A new likelihood ratio metric for the psychomotor vigilance test and its sensitivity to sleep loss

The Psychomotor Vigilance Test (PVT) is a widely used assay of behavioural alertness sensitive to the effects of sleep loss and circadian misalignment. However, there is currently no accepted PVT composite outcome metric that captures response slowing, attentional lapses and compensatory premature reactions observed typically in sleep‐deprived subjects. We developed a novel likelihood ratio metric (LRM) based on relative frequency distributions in 50 categories of reaction times (RT) and false starts in alert and sleep‐deprived subjects (acute total sleep deprivation: n = 31 subjects). The LRM had the largest effect size both in a 33‐h total sleep deprivation protocol [1.96; 95% confidence interval (CI): 1.61–2.44; followed by response speed 1/RT, effect size 1.93, 95% CI: 1.55–2.65] and in a chronic partial sleep restriction protocol (1.22; 95% CI: 0.96–1.59; followed by response speed 1/RT, effect size 1.21, 95% CI: 0.94–1.59; 5 nights at 4 h sleep per night; n = 43 subjects). LRM scores correlated highly with response speed (R² = 0.986), and less well with five other common PVT outcome metrics (R² = 0.111–0.886). In conclusion, the new LRM is a sensitive PVT outcome metric with high statistical power that takes subtle sleep loss‐related changes in the distribution of reaction times (including false starts) into account, is not prone to outliers, does not require baseline data and can be calculated and interpreted easily. Congruence between LRM and PVT response speed and their similar effect size rankings support the use of response speed as the primary, most sensitive and most parsimonious standard PVT outcome metric for determining neurobehavioural deficits from sleep loss.     

Age-related changes in the time course of vigilant attention during 40 hours without sleep in men

STUDY OBJECTIVES: To examine whether vigilant attention and sleepiness develop differently during prolonged wakefulness in young and older men. DESIGN, SETTING, AND PARTICIPANTS: Psychomotor vigilance task (PVT) performance and subjective sleepiness were determined in 14 sessions at 3 hour intervals in healthy young (n = 12, mean age: 25.2 years, range: 21-31 years) and older (n = 11, mean age: 66.4 years, range: 61-70 years) men who were kept awake for 40 hours under continuous supervision in a sleep laboratory and on the morning after the recovery night. MEASUREMENTS AND RESULTS: PVT speed, response lapses and performance variability, and subjective sleepiness were analyzed. Sleep deprivation led to reversal of an age-related difference in PVT speed at the circadian trough of performance on the morning of the second day of prolonged wakefulness (Session x Age interaction: P < .0006). Beginning after 22 hours of wakefulness, the young men also produced more lapses (P < .004), showed higher performance instability (P < .0001), and felt sleepier (P < .03) than older men, especially during the morning after the night without sleep. CONCLUSIONS: Vigilant attention is more impaired after 1 night without sleep in young men than in older men, which has important implications for the prevention of accidents associated with the loss of sleep.     

The interactive effects of extended wakefulness and low-dose alcohol on simulated driving and vigilance

OBJECTIVES: Sleep deprivation and alcohol both impair driving performance. This study assessed the interactive effect of low-dose alcohol and extended wakefulness. DESIGN: Repeated-measures, crossover design evaluating psychomotor and driving function in a non-sleep-deprived state and after extended wakefulness with and without low-dose alcohol. SETTING: Teaching hospital sleep laboratory. PARTICIPANTS: Nineteen volunteer professional drivers. INTERVENTION & MEASUREMENTS: Driving simulation (AusEd) and the Psychomotor Vigilance Task (PVT) were measured in a rested state (12-15 hours awake) and after extended wakefulness (18-21 hours awake) during two sessions. Alcohol was administered during one session, with performance measured at blood alcohol concentrations (BAC) of 0.00%, 0.03%, and 0.05% in a non-sleep-deprived state, and at 0.03% after extended wakefulness (at 01:00 and 03:00). During the second session, tests were performed at the same times without alcohol. RESULTS: The combination of extended wakefulness and low-dose alcohol had significant deleterious effects on reaction time and lapses (PVT) and variation in lane position and speed (AusEd). Extended wakefulness (18-21 hours awake) combined with low-dose alcohol (0.03% BAC) resulted in more lapses (t = -2.75, P < 0.05) and greater variation in lane position (t = -3.94, P < 0.01) and speed (t = -2.79, P < 0.05) than did a BAC of 0.05% in a rested state. CONCLUSION: The combination of legal low-dose alcohol and extended wakefulness results in impairment worse than that at an alcohol level known to increase accident risk. Avoiding alcohol when driving after extended wakefulness may reduce accident risk.     

Comparing the neurocognitive effects of 40 h sustained wakefulness in patients with untreated OSA and healthy controls

We hypothesized that individuals with untreated obstructive sleep apnea (OSA) would exhibit greater vulnerability to sleep deprivation than healthy controls, due to the additional neurobiological 'load' of chronic sleep fragmentation. After baseline sleep with 8 h time in bed, participants remained awake for 40 h. Psychomotor Vigilance Task (PVT, mean slowest 10% 1/RT), AusEd Driving Simulator task (steering and speed deviation), and subjective sleepiness (Karolinska Sleepiness Scale, KSS) were assessed every 2 h. Nonlinear mixed-effects models were used to characterize individual differences in baseline/average performance, the linear effect of increasing hours awake, circadian amplitude and phase. Eight participants with untreated OSA with mean (SD) age 44.6 (8.4), apnea–hypopnea index (AHI) 49.8 (24.7), Epworth Sleepiness Scale (ESS) 11.9 (4.8) and nine healthy controls age 27.8 (3.7), AHI 4.5 (2.7), ESS 7.3 (2.1) completed the protocol. Baseline KSS was significantly higher (1.4 units, P  = 0.03) in the OSA group and there was a trend toward lower baseline speed deviation on the AusEd ( P  = 0.05). After adjusting for the significant effects of accumulated time awake, circadian amplitude and phase (all P  < 0.005), there was no difference in performance decrements between those with and without sleep apnea in PVT, driving simulator performance and subjective sleepiness ( P  > 0.5). Random-effects modeling confirmed the presence of significant inter-individual variability in vulnerability to sleep deprivation. Patients with OSA did not respond differently to sleep deprivation than healthy controls. As expected, total sleep deprivation led to significant worsening in performance and subjective sleepiness in both groups.     

The dynamics of neurobehavioural recovery following sleep loss

Rate of recovery of daytime performance and sleepiness following moderate and severe sleep deprivation (SD) was examined when recovery opportunity was either augmented or restricted. Thirty healthy non-smokers, aged 18-33 years, participated in one of three conditions: moderate SD with augmented (9-h) recovery opportunities, moderate SD with restricted (6-h) recovery opportunities, or severe SD with augmented recovery opportunities. Each participant attended the laboratory for 8-9 consecutive nights: an adaptation and baseline night (23:00-08:00 hours), one or two night(s) of wakefulness, and five consecutive recovery sleep opportunities (23:00-08:00 hours or 02:00-08:00 hours). On each experimental day, psychomotor vigilance performance (PVT) and subjective sleepiness (SSS) were assessed at two-hourly intervals, and MSLTs were performed at 1000 h. PSG data was collected for each sleep period. For all groups, PVT performance significantly deteriorated during the period of wakefulness, and sleepiness significantly increased. Significant differences were observed between the groups during the recovery phase. Following moderate SD, response speed, lapses and SSS returned to baseline after one 9-h sleep opportunity, while sleep latencies required two 9-h opportunities. When the recovery opportunity was restricted to six hours, neither PVT performance nor sleepiness recovered, but stabilised at below-baseline levels. Following severe SD, sleepiness recovered after one (SSS) or two (physiological) 9-h sleep opportunities, however PVT performance remained significantly below baseline for the entire recovery period. These results suggest that the mechanisms underlying the recovery process may be more complicated than previously thought, and that we may have underestimated the impact of sleep loss and/or the restorative value of subsequent sleep.     

Predicting vulnerability to sleep deprivation using diffusion model parameters

We used diffusion modelling to predict vulnerability to decline in psychomotor vigilance task (PVT) performance following a night of total sleep deprivation (SD). A total of 135 healthy young adults (69 women, age = 21.9 ± 1.7 years) participated in several within‐subject cross‐over design studies that incorporated the PVT. Participants were classified as vulnerable (lower tertile) or non‐vulnerable (upper tertile) according to their change in lapse rate [lapse = reaction time (RT) ≥ 500 ms] between the evening before (ESD) and the morning after SD. RT data were fitted using Ratcliff's diffusion model. Although both groups showed significant change in RT during SD, there was no significant group difference in RT during the ESD session. In contrast, during ESD, the mean diffusion drift of vulnerable subjects was significantly lower than for non‐vulnerable subjects. Mean drift and non‐decision times were both adversely affected by sleep deprivation. Both mean drift and non‐decision time showed significant state × vulnerability interaction. Diffusion modelling appears to have promise in predicting vulnerability to vigilance decline induced by a night of total sleep deprivation.     

Mismatch between subjective alertness and objective performance under sleep restriction is greatest during the biological night

Subjective alertness may provide some insight into reduced performance capacity under conditions suboptimal to neurobehavioural functioning, yet the accuracy of this insight remains unclear. We therefore investigated whether subjective alertness reflects the full extent of neurobehavioural impairment during the biological night when sleep is restricted. Twenty‐seven young healthy males were assigned to a standard forced desynchrony (FD) protocol (n = 13; 9.33 h in bed/28 h day) or a sleep‐restricted FD protocol (n = 14; 4.67 h in bed/28 h day). For both protocols, subjective alertness and neurobehavioural performance were measured using a visual analogue scale (VAS) and the psychomotor vigilance task (PVT), respectively; both measures were given at various combinations of prior wake and circadian phase (biological night versus biological day). Scores on both measures were standardized within individuals against their respective baseline average and standard deviation. We found that PVT performance and VAS rating deviated from their respective baseline to a similar extent during the standard protocol, yet a greater deviation was observed for PVT performance than VAS rating during the sleep‐restricted protocol. The discrepancy between the two measures during the sleep‐restricted protocol was particularly prominent during the biological night compared with the biological day. Thus, subjective alertness did not reflect the full extent of performance impairment when sleep was restricted, particularly during the biological night. Given that subjective alertness is often the only available information upon which performance capacity is assessed, our results suggest that sleep‐restricted individuals are likely to under‐estimate neurobehavioural impairment, particularly during the biological night.     

Response speed measurements on the psychomotor vigilance test: how precise is precise enough?

Study ObjectivesThe psychomotor vigilance test (PVT) is frequently used to measure behavioral alertness in sleep research on various software and hardware platforms. In contrast to many other cognitive tests, PVT response time (RT) shifts of a few milliseconds can be meaningful. It is, therefore, important to use calibrated systems, but calibration standards are currently missing. This study investigated the influence of system latency bias and its variability on two frequently used PVT performance metrics, attentional lapses (RTs ≥500 ms) and response speed, in sleep-deprived and alert participants.MethodsPVT data from one acute total (N = 31 participants) and one chronic partial (N = 43 participants) sleep deprivation protocol were the basis for simulations in which response bias (±15 ms) and its variability (0–50 ms) were systematically varied and transgressions of predefined thresholds (i.e. ±1 for lapses, ±0.1/s for response speed) recorded.ResultsBoth increasing bias and its variability caused deviations from true scores that were higher for the number of lapses in sleep-deprived participants and for response speed in alert participants. Threshold transgressions were typically rare (i.e. <5%) if system latency bias was less than ±5 ms and its standard deviation was ≤10 ms.ConclusionsA bias of ±5 ms with a standard deviation of ≤10 ms could be considered maximally allowable margins for calibrating PVT systems for timing accuracy. Future studies should report the average system latency and its standard deviation in addition to adhering to published standards for administering and analyzing the PVT.     

Dose-response relationship between sleep duration and human psychomotor vigilance and subjective alertness

Although it has been well documented that sleep is required for human performance and alertness to recover from low levels after prolonged periods of wakefulness, it remains unclear whether they increase in a linear or asymptotic manner during sleep. It has been postulated that there is a relation between the rate of improvement in neurobehavioral functioning and rate of decline of slow-wave sleep and/or slow-wave activity (SWS/SWA) during sleep, but this has not been verified. Thus, a cross-study comparison was conducted in which dose-response curves (DRCs) were constructed for Stanford Sleepiness Scale (SSS) and Psychomotor Vigilance Task (PVT) tests taken at 1000 hours by subjects who had been allowed to sleep 0 hours, 2 hours, 5 hours or 8 hours the previous night. We found that the DRCs to each PVT metric improved in a saturating exponential manner, with recovery rates that were similar [time constant (T) approximately 2.14 hours] for all the metrics. This recovery rate was slightly faster than, though not statistically significantly different from, the reported rate of SWS/SWA decline (T approximately 2.7 hours). The DRC to the SSS improved much more slowly than psychomotor vigilance, so that it could be fit equally well by a linear function (slope = -0.26) or a saturating exponential function (T = 9.09 hours). We conclude that although SWS/SWA, subjective alertness, and a wide variety of psychomotor vigilance metrics may all change asymptotically during sleep, it remains to be determined whether the underlying physiologic processes governing their expression are different.     

Systematic interindividual differences in neurobehavioral impairment from sleep loss: evidence of trait-like differential vulnerability

OBJECTIVES: To investigate interindividual differences in neurobehavioral deficits during sleep deprivation, and to establish to what extent the neurobehavioral responses to sleep loss are a function of sleep history versus trait-like differential vulnerability. DESIGN: Individuals were exposed to sleep deprivation on 3 separate occasions in order to determine the stability of interindividual differences in neurobehavioral impairment. SETTING: The sleep-deprivation experiments were conducted under standardized laboratory conditions with continuous monitoring of wakefulness. Each subject underwent a laboratory-adaptation session before entering the sleep-deprivation phase of the study. PARTICIPANTS: A total of 21 healthy adults (aged 21-38 years) completed the experiment. INTERVENTIONS: Subjects came to the laboratory 3 times at intervals of at least 2 weeks. During each laboratory session, they underwent neurobehavioral testing every 2 hours during 36 hours of total sleep deprivation, which was preceded by baseline sleep and followed by recovery sleep. In the week prior to each sleep-deprivation session and on the baseline night in the laboratory, subjects were required to either restrict their sleep to 6 hours per day (prior sleep restriction condition) or to extend their time in bed to 12 hours per day (prior sleep extension condition), so as to experimentally manipulate sleep history (in randomized counterbalanced order). RESULTS: There was strong evidence that interindividual differences in neurobehavioral deficits during sleep deprivation were systematic and trait-like. The magnitude of interindividual variability was substantial relative to the magnitude of the effect of prior sleep restriction (which on average involved a reduction of 4.1 hours sleep per day, compared to prior sleep extension, for 7 days). Overall, interindividual differences were not explained by subjects' baseline functioning or a variety of other potential predictors. Interindividual variability clustered on 3 distinct neurobehavioral dimensions: self-evaluation of sleepiness, fatigue, and mood; cognitive processing capability; and behavioral alertness as measured by sustained attention performance. CONCLUSIONS: Neurobehavioral deficits from sleep loss varied significantly among individuals and were stable within individuals. Interindividual differences in neurobehavioral responses to sleep deprivation were not merely a consequence of variations in sleep history. Rather, they involved trait-like differential vulnerability to impairment from sleep loss, for which neurobiologic correlates have yet to be discovered.     

Comparison of sustained attention assessed by auditory and visual psychomotor vigilance tasks prior to and during sleep deprivation

To date, no detailed examination of the pattern of change in reaction time performance for different sensory modalities has been conducted across the circadian cycle during sleep deprivation. Therefore, we compared sustained auditory and visual attention performance during 40 h of sleep deprivation assessing multiple metrics of auditory and visual psychomotor vigilance tasks (PVT). Forty healthy participants (14 women) aged 30.8 ± 8.6 years were studied. Subjects were scheduled for an ∼8 h sleep schedule at home prior to three–six laboratory baseline days with an 8 h sleep schedule followed by 40 h sleep deprivation. Visual and auditory PVTs were 10 min in duration, and were administered every 2 h during sleep deprivation. Data were analysed with mixed‐model anova . Sleep deprivation and circadian phase increased response time, lapses, anticipations, standard deviation of response times and time on task decrements for visual and auditory PVTs. In general, auditory vigilance was faster and less variable than visual vigilance, with larger differences between auditory and visual PVT during sleep deprivation versus baseline. Failures to respond to stimuli within 10 s were four times more likely to occur to visual versus auditory stimuli. Our findings highlight that lapses during sleep deprivation are more than just long responses due to eye closure or visual distraction. Furthermore, our findings imply that the general pattern of change in attention during sleep deprivation (e.g. circadian variation, response slowing, lapsing and anticipations, time on task decrements and state instability) is similar among sensory–motor behavioral response modalities.     

Arterial pressure and heart rate changes during natural sleep in rat

Mean arterial pressure and heart rate data during quiet wakefulness and phases of sleep in conscious rat are sampled by a computer at a rate of 100/sec. Average values and variability expressed as standard deviation are computed for each recording session. Mean arterial pressure and heart rate and their variability decrease from quiet wakefulness to synchronized sleep. During desynchronized sleep, mean arterial pressure increases to the level of quiet wakefulness and is more variable than during synchronized sleep. Heart rate is lower and more uniform during sleep than during quiet wakefulness, and there is no difference between synchronized and desynchronized sleep except that a greater variability occurs during desynchronized sleep. The study shows that characteristic and specific cardiovascular changes accompany the phases of sleep and that a hierarchy of arterial pressure is present during the resting behavior in rat.     

Pupillary instability as an accurate,objective marker of alertness failure and performance impairment

Pupillary instability reflects alterations in autonomic nervous system activity and has been shown to reflect change in alertness. However, the extent to which it can predict subsequent performance impairment and alertness failure is not clear. Eighteen healthy young adults (group age = 21.44 ± 3.24 years, 10 men) underwent 40 hr of continuous wakefulness, completing an 11‐min Pupillographic Sleepiness Test (PST), the Karolinska Sleepiness Scale and a 10‐min Psychomotor Vigilance Task (PVT) every 2 hr. Waking electroencephalography was recorded continuously and scored for microsleeps and slow eye movements (SEMs) during PVTs. Pupillary instability was sensitive to time awake, significantly increasing after 18 hr of wakefulness. The time course of impairment was almost identical to PVT lapses, microsleeps and SEMs. Receiver operating characteristic curve analysis demonstrated reasonable sensitivity and specificity of pupillary instability in correctly classifying PVT lapses, microsleeps and SEMs above individual baseline thresholds (all AUC values >0.78, p < 0.0001). Preliminary cut‐off scores ranging from 10 to 11.5 mm/min for varying impairment thresholds are proposed for young adults. If reproducible in field settings, the PST may be a strong candidate as a fitness for duty/fitness to drive tool for detecting drowsiness‐related impairment.     

Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose-response study

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.     

A controlled intervention study on the effects of a very rapidly forward rotating shift system on sleep-wakefulness and well-being among young and elderly shift workers.

Shift work is related to problems in sleep/wakefulness and social life. The effects of a very rapidly forward rotating shift system on sleep, health and well-being of young (-45) and elderly (45+) maintenance workers were studied by a controlled intervention study. In the beginning, all the workers had a continuous backward rotating three-shift system. A very quickly forward rotating shift system was developed, avoiding consecutive night shifts and with more free-time between the individual shifts. The effect of the new shift system on sleep/wakefulness and general well-being was studied by questionnaire and field studies including on-site registration of sleep (actigraphy), subjective sleepiness (KSS) and psychomotor performance (PVT). Based on a linear mixed model for repeated measurements, the new shift system increased the main sleep length after the night shift and improved alertness and PVT performance during the night shift among the older workers. Alertness also improved during free-time after the night shift and sleep complaints decreased after all shifts. The workers on the new shift schedule perceived the effects of the new shift system on sleep, alertness, general health, well-being at work, social and family life more positively than the workers in the old shift system. At the end of the study, all subjects voted for the new shift system. It is concluded that although the new shift system increased the operating hours at night, the very rapidly forward rotating shift system had positive effects on the sleep, alertness and well-being of especially the older shift workers.     

Real‐time individualization of the unified model of performance

Existing mathematical models for predicting neurobehavioural performance are not suited for mobile computing platforms because they cannot adapt model parameters automatically in real time to reflect individual differences in the effects of sleep loss. We used an extended Kalman filter to develop a computationally efficient algorithm that continually adapts the parameters of the recently developed Unified Model of Performance (UMP) to an individual. The algorithm accomplishes this in real time as new performance data for the individual become available. We assessed the algorithm's performance by simulating real‐time model individualization for 18 subjects subjected to 64 h of total sleep deprivation (TSD) and 7 days of chronic sleep restriction (CSR) with 3 h of time in bed per night, using psychomotor vigilance task (PVT) data collected every 2 h during wakefulness. This UMP individualization process produced parameter estimates that progressively approached the solution produced by a post‐hoc fitting of model parameters using all data. The minimum number of PVT measurements needed to individualize the model parameters depended upon the type of sleep‐loss challenge, with ~30 required for TSD and ~70 for CSR. However, model individualization depended upon the overall duration of data collection, yielding increasingly accurate model parameters with greater number of days. Interestingly, reducing the PVT sampling frequency by a factor of two did not notably hamper model individualization. The proposed algorithm facilitates real‐time learning of an individual's trait‐like responses to sleep loss and enables the development of individualized performance prediction models for use in a mobile computing platform.     

Circadian and wake-dependent modulation of fastest and slowest reaction times during the psychomotor vigilance task

Performance on the psychomotor vigilance task (PVT) sensitively reflects a circadian modulation of neurobehavioral functions, as well as the effect of sleep pressure developing with duration of time awake, without being confounded by a learning curve. Sixteen healthy volunteers underwent two 40-h constant posture protocols in a balanced crossover design. During these protocols, either low sleep pressure conditions were attained by an alternating cycle of 150 min of wakefulness and 75 min of sleep (NAP) protocol, or high sleep pressure conditions were achieved by total sleep deprivation (SD) protocol. During scheduled wakefulness in both protocols, the PVT was carried out every 225 min. Quantitative analysis of the lapses, slowest (90th percentile) and fastest (10th percentile) reaction times (RTs) during the protocols, indicated that the lapses and slowest RTs were sensitive to changes in homeostatic sleep pressure. Our data indicate that the difference between the fastest and slowest RTs (interpercentile range 10th–90th percentile) was particular sensitive to detect very early effects of growing sleep pressure. On the other hand, decrements in PVT performance which were related to circadian phase did not depend significantly on any categorization (such as percentiles of the RTs).     

Sleep history affects task acquisition during subsequent sleep restriction and recovery

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 × 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.     

Speech‐perception training for older adults with hearing loss impacts word recognition and effort

The current pupillometry study examined the impact of speech‐perception training on word recognition and cognitive effort in older adults with hearing loss. Trainees identified more words at the follow‐up than at the baseline session. Training also resulted in an overall larger and faster peaking pupillary response, even when controlling for performance and reaction time. Perceptual and cognitive capacities affected the peak amplitude of the pupil response across participants but did not diminish the impact of training on the other pupil metrics. Thus, we demonstrated that pupillometry can be used to characterize training‐related and individual differences in effort during a challenging listening task. Importantly, the results indicate that speech‐perception training not only affects overall word recognition, but also a physiological metric of cognitive effort, which has the potential to be a biomarker of hearing loss intervention outcome.     

24 hours of sleep deprivation in the rat increases sleepiness and decreases vigilance: introduction of the rat‐psychomotor vigilance task

A novel animal‐analog of the human psychomotor vigilance task (PVT) was validated by subjecting rats to 24 h of sleep deprivation (SD) and examining the effect on performance in the rat‐PVT (rPVT), and a rat multiple sleep latency test (rMSLT). During a three‐phase (separate cohorts) crossover design, vigilance performance in the rPVT was compared with 24 h SD‐induced changes in sleepiness assessed by polysomnographic evaluation and the rMSLT. Twenty‐four hours of SD was produced by brief rotation of activity wheels at regular intervals in which the animals resided throughout the experiment. In the rPVT experiment, exercise controls (EC) experienced the same overall amount of locomotor activity as during SD, but allowed long periods of undisturbed sleep. After 24 h SD response latencies slowed, and lapses increased significantly during rPVT performance when compared with baseline and EC conditions. During the first 3 h of the recovery period following 24 h SD, polysomnographic measures indicated sleepiness. Latency to fall asleep after 24 h SD was assessed six times during the first 3 h after SD. Rats fell asleep significantly faster immediately after SD, than after non‐SD baseline sessions. In conclusion, 24 h of SD in rats increased sleepiness, as indicated by polysomnography and the rMSLT, and impaired vigilance as measured by the rPVT. The rPVT closely resembles the human PVT test widely used in human sleep research and will assist investigation of the neurobiologic mechanisms that produce vigilance impairments after sleep disruption.