Incorporation of caffeine into a quantitative model of fatigue and sleep

A recent physiologically based model of human sleep is extended to incorporate the effects of caffeine on sleep-wake timing and fatigue. The model includes the sleep-active neurons of the hypothalamic ventrolateral preoptic area (VLPO), the wake-active monoaminergic brainstem populations (MA), their interactions with cholinergic/orexinergic (ACh/Orx) input to MA, and circadian and homeostatic drives. We model two effects of caffeine on the brain due to competitive antagonism of adenosine (Ad): (i) a reduction in the homestatic drive and (ii) an increase in cholinergic activity. By comparing the model output to experimental data, constraints are determined on the parameters that describe the action of caffeine on the brain. In accord with experiment, the ranges of these parameters imply significant variability in caffeine sensitivity between individuals, with caffeine's effectiveness in reducing fatigue being highly dependent on an individual's tolerance, and past caffeine and sleep history. Although there are wide individual differences in caffeine sensitivity and thus in parameter values, once the model is calibrated for an individual it can be used to make quantitative predictions for that individual. A number of applications of the model are examined, using exemplar parameter values, including: (i) quantitative estimation of the sleep loss and the delay to sleep onset after taking caffeine for various doses and times; (ii) an analysis of the system's stable states showing that the wake state during sleep deprivation is stabilized after taking caffeine; and (iii) comparing model output successfully to experimental values of subjective fatigue reported in a total sleep deprivation study examining the reduction of fatigue with caffeine. This model provides a framework for quantitatively assessing optimal strategies for using caffeine, on an individual basis, to maintain performance during sleep deprivation.     

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.     

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.     

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.     

Mathematical Models for Sleep-Wake Dynamics: Comparison of the Two-Process Model and a Mutual Inhibition Neuronal Model

Sleep is essential for the maintenance of the brain and the body, yet many features of sleep are poorly understood and mathematical models are an important tool for probing proposed biological mechanisms. The most well-known mathematical model of sleep regulation, the two-process model, models the sleep-wake cycle by two oscillators: a circadian oscillator and a homeostatic oscillator. An alternative, more recent, model considers the mutual inhibition of sleep promoting neurons and the ascending arousal system regulated by homeostatic and circadian processes. Here we show there are fundamental similarities between these two models. The implications are illustrated with two important sleep-wake phenomena. Firstly, we show that in the two-process model, transitions between different numbers of daily sleep episodes can be classified as grazing bifurcations. This provides the theoretical underpinning for numerical results showing that the sleep patterns of many mammals can be explained by the mutual inhibition model. Secondly, we show that when sleep deprivation disrupts the sleep-wake cycle, ostensibly different measures of sleepiness in the two models are closely related. The demonstration of the mathematical similarities of the two models is valuable because not only does it allow some features of the two-process model to be interpreted physiologically but it also means that knowledge gained from study of the two-process model can be used to inform understanding of the behaviour of the mutual inhibition model. This is important because the mutual inhibition model and its extensions are increasingly being used as a tool to understand a diverse range of sleep-wake phenomena such as the design of optimal shift-patterns, yet the values it uses for parameters associated with the circadian and homeostatic processes are very different from those that have been experimentally measured in the context of the two-process model.     

Revisiting spontaneous internal desynchrony using a quantitative model of sleep physiology

Early attempts to characterize free-running human circadian rhythms generated three notable results: 1) observed circadian periods of 25 hours (considerably longer than the now established 24.1- to 24.2-hour average intrinsic circadian period) with sleep delayed to later circadian phases than during entrainment; 2) spontaneous internal desynchrony of circadian rhythms and sleep/wake cycles--the former with an approximately 24.9-hour period, and the latter with a longer (28-68 hour) or shorter (12-20 hour) period; and 3) bicircadian (48-50 hour) sleep/wake cycles. All three results are reproduced by Kronauer et al.'s (1982) coupled oscillator model, but the physiological basis for that phenomenological model is unclear. We use a physiologically based model of hypothalamic and brain stem nuclei to investigate alternative physiological mechanisms that could underlie internal desynchrony. We demonstrate that experimental observations can be reproduced by changes in two pathways: promotion of orexinergic (Orx) wake signals, and attenuation of the circadian signal reaching hypothalamic nuclei. We reason that delayed sleep is indicative of an additional wake-promoting drive, which may be of behavioral origin, associated with removal of daily schedules and instructions given to participants. We model this by increasing Orx tone during wake, which reproduces the observed period lengthening and delayed sleep. Weakening circadian input to the ventrolateral preoptic nucleus (possibly mediated by the dorsomedial hypothalamus) causes desynchrony, with observed sleep/wake cycle period determined by degree of Orx up-regulation. During desynchrony, sleep/wake cycles are driven by sleep homeostasis, yet sleep bout length maintains circadian phase dependence. The model predicts sleep episodes are shortest when started near the temperature minimum, consistent with experimental findings. The model also correctly predicts that it is possible to transition to bicircadian rhythms from either a synchronized or desynchronized state. Our findings suggest that feedback from behavioral choices to physiology could play an important role in spontaneous internal desynchrony.     

A quantitative model of sleep-wake dynamics based on the physiology of the brainstem ascending arousal system

A quantitative, physiology-based model of the ascending arousal system is developed, using continuum neuronal population modeling, which involves averaging properties such as firing rates across neurons in each population. The model includes the ventrolateral preoptic area (VLPO), where circadian and homeostatic drives enter the system, the monoaminergic and cholinergic nuclei of the ascending arousal system, and their interconnections. The human sleep-wake cycle is governed by the activities of these nuclei, which modulate the behavioral state of the brain via diffuse neuromodulatory projections. The model parameters are not free since they correspond to physiological observables. Approximate parameter bounds are obtained by requiring consistency with physiological and behavioral measures, and the model replicates the human sleep-wake cycle, with physiologically reasonable voltages and firing rates. Mutual inhibition between the wake-promoting monoaminergic group and sleep-promoting VLPO causes ;;flip-flop' behavior, with most time spent in 2 stable steady states corresponding to wake and sleep, with transitions between them on a timescale of a few minutes. The model predicts hysteresis in the sleep-wake cycle, with a region of bistability of the wake and sleep states. Reducing the monoaminergic-VLPO mutual inhibition results in a smaller hysteresis loop. This makes the model more prone to wake-sleep transitions in both directions and makes the states less distinguishable, as in narcolepsy. The model behavior is robust across the constrained parameter ranges, but with sufficient flexibility to describe a wide range of observed phenomena.     

Dynamical properties of the two-process model for sleep-wake cycles in infantile autism

The two-process model is a scheme for the timing of sleep that consists of homeostatic (Process S) and circadian (Process C) variables. The two-process model exhibits abnormal sleep patterns such as internal desynchronization or sleep fragmentation. Early infants with autism often experience sleep difficulties. Large day-by-day changes are found in the sleep onset and waking times in autistic children. Frequent night waking is a prominent property of their sleep. Further, the sleep duration of autistic children is often fragmented. These sleep patterns in infants with autism are not fully understood yet. In the present study, the sleep patterns in autistic children were reproduced by a modified two-process model using nonlinear analysis. A nap term was introduced into the original two-process model to reproduce the sleep patterns in early infants. The nap term and the time course of Process S are mentioned in the present study. Those parameters led to bifurcation of the sleep-wake cycle in the modified two-process model. In a certain range of these parameter sets, a small external noise was amplified, and an irregular sleep-wake cycle appeared. The short duration of sleep led to another irregular sleep onset or waking. Consequently, an irregular sleep-wake cycle appeared in early infantile autism.     

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.     

Age‐related Changes in the Circadian and Homeostatic Regulation of Human Sleep

The reduction of electroencephalographic (EEG) slow‐wave activity (SWA) (EEG power density between 0.75–4.5 Hz) and spindle frequency activity, together with an increase in involuntary awakenings during sleep, represent the hallmarks of human sleep alterations with age. It has been assumed that this decrease in non‐rapid eye movement (NREM) sleep consolidation reflects an age‐related attenuation of the sleep homeostatic drive. To test this hypothesis, we measured sleep EEG characteristics (i.e., SWA, sleep spindles) in healthy older volunteers in response to high (sleep deprivation protocol) and low sleep pressure (nap protocol) conditions. Despite the fact that the older volunteers had impaired sleep consolidation and reduced SWA levels, their relative SWA response to both high and low sleep pressure conditions was similar to that of younger persons. Only in frontal brain regions did we find an age‐related diminished SWA response to high sleep pressure. On the other hand, we have clear evidence that the circadian regulation of sleep during the 40 h nap protocol was changed such that the circadian arousal signal in the evening was weaker in the older study participants. More sleep occurred during the wake maintenance zone, and subjective sleepiness ratings in the late afternoon and evening were higher than in younger participants. In addition, we found a diminished melatonin secretion and a reduced circadian modulation of REM sleep and spindle frequency—the latter was phase‐advanced relative to the circadian melatonin profile. Therefore, we favor the hypothesis that age‐related changes in sleep are due to weaker circadian regulation of sleep and wakefulness. Our data suggest that manipulations of the circadian timing system, rather than the sleep homeostat, may offer a potential strategy to alleviate age‐related decrements in sleep and daytime alertness levels.     

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.     

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.     

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.     

Homeostatic and circadian regulation of cognitive performance

Cognitive processes are crucial for human performance. Basic cognitive processes, such as attention, working memory, and executive functions, show homeostatic (time awake, sleep deprivation) and circadian (time of day) variations. Each of these cognitive processes includes several components, which contribute sequentially to the homeostatic and circadian modulation of performance. Sudden (lapses) and gradual changes in cognitive performance occur with sleep deprivation or with time of day. The time course of human cognitive processes throughout the day is relevant to the programming of different human activities. The lowest level of cognitive performance occurs during nighttime and early in the morning, a better level occurs around noon, and even higher levels occur during afternoon and evening hours. However, this time course can be modulated by conditions such as chronotype, sleep deprivation, sleep disorders or medication that affects the central nervous system.     

Sleep Restriction Masks the Influence of the Circadian Process on Sleep Propensity

Previous forced desynchrony studies have highlighted the close relationship between the circadian rhythms of core body temperature (CBT) and sleep propensity. In particular, these studies have shown that a “forbidden zone” for sleep exists on the rising limb of the CBT rhythm. In these previous studies, the length of the experimental day was either ultrashort (90?min), short (20?h), or long (28?h), and the ratio of sleep to wake was normal (i.e., 1:2). The aim of the current study was to examine the relative effects of the circadian and homeostatic processes on sleep propensity using a 28-h forced desynchrony protocol in which the ratio of sleep to wake was substantially lower than normal (i.e., 1:5). Twenty-seven healthy males lived in a time-isolation sleep laboratory for 11 consecutive days. Participants completed either a control (n?=?13) or sleep restriction (n?=?14) condition. In both conditions, the protocol consisted of 2?×?24-h baseline days followed by 8?×?28-h forced desynchrony days. On forced desynchrony days, the control group had 9.3?h in bed and 18.7?h of wake, and the sleep restriction group had 4.7?h in bed and 23.3?h of wake. For all participants, each 30-s epoch of time in bed was scored as sleep or wake based on standard polysomnography recordings, and was also assigned a circadian phase (360°?=?24?h) based on a cosine equation fitted to continuously recorded CBT data. For each circadian phase (i.e., 72?×?5° bins), sleep propensity was calculated as the percentage of epochs spent in bed scored as sleep. For the control group, there was a clear circadian rhythm in sleep propensity, with a peak of 98.5% at 5° (～05:20?h), a trough of 64.9% at 245° (～21:20?h), and an average of 82.3%. In contrast, sleep propensity for the sleep restriction group was relatively high at all circadian phases, with an average of 96.7%. For this group, the highest sleep propensity (99.0%) occurred at 60° (～09:00?h), and the lowest sleep propensity (91.3%) occurred at 265° (～22:40?h). As has been shown previously, these current data indicate that with a normal sleep-to-wake ratio, the effect of the circadian process on sleep propensity is pronounced, such that a forbidden zone for sleep exists at a phase equivalent to evening time for a normally entrained individual. However, these current data also indicate that when the ratio of sleep to wake is substantially lower than normal, this circadian effect is masked. In particular, sleep propensity is very high at all circadian phases, including those that coincide with the forbidden zone for sleep. This finding suggests that if the homeostatic pressure for sleep is sufficiently high, then the circadian drive for wakefulness can be overridden. In future studies, it will be important to determine whether or not this masking effect occurs with less severe sleep restriction, e.g., with a sleep-to-wake ratio of 1:3. (Author correspondence: charli.sargent@cqu.edu.au)     

Young Women With Major Depression Live on Higher Homeostatic Sleep Pressure Than Healthy Controls

There is mounting evidence for the involvement of the sleep-wake cycle and the circadian system in the pathogenesis of major depression. However, only a few studies so far focused on sleep and circadian rhythms under controlled experimental conditions. Thus, it remains unclear whether homeostatic sleep pressure or circadian rhythms, or both, are altered in depression. Here, the authors aimed at quantifying homeostatic and circadian sleep-wake regulatory mechanisms in young women suffering from major depressive disorder and healthy controls during a multiple nap paradigm under constant routine conditions. After an 8-h baseline night, 9 depressed women, 8 healthy young women, and 8 healthy older women underwent a 40-h multiple nap protocol (10 short sleep-wake cycles) followed by an 8-h recovery night. Polysomnographic recordings were done continuously, and subjective sleepiness was assessed. In order to measure circadian output, salivary melatonin samples were collected during scheduled wakefulness, and the circadian modulation of sleep spindles was analyzed with reference to the timing of melatonin secretion. Sleep parameters as well as non-rapid eye movement (NREM) sleep electroencephalographic (EEG) spectra were determined for collapsed left, central, and right frontal, central, parietal, and occipital derivations for the night and nap-sleep episodes in the frequency range .75–25?Hz. Young depressed women showed higher frontal EEG delta activity, as a marker of homeostatic sleep pressure, compared to healthy young and older women across both night sleep episodes together with significantly higher subjective sleepiness. Higher delta sleep EEG activity in the naps during the biological day were observed in young depressed women along with reduced nighttime melatonin secretion as compared to healthy young volunteers. The circadian modulation of sleep spindles between the biological night and day was virtually absent in healthy older women and partially impaired in young depressed women. These data provide strong evidence for higher homeostatic sleep pressure in young moderately depressed women, along with some indications for impairment of the strength of the endogenous circadian output signal involved in sleep-wake regulation. This finding may have important repercussions on the treatment of the illness as such that a selective suppression of EEG slow-wave activity could promote acute mood improvement. (Author correspondence: Christian.cajochen@upkbs.ch)     

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.     

A network model for activity-dependent sleep regulation

We develop and characterize a dynamical network model for activity-dependent sleep regulation. Specifically, in accordance with the activity-dependent theory for sleep, we view organism sleep as emerging from the local sleep states of functional units known as cortical columns; these local sleep states evolve through integration of local activity inputs, loose couplings with neighboring cortical columns, and global regulation (e.g. by the circadian clock). We model these cortical columns as coupled or networked activity-integrators that transition between sleep and waking states based on thresholds on the total activity. The model dynamics for three canonical experiments (which we have studied both through simulation and system-theoretic analysis) match with experimentally observed characteristics of the cortical-column network. Most notably, assuming connectedness of the network graph, our model predicts the recovery of the columns to a synchronized state upon temporary overstimulation of a single column and/or randomization of the initial sleep and activity-integration states. In analogy with other models for networked oscillators, our model also predicts the possibility for such phenomena as mode-locking.     

Sleep rhythmicity and homeostasis in mice with targeted disruption of mPeriod genes

In mammals, sleep is regulated by circadian and homeostatic mechanisms. The circadian component, residing in the suprachiasmatic nucleus (SCN), regulates the timing of sleep, whereas homeostatic factors determine the amount of sleep. It is believed that these two processes regulating sleep are independent because sleep amount is unchanged after SCN lesions. However, because such lesions necessarily damage neuronal connectivity, it is preferable to investigate this question in a genetic model that overcomes the confounding influence of circadian rhythmicity. Mice with disruption of both mouse Period genes (mPer)1 and mPer2 have a robust diurnal sleep-wake rhythm in an entrained light-dark cycle but lose rhythmicity in a free-run condition. Here, we examine the role of the mPer genes on the rhythmic and homeostatic regulation of sleep. In entrained conditions, when averaged over the 24-h period, there were no significant differences in waking, slow-wave sleep (SWS), or rapid eye movement (REM) sleep between mPer1, mPer2, mPer3, mPer1-mPer2 double-mutant, and wild-type mice. The mice were then kept awake for 6 h (light period 6-12), and the mPer mutants exhibited increased sleep drive, indicating an intact sleep homeostatic response in the absence of the mPer genes. In free-run conditions (constant darkness), the mPer1-mPer2 double mutants became arrhythmic, but they continued to maintain their sleep levels even after 36 days in free-running conditions. Although mPer1 and mPer2 represent key elements of the molecular clock in the SCN, they are not required for homeostatic regulation of the daily amounts of waking, SWS, or REM sleep.     

CONTRIBUTION OF CIRCADIAN PHYSIOLOGY AND SLEEP HOMEOSTASIS TO AGE-RELATED CHANGES IN HUMAN SLEEP

The circadian pacemaker and sleep homeostasis play pivotal roles in vigilance state control. It has been hypothesized that age-related changes in the human circadian pacemaker, as well as sleep homeostatic mechanisms, contribute to the hallmarks of age-related changes in sleep, that is, earlier wake time and reduced sleep consolidation. Assessments of circadian parameters in healthy young (～20–30 years old) and older people (～65–75 years old)—in the absence of the confounding effects of sleep, changes in posture, and light exposure—have demonstrated that an earlier wake time in older people is accompanied by about a 1h advance of the rhythms of core body temperature and melatonin. In addition, older people wake up at an earlier circadian phase of the body temperature and plasma melatonin rhythm. The amplitude of the endogenous circadian component of the core body temperature rhythm assessed during constant routine and forced desynchrony protocols is reduced by 20–30% in older people. Recent assessments of the intrinsic period of the human circadian pacemaker in the absence of the confounding effects of light revealed no age-related reduction of this parameter in both sighted and blind individuals. Wake maintenance and sleep initiation are not markedly affected by age except that sleep latencies are longer in older people when sleep initiation is attempted in the early morning. In contrast, major age-related reductions in the consolidation and duration of sleep occur at all circadian phases. Sleep of older people is particularly disrupted when scheduled on the rising limb of the temperature rhythm, indicating that the sleep of older people is more susceptible to arousal signals genernpated by the circadian pacemaker. Sleep-homeostatic mechanisms, as assayed by the sleep-deprivation–induced increase of EEG slow-wave activity (SWA), are operative in older people, although during both baseline sleep and recovery sleep SWA in older people remains at lower levels. The internal circadian phase advance of awakening, as well as the age-related reduction in sleep consolidation, appears related to an age-related reduction in the promotion of sleep by the circadian pacemaker during the biological night in combination with a reduced homeostatic pressure for sleep. Early morning light exposure associated with this advance of awakening in older people could reinforce the advanced circadian phase. Quantification of the interaction between sleep homeostasis and circadian rhythmicity contributes to understanding age-related changes in sleep timing and quality. (Chronobiology International, 17(3), 285–311, 2000)