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Awareness of the consequences of sleep loss and its implications for public health and safety is increasing. Sleep loss has been shown to generally impair the entire spectrum of mental abilities, ranging from simple psychomotor performance to executive mental functions. Sleep loss may also impact metabolism in a manner that contributes to obesity and its attendant health consequences. Although objective measures of alertness and performance remain degraded, individuals subjectively habituate to chronic partial sleep loss (eg, sleep restriction), and recovery from this type of sleep loss is slow, factors that may help to explain the observation that many individuals in the general population are chronically sleep restricted. Individual differences in habitual sleep duration appear to be a trait-like characteristic that is determined by several factors, including genetic polymorphisms. [ABSTRACT FROM AUTHOR]

Rationale: Caffeine is widely used as a countermeasure against neurobehavioral impairment during sleep deprivation. However, little is known about the pharmacodynamic profile of caffeine administered repeatedly during total sleep deprivation., Objectives: To investigate the effects of repeated caffeine dosing on neurobehavioral performance during sleep deprivation, we conducted a laboratory-based, randomized, double-blind, placebo-controlled, crossover, multi-dose study of repeated caffeine administration during 48 h of sleep deprivation. Twelve healthy adults (mean age 27.4 years, six women) completed an 18-consecutive-day in-laboratory study consisting of three 48 h total sleep deprivation periods separated by 3-day recovery periods. During each sleep deprivation period, subjects were awakened at 07:00 and administered caffeine gum (0, 200, or 300 mg) at 6, 18, 30, and 42 h of wakefulness. The Psychomotor Vigilance Test and Karolinska Sleepiness Scale were administered every 2 h., Results: The 200 and 300 mg doses of caffeine mitigated neurobehavioral impairment across the sleep deprivation period, approaching two-fold performance improvements relative to placebo immediately after the nighttime gum administrations. No substantive differences were noted between the 200 mg and 300 mg caffeine doses, and adverse effects were minimal., Conclusions: The neurobehavioral effects of repeated caffeine dosing during sleep deprivation were most evident during the circadian alertness trough (i.e., at night). The difference between the 200 mg and 300 mg doses, in terms of the mitigation of performance impairment, was small. Neither caffeine dose fully restored performance to well-rested levels. These findings inform the development of biomathematical models that more accurately account for the time of day and sleep pressure-dependent effects of caffeine on neurobehavioral performance during sleep loss.

Study Objectives: Computational tools that predict the effects of daily sleep/wake amounts on neurobehavioral performance are critical components of fatigue management systems, allowing for the identification of periods during which individuals are at increased risk for performance errors. However, none of the existing computational tools is publicly available, and the commercially available tools do not account for the beneficial effects of caffeine on performance, limiting their practical utility. Here, we introduce 2B-Alert Web, an open-access tool for predicting neurobehavioral performance, which accounts for the effects of sleep/wake schedules, time of day, and caffeine consumption, while incorporating the latest scientific findings in sleep restriction, sleep extension, and recovery sleep., Methods: We combined our validated Unified Model of Performance and our validated caffeine model to form a single, integrated modeling framework instantiated as a Web-enabled tool. 2B-Alert Web allows users to input daily sleep/wake schedules and caffeine consumption (dosage and time) to obtain group-average predictions of neurobehavioral performance based on psychomotor vigilance tasks. 2B-Alert Web is accessible at: https://2b-alert-web.bhsai.org., Results: The 2B-Alert Web tool allows users to obtain predictions for mean response time, mean reciprocal response time, and number of lapses. The graphing tool allows for simultaneous display of up to seven different sleep/wake and caffeine schedules. The schedules and corresponding predicted outputs can be saved as a Microsoft Excel file; the corresponding plots can be saved as an image file. The schedules and predictions are erased when the user logs off, thereby maintaining privacy and confidentiality., Conclusions: The publicly accessible 2B-Alert Web tool is available for operators, schedulers, and neurobehavioral scientists as well as the general public to determine the impact of any given sleep/wake schedule, caffeine consumption, and time of day on performance of a group of individuals. This evidence-based tool can be used as a decision aid to design effective work schedules, guide the design of future sleep restriction and caffeine studies, and increase public awareness of the effects of sleep amounts, time of day, and caffeine on alertness., (© 2016 Associated Professional Sleep Societies, LLC.)

Study Objectives: Existing mathematical models of neurobehavioral performance cannot predict the beneficial effects of caffeine across the spectrum of sleep loss conditions, limiting their practical utility. Here, we closed this research gap by integrating a model of caffeine effects with the recently validated unified model of performance (UMP) into a single, unified modeling framework. We then assessed the accuracy of this new UMP in predicting performance across multiple studies., Methods: We hypothesized that the pharmacodynamics of caffeine vary similarly during both wakefulness and sleep, and that caffeine has a multiplicative effect on performance. Accordingly, to represent the effects of caffeine in the UMP, we multiplied a dose-dependent caffeine factor (which accounts for the pharmacokinetics and pharmacodynamics of caffeine) to the performance estimated in the absence of caffeine. We assessed the UMP predictions in 14 distinct laboratory- and field-study conditions, including 7 different sleep-loss schedules (from 5 h of sleep per night to continuous sleep loss for 85 h) and 6 different caffeine doses (from placebo to repeated 200 mg doses to a single dose of 600 mg)., Results: The UMP accurately predicted group-average psychomotor vigilance task performance data across the different sleep loss and caffeine conditions (6% < error < 27%), yielding greater accuracy for mild and moderate sleep loss conditions than for more severe cases. Overall, accounting for the effects of caffeine resulted in improved predictions (after caffeine consumption) by up to 70%., Conclusions: The UMP provides the first comprehensive tool for accurate selection of combinations of sleep schedules and caffeine countermeasure strategies to optimize neurobehavioral performance., (© 2016 Associated Professional Sleep Societies, LLC.)

Study Objectives: Historically, mathematical models of human neurobehavioral performance developed on data from one sleep study were limited to predicting performance in similar studies, restricting their practical utility. We recently developed a unified model of performance (UMP) to predict the effects of the continuum of sleep loss-from chronic sleep restriction (CSR) to total sleep deprivation (TSD) challenges-and validated it using data from two studies of one laboratory. Here, we significantly extended this effort by validating the UMP predictions across a wide range of sleep/wake schedules from different studies and laboratories., Methods: We developed the UMP on psychomotor vigilance task (PVT) lapse data from one study encompassing four different CSR conditions (7 d of 3, 5, 7, and 9 h of sleep/night), and predicted performance in five other studies (from four laboratories), including different combinations of TSD (40 to 88 h), CSR (2 to 6 h of sleep/night), control (8 to 10 h of sleep/night), and nap (nocturnal and diurnal) schedules., Results: The UMP accurately predicted PVT performance trends across 14 different sleep/wake conditions, yielding average prediction errors between 7% and 36%, with the predictions lying within 2 standard errors of the measured data 87% of the time. In addition, the UMP accurately predicted performance impairment (average error of 15%) for schedules (TSD and naps) not used in model development., Conclusions: The unified model of performance can be used as a tool to help design sleep/wake schedules to optimize the extent and duration of neurobehavioral performance and to accelerate recovery after sleep loss., (© 2016 Associated Professional Sleep Societies, LLC.)

Humans display a trait-like response to sleep loss. However, it is not known whether this trait-like response can be captured by a mathematical model from only one sleep-loss condition to facilitate neurobehavioural performance prediction of the same individual during a different sleep-loss condition. In this paper, we investigated the extent to which the recently developed unified mathematical model of performance (UMP) captured such trait-like features for different sleep-loss conditions. We used the UMP to develop two sets of individual-specific models for 15 healthy adults who underwent two different sleep-loss challenges (order counterbalanced; separated by 2-4 weeks): (i) 64 h of total sleep deprivation (TSD) and (ii) chronic sleep restriction (CSR) of 7 days of 3 h nightly time in bed. We then quantified the extent to which models developed using psychomotor vigilance task data under TSD predicted performance data under CSR, and vice versa. The results showed that the models customized to an individual under one sleep-loss condition accurately predicted performance of the same individual under the other condition, yielding, on average, up to 50% improvement over non-individualized, group-average model predictions. This finding supports the notion that the UMP captures an individual's trait-like response to different sleep-loss conditions., (© 2014 European Sleep Research Society.)

Caffeine is the most widely consumed stimulant to counter sleep-loss effects. While the pharmacokinetics of caffeine in the body is well-understood, its alertness-restoring effects are still not well characterized. In fact, mathematical models capable of predicting the effects of varying doses of caffeine on objective measures of vigilance are not available. In this paper, we describe a phenomenological model of the dose-dependent effects of caffeine on psychomotor vigilance task (PVT) performance of sleep-deprived subjects. We used the two-process model of sleep regulation to quantify performance during sleep loss in the absence of caffeine and a dose-dependent multiplier factor derived from the Hill equation to model the effects of single and repeated caffeine doses. We developed and validated the model fits and predictions on PVT lapse (number of reaction times exceeding 500 ms) data from two separate laboratory studies. At the population-average level, the model captured the effects of a range of caffeine doses (50-300 mg), yielding up to a 90% improvement over the two-process model. Individual-specific caffeine models, on average, predicted the effects up to 23% better than population-average caffeine models. The proposed model serves as a useful tool for predicting the dose-dependent effects of caffeine on the PVT performance of sleep-deprived subjects and, therefore, can be used for determining caffeine doses that optimize the timing and duration of peak performance., (Published by Elsevier Ltd.)

Whether caffeine and energy drink consumption presents a critical emerging health problem is not currently known. Available evidence suggests that energy drink consumption represents a change in the ways in which individuals in the United States consume caffeine but that the amount of caffeine consumed daily has not appreciably increased. In the present review, the question of whether Americans are sleep deprived (a potential reason for using caffeine) is briefly explored. Reported rates of daily caffeine consumption (based on beverage formulation) and data obtained from both civilian and military populations in the United States are examined, the efficacy of ingredients other than caffeine in energy drinks is discussed, and the safety and side effects of caffeine are addressed, including whether evidence supports the contention that excessive caffeine/energy drink consumption induces risky behavior. The available evidence suggests that the main legitimate concern regarding caffeine and energy drink use is the potential negative impact on sleep but that, otherwise, there is no cause for concern regarding caffeine use in the general population., (Published 2014. This article is a U.S. Government work and is in the public domain in the USA.)

Using a personal computer (PC) for simple visual reaction time testing is advantageous because of the relatively low hardware cost, user familiarity, and the relative ease of software development for specific neurobehavioral testing protocols. However, general-purpose computers are not designed with the millisecond-level accuracy of operation required for such applications. Software that does not control for the various sources of delay may return reaction time values that are substantially different from the true reaction times. We have developed and characterized a freely available system for PC-based simple visual reaction time testing that is analogous to the widely used psychomotor vigilance task (PVT). In addition, we have integrated individualized prediction algorithms for near-real-time neurobehavioral performance prediction. We characterized the precision and accuracy with which the system as a whole measures reaction times on a wide range of computer hardware configurations, comparing its performance with that of the "gold standard" PVT-192 device. We showed that the system is capable of measuring reaction times with an average delay of less than 10 ms, a margin of error that is comparable to that of the gold standard. The most critical aspect of hardware selection is the type of mouse used for response detection, with gaming mice showing a significant advantage over standard ones. The software is free to download from http://bhsai.org/downloads/pc-pvt/ .

It has long been known that short-term (days) insufficient sleep causes decrements in mental effectiveness that put individuals at increased risk of committing errors and causing accidents. More recently, it has been discovered that chronic poor sleep (over years) is associated with a variety of negative health outcomes (metabolic syndrome, obesity, degraded behavioral health). Implementing an effective sleep health program is, therefore, in the best interests of active duty personnel and their families both in the short- and long-term. Like managing physical activity or nutrition, effectively managing sleep health comes with its unique set of challenges arising from the fact that individuals who routinely do not obtain sufficient sleep are generally desensitized to feeling sleepy and are poor at judging their own performance capabilities--and individuals cannot be compelled to sleep. For these reasons, an optimally effective sleep health program requires 3 components: (1) a rigorous, evidence-based sleep education component to impart actionable knowledge about optimal sleep amounts, healthy sleep behaviors, the known benefits of sleep, the short- and long-term consequences of insufficient sleep, and to dispel myths about sleep; (2) a nonintrusive device that objectively and accurately measures sleep to empower the individual to track his/her own sleep/wake habits; and (3) a meaningful, actionable metric reflecting sleep/wake impact on daily effectiveness so that the individual sees the consequences of his/her sleep behavior and, therefore, can make informed sleep health choices.

Performance prediction models based on the classical two-process model of sleep regulation are reasonably effective at predicting alertness and neurocognitive performance during total sleep deprivation (TSD). However, during sleep restriction (partial sleep loss) performance predictions based on such models have been found to be less accurate. Because most modern operational environments are predominantly characterized by chronic sleep restriction (CSR) rather than by episodic TSD, the practical utility of this class of models has been limited. To better quantify performance during both CSR and TSD, we developed a unified mathematical model that incorporates extant sleep debt as a function of a known sleep/wake history, with recent history exerting greater influence. This incorporation of sleep/wake history into the classical two-process model captures an individual's capacity to recover during sleep as a function of sleep debt and naturally bridges the continuum from CSR to TSD by reducing to the classical two-process model in the case of TSD. We validated the proposed unified model using psychomotor vigilance task data from three prior studies involving TSD, CSR, and sleep extension. We compared and contrasted the fits, within-study predictions, and across-study predictions from the unified model against predictions generated by two previously published models, and found that the unified model more accurately represented multiple experimental studies and consistently predicted sleep restriction scenarios better than the existing models. In addition, we found that the model parameters obtained by fitting TSD data could be used to predict performance in other sleep restriction scenarios for the same study populations, and vice versa. Furthermore, this model better accounted for the relatively slow recovery process that is known to characterize CSR, as well as the enhanced performance that has been shown to result from sleep banking., (Published by Elsevier Ltd.)

The objective of the study was to determine whether ADORA2A or PER3 polymorphisms contribute to individual responsivity to sleep restriction. Nineteen healthy adults (ages 18-39, 11 males, 8 females) underwent sleep restriction (SR) which consisted of seven nights of 3 h time in bed (TIB) (04:00-07:00). SR was preceded by seven in-laboratory nights of 10 h TIB (21:00-07:00) and followed by three nights of 8 h TIB (23:00-07:00). Volunteers underwent psychomotor vigilance, objective alertness, and subjective sleepiness assessments throughout. Volunteers were genotyped for the PER3 VNTR polymorphism (PER3(4/4) n = 7; PER3(4/5) n = 10; PER3(5/5) n = 2) and the ADORA2A c.1083T>C polymorphism, (ADORA2A(C) (/T) n = 9; ADORA2A(T) (/T) n = 9; ADORA2A(C) (/C) n = 1) using polymerase chain reaction (PCR). Separate mixed-model anovas were used to assess contributions of ADORA2A and PER3 polymorphisms. Results showed that PER3(4/4) and ADORA2A(C/T) individuals expressed greater behavioral resiliency to SR compared to PER(4/5) and ADORA2A(T/T) individuals. Our findings contrast with previously reported non-significant effects for the PER3 polymorphism under a less challenging sleep restriction regimen (4 h TIB per night for five nights). We conclude that PER3 and ADORA2A polymorphisms become more behaviorally salient with increasing severity and/or duration of sleep restriction (based on psychomotor vigilance). Given the small sample size these results are preliminary and require replication., (© 2012 European Sleep Research Society.)

Rationale: While caffeine is widely used as a countermeasure to sleep loss, mathematical models are lacking., Objective: Develop a biomathematical model for the performance-restoring effects of caffeine in sleep-deprived subjects., Methods: We hypothesized that caffeine has a multiplicative effect on performance during sleep loss. Accordingly, we first used a phenomenological two-process model of sleep regulation to estimate performance in the absence of caffeine, and then multiplied a caffeine-effect factor, which relates the pharmacokinetic-pharmacodynamic effects through the Hill equation, to estimate the performance-restoring effects of caffeine., Results: We validated the model on psychomotor vigilance test data from two studies involving 12 subjects each: (1) single caffeine dose of 600mg after 64.5h of wakefulness and (2) repeated doses of 200mg after 20, 22, and 24h of wakefulness. Individualized caffeine models produced overall errors that were 19% and 42% lower than their population-average counterparts for the two studies. Had we not accounted for the effects of caffeine, the individualized model errors would have been 117% and 201% larger, respectively., Conclusions: The presented model captured the performance-enhancing effects of caffeine for most subjects in the single- and repeated-dose studies, suggesting that the proposed multiplicative factor is a feasible solution., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Naps are an effective strategy for maintaining alertness and cognitive performance; however, upon abrupt wakening from naps, sleep inertia (temporary performance degradation) may ensue. In the present study, attenuation of post-nap sleep inertia was attempted by administration of caffeine gum. Using a double-blind, placebo-controlled crossover design, 15 healthy, non-smoking adults were awakened at 1 hr. and again at 6 hr. after lights out (0100 and 0600, respectively) and were immediately administered a gum pellet containing 100 mg of caffeine or placebo. A 5-min. psychomotor vigilance task was administered at 0 min., 6 min., 12 min., and 18 min. post-awakening. At 0100, response speed with caffeine was significantly better at 12 min. and 18 min. post-awakening compared to placebo; at 0600, caffeine's effects were evident at 18 min. post-awakening. Caffeinated gum is a viable means of rapidly attenuating sleep inertia, suggesting that the adenosine receptor system is involved in sleep maintenance.

We have developed a new psychomotor vigilance test (PVT) metric for quantifying the effects of sleep loss on performance impairment. The new metric quantifies performance impairment by estimating the probability density of response times (RTs) in a PVT session, and then considering deviations of the density relative to that of a baseline-session density. Results from a controlled laboratory study involving 12 healthy adults subjected to 85 h of extended wakefulness, followed by 12 h of recovery sleep, revealed that the group performance variability based on the new metric remained relatively uniform throughout wakefulness. In contrast, the variability of PVT lapses, mean RT, median RT and (to a lesser extent) mean speed showed strong time-of-day effects, with the PVT lapse variability changing with time of day depending on the selected threshold. Our analysis suggests that the new metric captures more effectively the homeostatic and circadian process underlying sleep regulation than the other metrics, both directly in terms of larger effect sizes (4-61% larger) and indirectly through improved fits to the two-process model (9-67% larger coefficient of determination). Although the trend of the mean speed results followed those of the new metric, we found that mean speed yields significantly smaller (∼50%) intersubject performance variance than the other metrics. Based on these findings, and that the new metric considers performance changes based on the entire set of responses relative to a baseline, we conclude that it provides a number of potential advantages over the traditional PVT metrics., (© 2012 European Sleep Research Society.)

Objective: To determine the extent to which individual differences in vulnerability to total sleep deprivation also reflect individual differences in vulnerability to multiple nights of sleep restriction., Design: Two sleep loss conditions (order counterbalanced) separated by 2 to 4 weeks: (a) total sleep deprivation (TSD) of 2 nights (63 h continuous wakefulness); (b) sleep restriction (SR) of 7 nights of 3 h nightly time in bed (TIB). Both conditions were preceded by 7 in-laboratory nights with 10 h nightly TIB; and followed by 3 recovery nights with 8 h nightly TIB. Measures of cognitive performance (psychomotor vigilance, working memory [1-Back], and mathematical processing), objective alertness, subjective sleepiness, and mood were obtained at regular intervals under both conditions. Intra-class correlation coefficients (ICC) were computed using outcome metrics averaged over the last day (08:00-20:00) of TSD and SR., Setting: Residential sleep/performance testing facility., Participants: Nineteen healthy adults (ages 18-39; 11 males, 8 females)., Interventions: 2 nights of TSD and 7 nights SR (3 h nightly TIB)., Results: volunteers who displayed greater vulnerability to TSD displayed greater vulnerability to SR on cognitive performance tasks (ICC: PVT lapses = 0.89; PVT speed = 0.86; 1-Back = 0.88; mathematical processing = 0.68, Ps < 0.05). In addition, trait-like responsivity to TSD/SR was found for mood variables vigor (ICC = 0.91), fatigue (ICC = 0.73), and happiness (ICC = 0.85) (all Ps < 0.05)., Conclusion: Resilience to sleep loss is a trait-like characteristic that reflects an individual's ability to maintain performance during both types of sleep loss (SR and TSD). Whether the findings extend to sleep schedules other than those investigated here (63 h of TSD and 7 nights of 3 h nightly TIB) will be the focus of future studies.

Individual differences in vulnerability to sleep loss can be considerable, and thus, recent efforts have focused on developing individualized models for predicting the effects of sleep loss on performance. Individualized models constructed using a Bayesian formulation, which combines an individual's available performance data with a priori performance predictions from a group-average model, typically need at least 40 h of individual data before showing significant improvement over the group-average model predictions. Here, we improve upon the basic Bayesian formulation for developing individualized models by observing that individuals may be classified into three sleep-loss phenotypes: resilient, average, and vulnerable. For each phenotype, we developed a phenotype-specific group-average model and used these models to identify each individual's phenotype. We then used the phenotype-specific models within the Bayesian formulation to make individualized predictions. Results on psychomotor vigilance test data from 48 individuals indicated that, on average, ∼85% of individual phenotypes were accurately identified within 30 h of wakefulness. The percentage improvement of the proposed approach in 10-h-ahead predictions was 16% for resilient subjects and 6% for vulnerable subjects. The trade-off for these improvements was a slight decrease in prediction accuracy for average subjects.

Introduction: U.S. military troops deploying to war zones are currently administered the Automated Neuropsychological Assessment Metrics (ANAM4) Traumatic Brain Injury (TBI) Battery to establish individual neurocognitive performance baselines. In part, the utility of the ANAM4 TBI Battery baseline measurement depends on test-retest reliability of this instrument. The purpose of this report was to evaluate performance following multiple administrations of the ANAM4 TBI Battery: does performance in a repeated measures paradigm constitute a stable, interpretable indication of baseline neurocognitive ability?, Methods: The data presented here are from the ANAM4 TBI Battery administered four times to a group of U.S. Marines in Study 1 and eight times to a group of New Zealand Defence Force personnel in Study 2., Results: The results show practice effect in five of six performance subtests in both Study 1 and Study 2., Discussion: Results are consistent with expectations that multiple test sessions are required to reach stable performance on some computerized tasks. These results have implications for taking ANAM4 TBI Battery practice effects into account in test administration and in data interpretation.

The aim of the present study was to examine if sleep amount prior to sleep restriction mediated subsequent task acquisition on serial addition/subtraction and reaction time (RT) sub-tasks of the Automated Neuropsychological Assessment Metric. Eleven males and 13 females [mean (SD) age = 25 (6.5) years] were assigned to either an Extended [10 h time in bed (TIB)] (n = 12) or Habitual [Mean (SD) = 7.09 (0.7)] (n = 12) sleep group for 1 week followed by one baseline night, seven sleep restriction nights (3 h TIB) and five recovery nights (8 h TIB). Throughout baseline, restriction and recovery, mathematical and serial RT tasks were administered hourly each day (08:00-18:00 h). Math and serial RT throughput for each task (speed x accuracy product) was analysed using a mixed-model anova with fixed effects for sleep group, day and time-of-day followed by post hoc t-tests (Bonferroni correction). Math throughput improved for both groups during sleep restriction, but more so compared with baseline for the prior sleep Extended group versus the Habitual group during recovery. In sum, 1 week of sleep extension improved resilience during subsequent sleep restriction and facilitated task acquisition during recovery, demonstrating that nightly sleep duration exerts long-term (days, weeks) effects.

We present a new method for developing individualized biomathematical models that predict performance impairment for individuals restricted to total sleep loss. The underlying formulation is based on the two-process model of sleep regulation, which has been extensively used to develop group-average models. However, in the proposed method, the parameters of the two-process model are systematically adjusted to account for an individual's uncertain initial state and unknown trait characteristics, resulting in individual-specific performance prediction models. The method establishes the initial estimates of the model parameters using a set of past performance observations, after which the parameters are adjusted as each new observation becomes available. Moreover, by transforming the nonlinear optimization problem of finding the best estimates of the two-process model parameters into a set of linear optimization problems, the proposed method yields unique parameter estimates. Two distinct data sets are used to evaluate the proposed method. Results of simulated data (with superimposed noise) show that the model parameters asymptotically converge to their true values and the model prediction accuracy improves as the number of performance observations increases and the amount of noise in the data decreases. Results of a laboratory study (82 h of total sleep loss), for three sleep-loss phenotypes, suggest that individualized models are consistently more accurate than group-average models, yielding as much as a threefold reduction in prediction errors. In addition, we show that the two-process model of sleep regulation is capable of representing performance data only when the proposed individualized model is used.

Introduction: Round-the-clock operations in both military and civilian sectors have increased the need for alertness- and performance-maintaining strategies. The potential performance and objective alertness-enhancing effects of CX717 (a novel cognitive enhancer currently being tested in Phase II clinical trials) were evaluated using a simulated night shift work paradigm., Methods: In this randomized, double-blind, placebo-controlled, parallel groups design, 48 volunteers underwent 4 consecutive nights of simulated shift work. Each "shift" consisted of the following: at approximately 2145 (just prior to the start of each simulated night shift), volunteers ingested a single oral dose of CX717 200 mg, CX717 400 mg, CX717 1000 mg, or placebo (N = 12 per drug dosage). Performance, alertness, mood, and symptoms were then assessed from 2300 to 0700, followed by a polysomnographically monitored daytime sleep period from 0800 to 1200., Results: Performance and alertness significantly degraded across the simulated night shifts (P < 0.05). None of the dosages of CX717 reversed these effects (P > 0.05). CX717 exerted some effects on daytime sleep, most notably reduction of slow-wave sleep time (P < 0.05). CX71 7 caused very few side effects and none of those were serious or unexpected., Discussion and Conclusions: At the doses tested, CX717 was not effective for reversing performance and alertness deficits associated with night shift work. Further work evaluating higher doses of CX717 may be warranted, as are studies in which CX717 effects are explored under other conditions (e.g., Alzheimer's dementia, attention deficit disorder).

The effect of sleep loss on reaction time (RT) performance varies as a function of age, with RTs of older subjects typically showing less decrement (relative to rested baseline) than those of younger subjects. In the current paper, we examined the nature of this relationship in a 7-day sleep restriction study. The number of repeated measures made it possible to model both intra-individual trajectories over days and individual differences in these trajectories. Results revealed (a) consistent individual differences in RT patterns over time after controlling for experimental design effects; (b) less cumulative RT decline among older individuals regardless of the degree of sleep restriction; and (c) consistent individual variability in performance patterns even after accounting for the effects of age.

Sleep deprivation reduces regional cerebral metabolism within the prefrontal cortex, the brain region most responsible for higher-order cognitive processes, including judgment and decision making. Accordingly, we hypothesized that two nights of sleep loss would impair decision making quality and lead to increased risk-taking behavior on the Iowa Gambling Task (IGT), which mimics real-world decision making under conditions of uncertainty. Thirty-four healthy participants completed the IGT at rested baseline and again following 49.5 h of sleep deprivation. At baseline, volunteers performed in a manner similar to that seen in most samples of healthy normal individuals, rapidly learning to avoid high-risk decks and selecting more frequently from advantageous low-risk decks as the game progressed. After sleep loss, however, volunteers showed a strikingly different pattern of performance. Relative to rested baseline, sleep-deprived individuals tended to choose more frequently from risky decks as the game progressed, a pattern similar to, though less severe than, previously published reports of patients with lesions to the ventromedial prefrontal cortex. Although risky decision making was not related to participant age when tested at rested baseline, age was negatively correlated with advantageous decision making on the IGT, when tested following sleep deprivation (i.e. older subjects made more risky choices). These findings suggest that cognitive functions known to be mediated by the ventromedial prefrontal cortex, including decision making under conditions of uncertainty, may be particularly vulnerable to sleep loss and that this vulnerability may become more pronounced with increased age.

The performance- and alertness-sustaining/restoring effects of modafinil during sleep deprivation in normal, healthy adults were reviewed. Results indicate that modafinil is efficacious for sustaining/restoring objective performance and alertness during sleep deprivation with few adverse effects. At appropriate dosages, modafinil restores performance and alertness to non-sleep deprived levels. Modafinil also impairs post-sleep deprivation recovery sleep, but from the few studies available addressing this issue, it is unclear whether these sleep impairments translate into post-sleep performance impairments. Further research is needed to determine whether modafinil restores performance on simple cognitive tasks only or whether modafinil additionally restores executive functions (e.g., abstract thought, critical reasoning, planning, decision-making, situational awareness, and effective judgment) which are critical in most modern operational settings. In addition, studies are needed to determine whether modafinil use during sleep deprivation is preferable to that of other available controlled stimulants (such as dextroamphetamine) or non-controlled stimulants (such as caffeine). Such studies would be comprised of direct, head-to-head comparisons among various stimulants across a range of dosages.

Stimulants may provide short-term performance and alertness enhancement during sleep loss. Caffeine 600 mg, d-amphetamine 20 mg, and modafinil 400 mg were compared during 85 h of total sleep deprivation to determine the extent to which the three agents restored performance on simple psychomotor tasks, objective alertness and tasks of executive functions. Forty-eight healthy young adults remained awake for 85 h. Performance and alertness tests were administered bi-hourly from 8:00 hours day 2 to 19:00 hours day 5. At 23:50 hours on day 4 (after 64 h awake), subjects ingested placebo, caffeine 600 mg, dextroamphetamine 20 mg, or modafinil 400 mg (n=12 per group). Performance and alertness testing continued, and probe tasks of executive function were administered intermittently until the recovery sleep period (20:00 hours day 5 to 8:00 hours day 5). Bi-hourly postrecovery sleep testing occurred from 10:00 hours to 16:00 hours day 6. All three agents improved psychomotor vigilance speed and objectively measured alertness relative to placebo. Drugs did not affect recovery sleep, and postrecovery sleep performance for all drug groups was at presleep deprivation levels. Effects on executive function tasks were mixed, with improvement on some tasks with caffeine and modafinil, and apparent decrements with dextroamphetamine on others. At the doses tested, caffeine, dextroamphetamine, and modafinil are equally effective for approximately 2-4 h in restoring simple psychomotor performance and objective alertness. The duration of these benefits vary in accordance with the different elimination rates of the drugs. Whether caffeine, dextroamphetamine, and modafinil differentially restore executive functions during sleep deprivation remains unclear.

As both military and commercial operations increasingly become continuous, 24-h-per-day enterprises, the likelihood of operator errors or inefficiencies caused by sleep loss and/or circadian desynchrony also increases. Avoidance of such incidents requires the timely application of appropriate interventions--which, in turn, depend on the ability to measure and monitor the performance capacity of individuals in the operational environment. Several factors determine the potential suitability of candidate measures, including their relative sensitivity, reliability, content validity, intrusiveness and cumbersomeness/fieldability. In the present study, the relative sensitivity (defined as the ratio of effect size to 95% confidence interval) of several measures to the effects of sleep loss was compared in a sleep restriction experiment, in which groups were allowed 3, 5, 7, or 9 h time in bed (TIB) across seven consecutive nights. Of the measures compared, the Psychomotor Vigilance Test was among the most sensitive to sleep restriction, was among the most reliable with no evidence of learning over repeated administrations, and possesses characteristics that make it among the most practical for use in the operational environment.

Introduction: The extent to which modafinil and caffeine reverse fatigue effects (defined as performance decrements with time on task) during total sleep deprivation was investigated., Methods: There were 50 healthy young adults who remained awake for 54.5 h (06:30 day 1 to 13:00 day 3). A 10-min vigilance test was administered bi-hourly from 08:00 day 1 until 22:00 day 2. At 23:55 day 2 (after 41.5 h awake), double-blind administration of one of five drug doses (placebo; modafinil 100, 200, or 400 mg; or caffeine 600 mg; n = 10 per group) was followed by hourly testing from 00:00 through 12:00 day 3. Response speed (reciprocal of reaction time) across the 10-min task (by 1-min block) was analyzed prior to and after drug administration., Results: A fatigue effect (response speed degradation across the 10-min task) was exacerbated by sleep deprivation and circadian rhythmicity. Prior to the drug, this effect was maximal between 08:00 and 12:00 day 3 (24-28 h sleep deprivation). Modafinil 400 mg attenuated fatigue in a manner comparable to that seen with caffeine 600 mg; these effects were especially salient during the circadian nadir of performance (06:00 through 10:00); modafinil 200 mg also reversed fatigue, but for a shorter duration (3 min) than modafinil 400 mg (8 min) or caffeine 600 mg (6 min)., Discussion and Conclusions: Time-on-task effects contributed to the performance degradation seen during sleep deprivation; effects which were reversed by caffeine and, at appropriate doses, by modafinil. Because the duration of efficacy for reversing time-on-task effects was shorter at lower drug dosages, the latter must be considered when determining the appropriate dose to use during sustained operations.

Daytime performance changes were examined during chronic sleep restriction or augmentation and following subsequent recovery sleep. Sixty-six normal volunteers spent either 3 (n = 18), 5 (n= 16), 7 (n = 16), or 9 h (n = 16) daily time in bed (TIB) for 7 days (restriction/augmentation) followed by 3 days with 8 h daily TIB (recovery). In the 3-h group, speed (mean and fastest 10% of responses) on the psychomotor vigilance task (PVT) declined, and PVT lapses (reaction times greater than 500 ms) increased steadily across the 7 days of sleep restriction. In the 7- and 5-h groups speed initially declined, then appeared to stabilize at a reduced level; lapses were increased only in the 5-h group. In the 9-h group, speed and lapses remained at baseline levels. During recovery, PVT speed in the 7- and 5-h groups (and lapses in the 5-h group) remained at the stable, but reduced levels seen during the last days of the experimental phase, with no evidence of recovery. Speed and lapses in the 3-h group recovered rapidly following the first night of recovery sleep; however, recovery was incomplete with speed and lapses stabilizing at a level comparable with the 7- and 5-h groups. Performance in the 9-h group remained at baseline levels during the recovery phase. These results suggest that the brain adapts to chronic sleep restriction. In mild to moderate sleep restriction this adaptation is sufficient to stabilize performance, although at a reduced level. These adaptive changes are hypothesized to restrict brain operational capacity and to persist for several days after normal sleep duration is restored, delaying recovery.

Awakening from sleep entails rapid re-establishment of consciousness followed by the relatively slow (20-30 min later) re-establishment of alertness--a temporal dissociation that facilitates specification of the physiological underpinnings of each of these facets of the awakening process. H(2)(15)O PET was used to assess changes in regional cerebral blood flow (rCBF) upon awakening from stage 2 sleep. Cerebral blood flow (CBF) was most rapidly re-established in centrencephalic regions (e.g. brainstem and thalamus), suggesting that the reactivation of these regions underlies the re-establishment of conscious awareness. Across the ensuing 15 min of wakefulness, further increases in CBF were evident primarily in anterior cortical regions, suggesting that the dissipation of sleep inertia effects (post-awakening performance and alertness deficits) is effected by reactivation of these regions. Concomitant shifts in correlation patterns of regional brain activity across the post-awakening period [in particular, a waning negative correlation between prefrontal cortex and mesencephalic reticular formation (RF) activity, and a waxing positive correlation between prefrontal cortex and ventromedial caudate nucleus (CAUD) activity] suggest that the post-awakening reversal of sleep inertia effects may be mediated by more than mere reactivation--it may also involve the functional reorganization of brain activity. Conversely, stable post-awakening correlations--such as those found between the anterior cingulate cortex (ACC) and most other brain regions--may denote the pattern of functional connectivity that underlies consciousness itself.

Rationale: The performance and alertness effects of modafinil were evaluated to determine whether modafinil should replace caffeine for restoring performance and alertness during total sleep deprivation in otherwise healthy adults., Objectives: Study objectives were to determine (a) the relative efficacy of three doses of modafinil versus an active control dose of caffeine 600 mg; (b) whether modafinil effects are dose-dependent; and (c) the extent to which both agents maintain performance and alertness during the circadian trough., Methods: Fifty healthy young adults remained awake for 54.5 h (from 6:30 a.m. day 1 to 1:00 p.m. on day 3) and performance and alertness tests were administered bi-hourly from 8:00 a.m. day 1 until 10:00 p.m. day 2. At 11:55 p.m. on day 2 (after 41.5 h awake), subjects received double blind administration of one of five drug doses: placebo; modafinil 100, 200, or 400 mg; or caffeine 600 mg ( n=10 per group), followed by hourly testing from midnight through 12:00 p.m. on day 3., Results: Performance and alertness were significantly improved by modafinil 200 and 400 mg relative to placebo, and effects were comparable to those obtained with caffeine 600 mg. Although a trend toward better performance at higher modafinil doses suggested a dose-dependent effect, differences between modafinil doses were not significant. Performance enhancing effects were especially salient during the circadian nadir (6:00 a.m. through 10:00 a.m.). Few instances of adverse subjective side effects (nausea, heart pounding) were reported., Conclusions: Like caffeine, modafinil maintained performance and alertness during the early morning hours, when the combined effects of sleep loss and the circadian trough of performance and alertness trough were manifest. Thus, equivalent performance- and alertness-enhancing effects were obtained with drugs possessing different mechanisms of action. However, modafinil does not appear to offer advantages over caffeine (which is more readily available and less expensive) for improving performance and alertness during sleep loss in otherwise normal, healthy adults.

Studies have shown that next-day performance and alertness are impaired by sleep fragmentation procedures even when total sleep time (TST) is unaffected. Based on these studies it has been hypothesized that both the duration and continuity of sleep determine its recuperative value. This review of the literature suggests that when sleep fragmentation procedures increase the relative amount of stage 1 sleep, next-day performance and alertness are impaired. Other studies suggest that stage 1 sleep has little or no recuperative value. Total sleep time, however, is typically defined as the sum of time spent in sleep stages 1, 2, 3, 4, and REM. In the present paper it is shown that when stage 1 sleep is excluded from TST, a stronger relationship between TST and subsequent alertness and performance emerges--and the need to invoke 'sleep continuity' as a variable that contributes independently to recuperative sleep processes is obviated. In the same way that partial or total sleep deprivation impairs alertness and performance, it is proposed that sleep disruption also impairs alertness and performance by reducing true recuperative sleep time.

Positron emission tomography was used to measure cerebral activity and to evaluate regional interrelationships within visual cortices and their projections during rapid eye movement (REM) sleep in human subjects. REM sleep was associated with selective activation of extrastriate visual cortices, particularly within the ventral processing stream, and an unexpected attenuation of activity in the primary visual cortex; increases in regional cerebral blood flow in extrastriate areas were significantly correlated with decreases in the striate cortex. Extrastriate activity was also associated with concomitant activation of limbic and paralimbic regions, but with a marked reduction of activity in frontal association areas including lateral orbital and dorsolateral prefrontal cortices. This pattern suggests a model for brain mechanisms subserving REM sleep where visual association cortices and their paralimbic projections may operate as a closed system dissociated from the regions at either end of the visual hierarchy that mediate interactions with the external world.

Unlabelled: BACKGROUND AND HYPOTHESES: The performance-impairing effects of the short-acting imidazopyridine zolpidem (Ambien) were compared to those of triazolam (Halcion) following daytime administration., Methods: There were 70 male subjects who received oral zolpidem (5, 10 or 15 mg), triazolam (0.125, 0.25 or 0.5 mg), or placebo at 1000 hours. Performance on Logical Reasoning, Column Addition, and Repeated Acquisition (computerized tasks of the Walter Reed Performance Assessment Battery) was assessed prior to drug administration, then at 1.5 h (estimated time of peak drug effects) and 6 h post-administration., Results: Number of trials completed (TC) and response time (RT) for correct answers on the Logical Reasoning (LR) and Column Addition (CA) tasks (expressed as percentage of pre-drug performance) were impaired by triazolam 0.5 mg (TC = 76.6 and 67.4% for LR and CA; RT = 182.1 and 127.0% for LR, CA) and zolpidem 15 mg (TC = 87.0 and 75.8% for LR, CA; RT = 198.7 and 161.8% for LR, CA) at 1.5 h post-administration. By 6 h post-administration, drug effects on performance had dissipated. Other doses of triazolam and zolpidem failed to impair performance significantly., Conclusions: These results indicate substantial performance impairment at estimated peak plasma concentrations of both triazolam and zolpidem, at or near doses coinciding with somnogenic efficacy. Thus, the present results suggest no advantage of benzodiazepine receptor-subtype-specific drugs (e.g., zolpidem). Rather, these results suggest that the performance-impairing effects of both drugs are dose-dependent and functionally coupled to their sleep-inducing properties.

The effects of flumazenil, a benzodiazepine receptor antagonist, on triazolam- and zolpidem-induced memory impairment were investigated. Sixty subjects received oral triazolam 0.5 mg, zolpidem 20.0 mg, or placebo at 10 a.m. (n = 20 per drug). Ninety minutes later, half of the subjects (n = 10) in each oral drug group were administered flumazenil 1.0 mg, while the remaining half received placebo (normal saline), through indwelling venous catheters. Learning/memory tests (including Simulated Escape, Restricted Reminding, Paired-Associates, and Repeated Acquisition) were administered at that time, and at 1.5-h intervals over the next 6 h. Triazolam/placebo and zolpidem/placebo drug combinations impaired memory on all tests (all Ps < 0.05). However, the triazolam/flumazenil and zolpidem/flumazenil groups showed no evidence of impairment during any test session. These results demonstrate that flumazenil 1.0 mg rapidly and lastingly reverses memory impairment caused by agonists of the benzodiazepine receptor. Furthermore, nonsignificant trends suggested that performance of the placebo/flumazenil group was consistently better than that of the placebo/placebo group, denoting a possible role of endogenous benzodiazepine agonists in natural sleep/wake processes.

To determine whether zolpidem (an imidazopyridine hypnotic) produces amnestic effects which are similar to those produced by triazolam (a benzodiazepine hypnotic), 70 subjects were administered either triazolam (0.125, 0.25, or 0.5 mg), zolpidem (5, 10, or 15 mg) or placebo, then tested on Simulated Escape, Restricted Reminding, and Paired-Associates memory tests at 1.5 hours post-dosing (i.e., near the time of estimated peak blood concentration for both drugs) and again at 6 hours post-dosing. Triazolam 0.5 mg produced the greatest memory impairment at both test times, and also produced the greatest degree of sedation during intervening daytime naps in a non-sleep-conducive environment. Other doses of triazolam and zolpidem produced less memory impairment, but also failed to significantly enhance sleep. The results are consistent with the view that the amnestic and hypnotic effects of these sleep-inducing medications are functionally coupled.

Three experiments (N = 234) examined anchoring effects on judgement, estimation, and discrimination of numerosity. Subjects were anchored by preexposing them to random dot patterns with a mean quantity of 25, 50, or 75 dots. Subsequent testing with patterns having greater or less numerosity than the anchoring point resulted in predictable effects, including positive or negative contrast effects for numerosity judgements (Exp. 1), positive or negative contrast for the numerical estimation of quantity (Exp. 2), and a larger number of errors when subjects attempted simultaneous discrimination between two dot patterns (Exp. 3). The results extend previous findings for anchoring effects to the stimulus dimension of numerosity.

Electroencephalographic (EEG) recordings were obtained from nine male subjects at sea level and again following rapid ascent to high altitude (4300 meters) at 0900, 1600, and 1830 h. Electroencephalographic data were subjected to Fast Fourier Transformation and analyzed for beta, spindle, alpha, theta, delta, and total amplitudes. Total amplitude increased from baseline to altitude while relative theta (absolute theta/total amplitude) decreased from baseline to altitude. Amplitude for absolute and relative spindle and total amplitude increased across the day. The results indicate that altitude exerts an effect on the waking electroencephalogram which can be quantified via spectral analysis.

The N100, P200, N200 and P300 components of the auditory event-related potential were recorded from 10 male subjects at 0900, 1600, and 1830 hours at sea level and again following a rapid ascent to simulated 4300 m altitude. Amplitude and latency of components, ear oximetry, and concurrent performance measures (reaction time and counting errors) were assessed. Amplitude of P300 decreased, while P300 latency and reaction time increased, following ascent to altitude. However, the time course of altitude effects differed for amplitude versus latency. Components N100, P200, N200, and counting errors were unaffected by altitude. The results indicate that central measures of cognitive capacities are differentially sensitive to high altitude. The time course of altitude effects on P300 amplitude versus P300 latency suggests that the two measures reflect different aspects of a response to hypobaric hypoxia exposure.

The N100, P200, N400 and P600 components of the visual event-related potential were recorded from 11 female subjects every 2 h from 09:00 to 21:00 hours using a semantic categorization task. All subjects scored as "Intermediate" or marginal "Evening" types on a Morningness-Eveningness questionnaire. Amplitude and latency of components, tympanic temperature, and performance measures for positive and negative category instances were assessed. Amplitude of P200 increased across the day. Amplitude of N400 was larger, and latency of P600 was longer, for negative category instances, but neither component varied with time of day. N100 was unaffected by time of day. The results suggest that previous reports of diurnal variations in visual N100-P200 were due to variations in P200 alone, and that diurnal variations in P200 may reflect diurnal variations in underlying arousal levels. In addition, overlap with P600 may have obscured time of day effects for N400.

Time of day, repeated testing, and interblock interval effects on P300 amplitude were investigated. Subjects (N = 50) were tested using a standard oddball paradigm in either morning or afternoon sessions consisting of six test blocks per session. Amplitude of P300 was significantly higher in the morning than in the afternoon for all test blocks. In addition, amplitude of P300 habituated across test blocks from a mean of 9.59 microV on Block 1 to a mean of 4.98 microV on Block 6. Inserting a one-hour interval between Blocks 2 and 3 attenuated the rate of habituation. The results indicate that time of day, repeated testing, and interblock intervals affect P300 amplitude. Amplitude changes due to time of day may reflect circadian variations in cognitive resources indexed by the P300 component, while decrements due to repeated testing may reflect changes in allocation of resources across test sessions.

The present investigation utilized the P300 component of the auditory evoked potential as an index of information processing (discrimination) in sleep. Auditory evoked potentials were recorded to target and nontarget stimuli during sleep stages 3/4, 2 and REM under two probability conditions. Corresponding "nontone" waveforms were generated in each sleep stage, representing averaged EEG activity with no tones presented. Target P300 amplitude was higher than both corresponding "nontone" targets and tone nontargets. Probability did not affect the target-nontarget relationship. Latency of P300 increased and amplitude decreased from wakefulness through sleep; however, neither amplitude nor latency differed among sleep stages. Amplitude and latency of N200 increased during sleep. While N200 amplitude was highest in Stage 3-4, N200 latency did not differ among sleep stages. These findings suggest that the P300 recorded in sleep indexes similar cognitive processes as the P300 recorded in wakefulness. That P300 as well as N200 latency increased in sleep suggests that processes indexed by these components may slow during sleep.