Sleep homeostasis and models of sleep regulation

According to the two-process model of sleep regulation, the timing and structure of sleep are determined by the interaction of a homeostatic and a circadian process. The original qualitative model was elaborated to quantitative versions that included the ultradian dynamics of sleep in relation to the non-REM-REM sleep cycle. The time course of EEG slow-wave activity, the major marker of non-REM sleep homeostasis, as well as daytime alertness were simulated successfully for a considerable number of experimental protocols. They include sleep after partial sleep deprivation and daytime napping, sleep in habitual short and long sleepers, and alertness in a forced desynchrony protocol or during an extended photoperiod. Simulations revealed that internal desynchronization can be obtained for different shapes of the thresholds. New developments include the analysis of the waking EEG to delineate homeostatic and circadian processes, studies of REM sleep homeostasis, and recent evidence for local, use-dependent sleep processes. Moreover, nonlinear interactions between homeostatic and circadian processes were identified. In the past two decades, models have contributed considerably to conceptualizing and analyzing the major processes underlying sleep regulation, and they are likely to play an important role in future advances in the field.     

Sleep initiation and initial sleep intensity: interactions of homeostatic and circadian mechanisms

Sleep initiation and sleep intensity in humans show a dissimilar time course. The propensity of sleep initiation (PSI), as measured by the multiple sleep latency test, remains at a relatively constant level throughout the habitual period of waking or exhibits a midafternoon peak. When waking is extended into the sleep period, PSI rises rapidly within a few hours. In contrast, sleep intensity, as measured by electroencephalographic slow-wave activity during naps, shows a gradual increase during the period of habitual waking. In the two-process model of sleep regulation, it corresponds to the rising limb of the homeostatic Process S. We propose that PSI is determined by the difference between Process S and the threshold H defining sleep onset, which is modulated by the circadian process C. In contrast to a previous version of the model, the parameters of H (amplitude, phase, skewness) differ from those of threshold L, which defines sleep termination. The present model is able to simulate the time course of PSI under baseline conditions as well as following recovery sleep after extended sleep deprivation. The simulations suggest that during the regular period of waking, a circadian process counteracts the increasing sleep propensity induced by a homeostatic process. Data obtained in the rat indicate that during the circadian period of predominant waking, a circadian process prevents a major intrusion of sleep.     

Shift work and inter-individual differences in sleep and sleepiness

Inter-individual differences in tolerance for shift work have been studied primarily in terms of external factors affecting alertness on the job or the ability to rest and sleep while at home. However, there is increasing evidence that neurobiological factors play a role as well, particularly the major processes involved in the regulation of sleep and wakefulness. These include a sleep homeostatic process seeking to balance wakefulness and sleep and a circadian process seeking to promote wakefulness during the day and sleep during the night. Shift work is associated with a temporal misalignment of these two endogenous processes. During nightwork, this misalignment makes it difficult to stay awake during the nightshift and sleep during the day. However, inter-individual variability in the processes involved in sleep/wake regulation is substantial. Recent studies have demonstrated the existence of inter-individual differences in vulnerability to cognitive deficits from sleep loss. Moreover, these inter-individual differences were shown to constitute a trait. Interestingly, self-evaluations of sleepiness did not correspond well with the trait inter-individual variability in objective levels of performance impairment during sleep deprivation. Perhaps because of this discrepancy, in operational settings, the inter-individual differences in vulnerability to sleep loss do not appear to be limited due to self-selection mechanisms. Indeed, even among a highly select group of active-duty jet fighter pilots flying a series of simulated night missions, systematic inter-individual differences in performance impairment from sleep loss were still observed. There are significant personal and economic consequences to human error and accidents caused by performance deficits due to sleep loss. It is important, therefore, to study the inter-individual differences in the regulation of sleep and wakefulness in the work environment so that cognitive impairment during shift work may be better anticipated and prevented.     

Shift Work and Inter‐Individual Differences in Sleep and Sleepiness

Inter‐individual differences in tolerance for shift work have been studied primarily in terms of external factors affecting alertness on the job or the ability to rest and sleep while at home. However, there is increasing evidence that neurobiological factors play a role as well, particularly the major processes involved in the regulation of sleep and wakefulness. These include a sleep homeostatic process seeking to balance wakefulness and sleep and a circadian process seeking to promote wakefulness during the day and sleep during the night. Shift work is associated with a temporal misalignment of these two endogenous processes. During nightwork, this misalignment makes it difficult to stay awake during the nightshift and sleep during the day. However, inter‐individual variability in the processes involved in sleep/wake regulation is substantial. Recent studies have demonstrated the existence of inter‐individual differences in vulnerability to cognitive deficits from sleep loss. Moreover, these inter‐individual differences were shown to constitute a trait. Interestingly, self‐evaluations of sleepiness did not correspond well with the trait inter‐individual variability in objective levels of performance impairment during sleep deprivation. Perhaps because of this discrepancy, in operational settings, the inter‐individual differences in vulnerability to sleep loss do not appear to be limited due to self‐selection mechanisms. Indeed, even among a highly select group of active‐duty jet fighter pilots flying a series of simulated night missions, systematic inter‐individual differences in performance impairment from sleep loss were still observed. There are significant personal and economic consequences to human error and accidents caused by performance deficits due to sleep loss. It is important, therefore, to study the inter‐individual differences in the regulation of sleep and wakefulness in the work environment so that cognitive impairment during shift work may be better anticipated and prevented.     

Spectral EEG indicator of pressure to enter into deep sleep: its responsiveness to closing the eyes for just a few minutes exhibits a pure exponential buildup during sleep deprivation

According to the two-process model of sleep–wake regulation, a homeostatic sleep pressure, i.e. a pressure to enter into deep non-rapid eyes movement (NREM) sleep, must exhibit a purely exponential buildup during prolonged wakefulness. However, this pressure is usually measured indirectly, i.e. during the following episode of actual deep NREM sleep. The purpose of this paper was to show that, despite a prominent circadian modulation of time course of any waking EEG index, the model-postulated purely exponential buildup of the homeostatic sleep pressure can be directly confirmed. During two days of sleep deprivation experiments, the EEG of healthy adults (N = 30) was recorded every other hour throughout 5-min eyes closed relaxation. Sixteen ln-transformed single-Hz power densities (from 1 to 16 Hz) were computed for each of 5 one-min intervals. Differences between these densities obtained for the first and the following intervals were calculated and averaged. The obtained 16 values were used as the frequency weighting curve for weighting densities of each set of 16 single-Hz power densities. Summing-up of these weighted densities provided a single measure that was found to co-vary with self-rated sleepiness throughout two-day interval of sleep deprivation, thus reflecting the joint influence of the circadian and homeostatic processes. However, two-day time course of responsiveness of this measure to closing the eyes for just a few minutes exhibited a purely exponential buildup. It was concluded that this result provided a direct experimental confirmation of the model-predicted exponential buildup of the homeostatic sleep pressure across prolonged episode of wakefulness.     

Effects of Partial and Acute Total Sleep Deprivation on Performance across Cognitive Domains,Individuals and Circadian Phase

Background

Cognitive performance deteriorates during extended wakefulness and circadian phase misalignment, and some individuals are more affected than others. Whether performance is affected similarly across cognitive domains, or whether cognitive processes involving Executive Functions are more sensitive to sleep and circadian misalignment than Alertness and Sustained Attention, is a matter of debate.

Methodology/Principal Findings

We conducted a 2 × 12-day laboratory protocol to characterize the interaction of repeated partial and acute total sleep deprivation and circadian phase on performance across seven cognitive domains in 36 individuals (18 males; mean ± SD of age = 27.6±4.0 years). The sample was stratified for the rs57875989 polymorphism in PER3, which confers cognitive susceptibility to total sleep deprivation. We observed a deterioration of performance during both repeated partial and acute total sleep deprivation. Furthermore, prior partial sleep deprivation led to poorer cognitive performance in a subsequent total sleep deprivation period, but its effect was modulated by circadian phase such that it was virtually absent in the evening wake maintenance zone, and most prominent during early morning hours. A significant effect of PER3 genotype was observed for Subjective Alertness during partial sleep deprivation and on n-back tasks with a high executive load when assessed in the morning hours during total sleep deprivation after partial sleep loss. Overall, however, Subjective Alertness and Sustained Attention were more affected by both partial and total sleep deprivation than other cognitive domains and tasks including n-back tasks of Working Memory, even when implemented with a high executive load.

Conclusions/Significance

Sleep loss has a primary effect on Sleepiness and Sustained Attention with much smaller effects on challenging Working Memory tasks. These findings have implications for understanding how sleep debt and circadian rhythmicity interact to determine waking performance across cognitive domains and individuals.     

Interactive mathematical models of subjective alertness and cognitive throughput in humans

The authors present here mathematical models in which levels of subjective alertness and cognitive throughput are predicted by three components that interact with one another in a nonlinear manner. These components are (1) a homeostatic component (H) that falls in a sigmoidal manner during wake and rises in a saturating exponential manner at a rate that is determined by circadian phase during sleep; (2) a circadian component (C) that is a function of the output of our mathematical model of the effect of light on the circadian pacemaker, with the amplitude further regulated by the level of H; and (3) a sleep inertia component (W) that rises in a saturating exponential manner after waketime. The authors first construct initial models of subjective alertness and cognitive throughput based on the results of sleep inertia studies, sleep deprivation studies initiated across all circadian phases, 28-h forced desynchrony studies, and alertness and performance dose response curves to sleep. These initial models are then refined using data from nearly one hundred fifty 30- to 50-h sleep deprivation studies in which subjects woke at their habitual times. The interactive three-component models presented here are able to predict even the fine details of neurobehavioral data from sleep deprivation studies and, after further validation, may provide a powerful tool for the design of safe shift work and travel schedules, including those in which people are exposed to unusual patterns of light.     

Selective REM sleep deprivation during daytime. II. Muscle atonia in non-REM sleep

One of the hallmarks of rapid eye movement (REM) sleep is muscle atonia. Here we report extended epochs of muscle atonia in non-REM sleep (MAN). Their extent and time course was studied in a protocol that included a baseline night, a daytime sleep episode with or without selective REM sleep deprivation, and a recovery night. The distribution of the latency to the first occurrence of MAN was bimodal with a first mode shortly after sleep onset and a second mode 40 min later. Within a non-REM sleep episode, MAN showed a U-shaped distribution with the highest values before and after REM sleep. Whereas MAN was at a constant level over consecutive 2-h intervals of nighttime sleep, MAN showed high initial values when sleep began in the morning. Selective daytime REM sleep deprivation caused an initial enhancement of MAN during recovery sleep. It is concluded that episodes of MAN may represent an REM sleep equivalent and that it may be a marker of homeostatic and circadian REM sleep regulating processes. MAN episodes may contribute to the compensation of an REM sleep deficit.     

CIRCADIAN RHYTHMS OF PERFORMANCE: NEW TRENDS

This brief review is concerned with how human performance efficiency changes as a function of time of day. It presents an overview of some of the research paradigms and conceptual models that have been used to investigate circadian performance rhythms. The influence of homeostatic and circadian processes on performance regulation is discussed. The review also briefly presents recent mathematical models of alertness that have been used to predict cognitive performance. Related topics such as interindividual differences and the postlunch dip are presented. (Chronobiology International, 17(6), 719–732, 2000)     

Increasing length of wakefulness and modulation of hypocretin-1 in the wake-consolidated squirrel monkey

The neuropeptides hypocretins (orexins), the loss of which results in the sleep disorder narcolepsy, are hypothesized to be involved in the consolidation of wakefulness and have been proposed to be part of the circadian-driven alertness signal. To elucidate the role of hypocretins in the consolidation of human wakefulness we examined the effect of wake extension on hypocretin-1 in squirrel monkeys, primates that consolidate wakefulness during the daytime as do humans. Wake was extended up to 7 h with hypocretin-1, cortisol, ghrelin, leptin, locomotion, and feeding, all being assayed. Hypocretin-1 (P < 0.01), cortisol (P < 0.001), and locomotion (P < 0.005) all increased with sleep deprivation, while ghrelin (P = 0.79) and leptin (P = 1.00) did not change with sleep deprivation. Using cross-correlation and multivariate modeling of these potential covariates along with homeostatic pressure (a measure of time awake/asleep), we found that time of day and homeostatic pressure together explained 44% of the variance in the hypocretin-1 data (P < 0.001), while cortisol did not significantly contribute to the overall hypocretin-1 variance. Locomotion during the daytime, but not during the nighttime, helped explain < 5% of the hypocretin-1 variance (P < 0.05). These data are consistent with earlier evidence indicating that in the squirrel monkey hypocretin-1 is mainly regulated by circadian inputs and homeostatic sleep pressure. Concomitants of wakefulness that affect hypocretin-1 in polyphasic species, such as locomotion, food intake, and food deprivation, likely have a more minor role in monophasic species, such as humans.     

Circadian rhythms of performance: new trends

This brief review is concerned with how human performance efficiency changes as a function of time of day. It presents an overview of some of the research paradigms and conceptual models that have been used to investigate circadian performance rhythms. The influence of homeostatic and circadian processes on performance regulation is discussed. The review also briefly presents recent mathematical models of alertness that have been used to predict cognitive performance. Related topics such as interindividual differences and the postlunch dip are presented. (Chronobiology International, 17(6), 719-732, 2000)     

Circadian and sleep-deprivation variations of monophosphorylated MAP-Kinase in hypothalamus and pons of rats

Behavior and physiological changes are under the influence of circadian and homeostatic variations. Temporal alignment regulates timing of neurobiological phenomena, such as protein phosphorylation. In the current report, we describe the circadian and sleep homeostatic phosphorylated mitogen-activated protein kinase (MAP-K) variations in hypothalamus and pons of rats across 24 h as well as after sleep deprivation. In the circadian study, MAP-K expression showed a building-up profile during the dark phase in hypothalamus, whereas an increase across the lights-on period was found in pons. On the other hand, that phosphorylation of MAP-K in hypothalamus and pons displayed a significant reduction after sleep rebound period. Data demonstrate that MAP-K phosphorylation undergoes circadian and sleep homeostatic variations in brain areas linked to sleep modulation.     

Selective REM sleep deprivation during daytime I. Time course of interventions and recovery sleep

Although repeated selective rapid eye movement (REM) sleep deprivation by awakenings during nighttime has shown that the number of sleep interruptions required to prevent REM sleep increases within and across consecutive nights, the underlying regulatory processes remained unspecified. To assess the role of circadian and homeostatic factors in REM sleep regulation, REM sleep was selectively deprived in healthy young adult males during a daytime sleep episode (7-15 h) after a night without sleep. Circadian REM sleep propensity is known to be high in the early morning. The number of interventions required to prevent REM sleep increased from the first to the third 2-h interval by a factor of two and then leveled off. Only a minor REM sleep rebound (11.6%) occurred in the following undisturbed recovery night. It is concluded that the limited rise of interventions during selective daytime REM sleep deprivation may be due to the declining circadian REM sleep propensity, which may partly offset the homeostatic drive and the sleep-dependent disinhibition of REM sleep.     

Quantitative physiologically based modeling of subjective fatigue during sleep deprivation

A quantitative physiologically based model of the sleep-wake switch is used to predict variations in subjective fatigue-related measures during total sleep deprivation. The model includes the mutual inhibition of the sleep-active neurons in the hypothalamic ventrolateral preoptic area (VLPO) and the wake-active monoaminergic brainstem populations (MA), as well as circadian and homeostatic drives. We simulate sleep deprivation by introducing a drive to the MA, which we call wake effort, to maintain the system in a wakeful state. Physiologically this drive is proposed to be afferent from the cortex or the orexin group of the lateral hypothalamus. It is hypothesized that the need to exert this effort to maintain wakefulness at high homeostatic sleep pressure correlates with subjective fatigue levels. The model's output indeed exhibits good agreement with existing clinical time series of subjective fatigue-related measures, supporting this hypothesis. Subjective fatigue, adrenaline, and body temperature variations during two 72 h sleep deprivation protocols are reproduced by the model. By distinguishing a motivation-dependent orexinergic contribution to the wake-effort drive, the model can be extended to interpret variation in performance levels during sleep deprivation in a way that is qualitatively consistent with existing, clinically derived results. The example of sleep deprivation thus demonstrates the ability of physiologically based sleep modeling to predict psychological measures from the underlying physiological interactions that produce them.     

Timing and consolidation of human sleep, wakefulness, and performance by a symphony of oscillators

Daily rhythms in sleep and waking performance are generated by the interplay of multiple external and internal oscillators. These include the light-dark and social cycles, a circadian hypothalamic oscillator oscillating virtually independently of behavior, and a homeostatic oscillator driven primarily by sleep-wake behavior. Both internal oscillators contribute to variation in many aspects of sleep and wakefulness (e.g., sleep timing and duration, REM sleep, non-REM sleep, REM density, sleep spindles, slow-wave sleep, electroencephalographic oscillations during wakefulness and sleep, and performance parameters, including attention and memory). The relative contribution of the oscillators varies greatly between these variables. Sleep and performance cannot be predicted by either oscillator independently but critically depend on their phase relationship and amplitude. The homeostatic oscillator feeds back onto the central pacemaker or its outputs. Thus, the amplitude of observed circadian variation in sleep and performance depends on how long we have been asleep or awake. During entrainment to external 24-h cycles, the opposing interplay between circadian and homeostatic changes in sleep propensity consolidates sleep and wakefulness. Some physiological correlates and mediators of both the circadian process (e.g., melatonin and hypocretin rhythms) and the homeostat (e.g., EEG, slow-wave activity, and adenosine release) have been established, offering targets for the development of countermeasures for circadian sleep and performance disorders. Interindividual differences in sleep timing, duration, and morning or evening preference are associated with changes of circadian or sleep homeostatic processes or both. Molecular genetic correlates, including polymorphisms in clock genes, of some of these interindividual differences are emerging.     

An endogenous circadian rhythm in sleep inertia results in greatest cognitive impairment upon awakening during the biological night

Sleep inertia is the impaired cognitive performance immediately upon awakening, which decays over tens of minutes. This phenomenon has relevance to people who need to make important decisions soon after awakening, such as on-call emergency workers. Such awakenings can occur at varied times of day or night, so the objective of the study was to determine whether or not the magnitude of sleep inertia varies according to the phase of the endogenous circadian cycle. Twelve adults (mean, 24 years; 7 men) with no medical disorders other than mild asthma were studied. Following 2 baseline days and nights, subjects underwent a forced desynchrony protocol composed of seven 28-h sleep/wake cycles, while maintaining a sleep/wakefulness ratio of 1:2 throughout. Subjects were awakened by a standardized auditory stimulus 3 times each sleep period for sleep inertia assessments. The magnitude of sleep inertia was quantified as the change in cognitive performance (number of correct additions in a 2-min serial addition test) across the first 20 min of wakefulness. Circadian phase was estimated from core body temperature (fitted temperature minimum assigned 0 degrees ). Data were segregated according to: (1) circadian phase (60 degrees bins); (2) sleep stage; and (3) 3rd of the night after which awakenings occurred (i.e., tertiary 1, 2, or 3). To control for any effect of sleep stage, the circadian rhythm of sleep inertia was initially assessed following awakenings from Stage 2 (62% of awakening occurred from this stage; n = 110). This revealed a significant circadian rhythm in the sleep inertia of cognitive performance (p = 0.007), which was 3.6 times larger during the biological night (circadian bin 300 degrees , approximately 2300-0300 h in these subjects) than during the biological day (bin 180 degrees , approximately 1500-1900 h). The circadian rhythm in sleep inertia was still present when awakenings from all sleep stages were included (p = 0.004), and this rhythm could not be explained by changes in underlying sleep drive prior to awakening (changes in sleep efficiency across circadian phase or across the tertiaries), or by the proportion of the varied sleep stages prior to awakenings. This robust endogenous circadian rhythm in sleep inertia may have important implications for people who need to be alert soon after awakening.     

Total sleep deprivation does not significantly degrade semantic encoding

ABSTRACT

Sleep deprivation impairs performance on cognitive tasks, but it is unclear which cognitive processes it degrades. We administered a semantic matching task with variable stimulus onset asynchrony (SOA) and both speeded and self-paced trial blocks. The task was administered at the baseline and 24 hours later after 30.8 hours of total sleep deprivation (TSD) or matching well-rested control. After sleep deprivation, the 20% slowest response times (RTs) were significantly increased. However, the semantic encoding time component of the RTs remained at baseline level. Thus, the performance impairment induced by sleep deprivation on this task occurred in cognitive processes downstream of semantic encoding.     

Sleep deprivation in a quantitative physiologically based model of the ascending arousal system

A physiologically based quantitative model of the human ascending arousal system is used to study sleep deprivation after being calibrated on a small set of experimentally based criteria. The model includes the sleep-wake switch of mutual inhibition between nuclei which use monoaminergic neuromodulators, and the ventrolateral preoptic area. The system is driven by the circadian rhythm and sleep homeostasis. We use a small number of experimentally derived criteria to calibrate the model for sleep deprivation, then investigate model predictions for other experiments, demonstrating the scope of application. Calibration gives an improved parameter set, in which the form of the homeostatic drive is better constrained, and its weighting relative to the circadian drive is increased. Within the newly constrained parameter ranges, the model predicts repayment of sleep debt consistent with experiment in both quantity and distribution, asymptoting to a maximum repayment for very long deprivations. Recovery is found to depend on circadian phase, and the model predicts that it is most efficient to recover during normal sleeping phases of the circadian cycle, in terms of the amount of recovery sleep required. The form of the homeostatic drive suggests that periods of wake during recovery from sleep deprivation are phases of relative recovery, in the sense that the homeostatic drive continues to converge toward baseline levels. This undermines the concept of sleep debt, and is in agreement with experimentally restricted recovery protocols. Finally, we compare our model to the two-process model, and demonstrate the power of physiologically based modeling by correctly predicting sleep latency times following deprivation from experimental data.     

An altered balance of integrated and segregated brain activity is a marker of cognitive deficits following sleep deprivation

Sleep deprivation (SD) leads to impairments in cognitive function. Here, we tested the hypothesis that cognitive changes in the sleep-deprived brain can be explained by information processing within and between large-scale cortical networks. We acquired functional magnetic resonance imaging (fMRI) scans of 20 healthy volunteers during attention and executive tasks following a regular night of sleep, a night of SD, and a recovery nap containing nonrapid eye movement (NREM) sleep. Overall, SD was associated with increased cortex-wide functional integration, driven by a rise of integration within cortical networks. The ratio of within versus between network integration in the cortex increased further in the recovery nap, suggesting that prolonged wakefulness drives the cortex towards a state resembling sleep. This balance of integration and segregation in the sleep-deprived state was tightly associated with deficits in cognitive performance. This was a distinct and better marker of cognitive impairment than conventional indicators of homeostatic sleep pressure, as well as the pronounced thalamocortical connectivity changes that occurs towards falling asleep. Importantly, restoration of the balance between segregation and integration of cortical activity was also related to performance recovery after the nap, demonstrating a bidirectional effect. These results demonstrate that intra- and interindividual differences in cortical network integration and segregation during task performance may play a critical role in vulnerability to cognitive impairment in the sleep-deprived state.

Can the cognitive changes that result from sleep deprivation be explained by information processing within and between large-scale networks in the brain? This study shows that the ratio of within- vs between-network integration is tightly associated with deficits in cognitive performance.     

Morning Anaerobic Performance Is Not Altered by Vigilance Impairment

The aim of this study was to determine the role played by vigilance on the anaerobic performance recorded during a Wingate test performed at the bathyphase (nadir) of the circadian rhythmicity. Twenty active male participants performed a 60-s Wingate test at 6 a.m. during 3 test sessions in counter-balanced order the day after either (i) a normal reference night, (ii) a total sleep deprivation night, or (iii) a total sleep deprivation night associated with an extended simulated driving task from 9 p.m. to 5 a.m. During this task, the number of inappropriate line crossings (ILCs) was used to control and quantify the effective decrease in the level of vigilance. The main findings show that (i) vigilance of each participant was significantly altered (i.e., a drastic and progressive increase in ILCs is shown during the 7.5 hours of driving) by the sleep deprivation night associated with an extended driving task; (ii) the subjective evaluation of vigilance performed by self-rated scale revealed an increased impairment of the vigilance level between the normal reference night, the total sleep deprivation night and the total sleep deprivation night associated with an extended driving task; and (iii) the morning following this last condition, during the Wingate test, the recorded cycling biomechanical parameters (peak power, mean power and fatigue index values, power decrease, and cycling kinetic and kinematic patterns) were not significantly different from the two other conditions. Consequently, these results show that anaerobic performances recorded during a Wingate test performed at the bathyphase of the circadian rhythmicity are not altered by a drastic impairment in vigilance. These findings seem to indicate that vigilance is probably not a factor that contributes to circadian variations in anaerobic performance.