The extent to which sleep restriction impairs objectively measured alertness and performance, and the rate at which these impairments are subsequently reversed by recovery sleep, varies as a function of the amount of nightly sleep obtained prior to the sleep restriction period. This suggests that the physiological mechanism(s) underlying chronic sleep debt undergo long-term (days/weeks) accommodative/adaptive changes.

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.

Summary Prolonged sleep loss impairs alertness, vigilance and some higher‐order cognitive and affective capacities. Some deficits can be temporarily reversed by stimulant medications including caffeine, dextroamphetamine, and modafinil. To date, only one study has directly compared the effectiveness of these three compounds and specified the doses at which all were equally effective in restoring alertness and vigilance following 64 h of wakefulness. The present study compared the effectiveness of these same three stimulants/doses following a less extreme period of sleep loss (i.e., 44 h). Fifty‐three healthy adults received a single dose of modafinil 400 mg (n = 11), dextroamphetamine 20 mg (n = 16), caffeine 600 mg (n = 12), or placebo (n = 14) after 44 h of continuous wakefulness. After 61 h of being awake, participants obtained 12 h of recovery sleep. Psychomotor vigilance was assessed bi‐hourly during waking and following recovery sleep. Relative to placebo, all three stimulants were equally effective in restoring psychomotor vigilance test speed and reducing lapses, although the duration of action was shortest for caffeine and longest for dextroamphetamine. At these doses, caffeine was associated with the highest percentage of subjectively reported side‐effects while modafinil did not differ significantly from placebo. Subsequent recovery sleep was adversely affected in the dextroamphetamine group, but none of the stimulants had deleterious effects on postrecovery performance. Decisions regarding stimulant selection should be made with consideration of how factors such as duration of action, potential side‐effects, and subsequent disruption of recovery sleep may interact with the demands of a particular operational environment.

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.

Sleep/wake identification and sleep parameter estimates from Motionlogger Watch and Actiwatch-64 actigraphs were compared to polysomnography (PSG). Following one night of baseline sleep, 29 volunteers remained awake for 36 h, followed by 11 h of recovery sleep in the laboratory. Two sets of analyses were performed: (1) epoch-by-epoch agreement and discriminability index (d') calculations, and (2) sleep parameter concordance with repeated measures ANOVAs. Sensitivity (sleep identification), specificity (wake detection), and overall agreement with PSG, as well as d', were higher for the Motionlogger than for Actiwatch. Relative to PSG, the Actiwatch-estimated total sleep time and sleep efficiency were underestimated and the number of awakenings was overestimated for baseline and recovery; sleep latency was underestimated on the baseline night. On the other hand, the Motionlogger-estimated total sleep time and sleep efficiency estimates were underestimated, and the sleep latency was overestimated on recovery, versus PSG. Despite these misestimations, it was concluded that the Motionlogger provided nominally better agreement with PSG, and that actigraphy generally constitutes a reasonably reliable tool for producing objective measurements of sleep/ wake, but that users should remain mindful of its limitations.