Revisiting spontaneous internal desynchrony using a quantitative model of sleep physiology

A mathematical model for the role of dopamine-D2 self-regulation in the production of ultradian rhythms

Many self-motivated and goal-directed behaviours display highly flexible, approximately 4 hour ultradian (shorter than a day) oscillations. Despite lacking direct correspondence to physical cycles in the environment, these ultradian rhythms may be involved in optimizing functional interactions with the environment and reflect intrinsic neural dynamics. Current evidence supports a role of mesostriatal dopamine (DA) in the expression and propagation of ultradian rhythmicity, however, the biochemical processes underpinning these oscillations remain to be identified. Here, we use a mathematical model to investigate D2 autoreceptor-dependent DA self-regulation as the source of ultradian behavioural rhythms. DA concentration at the midbrain-striatal synapses is governed through a dual-negative feedback-loop structure, which naturally gives rise to rhythmicity. This model shows the propensity of striatal DA to produce an ultradian oscillation characterized by a flexible period that is highly sensitive to parameter variations. Circadian (approximately 24 hour) regulation consolidates the ultradian oscillations and alters their response to the phase-dependent, rapid-resetting effect of a transient excitatory stimulus. Within a circadian framework, the ultradian rhythm orchestrates behavioural activity and enhances responsiveness to an external stimulus. This suggests a role for the circadian-ultradian timekeeping hierarchy in governing organized behaviour and shaping daily experience through coordinating the motivation to engage in recurring, albeit not highly predictable events, such as social interactions.

Predicting neurobehavioral performance of resident physicians in a Randomized Order Safety Trial Evaluating Resident-Physician Schedules (ROSTERS)

OBJECTIVES

Mathematical models of human neurobehavioral performance that include the effects of acute and chronic sleep restriction can be key tools in assessment and comparison of work schedules, allowing quantitative predictions of performance when empirical assessment is impractical.

METHODS

Using such a model, we tested the hypothesis that resident physicians working an extended duration work roster, including 24-28 hours of continuous duty and up to 88 hours per week averaged over 4weeks, would have worse predicted performance than resident physicians working a rapidly cycling work roster intervention designed to reduce the duration of extended shifts. The performance metric used was attentional failures (ie, Psychomotor Vigilance Task lapses). Model input was 169 actual work and sleep schedules. Outcomes were predicted hours per week during work hours spent at moderate (equivalent to 16-20 hours of continuous wakefulness) or high (equivalent to ≥20 hours of continuous wakefulness) performance impairment.

RESULTS

The model predicted that resident physicians working an extended duration work roster would spend significantly more time at moderate impairment (p = .02, effect size=0.2) than those working a rapidly cycling work roster; this difference was most pronounced during the circadian night (p < .001). On both schedules, performance was predicted to decline from weeks 1 + 2 to weeks 3 + 4 (p < .001), but the rate of decline was significantly greater on extended duration work roster (p < .01). Predicted performance impairment was inversely related to prior sleep duration (p < .001).

CONCLUSIONS

These findings demonstrate the utility of a mathematical model to evaluate the predicted performance profile of schedules for resident physicians and others who experience chronic sleep restriction and circadian misalignment.

NREM-REM alternation complicates transitions from napping to non-napping behavior in a three-state model of sleep-wake regulation

The temporal structure of human sleep changes across development as it consolidates from the polyphasic sleep of infants to the single nighttime sleep episode typical in adults. Experimental studies have shown that changes in the dynamics of sleep need may mediate this developmental transition in sleep patterning, however, it is unknown how sleep architecture interacts with these changes. We employ a physiologically-based mathematical model that generates wake, rapid eye movement (REM) and non-REM (NREM) sleep states to investigate how NREM-REM alternation affects the transition in sleep patterns as the dynamics of the homeostatic sleep drive are varied. To study the mechanisms producing these transitions, we analyze the bifurcations of numerically-computed circle maps that represent key dynamics of the full sleep-wake network model by tracking the evolution of sleep onsets across different circadian (∼ 24 h) phases. The maps are non-monotonic and discontinuous, being composed of branches that correspond to sleep-wake cycles containing distinct numbers of REM bouts. As the rates of accumulation and decay of the homeostatic sleep drive are varied, we identify the bifurcations that disrupt a period-adding-like behavior of sleep patterns in the transition between biphasic and monophasic sleep. These bifurcations include border collision and saddle-node bifurcations that initiate new sleep patterns, period-doubling bifurcations leading to higher-order patterns of NREM-REM alternation, and intervals of bistability of sleep patterns with different NREM-REM alternations. Furthermore, patterns of NREM-REM alternation exhibit variable behaviors in different regimes of constant sleep-wake patterns. Overall, the sequence of sleep-wake behaviors, and underlying bifurcations, in the transition from biphasic to monophasic sleep in this three-state model is more complex than behavior observed in models of sleep-wake regulation that do not consider the dynamics of NREM-REM alternation. These results suggest that interactions between the dynamics of the homeostatic sleep drive and the dynamics of NREM-REM alternation may contribute to the wide interindividual variation observed when young children transition from napping to non-napping behavior.

Timing is everything: Circadian rhythms and their role in the control of sleep

Sleep and the circadian clock are intertwined and have persisted throughout history. The suprachiasmatic nucleus (SCN) orchestrates sleep by controlling circadian (Process C) and homeostatic (Process S) activities. As a "hand" on the endogenous circadian clock, melatonin is critical for sleep regulation. Light serves as a cue for sleep/wake control by activating retino-recipient cells in the SCN and subsequently suppressing melatonin. Clock genes are the molecular timekeepers that keep the 24 h cycle in place. Two main sleep and behavioural disorder diagnostic manuals have now officially recognised the importance of these processes for human health and well-being. The body's ability to respond to daily demands with the least amount of effort is maximised by carefully timing and integrating all components of sleep and waking. In the brain, the organization of timing is essential for optimal brain physiology.

A Phenomenological Mouse Circadian Pacemaker Model

Mathematical models have been used extensively in chronobiology to explore characteristics of biological clocks. In particular, for human circadian studies, the Kronauer model has been modified multiple times to describe rhythm production and responses to sensory input. This phenomenological model comprises a single set of parameters which can simulate circadian responses in humans under a variety of environmental conditions. However, corresponding models for nocturnal rodents commonly used in circadian rhythm studies are not available and may require new parameter values for different species and even strains. Moreover, due to a considerable variation in experimental data collected from mice of the same strain, within and across laboratories, a range of valid parameters is essential. This study develops a Kronauer-like model for mice by re-fitting relevant parameters to published phase response curve and period data using total least squares. Local parameter sensitivity analysis and parameter distributions determine the parameter ranges that give a near-identical model and data distribution of periods. However, the model required further parameter adjustments to match characteristics of other mouse strains, implying that the model itself detects changes in the core processes of rhythm generation and control. The model is a useful tool to understand and interpret future mouse circadian clock experiments.

Modeling the Influence of Chronic Sleep Restriction on Cortisol Circadian Rhythms, with Implications for Metabolic Disorders

Chronic sleep deficiency is prevalent in modern society and is associated with increased risk of metabolic and other diseases. While the mechanisms by which chronic sleep deficiency induces pathophysiological changes are yet to be elucidated, the hypothalamic–pituitary–adrenal (HPA) axis may be an important mediator of these effects. Cortisol, the primary hormone of the HPA axis, exhibits robust circadian rhythmicity and is moderately influenced by sleep and wake states and other physiology. Several studies have explored the effects of acute or chronic sleep deficiency (i.e., usually from self-selected chronic sleep restriction, CSR) on the HPA axis. Quantifying long-term changes in the circadian rhythm of cortisol under CSR in controlled conditions is inadequately studied due to practical limitations. We use a semi-mechanistic mathematical model of the HPA axis and the sleep/wake cycle to explore the influence of CSR on cortisol circadian rhythmicity. In qualitative agreement with experimental findings, model simulations predict that CSR results in physiologically relevant disruptions in the phase and amplitude of the cortisol rhythm. The mathematical model presented in this work provides a mechanistic framework to further explore how CSR might lead to HPA axis disruption and subsequent development of chronic metabolic complications.

Sleep Modelling across Physiological Levels

Sleep and circadian rhythms are regulated across multiple functional, spatial and temporal levels: from genes to networks of coupled neurons and glial cells, to large scale brain dynamics and behaviour. The dynamics at each of these levels are complex and the interaction between the levels is even more so, so research have mostly focused on interactions within the levels to understand the underlying mechanisms—the so-called reductionist approach. Mathematical models were developed to test theories of sleep regulation and guide new experiments at each of these levels and have become an integral part of the field. The advantage of modelling, however, is that it allows us to simulate and test the dynamics of complex biological systems and thus provides a tool to investigate the connections between the different levels and study the system as a whole. In this paper I review key models of sleep developed at different physiological levels and discuss the potential for an integrated systems biology approach for sleep regulation across these levels. I also highlight the necessity of building mechanistic connections between models of sleep and circadian rhythms across these levels.

What works for jetlag? A systematic review of non-pharmacological interventions

Jetlag is a combination of travel fatigue and circadian misalignment resulting from air travel across time zones. Routinely recommended interventions based on circadian science include timely exposure to light and darkness (scheduled sleep), but the real-world effectiveness of these and other non-circadian strategies is unknown. We systematically reviewed the evidence for non-pharmacological interventions for jetlag. PubMed, EMBASE, Scopus, and Web of Science were searched. Studies reviewed 1) involved human participants undergoing air travel with a corresponding shift in the external light-dark cycle; 2) administered a non-pharmacological intervention; 3) had a control or comparison group; and 4) examined outcomes such as jetlag symptoms, sleep, cognitive/physical performance, mood, fatigue, or circadian markers. Thirteen studies used light exposure, physical activity, diet, chiropractic treatment, or a multifaceted intervention to counteract jetlag. Nine studies found no significant change in the outcomes, three reported mixed findings, and one was positive. The null findings are likely due to poorly designed circadian interventions and neglect of contributors to travel fatigue. Higher quality studies that schedule darkness as well as light, in the periods before, during, and after flight are needed to reduce the circadian component of jetlag. Interventions should also address the stressors that contribute to travel fatigue.

Implicating a Temperature-Dependent Clock in the Regulation of Torpor Bout Duration in Classic Hibernation

Syrian hamsters may present 2 types of torpor when exposed to ambient temperatures in the winter season, from 8°C to 22°C (short photoperiod). The first is daily torpor, which is controlled by the master circadian clock of the body, located in the SCN. In this paper, we show that daily torpor bout duration is unchanged over the 8°C to 22°C temperature range, as predicted from the thermal compensation of circadian clocks. These findings contrast with the second type of torpor: multi-day torpor or classic hibernation. In multi-day torpor, bout duration increases as temperature decreases, following Arrhenius thermodynamics. We found no evidence of hysteresis from metabolic inhibition and the process was thus reversible. As a confirmation, at any temperature, the arousal from multi-day torpor occurred at about the same subjective time given by this temperature-dependent clock. The temperature-dependent clock controls the reduced torpor metabolic rate while providing a reversible recovery of circadian synchronization on return to euthermy.

A unified model of melatonin, 6-sulfatoxymelatonin, and sleep dynamics

A biophysical model of the key aspects of melatonin synthesis and excretion has been developed, which is able to predict experimental dynamics of melatonin in plasma and saliva, and of its urinary metabolite 6-sulfatoxymelatonin (aMT6s). This new model is coupled to an established model of arousal dynamics, which predicts sleep and circadian dynamics based on light exposure and times of wakefulness. The combined model thus predicts melatonin levels over the sleep-wake/dark-light cycle and enables prediction of melatonin-based circadian phase markers, such as dim light melatonin onset (DLMO) and aMT6s acrophase under conditions of normal sleep and circadian misalignment. The model is calibrated and tested against group average data from 10 published experimental studies and is found to reproduce quantitatively the key dynamics of melatonin and aMT6s, including the timing of release and amplitude, as well as response to controlled lighting and shift work.

Are Individual Differences in Sleep and Circadian Timing Amplified by Use of Artificial Light Sources?

Within the human population, there is large interindividual variability in the timing of sleep and circadian rhythms. This variability has been attributed to individual differences in sleep physiology, circadian physiology, and/or light exposure. Recent experimental evidence suggests that the latter is necessary to evoke large interindividual differences in sleep and circadian timing. We used a validated model of human sleep and circadian physiology to test the hypothesis that intrinsic differences in sleep and circadian timing are amplified by self-selected use of artificial light sources. We tested the model under 2 conditions motivated by an experimental study (Wright et al., 2013): (1) a "natural" light cycle, and (2) a "realistic" light cycle that included attenuation of light due to living indoors when natural light levels are high and use of electric light when natural light levels are low. Within these conditions, we determined the relationship between intrinsic circadian period (within the range of 23.7-24.6 h) and timing of sleep onset, sleep offset, and circadian rhythms. In addition, we simulated a work week, with fixed wake time for 5 days and free sleep times on weekends. Under both conditions, a longer intrinsic period resulted in later sleep and circadian timing. Compared to the natural condition, the realistic condition evoked more than double the variation in sleep timing across the physiological range of intrinsic circadian periods. Model predictions closely matched data from the experimental study. We found that if the intrinsic circadian period was long (>24.2 h) under the realistic condition, there was significant mismatch in sleep timing between weekdays and weekends, which is known as social jetlag. These findings indicate that individual tendencies to have very delayed schedules can be greatly amplified by self-selected modifications to the natural light/dark cycle. This has important implications for therapeutic treatment of advanced or delayed sleep phase disorders.

The effects of self-selected light-dark cycles and social constraints on human sleep and circadian timing: a modeling approach

Why do we go to sleep late and struggle to wake up on time? Historically, light-dark cycles were dictated by the solar day, but now humans can extend light exposure by switching on artificial lights. We use a mathematical model incorporating effects of light, circadian rhythmicity and sleep homeostasis to provide a quantitative theoretical framework to understand effects of modern patterns of light consumption on the human circadian system. The model shows that without artificial light humans wakeup at dawn. Artificial light delays circadian rhythmicity and preferred sleep timing and compromises synchronisation to the solar day when wake-times are not enforced. When wake-times are enforced by social constraints, such as work or school, artificial light induces a mismatch between sleep timing and circadian rhythmicity ('social jet-lag'). The model implies that developmental changes in sleep homeostasis and circadian amplitude make adolescents particularly sensitive to effects of light consumption. The model predicts that ameliorating social jet-lag is more effectively achieved by reducing evening light consumption than by delaying social constraints, particularly in individuals with slow circadian clocks or when imposed wake-times occur after sunrise. These theory-informed predictions may aid design of interventions to prevent and treat circadian rhythm-sleep disorders and social jet-lag.

Sleep Propensity under Forced Desynchrony in a Model of Arousal State Dynamics

An improvement to our current quantitative model of arousal state dynamics is presented that more accurately predicts sleep propensity as measured with sleep dynamics depending on circadian phase and prior wakefulness. A nonlinear relationship between the circadian variables within the dynamic circadian oscillator model is introduced to account for the skewed shape of the circadian rhythm of alertness that peaks just prior to the onset of the biological night (the “wake maintenance zone”) and has a minimum toward the end of the biological night. The revised circadian drive thus provides a strong inhibitory input to the sleep-active neuronal population in the evening, counteracting the excitatory effects of the increased homeostatic sleep drive as originally proposed in the opponent process model of sleep-wake regulation. The revised model successfully predicts the sleep propensity profile as reflected in the dynamics of the total sleep time, sleep onset latency, wake/sleep ratio, and sleep efficiency during a wide range of experimental protocols. Specifically, all of these sleep measures are predicted for forced desynchrony schedules with day lengths ranging from 1.5 to 42.85 h and scheduled time in bed from 0.5 to 14.27 h. The revised model is expected to facilitate more accurate predictions of sleep under normal conditions as well as during circadian misalignment, for example, during shiftwork and jetlag.

The two-process model of sleep regulation: a reappraisal

In the last three decades the two-process model of sleep regulation has served as a major conceptual framework in sleep research. It has been applied widely in studies on fatigue and performance and to dissect individual differences in sleep regulation. The model posits that a homeostatic process (Process S) interacts with a process controlled by the circadian pacemaker (Process C), with time-courses derived from physiological and behavioural variables. The model simulates successfully the timing and intensity of sleep in diverse experimental protocols. Electrophysiological recordings from the suprachiasmatic nuclei (SCN) suggest that S and C interact continuously. Oscillators outside the SCN that are linked to energy metabolism are evident in SCN-lesioned arrhythmic animals subjected to restricted feeding or methamphetamine administration, as well as in human subjects during internal desynchronization. In intact animals these peripheral oscillators may dissociate from the central pacemaker rhythm. A sleep/fast and wake/feed phase segregate antagonistic anabolic and catabolic metabolic processes in peripheral tissues. A deficiency of Process S was proposed to account for both depressive sleep disturbances and the antidepressant effect of sleep deprivation. The model supported the development of novel non-pharmacological treatment paradigms in psychiatry, based on manipulating circadian phase, sleep and light exposure. In conclusion, the model remains conceptually useful for promoting the integration of sleep and circadian rhythm research. Sleep appears to have not only a short-term, use-dependent function; it also serves to enforce rest and fasting, thereby supporting the optimization of metabolic processes at the appropriate phase of the 24-h cycle.

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.

A physiologically based model of orexinergic stabilization of sleep and wake

The orexinergic neurons of the lateral hypothalamus (Orx) are essential for regulating sleep-wake dynamics, and their loss causes narcolepsy, a disorder characterized by severe instability of sleep and wake states. However, the mechanisms through which Orx stabilize sleep and wake are not well understood. In this work, an explanation of the stabilizing effects of Orx is presented using a quantitative model of important physiological connections between Orx and the sleep-wake switch. In addition to Orx and the sleep-wake switch, which is composed of mutually inhibitory wake-active monoaminergic neurons in brainstem and hypothalamus (MA) and the sleep-active ventrolateral preoptic neurons of the hypothalamus (VLPO), the model also includes the circadian and homeostatic sleep drives. It is shown that Orx stabilizes prolonged waking episodes via its excitatory input to MA and by relaying a circadian input to MA, thus sustaining MA firing activity during the circadian day. During sleep, both Orx and MA are inhibited by the VLPO, and the subsequent reduction in Orx input to the MA indirectly stabilizes sustained sleep episodes. Simulating a loss of Orx, the model produces dynamics resembling narcolepsy, including frequent transitions between states, reduced waking arousal levels, and a normal daily amount of total sleep. The model predicts a change in sleep timing with differences in orexin levels, with higher orexin levels delaying the normal sleep episode, suggesting that individual differences in Orx signaling may contribute to chronotype. Dynamics resembling sleep inertia also emerge from the model as a gradual sleep-to-wake transition on a timescale that varies with that of Orx dynamics. The quantitative, physiologically based model developed in this work thus provides a new explanation of how Orx stabilizes prolonged episodes of sleep and wake, and makes a range of experimentally testable predictions, including a role for Orx in chronotype and sleep inertia.

Physiologically-based modeling of sleep-wake regulatory networks

Mathematical modeling has played a significant role in building our understanding of sleep-wake and circadian behavior. Over the past 40 years, phenomenological models, including the two-process model and oscillator models, helped frame experimental results and guide progress in understanding the interaction of homeostatic and circadian influences on sleep and understanding the generation of rapid eye movement sleep cycling. Recent advances in the clarification of the neural anatomy and physiology involved in the regulation of sleep and circadian rhythms have motivated the development of more detailed and physiologically-based mathematical models that extend the approach introduced by the classical reciprocal-interaction model. Using mathematical formalisms developed in the field of computational neuroscience to model neuronal population activity, these models investigate the dynamics of proposed conceptual models of sleep-wake regulatory networks with a focus on generating appropriate sleep and wake state transition patterns as well as simulating disease states and experimental protocols. In this review, we discuss several recent physiologically-based mathematical models of sleep-wake regulatory networks. We identify common features among these models in their network structures, model dynamics and approaches for model validation. We describe how the model analysis technique of fast-slow decomposition, which exploits the naturally occurring multiple timescales of sleep-wake behavior, can be applied to understand model dynamics in these networks. Our purpose in identifying commonalities among these models is to propel understanding of both the mathematical models and their underlying conceptual models, and focus directions for future experimental and theoretical work.

Effects of Rotation Interval on Sleepiness and Circadian Dynamics on Forward Rotating 3-Shift Systems

A physiologically based mathematical model of sleep-wake cycles is used to examine the effects of shift rotation interval (RI) (i.e., the number of days spent on each shift) on sleepiness and circadian dynamics on forward rotating 3-shift schedules. The effects of the schedule start time on the mean shift sleepiness are also demonstrated but are weak compared to the effects of RI. The dynamics are studied for a parameter set adjusted to match a most common natural sleep pattern (i.e., sleep between 0000 and 0800) and for common light conditions (i.e., 350 lux of shift lighting, 200 lux of daylight, 100 lux of artificial lighting during nighttime, and 0 lux during sleep). Mean shift sleepiness on a rotating schedule is found to increase with RI, reach maximum at intermediate RI=6 d, and then decrease. Complete entrainment to shifts within the schedules is not achieved at RI≤10 d. However, circadian oscillations synchronize to the rotation cycles, with RI=1,2 d and RI≥6 d demonstrating regular periodic changes of the circadian rhythm. At rapid rotation, circadian phase stays within a small 4-h interval, whereas slow rotation leads to around-the-clock transitions of the circadian phase with constantly delayed sleep times. Schedules with RI=3-5 d are not able to entrain the circadian rhythms, even in the absence of external circadian disturbances like social commitments and days off. To understand the circadian dynamics on the rotating shift schedules, a shift response map is developed, showing the direction of circadian change (i.e., delay or advance) depending on the relation between the shift start time and actual circadian phase. The map predicts that the un-entrained dynamics come from multiple transitions between advance and delay behavior on the shifts in the schedules. These are primarily caused by the imbalance between the amount of delay and advance on the different shift types within the schedule. Finally, it is argued that shift response maps can aid in the development of shift schedules with desired circadian characteristics.

Body Temperature Predicts the Direction of Internal Desynchronization in Humans Isolated from Time Cues

This publication presents a new analysis of experiments that were carried out in human subjects in isolation from time cues, under supervision of Jürgen Aschoff and Rütger Wever at the Max Planck Institute for Behavioural Physiology (Erling-Andechs, Germany, 1964-1974). Mean rectal temperatures (tb) were compared between subjects who showed internal desynchronization (ID) and internal synchronization (IS) of the endogenous rhythms of sleep-wakefulness and of body temperature. The results showed that tb was reduced in long ID (circadian sleep-wake cycle length [τSW] > 27 h) and increased in short ID (τSW < 22 h) relative to IS. In subjects with both ID and IS sections in the complete record, these differences were also found when comparing only the IS sections: Low tb during IS predicts the later occurrence of long ID, and high tb predicts the incidence of short ID. While this association is associated with sex differences in tb, it also occurs within each sex. To the extent that the variation in tb reflects the variation in heat production (metabolic rate), the results are consistent with the proposition that the spontaneous frequency of the human sleep-wake oscillator is associated with the metabolic rate, as suggested on the basis of the proportionality of meal frequency and sleep-wake frequency. The finding thus has implications for our views on spontaneous sleep timing.

Modeling Interindividual Differences in Spontaneous Internal Desynchrony Patterns

A physiologically based mathematical model of a putative sleep-wake regulatory network is used to investigate the transition from typical human sleep patterns to spontaneous internal desynchrony behavior observed under temporal isolation conditions. The model sleep-wake regulatory network describes the neurotransmitter-mediated interactions among brainstem and hypothalamic neuronal populations that participate in the transitions between wake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. Physiologically based interactions among these sleep-wake centers and the suprachiasmatic nucleus (SCN), whose activity is driven by an established circadian oscillator model, mediate circadian modulation of sleep-wake behavior. When the sleep-wake and circadian rhythms are synchronized, the model simulates stereotypically normal human sleep-wake behavior within the limits of individual variation, including typical NREM-REM cycling across the night. When effects of temporal isolation are simulated by increasing the period of the sleep-wake cycle, the model replicates spontaneous internal desynchrony with the appropriate dependence of multiple features of REM sleep on circadian phase. In temporal isolation experiments, subjects have exhibited different desynchronized sleep-wake behaviors. Our model can generate similar ranges of desynchronized behaviors by variations in the period of the sleep-wake cycle and the strength of interactions between the SCN and the sleep-wake centers. Analysis of the model suggests that similar mechanisms underlie several different desynchronized behaviors and that the phenomenon of phase trapping may be dependent on SCN modulation of REM sleep-promoting centers. These results provide predictions for physiologically plausible mechanisms underlying interindividual variations in sleep-wake behavior observed during temporal isolation experiments.

A mathematical model of the circadian phase-shifting effects of exogenous melatonin

Melatonin is endogenously produced and released in humans during nighttime darkness and is suppressed by ocular light exposure. Exogenous melatonin is used to induce circadian phase shifts and sleep. The circadian phase-shifting ability of a stimulus (e.g., melatonin or light) relative to its timing may be displayed as a phase response curve (PRC). Published PRCs to exogenous melatonin show a transition from phase advances to delays approximately 1 h after dim light melatonin onset. A previously developed mathematical model simulates endogenous production and clearance of melatonin as a function of circadian phase, light-induced suppression, and resetting of circadian phase by light. We extend this model to include the pharmacokinetics of oral exogenous melatonin and phase-shifting effects via melatonin receptors in the suprachiasmatic nucleus of the mammalian hypothalamus. Model parameters are fit using 2 data sets: (1) blood melatonin concentration following a 0.3- or 5.0-mg dose, and (2) a PRC to a 3.0-mg dose of melatonin. After fitting to the 3.0-mg PRC, the model correctly predicts that, by comparison, the 0.5-mg PRC is slightly decreased in amplitude and shifted to a later circadian phase. This model also reproduces blood concentration profiles of various melatonin preparations that differ only in absorption rate and percentage degradation by first-pass hepatic metabolism. This model can simulate experimental protocols using oral melatonin, with potential application to guide dose size and timing to optimally shift and entrain circadian rhythms.

Mammalian rest/activity patterns explained by physiologically based modeling

Circadian rhythms are fundamental to life. In mammals, these rhythms are generated by pacemaker neurons in the suprachiasmatic nucleus (SCN) of the hypothalamus. The SCN is remarkably consistent in structure and function between species, yet mammalian rest/activity patterns are extremely diverse, including diurnal, nocturnal, and crepuscular behaviors. Two mechanisms have been proposed to account for this diversity: (i) modulation of SCN output by downstream nuclei, and (ii) direct effects of light on activity. These two mechanisms are difficult to disentangle experimentally and their respective roles remain unknown. To address this, we developed a computational model to simulate the two mechanisms and their influence on temporal niche. In our model, SCN output is relayed via the subparaventricular zone (SPZ) to the dorsomedial hypothalamus (DMH), and thence to ventrolateral preoptic nuclei (VLPO) and lateral hypothalamus (LHA). Using this model, we generated rich phenotypes that closely resemble experimental data. Modulation of SCN output at the SPZ was found to generate a full spectrum of diurnal-to-nocturnal phenotypes. Intriguingly, we also uncovered a novel mechanism for crepuscular behavior: if DMH/VLPO and DMH/LHA projections act cooperatively, daily activity is unimodal, but if they act competitively, activity can become bimodal. In addition, we successfully reproduced diurnal/nocturnal switching in the rodent Octodon degu using coordinated inversions in both masking and circadian modulation. Finally, the model correctly predicted the SCN lesion phenotype in squirrel monkeys: loss of circadian rhythmicity and emergence of ∼4-h sleep/wake cycles. In capturing these diverse phenotypes, the model provides a powerful new framework for understanding rest/activity patterns and relating them to underlying physiology. Given the ubiquitous effects of temporal organization on all aspects of animal behavior and physiology, this study sheds light on the physiological changes required to orchestrate adaptation to various temporal niches.

Adaptation to shift work: physiologically based modeling of the effects of lighting and shifts' start time

Shift work has become an integral part of our life with almost 20% of the population being involved in different shift schedules in developed countries. However, the atypical work times, especially the night shifts, are associated with reduced quality and quantity of sleep that leads to increase of sleepiness often culminating in accidents. It has been demonstrated that shift workers’ sleepiness can be improved by a proper scheduling of light exposure and optimizing shifts timing. Here, an integrated physiologically-based model of sleep-wake cycles is used to predict adaptation to shift work in different light conditions and for different shift start times for a schedule of four consecutive days of work. The integrated model combines a model of the ascending arousal system in the brain that controls the sleep-wake switch and a human circadian pacemaker model. To validate the application of the integrated model and demonstrate its utility, its dynamics are adjusted to achieve a fit to published experimental results showing adaptation of night shift workers (n = 8) in conditions of either bright or regular lighting. Further, the model is used to predict the shift workers’ adaptation to the same shift schedule, but for conditions not considered in the experiment. The model demonstrates that the intensity of shift light can be reduced fourfold from that used in the experiment and still produce good adaptation to night work. The model predicts that sleepiness of the workers during night shifts on a protocol with either bright or regular lighting can be significantly improved by starting the shift earlier in the night, e.g.; at 21∶00 instead of 00∶00. Finally, the study predicts that people of the same chronotype, i.e. with identical sleep times in normal conditions, can have drastically different responses to shift work depending on their intrinsic circadian and homeostatic parameters.

Arousal state feedback as a potential physiological generator of the ultradian REM/NREM sleep cycle

Human sleep episodes are characterized by an approximately 90-min ultradian oscillation between rapid eye movement (REM) and non-REM (NREM) sleep stages. The source of this oscillation is not known. Pacemaker mechanisms for this rhythm have been proposed, such as a reciprocal interaction network, but these fail to account for documented homeostatic regulation of both sleep stages. Here, two candidate mechanisms are investigated using a simple model that has stable states corresponding to Wake, REM sleep, and NREM sleep. Unlike other models of the ultradian rhythm, this model of sleep dynamics does not include an ultradian pacemaker, nor does it invoke a hypothetical homeostatic process that exists purely to drive ultradian rhythms. Instead, only two inputs are included: the homeostatic drive for Sleep and the circadian drive for Wake. These two inputs have been the basis for the most influential Sleep/Wake models, but have not previously been identified as possible ultradian rhythm generators. Using the model, realistic ultradian rhythms are generated by arousal state feedback to either the homeostatic or circadian drive. For the proposed 'homeostatic mechanism', homeostatic pressure increases in Wake and REM sleep, and decreases in NREM sleep. For the proposed 'circadian mechanism', the circadian drive is up-regulated in Wake and REM sleep, and is down-regulated in NREM sleep. The two mechanisms are complementary in the features they capture. The homeostatic mechanism reproduces experimentally observed rebounds in NREM sleep duration and intensity following total sleep deprivation, and rebounds in both NREM sleep intensity and REM sleep duration following selective REM sleep deprivation. The circadian mechanism does not reproduce sleep state rebounds, but more accurately reproduces the temporal patterns observed in a normal night of sleep. These findings have important implications in terms of sleep physiology and they provide a parsimonious explanation for the observed ultradian rhythm of REM/NREM sleep.

Age-related changes in sleep and circadian rhythms: impact on cognitive performance and underlying neuroanatomical networks

Circadian and homeostatic sleep-wake regulatory processes interact in a fine tuned manner to modulate human cognitive performance. Dampening of the circadian alertness signal and attenuated deterioration of psychomotor vigilance in response to elevated sleep pressure with aging change this interaction pattern. As evidenced by neuroimaging studies, both homeostatic sleep pressure and circadian sleep-wake promotion impact on cognition-related cortical and arousal-promoting subcortical brain regions including the thalamus, the anterior hypothalamus, and the brainstem locus coeruleus (LC). However, how age-related changes in circadian and homeostatic processes impact on the cerebral activity subtending waking performance remains largely unexplored. Post-mortem studies point to neuronal degeneration in the SCN and age-related modifications in the arousal-promoting LC. Alongside, cortical frontal brain areas are particularly susceptible both to aging and misalignment between circadian and homeostatic processes. In this perspective, we summarize and discuss here the potential neuroanatomical networks underlying age-related changes in circadian and homeostatic modulation of waking performance, ranging from basic arousal to higher order cognitive behaviors.

Circadian profiles in young people during the early stages of affective disorder

Although disturbances of the circadian system are strongly linked to affective disorders, no known studies have examined melatonin profiles in young people in early stages of illness. In this study, 44 patients with an affective disorder underwent clinical and neuropsychological assessments. They were then rated by a psychiatrist according to a clinical staging model and were categorized as having an 'attenuated syndrome' or an 'established disorder'. During the evening, salivary melatonin was sampled under dim light conditions over an 8-h interval and for each patient, the time of melatonin onset, total area under the curve and phase angle (difference between time of melatonin onset and time of habitual sleep onset) were computed. Results showed that there was no difference in the timing of melatonin onset across illness stages. However, area under the curve analyses showed that those patients with 'established disorders' had markedly reduced levels of melatonin secretion, and shorter phase angles, relative to those with 'attenuated syndromes'. These lower levels, in turn, were related to lower subjective sleepiness, and poorer performance on neuropsychological tests of verbal memory. Overall, these results suggest that for patients with established illness, dysfunction of the circadian system relates clearly to functional features and markers of underlying neurobiological change. Although the interpretation of these results would be greatly enhanced by control data, this work has important implications for the early delivery of chronobiological interventions in young people with affective disorders.

Familial circadian rhythm disorder in the diurnal primate, Macaca mulatta

In view of the inverse temporal relationship of central clock activity to physiological or behavioral outputs in diurnal and nocturnal species, understanding the mechanisms and physiological consequences of circadian disorders in humans would benefit from studies in a diurnal animal model, phylogenetically close to humans. Here we report the discovery of the first intrinsic circadian disorder in a family of diurnal non-human primates, the rhesus monkey. The disorder is characterized by a combination of delayed sleep phase, relative to light-dark cycle, mutual desynchrony of intrinsic rhythms of activity, food intake and cognitive performance, enhanced nighttime feeding or, in the extreme case, intrinsic asynchrony. The phenotype is associated with normal length of intrinsic circadian period and requires an intact central clock, as demonstrated by an SCN lesion. Entrainment to different photoperiods or melatonin administration does not eliminate internal desynchrony, though melatonin can temporarily reinstate intrinsic activity rhythms in the animal with intrinsic asynchrony. Entrainment to restricted feeding is highly effective in animals with intrinsic or SCN lesion-induced asynchrony. The large isolated family of rhesus macaques harboring the disorder provides a powerful new tool for translational research of regulatory circuits underlying circadian disorders and their effective treatment.

Exploring Sleepiness and Entrainment on Permanent Shift Schedules in a Physiologically Based Model

The effects of permanent shift work on entrainment and sleepiness are examined using a mathematical model that combines a model of sleep-wake switch in the brain with a model of the human circadian pacemaker entrained by light and nonphotic inputs. The model is applied to 8-hour permanent shift schedules to understand the basic mechanisms underlying changes of entrainment and sleepiness. Average sleepiness is shown to increase during the first days on the night and evening schedules, that is, shift start times between 0000 to 0700 h and 1500 to 2200 h, respectively. After the initial increase, sleepiness decreases and stabilizes via circadian re-entrainment to the cues provided by the shifts. The increase in sleepiness until entrainment is achieved is strongly correlated with the phase difference between a circadian oscillator entrained to the ambient light and one entrained to the shift schedule. The higher this phase difference, the larger the initial increase in sleepiness. When entrainment is achieved, sleepiness stabilizes and is the same for different shift onsets within the night or evening schedules. The simulations reveal the presence of a critical shift onset around 2300 h that separates schedules, leading to phase advance (night shifts) and phase delay (evening shifts) of the circadian pacemaker. Shifts starting around this time take longest to entrain and are expected to be the worst for long-term sleepiness and well-being of the workers. Surprisingly, we have found that the circadian pacemaker entrains faster to night schedules than to evening ones. This is explained by the longer photoperiod on night schedules compared to evening. In practice, this phenomenon is difficult to see due to days off on which workers switch to free sleep-wake activity. With weekends, the model predicts that entrainment is never achieved on evening and night schedules unless the workers follow the same sleep routine during weekends as during work days. Overall, the model supports experimental observations, providing new insights into the mechanisms and allowing the examination of conditions that are not accessible experimentally.