Simulation of circadian rhythm generation in the suprachiasmatic nucleus with locally coupled self-sustained oscillators

The seasons within: a theoretical perspective on photoperiodic entrainment and encoding

Circadian clocks are internal timing devices that have evolved as an adaption to the omnipresent natural 24 h rhythmicity of daylight intensity. Properties of the circadian system are photoperiod dependent. The phase of entrainment varies systematically with season. Plastic photoperiod-dependent re-arrangements in the mammalian circadian core pacemaker yield an internal representation of season. Output pathways of the circadian clock regulate photoperiodic responses such as flowering time in plants or hibernation in mammals. Here, we review the concepts of seasonal entrainment and photoperiodic encoding. We introduce conceptual phase oscillator models as their high level of abstraction, but, yet, intuitive interpretation of underlying parameters allows for a straightforward analysis of principles that determine entrainment characteristics. Results from this class of models are related and discussed in the context of more complex conceptual amplitude-phase oscillators as well as contextual molecular models that take into account organism, tissue, and cell-type-specific details.

Cut the noise or couple up: Coordinating circadian and synthetic clocks

Circadian clocks are important to much of life on Earth and are of inherent interest to humanity, implicated in fields ranging from agriculture and ecology to developmental biology and medicine. New techniques show that it is not simply the presence of clocks, but coordination between them that is critical for complex physiological processes across the kingdoms of life. Recent years have also seen impressive advances in synthetic biology to the point where parallels can be drawn between synthetic biological and circadian oscillators. This review will emphasize theoretical and experimental studies that have revealed a fascinating dichotomy of coupling and heterogeneity among circadian clocks. We will also consolidate the fields of chronobiology and synthetic biology, discussing key design principles of their respective oscillators.

Network Structure of the Master Clock Is Important for Its Primary Function

A master clock located in the suprachiasmatic nucleus (SCN) regulates the circadian rhythm of physiological and behavioral activities in mammals. The SCN has two main functions in the regulation: an endogenous clock produces the endogenous rhythmic signal in body rhythms, and a calibrator synchronizes the body rhythms to the external light-dark cycle. These two functions have been determined to depend on either the dynamic behaviors of individual neurons or the whole SCN neuronal network. In this review, we first introduce possible network structures for the SCN, as revealed by time series analysis from real experimental data. It was found that the SCN network is heterogeneous and sparse, that is, the average shortest path length is very short, some nodes are hubs with large node degrees but most nodes have small node degrees, and the average node degree of the network is small. Secondly, the effects of the SCN network structure on the SCN function are reviewed based on mathematical models of the SCN network. It was found that robust rhythms with large amplitudes, a high synchronization between SCN neurons and a large entrainment ability exists mainly in small-world and scale-free type networks, but not other types. We conclude that the SCN most probably is an efficient small-world type or scale-free type network, which drives SCN function.

Modelling the functional roles of synaptic and extra-synaptic γ-aminobutyric acid receptor dynamics in circadian timekeeping

In the suprachiasmatic nucleus (SCN), γ-aminobutyric acid (GABA) is a primary neurotransmitter. GABA can signal through two types of GABAA receptor subunits, often referred to as synaptic GABAA (gamma subunit) and extra-synaptic GABAA (delta subunit). To test the functional roles of these distinct GABAA in regulating circadian rhythms, we developed a multicellular SCN model where we could separately compare the effects of manipulating GABA neurotransmitter or receptor dynamics. Our model predicted that blocking GABA signalling modestly increased synchrony among circadian cells, consistent with published SCN pharmacology. Conversely, the model predicted that lowering GABAA receptor density reduced firing rate, circadian cell fraction, amplitude and synchrony among individual neurons. When we tested these predictions, we found that the knockdown of delta GABAA reduced the amplitude and synchrony of clock gene expression among cells in SCN explants. The model further predicted that increasing gamma GABAA densities could enhance synchrony, as opposed to increasing delta GABAA densities. Overall, our model reveals how blocking GABAA receptors can modestly increase synchrony, while increasing the relative density of gamma over delta subunits can dramatically increase synchrony. We hypothesize that increased gamma GABAA density in the winter could underlie the tighter phase relationships among SCN cells.

A common role for astrocytes in rhythmic behaviours?

Astrocytes are a functionally diverse form of glial cell involved in various aspects of nervous system infrastructure, from the metabolic and structural support of neurons to direct neuromodulation of synaptic activity. Investigating how astrocytes behave in functionally related circuits may help us understand whether there is any conserved logic to the role of astrocytes within neuronal networks. Astrocytes are implicated as key neuromodulatory cells within neural circuits that control a number of rhythmic behaviours such as breathing, locomotion and circadian sleep-wake cycles. In this review, we examine the evidence that astrocytes are directly involved in the regulation of the neural circuits underlying six different rhythmic behaviours: locomotion, breathing, chewing, gastrointestinal motility, circadian sleep-wake cycles and oscillatory feeding behaviour. We discuss how astrocytes are integrated into the neuronal networks that regulate these behaviours, and identify the potential gliotransmission signalling mechanisms involved. From reviewing the evidence of astrocytic involvement in a range of rhythmic behaviours, we reveal a heterogenous array of gliotransmission mechanisms, which help to regulate neuronal networks. However, we also observe an intriguing thread of commonality, in the form of purinergic gliotransmission, which is frequently utilised to facilitate feedback inhibition within rhythmic networks to constrain a given behaviour within its operational range.

Topology-induced dynamics in a network of synthetic oscillators with piecewise affine approximation

In synthetic biology approaches, minimal systems are used to reproduce complex molecular mechanisms that appear in the core functioning of multi-cellular organisms. In this paper, we study a piecewise affine model of a synthetic two-gene oscillator and prove existence and stability of a periodic solution for all parameters in a given region. Motivated by the synchronization of circadian clocks in a cluster of cells, we next consider a network of N identical oscillators under diffusive coupling to investigate the effect of the topology of interactions in the network's dynamics. Our results show that both all-to-all and one-to-all coupling topologies may introduce new stable steady states in addition to the expected periodic orbit. Both topologies admit an upper bound on the coupling parameter that prevents the generation of new steady states. However, this upper bound is independent of the number of oscillators in the network and less conservative for the one-to-all topology.

Global sleep homeostasis reflects temporally and spatially integrated local cortical neuronal activity

Sleep homeostasis manifests as a relative constancy of its daily amount and intensity. Theoretical descriptions define 'Process S', a variable with dynamics dependent on global sleep-wake history, and reflected in electroencephalogram (EEG) slow wave activity (SWA, 0.5-4 Hz) during sleep. The notion of sleep as a local, activity-dependent process suggests that activity history must be integrated to determine the dynamics of global Process S. Here, we developed novel mathematical models of Process S based on cortical activity recorded in freely behaving mice, describing local Process S as a function of the deviation of neuronal firing rates from a locally defined set-point, independent of global sleep-wake state. Averaging locally derived Processes S and their rate parameters yielded values resembling those obtained from EEG SWA and global vigilance states. We conclude that local Process S dynamics reflects neuronal activity integrated over time, and global Process S reflects local processes integrated over space.

Coherency of circadian rhythms in the SCN is governed by the interplay of two coupling factors

Circadian clocks are autonomous oscillators driving daily rhythms in physiology and behavior. In mammals, a network of coupled neurons in the suprachiasmatic nucleus (SCN) is entrained to environmental light-dark cycles and orchestrates the timing of peripheral organs. In each neuron, transcriptional feedbacks generate noisy oscillations. Coupling mediated by neuropeptides such as VIP and AVP lends precision and robustness to circadian rhythms. The detailed coupling mechanisms between SCN neurons are debated. We analyze organotypic SCN slices from neonatal and adult mice in wild-type and multiple knockout conditions. Different degrees of rhythmicity are quantified by pixel-level analysis of bioluminescence data. We use empirical orthogonal functions (EOFs) to characterize spatio-temporal patterns. Simulations of coupled stochastic single cell oscillators can reproduce the diversity of observed patterns. Our combination of data analysis and modeling provides deeper insight into the enormous complexity of the data: (1) Neonatal slices are typically stronger oscillators than adult slices pointing to developmental changes of coupling. (2) Wild-type slices are completely synchronized and exhibit specific spatio-temporal patterns of phases. (3) Some slices of Cry double knockouts obey impaired synchrony that can lead to co–existing rhythms (“splitting”). (4) The loss of VIP-coupling leads to desynchronized rhythms with few residual local clusters. Additional information was extracted from co–culturing slices with rhythmic neonatal wild-type SCNs. These co–culturing experiments were simulated using external forcing terms representing VIP and AVP signaling. The rescue of rhythmicity via co–culturing lead to surprising results, since a cocktail of AVP-antagonists improved synchrony. Our modeling suggests that these counter-intuitive observations are pointing to an antagonistic action of VIP and AVP coupling. Our systematic theoretical and experimental study shows that dual coupling mechanisms can explain the astonishing complexity of spatio-temporal patterns in SCN slices.

The mammalian circadian clock is orchestrated by a network of coupled neurons. Brain slice preparations allow the analysis of coupling mechanisms mediated by neuropeptides. From bioluminescence recordings, we extract single cell characteristics such as period, amplitude and damping rate. Our data-based stochastic network model involves local coupling between cells and additional external forcing. Available experimental data guide our simulations with two distinct coupling and forcing mechanisms representing the neuropeptides VIP and AVP. We compare our simulations with experiments from neonatal and adult wild-type brain slices and multiple knockouts. Furthermore, we study co–culturing of slices with synchronized neonatal wild-type slices. The extreme complexity of the spatio-temporal patterns is quantified using empirical orthogonal functions (EOFs). The experimental reduction of AVP coupling leads to surprising observations. In double knockouts, inhibition of AVP signaling can improve synchrony, whereas, in triple knockouts, coherency is reduced. Our network modeling shows that these counter-intuitive observations can be explained by an antagonistic action of VIP and AVP signaling. The agreement of experiments and simulations suggests that quite complex spatio-temporal patterns can appear as emergent properties of oscillator networks with dual coupling mechanisms.

Protein sequestration versus Hill-type repression in circadian clock models

Circadian (∼24 h) clocks are self-sustained endogenous oscillators with which organisms keep track of daily and seasonal time. Circadian clocks frequently rely on interlocked transcriptional-translational feedback loops to generate rhythms that are robust against intrinsic and extrinsic perturbations. To investigate the dynamics and mechanisms of the intracellular feedback loops in circadian clocks, a number of mathematical models have been developed. The majority of the models use Hill functions to describe transcriptional repression in a way that is similar to the Goodwin model. Recently, a new class of models with protein sequestration-based repression has been introduced. Here, the author discusses how this new class of models differs dramatically from those based on Hill-type repression in several fundamental aspects: conditions for rhythm generation, robust network designs and the periods of coupled oscillators. Consistently, these fundamental properties of circadian clocks also differ among Neurospora, Drosophila, and mammals depending on their key transcriptional repression mechanisms (Hill-type repression or protein sequestration). Based on both theoretical and experimental studies, this review highlights the importance of careful modelling of transcriptional repression mechanisms in molecular circadian clocks.

Neuronal oscillations on an ultra-slow timescale: daily rhythms in electrical activity and gene expression in the mammalian master circadian clockwork

Neuronal oscillations of the brain, such as those observed in the cortices and hippocampi of behaving animals and humans, span across wide frequency bands, from slow delta waves (0.1 Hz) to ultra-fast ripples (600 Hz). Here, we focus on ultra-slow neuronal oscillators in the hypothalamic suprachiasmatic nuclei (SCN), the master daily clock that operates on interlocking transcription-translation feedback loops to produce circadian rhythms in clock gene expression with a period of near 24 h (< 0.001 Hz). This intracellular molecular clock interacts with the cell's membrane through poorly understood mechanisms to drive the daily pattern in the electrical excitability of SCN neurons, exhibiting an up-state during the day and a down-state at night. In turn, the membrane activity feeds back to regulate the oscillatory activity of clock gene programs. In this review, we emphasise the circadian processes that drive daily electrical oscillations in SCN neurons, and highlight how mathematical modelling contributes to our increasing understanding of circadian rhythm generation, synchronisation and communication within this hypothalamic region and across other brain circuits.

Synchronizing Genetic Oscillators by Signaling Molecules

The authors examine collective rhythms in a general multicell system with both linearly diffusive and nondiffusive couplings. The effect of coupling on synchronization through intercellular signaling in a population of Escherichia coli cells is studied. In particular, a synchronization solution is given through the auxiliary individual system for 2 types of couplings. The sufficient conditions for the global synchronization of such a coupled system are derived based on the Lyapunov function method. The authors show that an appropriate design of the coupling and the inner-linking matrix can ensure global synchronization of the coupled synthetic biological system. Moreover, they demonstrate that the dynamics of an individual cell with coupling and without coupling may be qualitatively different; one is oscillatory, and the other is steady state. The change from a nonoscillatory state to an oscillatory one is induced by appropriate coupling, which also entrains all cells to synchronization. These results establish not only a theoretical foundation but also a quantitative basis for understanding the essential cooperative dynamics, such as collective rhythms or synchronization, in a population of cells.

Simulation of Day-Length Encoding in the SCN: From Single-Cell to Tissue-Level Organization

The circadian pacemaker of the SCN is a heterogeneous structure containing many single-cell oscillators that display phase differences in gene expression and electrical activity rhythms. Thus far, it is unknown how single neurons contribute to the population signal measured from the SCN. The authors used single-unit electrical activity rhythms that have previously been recorded in SCN slices and investigated in simulation studies how changes in pattern shape and distribution of single neurons alter the ensemble activity rhythm of the SCN. The results were compared with recorded ensemble rhythms. The simulations show that single units should be distributed in phase to render the recorded multiunit waveform and that different distributions can account for the multiunit pattern of the SCN, including a bimodal distribution. Vice versa, the authors show that the single-unit distribution cannot be inferred from the ensemble pattern. Photoperiodic encoding by the SCN relies on changes in waveform of the neuronal output from the SCN and received special attention in this study’s simulations. The authors show that a broadening or narrowing of the multiunit pattern can be based on changes in phase differences between neurons, as well as on changes in the circadian pattern of individual neurons. However, these mechanisms give rise to differences in the maximal discharge level of the multiunit pattern, leading to testable predictions to distinguish between the 2 mechanisms. If single units broaden their activity pattern in long days, the maximum frequency of the multiunit activity should increase, while an increase in phase difference between the single-unit activity rhythms should lead to a decrement in maximum frequency. The simulations also show that coding for day-length by an evening and morning oscillator is not self-evident and will only work under a limited set of conditions in which the distribution within each component and temporal distance between the components is taken into account. While the simulations were based on single-cell and multiunit electrical activity patterns, they are also relevant for understanding the relation between single-cell and population molecular expression profiles.

Why and How Do We Model Circadian Rhythms?

In our attempts to understand the circadian system, we unavoidably rely on abstractions. Instead of describing the behavior of the circadian system in all its complexity, we try to derive basic features from which we form a global concept on how the system works. Such a basic concept is a model of reality. The author discusses why it is advantageous or even necessary to transform conceptual models into mathematical formulations. As examples to demonstrate those advantages, the author reviews 4 types of mathematical models: negative feedback models thought to operate within pacemaker cells, models on coupling between pacemaker cells to generate pacemaker output, oscillator models describing the behavior of the composite circadian pacemaker, and models describing how the circadian pacemaker influences behavior.

Modeling the Behavior of Coupled Cellular Circadian Oscillators in the Suprachiasmatic Nucleus

The suprachiasmatic nucleus (SCN) in the hypothalamus is the site of the master circadian clock in mammals, a complex tissue composed of multiple, coupled, single-cell circadian oscillators. Mathematical modeling is now providing insights on how individual SCN cells might interact and assemble to create an integrated pacemaker that governs the circadian behavior of whole animals. In this article, we will discuss the neurobiological constraints for modeling SCN behavior, system precision, implications of cellular heterogeneity, and analysis of heterogeneously coupled oscillator networks. Mathematical approaches will be critical for better understanding intercellular interactions within the SCN.

Deconstructing Circadian Rhythmicity with Models and Manipulations

A master brain clock, localized to the hypothalamic suprachiasmatic nucleus (SCN), coordinates daily rhythms of physiology and behavior. Within the SCN, interconnected individual neurons are oscillators that, as an ensemble, function to send a coherent timing signal to the brain and body. However, individually, these neurons display different amplitudes, periods, and phases of oscillation. The dynamic properties of the SCN have been characterized over several spatial levels of analysis, from proteins to cells to tissues, and over several temporal ranges, from milliseconds to weeks. Modeling tools guide empirical research in this complex and multiscale spatiotemporal environment. Given that the SCN is a prototypical example of oscillating neural systems, principles of its organization hold promise as general prototypes of rhythms in other frequencies.

Distinct roles for GABA across multiple timescales in mammalian circadian timekeeping

The suprachiasmatic nuclei (SCN), the central circadian pacemakers in mammals, comprise a multiscale neuronal system that times daily events. We use recent advances in graphics processing unit computing to generate a multiscale model for the SCN that resolves cellular electrical activity down to the timescale of individual action potentials and the intracellular molecular events that generate circadian rhythms. We use the model to study the role of the neurotransmitter GABA in synchronizing circadian rhythms among individual SCN neurons, a topic of much debate in the circadian community. The model predicts that GABA signaling has two components: phasic (fast) and tonic (slow). Phasic GABA postsynaptic currents are released after action potentials, and can both increase or decrease firing rate, depending on their timing in the interspike interval, a modeling hypothesis we experimentally validate; this allows flexibility in the timing of circadian output signals. Phasic GABA, however, does not significantly affect molecular timekeeping. The tonic GABA signal is released when cells become very excited and depolarized; it changes the excitability of neurons in the network, can shift molecular rhythms, and affects SCN synchrony. We measure which neurons are excited or inhibited by GABA across the day and find GABA-excited neurons are synchronized by-and GABA-inhibited neurons repelled from-this tonic GABA signal, which modulates the synchrony in the SCN provided by other signaling molecules. Our mathematical model also provides an important tool for circadian research, and a model computational system for the many multiscale projects currently studying brain function.

The role of the circadian system in fractal neurophysiological control

Many neurophysiological variables such as heart rate, motor activity, and neural activity are known to exhibit intrinsic fractal fluctuations - similar temporal fluctuation patterns at different time scales. These fractal patterns contain information about health, as many pathological conditions are accompanied by their alteration or absence. In physical systems, such fluctuations are characteristic of critical states on the border between randomness and order, frequently arising from nonlinear feedback interactions between mechanisms operating on multiple scales. Thus, the existence of fractal fluctuations in physiology challenges traditional conceptions of health and disease, suggesting that high levels of integrity and adaptability are marked by complex variability, not constancy, and are properties of a neurophysiological network, not individual components. Despite the subject's theoretical and clinical interest, the neurophysiological mechanisms underlying fractal regulation remain largely unknown. The recent discovery that the circadian pacemaker (suprachiasmatic nucleus) plays a crucial role in generating fractal patterns in motor activity and heart rate sheds an entirely new light on both fractal control networks and the function of this master circadian clock, and builds a bridge between the fields of circadian biology and fractal physiology. In this review, we sketch the emerging picture of the developing interdisciplinary field of fractal neurophysiology by examining the circadian system's role in fractal regulation.

Modeling the seasonal adaptation of circadian clocks by changes in the network structure of the suprachiasmatic nucleus

The dynamics of circadian rhythms needs to be adapted to day length changes between summer and winter. It has been observed experimentally, however, that the dynamics of individual neurons of the suprachiasmatic nucleus (SCN) does not change as the seasons change. Rather, the seasonal adaptation of the circadian clock is hypothesized to be a consequence of changes in the intercellular dynamics, which leads to a phase distribution of electrical activity of SCN neurons that is narrower in winter and broader during summer. Yet to understand this complex intercellular dynamics, a more thorough understanding of the impact of the network structure formed by the SCN neurons is needed. To that effect, we propose a mathematical model for the dynamics of the SCN neuronal architecture in which the structure of the network plays a pivotal role. Using our model we show that the fraction of long-range cell-to-cell connections and the seasonal changes in the daily rhythms may be tightly related. In particular, simulations of the proposed mathematical model indicate that the fraction of long-range connections between the cells adjusts the phase distribution and consequently the length of the behavioral activity as follows: dense long-range connections during winter lead to a narrow activity phase, while rare long-range connections during summer lead to a broad activity phase. Our model is also able to account for the experimental observations indicating a larger light-induced phase-shift of the circadian clock during winter, which we show to be a consequence of higher synchronization between neurons. Our model thus provides evidence that the variations in the seasonal dynamics of circadian clocks can in part also be understood and regulated by the plasticity of the SCN network structure.

Circadian clocks drive the temporal coordination of internal biological processes, which in turn determine daily rhythms in physiology and behavior in the most diverse organisms. In mammals, the 24-hour timing clock resides in the suprachiasmatic nucleus (SCN) of the hypothalamus. The SCN is a network of interconnected neurons that serves as a robust self-sustained circadian pacemaker. The electrical activity of these neurons and their synchronization with the 24-hour cycle is established via the environmental day and night cycles. Apart from daily luminance changes, mammals are exposed to seasonal day length changes as well. Remarkably, it has been shown experimentally that the seasonal adaptations to different photoperiods are related to the modifications of the neuronal activity of the SCN due to the plasticity of the network. In our paper, by developing a mathematical model of the SCN architecture, we explore in depth the role of the structure of this important neuronal network. We show that the redistribution of the neuronal activity during winter and summer can in part be explained by structural changes of the network. Interestingly, the alterations of the electrical activity patterns can be related with small-world properties of our proposed SCN network.

Transcription-based oscillator model for light-induced splitting as antiphase circadian gene expression in the suprachiasmatic nuclei

Daily locomotor patterns of a variety of organisms have been interpreted as driven by dual circadian oscillators. Yet, in mammals, cellular data have revealed many circadian oscillators in the bilateral suprachiasmatic nucleus (SCN). To test how large numbers of oscillators could respond to environmental cues as a pair of oscillators, the authors developed a computational model composed of 2 groups of oscillators with strong local interactions and with weaker coupling between the 2 groups. Unlike previous models that assumed that light affects the timing or polarity of coupling between a pair of oscillators, this simulation assumed that light increased the transcription rate of a clock gene and consequently altered circadian properties of individual cells. In constant dark, weak local (within each of the 2 groups) and distant (between group) coupling established in-phase oscillations and a typical single bout of daily activity. In constant light, local synchrony developed only if coupling was strong and resulted in antiphase synchrony between the 2 groups and bimodal daily activity reminiscent of split behavior. These numerical simulations thus showed that splitting behavior can develop with increased light intensity without structural changes in the coupling topology or sign. Instead, the authors propose that light changes intrinsic oscillator properties through the increase of maximal transcription rate of a clock gene, so that as light intensity increases, the output of the coupled network transitions from a single bout of activity through irregular beating to 2 bouts and, in bright constant light, arrhythmicity.

Does the precision of a biological clock depend upon its period? Effects of the duper and tau mutations in Syrian hamsters

Mutations which alter the feedback loops that generate circadian rhythms may provide insight into their insensitivity to perturbation robustness) and their consistency of period (precision). I examined relationships between endogenous period, activity and rest (τ_DD, α and ρ) in Syrian hamsters using two different mutations, duper and tau, both of which speed up the circadian clock. I generated 8 strains of hamsters that are homozygous or heterozygous for the tau, duper, and wild type alleles in all combinations. The endogenous period of activity onsets among these strains ranged from 17.94+0.04 to 24.13±0.04 h. Contrary to predictions, the variability of period was unrelated to its absolute value: all strains showed similar variability of τ_DD when activity onsets and acrophase were used as phase markers. The τ_DD of activity offsets was more variable than onsets but also differed little between genotypes. Cycle variation and precision were not correlated with τ_DD within any strain, and only weakly correlated when all strains are considered together. Only in animals homozygous for both mutations (super duper hamsters) were cycle variation and precision reduced. Rhythm amplitude differed between strains and was positively correlated with τ_DD and precision. All genotypes showed negative correlations between α and ρ. This confirms the expectation that deviations in the duration of subjective day and night should offset one another in order to conserve circadian period, even though homeostatic maintenance of energy reserves predicts that longer intervals of activity or rest would be followed by longer durations of rest or activity. Females consistently showed greater variability of the period of activity onset and acrophase, and of α, but variability of the period of offset differed between sexes only in super duper hamsters. Despite the differences between genotypes in τ_DD, ρ was consistently more strongly correlated with the preceding than the succeeding α.

Effect of network architecture on synchronization and entrainment properties of the circadian oscillations in the suprachiasmatic nucleus

In mammals, the suprachiasmatic nucleus (SCN) of the hypothalamus constitutes the central circadian pacemaker. The SCN receives light signals from the retina and controls peripheral circadian clocks (located in the cortex, the pineal gland, the liver, the kidney, the heart, etc.). This hierarchical organization of the circadian system ensures the proper timing of physiological processes. In each SCN neuron, interconnected transcriptional and translational feedback loops enable the circadian expression of the clock genes. Although all the neurons have the same genotype, the oscillations of individual cells are highly heterogeneous in dispersed cell culture: many cells present damped oscillations and the period of the oscillations varies from cell to cell. In addition, the neurotransmitters that ensure the intercellular coupling, and thereby the synchronization of the cellular rhythms, differ between the two main regions of the SCN. In this work, a mathematical model that accounts for this heterogeneous organization of the SCN is presented and used to study the implication of the SCN network topology on synchronization and entrainment properties. The results show that oscillations with larger amplitude can be obtained with scale-free networks, in contrast to random and local connections. Networks with the small-world property such as the scale-free networks used in this work can adapt faster to a delay or advance in the light/dark cycle (jet lag). Interestingly a certain level of cellular heterogeneity is not detrimental to synchronization performances, but on the contrary helps resynchronization after jet lag. When coupling two networks with different topologies that mimic the two regions of the SCN, efficient filtering of pulse-like perturbations in the entrainment pattern is observed. These results suggest that the complex and heterogeneous architecture of the SCN decreases the sensitivity of the network to short entrainment perturbations while, at the same time, improving its adaptation abilities to long term changes.

In order to adapt to their cycling environment, virtually all living organisms have developed an internal timer, the circadian clock. In mammals, the circadian pacemaker is composed of about 20,000 neurons, called the suprachiasmatic nucleus (SCN) located in the hypothalamus. The SCN receives light signals from the retina and controls peripheral circadian clocks to ensure the proper timing of physiological processes. In each SCN neuron, a genetic regulatory network enables the circadian expression of the clock genes, but individual dynamics are highly heterogeneous in dispersed cell culture: many cells present damped oscillations and the period of the oscillations varies from cell to cell. In addition, the neurotransmitters that ensure the intercellular coupling, and thereby the synchronization of the cellular rhythms, differ between the two main regions of the SCN. We present here a mathematical model that accounts for this heterogeneous organization of the SCN and study the implication of the network topology on synchronization and entrainment properties. Our results show that cellular heterogeneity may help the resynchronization after jet lag and suggest that the complex architecture of the SCN decreases the sensitivity of the network to short entrainment perturbations while, at the same time, improving its adaptation abilities to long term changes.

Modeling circadian clocks: From equations to oscillations

Circadian rhythms are generated at the cellular level by a small but tightly regulated genetic network. In higher eukaryotes, interlocked transcriptional-translational feedback loops form the core of this network, which ensures the activation of the right genes (proteins) at the right time of the day. Understanding how such a complex molecular network can generate robust, self-sustained oscillations and accurately responds to signals from the environment (such as light and temperature) is greatly helped by mathematical modeling. In the present paper we review some mathematical models for circadian clocks, ranging from abstract, phenomenological models to the most detailed molecular models. We explain how the equations are derived, highlighting the challenges for the modelers, and how the models are analyzed. We show how to compute bifurcation diagrams, entrainment, and phase response curves. In the subsequent paper, we discuss, through a selection of examples, how modeling efforts have contributed to a better understanding of the dynamics of the circadian regulatory network.

Quantitative analysis of phase wave of gene expression in the mammalian central circadian clock network

Background

The suprachiasmatic nucleus (SCN), the master circadian clock, is a heterogeneous oscillator network, yet displays a robust synchronization dynamics. Recent single-cell bioluminescent imaging revealed temporal gradients in circadian clock gene expression in the SCN ex vivo. However, due to technical difficulty in biological approaches to elucidate the entire network structure of the SCN, characteristics of the gradient, which we refer to as phase wave, remain unknown.

Methodology/Principal Findings

We implemented new approaches, i.e., quantitative analysis and model simulation to characterize the phase waves in Per2::Luciferase clock reporter gene expression of the rat SCN slice. Our quantitative study demonstrated not only a high degree of synchronization between the neurons and regular occurrence of the phase wave propagation, but also a significant amount of phase fluctuations contained in the wave. In addition, our simulations based on local coupling model suggest that the intercellular coupling strength estimated by the model simulations is significantly higher than the critical value for generating the phase waves. Model simulations also suggest that heterogeneity of the SCN neurons is one of the main factors causing the phase wave fluctuations. Furthermore, robustness of the SCN network against dynamical noise and variation of the natural frequencies inherent in these neurons was quantitatively assessed.

Conclusions/Significance

To our knowledge, this is the first quantitative evaluation of the phase wave and further characterization of the SCN neuronal network features generating the wave i.e., intercellular synchrony, phase fluctuation, strong local coupling, heterogeneous periodicity and robustness. Our present study provides an approach, which will lead to a comprehensive understanding of mechanistic and/or biological significance of the phase wave in the central circadian oscillatory system.

Multicellular model for intercellular synchronization in circadian neural networks

We developed a multicellular model characterized by a high degree of heterogeneity to investigate possible mechanisms that underlie circadian network synchronization and rhythmicity in the suprachiasmatic nucleus (SCN). We populated a two-dimensional grid with 400 model neurons coupled via γ-aminobutyric acid (GABA) and vasoactive intestinal polypeptide (VIP) neurotransmitters through a putative Ca(2+) mediated signaling cascade to investigate their roles in gene expression and electrical firing activity of cell populations. As observed experimentally, our model predicted that GABA would affect the amplitude of circadian oscillations but not synchrony among individual oscillators. Our model recapitulated experimental findings of decreased synchrony and average periods, loss of rhythmicity, and reduced circadian amplitudes as VIP signaling was eliminated. In addition, simulated increases of VIP reduced periodicity and synchrony. We therefore postulated a physiological range of VIP within which the system is able to produce sustained and synchronized oscillations. Our model recapitulated experimental findings of diminished amplitudes and periodicity with decreasing intracellular Ca(2+) concentrations, suggesting that such behavior could be due to simultaneous decrease of individual oscillation amplitudes and population synchrony. Simulated increases in Cl(-) levels resulted in increased Cl(-) influx into the cytosol, a decrease of inhibitory postsynaptic currents, and ultimately a shift of GABA-elicited responses from inhibitory to excitatory. The simultaneous reduction of IPSCs and increase in membrane resting potential produced GABA dose-dependent increases in firing rates across the population, as has been observed experimentally. By integrating circadian gene regulation and electrophysiology with intracellular and intercellular signaling, we were able to develop the first (to our knowledge) multicellular model that allows the effects of clock genes, electrical firing, Ca(2+), GABA, and VIP on circadian system behavior to be predicted.

Multiscale complexity in the mammalian circadian clock

The field of systems biology studies how the interactions among individual components (e.g. genes and proteins) yield interesting and complex behavior. The circadian (daily) timekeeping system in mammals is an ideal system to study complexity because of its many biological scales (from genes to animal behavior). A wealth of data at each of these scales has recently been discovered. Within each scale, modeling can advance our understanding of challenging problems that arise in studying mammalian timekeeping. However, future work must focus on bridging the multiple spatial and temporal scales in the modeling of SCN network. Here we review recent advances, and then delve into a few areas that are promising research directions. We also discuss the flavor of modeling needed (simple or detailed) as well as new techniques that are needed to meet the challenges in modeling data across scales.

Emergence of noise-induced oscillations in the central circadian pacemaker

Bmal1 is an essential transcriptional activator within the mammalian circadian clock. We report here that the suprachiasmatic nucleus (SCN) of Bmal1-null mutant mice, unexpectedly, generates stochastic oscillations with periods that overlap the circadian range. Dissociated SCN neurons expressed fluctuating levels of PER2 detected by bioluminescence imaging but could not generate circadian oscillations intrinsically. Inhibition of intercellular communication or cyclic-AMP signaling in SCN slices, which provide a positive feed-forward signal to drive the intracellular negative feedback loop, abolished the stochastic oscillations. Propagation of this feed-forward signal between SCN neurons then promotes quasi-circadian oscillations that arise as an emergent property of the SCN network. Experimental analysis and mathematical modeling argue that both intercellular coupling and molecular noise are required for the stochastic rhythms, providing a novel biological example of noise-induced oscillations. The emergence of stochastic circadian oscillations from the SCN network in the absence of cell-autonomous circadian oscillatory function highlights a previously unrecognized level of circadian organization.

Dynamic interactions between coupled oscillators within the hamster circadian pacemaker

Within the mammalian suprachiasmatic nucleus, multiple oscillators interact to coordinate circadian rhythms in behavior and physiology. We have developed a behavioral assay that disassociates central oscillators and allows rigorous study of their formal properties and interactions. Rodents held under 24h light:dark:light:dark (LDLD) cycles display "split" activity rhythms that reflect the reorganization of the central pacemaker into two oscillator groups cycling ~12h apart. After transfer to constant conditions, the two activity components rejoin through a series of transients lasting 2-7 days. Here we analyze fusion dynamics, characterize the underlying oscillator interactions, and assess two influencing factors: phase of transfer and lighting conditions upon transfer. Syrian hamsters were split under LDLD with dimly lit nights and then transferred to constant dim illumination or complete darkness during one of the two daily scotophases. Fusion was influenced by phase of transfer, suggesting that the oscillators split under LDLD exert an asymmetric influence over one another. Transfer to constant dim and dark conditions produced similar overall patterns of fusion, but nevertheless differed in the rejoined state of the system. The present results are discussed within a model wherein oscillators influence one another in a phase-dependent manner.

Suprachiasmatic nucleus: cell autonomy and network properties

The suprachiasmatic nucleus (SCN) is the primary circadian pacemaker in mammals. Individual SCN neurons in dispersed culture can generate independent circadian oscillations of clock gene expression and neuronal firing. However, SCN rhythmicity depends on sufficient membrane depolarization and levels of intracellular calcium and cAMP. In the intact SCN, cellular oscillations are synchronized and reinforced by rhythmic synaptic input from other cells, resulting in a reproducible topographic pattern of distinct phases and amplitudes specified by SCN circuit organization. The SCN network synchronizes its component cellular oscillators, reinforces their oscillations, responds to light input by altering their phase distribution, increases their robustness to genetic perturbations, and enhances their precision. Thus, even though individual SCN neurons can be cell-autonomous circadian oscillators, neuronal network properties are integral to normal function of the SCN.

Circadian clocks and phosphorylation: Insights from computational modeling

Circadian clocks are based on a molecular mechanism regulated at the transcriptional, translational and post-translational levels. Recent experimental data unravel a complex role of the phosphorylations in these clocks. In mammals, several kinases play differential roles in the regulation of circadian rhythmicity. A dysfunction in the phosphorylation of one clock protein could lead to sleep disorders such as the Familial Advanced Sleep Phase Disorder, FASPS. Moreover, several drugs are targeting kinases of the circadian clocks and can be used in cancer chronotherapy or to treat mood disorders. In Drosophila, recent experimental observations also revealed a complex role of the phosphorylations. Because of its high degree of homology with mammals, the Drosophila system is of particular interest. In the circadian clock of cyanobacteria, an atypical regulatory mechanism is based only on three clock proteins (KaiA, KaiB, KaiC) and ATP and is sufficient to produce robust temperature-compensated circadian oscillations of KaiC phosphorylation. This review will show how computational modeling has become a powerful and useful tool in investigating the regulatory mechanism of circadian clocks, but also how models can give rise to testable predictions or reveal unexpected results.

Small-world network models of intercellular coupling predict enhanced synchronization in the suprachiasmatic nucleus

The suprachiasmatic nucleus (SCN) of the hypothalamus is a multioscillator system that drives daily rhythms in mammalian behavior and physiology. Based on recent data implicating vasoactive intestinal polypeptide (VIP) as the key intercellular synchronizing agent, we developed a multicellular SCN model to investigate the effects of cellular heterogeneity and intercellular connectivity on circadian behavior. A 2-dimensional grid was populated with 400 model cells that were heterogeneous with respect to their uncoupled rhythmic behavior (intrinsic and damped pacemakers with a range of oscillation periods) and VIP release characteristics (VIP producers and nonproducers). We constructed small-world network architectures in which local connections between VIP producing cells and their 4 nearest neighbors were augmented with random connections, resulting in long-range coupling across the grid. With only 10% of the total possible connections, the small-world network model was able to produce similar phase synchronization indices as a mean-field model with VIP producing cells connected to all other cells. Partial removal of random connections decreased the synchrony among neurons, the amplitude of VIP and cAMP response element binding protein oscillations, the mean period of intrinsic periods across the population, and the percentage of oscillating cells. These results indicate that small-world connectivity provides the optimal compromise between the number of connections and control of circadian amplitude and synchrony. This model predicts that small decreases in long-range VIP connections in the SCN could have dramatic effects on period and amplitude of daily rhythms, features commonly described with aging.

How to synchronize biological clocks

This paper is concerned with a novel algorithm to study networks of biological clocks. A new set of conditions is established that can be used to verify whether an existing network synchronizes or to give guidelines to construct a new synthetic network of biological oscillators that synchronize. The methodology uses the so-called contraction theory from dynamical system theory and Gershgorin disk theorem. The strategy is validated on two examples: a model of glycolisis in yeast cells and a synthetic network of Repressilators that synchronizes.

Design principles for phase-splitting behaviour of coupled cellular oscillators: clues from hamsters with 'split' circadian rhythms

Nonlinear interactions among coupled cellular oscillators are likely to underlie a variety of complex rhythmic behaviours. Here we consider the case of one such behaviour, a doubling of rhythm frequency caused by the spontaneous splitting of a population of synchronized oscillators into two subgroups each oscillating in anti-phase (phase-splitting). An example of biological phase-splitting is the frequency doubling of the circadian locomotor rhythm in hamsters housed in constant light, in which the pacemaker in the suprachiasmatic nucleus (SCN) is reconfigured with its left and right halves oscillating in anti-phase. We apply the theory of coupled phase oscillators to show that stable phase-splitting requires the presence of negative coupling terms, through delayed and/or inhibitory interactions. We also find that the inclusion of real biological constraints (that the SCN contains a finite number of non-identical noisy oscillators) implies the existence of an underlying non-uniform network architecture, in which the population of oscillators must interact through at least two types of connections. We propose that a key design principle for the frequency doubling of a population of biological oscillators is inhomogeneity of oscillator coupling.

Global parameter search reveals design principles of the mammalian circadian clock

BACKGROUND

Virtually all living organisms have evolved a circadian (~24 hour) clock that controls physiological and behavioural processes with exquisite precision throughout the day/night cycle. The suprachiasmatic nucleus (SCN), which generates these ~24 h rhythms in mammals, consists of several thousand neurons. Each neuron contains a gene-regulatory network generating molecular oscillations, and the individual neuron oscillations are synchronised by intercellular coupling, presumably via neurotransmitters. Although this basic mechanism is currently accepted and has been recapitulated in mathematical models, several fundamental questions about the design principles of the SCN remain little understood. For example, a remarkable property of the SCN is that the phase of the SCN rhythm resets rapidly after a 'jet lag' type experiment, i.e. when the light/dark (LD) cycle is abruptly advanced or delayed by several hours.

RESULTS

Here, we describe an extensive parameter optimization of a previously constructed simplified model of the SCN in order to further understand its design principles. By examining the top 50 solutions from the parameter optimization, we show that the neurotransmitters' role in generating the molecular circadian rhythms is extremely important. In addition, we show that when a neurotransmitter drives the rhythm of a system of coupled damped oscillators, it exhibits very robust synchronization and is much more easily entrained to light/dark cycles. We were also able to recreate in our simulations the fast rhythm resetting seen after a 'jet lag' type experiment.

CONCLUSION

Our work shows that a careful exploration of parameter space for even an extremely simplified model of the mammalian clock can reveal unexpected behaviours and non-trivial predictions. Our results suggest that the neurotransmitter feedback loop plays a crucial role in the robustness and phase resetting properties of the mammalian clock, even at the single neuron level.

A molecular model for intercellular synchronization in the mammalian circadian clock

The mechanisms and consequences of synchrony among heterogeneous oscillators are poorly understood in biological systems. We present a multicellular, molecular model of the mammalian circadian clock that incorporates recent data implicating the neurotransmitter vasoactive intestinal polypeptide (VIP) as the key synchronizing agent. The model postulates that synchrony arises among circadian neurons because they release VIP rhythmically on a daily basis and in response to ambient light. Two basic cell types, intrinsically rhythmic pacemakers and damped oscillators, are assumed to arise from a distribution of Period gene transcription rates. Postsynaptic neurons show time-of-day dependent responses to VIP binding through a signaling cascade that activates Period mRNA transcription. The heterogeneous cell ensemble model self-synchronizes, entrains to ambient light-dark cycles, and desynchronizes in constant bright light or upon removal of VIP signaling. The degree of synchronicity observed depends on cell-specific features (e.g., mean and variability of parameters within the rhythm-generating loop), in addition to the more commonly studied effect of intercellular coupling strength. These simulations closely replicate experimental data and predict that heterogeneous oscillations (e.g., sustained, damped, and arrhythmic) arise from small differences in the molecular parameters between cells, that damped oscillators participate in entrainment and synchrony of the ensemble of cells, and that constant light desynchronizes oscillators by maximizing VIP release.

Synchronization-induced rhythmicity of circadian oscillators in the suprachiasmatic nucleus

The suprachiasmatic nuclei (SCN) host a robust, self-sustained circadian pacemaker that coordinates physiological rhythms with the daily changes in the environment. Neuronal clocks within the SCN form a heterogeneous network that must synchronize to maintain timekeeping activity. Coherent circadian output of the SCN tissue is established by intercellular signaling factors, such as vasointestinal polypeptide. It was recently shown that besides coordinating cells, the synchronization factors play a crucial role in the sustenance of intrinsic cellular rhythmicity. Disruption of intercellular signaling abolishes sustained rhythmicity in a majority of neurons and desynchronizes the remaining rhythmic neurons. Based on these observations, the authors propose a model for the synchronization of circadian oscillators that combines intracellular and intercellular dynamics at the single-cell level. The model is a heterogeneous network of circadian neuronal oscillators where individual oscillators are damped rather than self-sustained. The authors simulated different experimental conditions and found that: (1) in normal, constant conditions, coupled circadian oscillators quickly synchronize and produce a coherent output; (2) in large populations, such oscillators either synchronize or gradually lose rhythmicity, but do not run out of phase, demonstrating that rhythmicity and synchrony are codependent; (3) the number of oscillators and connectivity are important for these synchronization properties; (4) slow oscillators have a higher impact on the period in mixed populations; and (5) coupled circadian oscillators can be efficiently entrained by light-dark cycles. Based on these results, it is predicted that: (1) a majority of SCN neurons needs periodic synchronization signal to be rhythmic; (2) a small number of neurons or a low connectivity results in desynchrony; and (3) amplitudes and phases of neurons are negatively correlated. The authors conclude that to understand the orchestration of timekeeping in the SCN, intracellular circadian clocks cannot be isolated from their intercellular communication components.

Inherent multistability in arrays of autoinducer coupled genetic oscillators

Rhythm generation mechanisms are very important for genetic network functions as well as for the design of synthetic genetic circuits. A significant attention to date has been focused on the synchronization of communicating genetic units, which results in the production of an unified rhythm. In contrast to this we address the question: what mechanisms of intercell communication can be responsible for multirhythmicity in globally coupled genetic units? Here, we show that an autoinducer intercell communication system that provides coupling between synthetic genetic oscillators will inherently lead to multirhythmicity and the appearance of several coexisting dynamical regimes, if the time evolution of the genetic network can be split in two well-separated time scales. We investigate in detail a variety of dynamical regimes in a genetic population and show the possibility for multiple element distributions between clusters, as well as the possibility of generating complex oscillations with different return times in one limit cycle.

Exploring spatiotemporal organization of SCN circuits

Suprachiasmatic nucleus (SCN) neuroanatomy has been a subject of intense interest since the discovery of the SCN's function as a brain clock and subsequent studies revealing substantial heterogeneity of its component neurons. Understanding the network organization of the SCN has become increasingly relevant in the context of studies showing that its functional circuitry, evident in the spatial and temporal expression of clock genes, can be reorganized by inputs from the internal and external environment. Although multiple mechanisms have been proposed for coupling among SCN neurons, relatively little is known of the precise pattern of SCN circuitry. To explore SCN networks, we examine responses of the SCN to various photic conditions, using in vivo and in vitro studies with associated mathematical modeling to study spatiotemporal changes in SCN activity. We find an orderly and reproducible spatiotemporal pattern of oscillatory gene expression in the SCN, which requires the presence of the ventrolateral core region. Without the SCN core region, behavioral rhythmicity is abolished in vivo, whereas low-amplitude rhythmicity can be detected in SCN slices in vitro, but with loss of normal topographic organization. These studies reveal SCN circuit properties required to signal daily time.

Phase angle difference alters coupling relations of functionally distinct circadian oscillators revealed by rhythm splitting

The interactions (i.e., coupling) between multiple oscillators of a circadian system determine basic properties of the integrated pacemaker. Unfortunately, there are few experimental models to investigate the putative interactions of functionally defined oscillators comprising the mammalian circadian pacemaker. Here the authors induce in hamsters a novel circadian entrainment pattern that is characterized by the daily expression of robust wheel-running activity in each scotophase of a 24-h light:dark:light:dark cycle. The daily activity bouts are mediated by 2 circadian oscillators, here designated "daytime" and "nighttime," that have been temporally dissociated under this light regime. To assess the phase dependence of interactions between oscillatory components, the phase relationship of the 2 daily scotophases was manipulated over a 4-h range, and the timing of activity of the daytime and nighttime components under entrained and probe conditions was examined. The average phase angle of entrainment and the day-to-day variability of activity onset of each activity component depended on the phase relationship of the respective scotophases and not on whether the component occurred in the daytime or the nighttime. Short-term denial of wheel access subsequently influenced amount and duration of wheel running but not timing of its onset, suggesting that only the former measures depend on a homeostatic mechanism sensitive to the time elapsed since prior intense running. Replacement of individual photophases with darkness revealed phase attraction between oscillators that was not dependent on the phase relationship of component oscillators but differed for daytime versus nighttime activity components. Entrainment patterns shown here cannot be accounted for by only nonparametric actions of light. Instead, the phase-dependent interactions of oscillators strongly influence entrainment properties, whereas intrinsic functional differences in dissociated oscillators apparently influence their attraction in darkness. This model system may be ideal for identifying genomic and physiological factors that mediate these interactions and thus contribute importantly to system properties of the mammalian circadian clock.

Development of a two-dimension manifold to represent high dimension mathematical models of the intracellular Mammalian circadian clock

A new focus for mathematical models of the circadian pacemaker involves the encapsulation within the models of detailed biological processes responsible for generating those circadian rhythms. Representing greater biological detail requires more mathematical equations, which pose a greater challenge for the analysis of such systems. Development of a method that retains the predominant dynamics while still providing biologically detailed information is advantageous. Two high-dimension mathematical models of intracellular mammalian circadian pacemakers, Leloup-Goldbeter and Forger-Peskin, with 19 and 73 differential equations, respectively, have been published. The authors projected each of these high-dimension models onto their respective manifold using proper orthogonal functions (POFs) obtained from the empirical decomposition of the model's phase space to obtain a 2-dimension model. The resulting 2-dimension model, represented by 2 differential equations, predicts most of the salient characteristics of a biological clock including approximately 24-h oscillations, entrainment to an LD cycle, phase response curves, and the amplitude recovery dynamics that emerge following amplitude suppression. The manifold representation simplifies the mathematical analysis, since only 2 variables need to be observed and analyzed to understand the behavior of the biological clock. This reduced model derived from a model based on biological variables can be used for the development and analysis of mathematical models of the coupled mammalian oscillators to understand the dynamics of the integrated circadian pacemaker.

Circadian rhythms and molecular noise

Circadian rhythms, characterized by a period of about 24 h, are the most widespread biological rhythms generated autonomously at the molecular level. The core molecular mechanism responsible for circadian oscillations relies on the negative regulation exerted by a protein on the expression of its own gene. Deterministic models account for the occurrence of autonomous circadian oscillations, for their entrainment by light-dark cycles, and for their phase shifting by light pulses. Stochastic versions of these models take into consideration the molecular fluctuations that arise when the number of molecules involved in the regulatory mechanism is low. Numerical simulations of the stochastic models show that robust circadian oscillations can already occur with a limited number of mRNA and protein molecules, in the range of a few tens and hundreds, respectively. Various factors affect the robustness of circadian oscillations with respect to molecular noise. Besides an increase in the number of molecules, entrainment by light-dark cycles, and cooperativity in repression enhance robustness, whereas the proximity of a bifurcation point leads to less robust oscillations. Another parameter that appears to be crucial for the coherence of circadian rhythms is the binding/unbinding rate of the inhibitory protein to the promoter of the clock gene. Intercellular coupling further increases the robustness of circadian oscillations.

Pigment-dispersing factor and GABA synchronize cells of the isolated circadian clock of the cockroach Leucophaea maderae

Pigment-dispersing factor-immunoreactive circadian pacemaker cells, which arborize in the accessory medulla, control circadian locomotor activity rhythms in Drosophila as well as in the cockroach Leucophaea maderae via unknown mechanisms. Here, we show that circadian pacemaker candidates of the accessory medulla of the cockroach produce regular interspike intervals. Therefore, the membrane potential of the cells oscillates with ultradian periods. Most or all oscillating cells within the accessory medulla are coupled via synaptic and nonsynaptic mechanisms, forming different assemblies. The cells within an assembly share the same ultradian period (interspike interval) and the same phase (timing of spikes), whereas cells between assemblies differ in phase. Apparently, the majority of these assemblies are formed by inhibitory GABAergic synaptic interactions. Application of pigment-dispersing factor phase locked and thereby synchronized different assemblies. The data suggest that pigment-dispersing factor inhibits GABAergic interneurons, resulting in disinhibition and phase locking of their postsynaptic cells, which previously belonged to different assemblies. Our data suggest that phase control of action potential oscillations in the ultradian range is a main task of the circadian pacemaker network. We hypothesize that neuropeptide-dependent phase control is used to gate circadian outputs to locomotor control centers.

Sleep wake disturbances in people with cancer and their caregivers: state of the science

PURPOSE/OBJECTIVES

To review the state of the science on sleep/wake disturbances in people with cancer and their caregivers.

DATA SOURCES

Published articles, books and book chapters, conference proceedings, and MEDLINE, the Cumulative Index to Nursing and Allied Health Literature, PsycINFO, and the Cochrane Library computerized databases.

DATA SYNTHESIS

Scientists have initiated studies on the prevalence of sleep/wake disturbances and the etiology of sleep disturbances specific to cancer. Measurement has been limited by lack of clear definitions of sleep/wake variables, use of a variety of instruments, and inconsistent reporting of sleep parameters. Findings related to use of nonpharmacologic interventions were limited to 20 studies, and the quality of the evidence remains poor. Few pharmacologic approaches have been studied, and evidence for use of herbal and complementary supplements is almost nonexistent.

CONCLUSIONS

Current knowledge indicates that sleep/wake disturbances are prevalent in cancer populations. Few instruments have been validated in this population. Nonpharmacologic interventions show positive outcomes, but design issues and small samples limit generalizability. Little is known regarding use of pharmacologic and herbal and complementary supplements and potential adverse outcomes or interactions with cancer therapies.

IMPLICATIONS FOR NURSING

All patients and caregivers need initial and ongoing screening for sleep/wake disturbances. When disturbed sleep/wakefulness is evident, further assessment and treatment are warranted. Nursing educational programs should include content regarding healthy and disrupted sleep/wake patterns. Research on sleep/wake disturbances in people with cancer should have high priority.

Spontaneous synchronization of coupled circadian oscillators

In mammals, the circadian pacemaker, which controls daily rhythms, is located in the suprachiasmatic nucleus (SCN). Circadian oscillations are generated in individual SCN neurons by a molecular regulatory network. Cells oscillate with periods ranging from 20 to 28 h, but at the tissue level, SCN neurons display significant synchrony, suggesting a robust intercellular coupling in which neurotransmitters are assumed to play a crucial role. We present a dynamical model for the coupling of a population of circadian oscillators in the SCN. The cellular oscillator, a three-variable model, describes the core negative feedback loop of the circadian clock. The coupling mechanism is incorporated through the global level of neurotransmitter concentration. Global coupling is efficient to synchronize a population of 10,000 cells. Synchronized cells can be entrained by a 24-h light-dark cycle. Simulations of the interaction between two populations representing two regions of the SCN show that the driven population can be phase-leading. Experimentally testable predictions are: 1), phases of individual cells are governed by their intrinsic periods; and 2), efficient synchronization is achieved when the average neurotransmitter concentration would dampen individual oscillators. However, due to the global neurotransmitter oscillation, cells are effectively synchronized.

Modeling the mammalian circadian clock: sensitivity analysis and multiplicity of oscillatory mechanisms

We extend the study of a computational model recently proposed for the mammalian circadian clock (Proc. Natl Acad. Sci. USA 100 (2003) 7051). The model, based on the intertwined positive and negative regulatory loops involving the Per, Cry, Bmal1, and Clock genes, can give rise to sustained circadian oscillations in conditions of continuous darkness. These limit cycle oscillations correspond to circadian rhythms autonomously generated by suprachiasmatic nuclei and by some peripheral tissues. By using different sets of parameter values producing circadian oscillations, we compare the effect of the various parameters and show that both the occurrence and the period of the oscillations are generally most sensitive to parameters related to synthesis or degradation of Bmal1 mRNA and BMAL1 protein. The mechanism of circadian oscillations relies on the formation of an inactive complex between PER and CRY and the activators CLOCK and BMAL1 that enhance Per and Cry expression. Bifurcation diagrams and computer simulations nevertheless indicate the possible existence of a second source of oscillatory behavior. Thus, sustained oscillations might arise from the sole negative autoregulation of Bmal1 expression. This second oscillatory mechanism may not be functional in physiological conditions, and its period need not necessarily be circadian. When incorporating the light-induced expression of the Per gene, the model accounts for entrainment of the oscillations by light-dark (LD) cycles. Long-term suppression of circadian oscillations by a single light pulse can occur in the model when a stable steady state coexists with a stable limit cycle. The phase of the oscillations upon entrainment in LD critically depends on the parameters that govern the level of CRY protein. Small changes in the parameters governing CRY levels can shift the peak in Per mRNA from the L to the D phase, or can prevent entrainment. The results are discussed in relation to physiological disorders of the sleep-wake cycle linked to perturbations of the human circadian clock, such as the familial advanced sleep phase syndrome or the non-24h sleep-wake syndrome.

Modeling feedback loops of the Mammalian circadian oscillator

The suprachiasmatic nucleus governs daily variations of physiology and behavior in mammals. Within single neurons, interlocked transcriptional/translational feedback loops generate circadian rhythms on the molecular level. We present a mathematical model that reflects the essential features of the mammalian circadian oscillator to characterize the differential roles of negative and positive feedback loops. The oscillations that are obtained have a 24-h period and are robust toward parameter variations even when the positive feedback is replaced by a constantly expressed activator. This demonstrates the crucial role of the negative feedback for rhythm generation. Moreover, it explains the rhythmic phenotype of Rev-erbalpha-/- mutant mice, where a positive feedback is missing. The interplay of negative and positive feedback reveals a complex dynamics. In particular, the model explains the unexpected rescue of circadian oscillations in Per2Brdm1/Cry2-/- double-mutant mice (Per2Brdm1 single-mutant mice are arrhythmic). Here, a decrease of positive feedback strength associated with mutating the Per2 gene is compensated by the Cry2-/- mutation that simultaneously decreases the negative feedback strength. Finally, this model leads us to a testable prediction of a molecular and behavioral phenotype: circadian oscillations should be rescued when arrhythmic Per2Brdm1 mutant mice are crossed with Rev- erbalpha -/- mutant mice.