SWS after moderate-severe TBI reflects post-injury cortical reorganization and restructuring. Suggestions for future research are discussed, including adoption of common data elements in future studies to facilitate cross-study comparability, reliability, and replicability, thereby increasing the likelihood that meaningful sleep (and other) biomarkers of TBI will be identified.