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.     

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.     

Circadian Activity Rhythms and Phase‐Shifting of Cultured Neurons of the Rat Suprachiasmatic Nucleus

The mammalian suprachiasmatic nucleus (SCN) is the major endogenous pacemaker that coordinates various daily rhythms including locomotor activity and autonomous and endocrine responses, through a neuronal and humoral influence. In the present study we examined the behavior of dispersed individual SCN neurons obtained from 1‐ to 3‐day‐old rats cultured on multi‐microelectrode arrays (MEAs). SCN neurons were identified by immunolabeling for the neuropeptides arginine‐vasopressin (AVP) and vasoactive intestinal polypeptide (VIP). Single SCN neurons cultured at low density onto an MEA can express firing rate patterns with different circadian phases. In these cultures we observed rarely synchronized firing patterns on adjacent electrodes. This suggests that, in cultures of low cell densities, SCN neurons function as independent pacemakers. To investigate whether individual pacemakers can be influenced independently by phase‐shifting stimuli, we applied melatonin (10 pM to 100 nM) for 30 min at different circadian phases and continuously monitored the firing rate rhythms. Melatonin could elicit phase‐shifting responses in individual clock cells which had no measurable input from other neurons. In several neurons, phase‐shifts occurred with a long delay in the second or third cycle after melatonin treatment, but not in the first cycle. Phase‐shifts of isolated SCN neurons were also observed at times when the SCN showed no sensitivity to these phase‐shifting stimuli in recordings from brain slices. This finding suggests that the neuronal network plays an essential role in the control of phase‐shifts.     

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.     

Phase differences between SCN neurons and their role in photoperiodic encoding; a simulation of ensemble patterns using recorded single unit electrical activity patterns

In mammals, a major circadian pacemaker is located in the suprachiasmatic nuclei (SCN), at the base of the anterior hypothalamus. The pacemaker controls daily rhythms in behavioral, physiological and endocrine functions and is synchronized to the external light-dark cycle via the retinohypothalamic tract. The SCN are also involved in photoperiodic processes. Changes in day-length are perceived by the SCN, and result in a compression or decompression of the SCN ensemble pattern, which appears to be effectuated by changes in phase relationship among oscillating neurons. By simulation experiments, we have previously shown that the duration of the single unit activity pattern is of minor importance for the broadness of the population activity peak. Instead, the phase distribution among neurons is leading to substantial differences in the broadness of the population pattern. We now show that the combination of (i) changes in the single unit activity pattern and (ii) changes in the phase distribution among oscillating neurons is also effective to encode photoperiodic information. Moreover, we simulated the ensemble waveform of the SCN with recently recorded single unit electrical activity patterns of mice under long and short photoperiods. We show that these single unit activity patterns cannot account for changes in the population waveform of the SCN unless their phase distribution is changed. A narrow distribution encodes for short photoperiods, while a wider distribution is required to encode long photoperiods. The present studies show that recorded patterns in single unit activity rhythms, measured under long and short day conditions, can be used in simulation experiments and are informative in showing which attributes of the neuronal discharge patterns leads to the capacity of the SCN to encode photoperiod.     

Neural correlates of individual differences in circadian behaviour

Daily rhythms in mammals are controlled by the circadian system, which is a collection of biological clocks regulated by a central pacemaker within the suprachiasmatic nucleus (SCN) of the anterior hypothalamus. Changes in SCN function have pronounced consequences for behaviour and physiology; however, few studies have examined whether individual differences in circadian behaviour reflect changes in SCN function. Here, PERIOD2::LUCIFERASE mice were exposed to a behavioural assay to characterize individual differences in baseline entrainment, rate of re-entrainment and free-running rhythms. SCN slices were then collected for ex vivo bioluminescence imaging to gain insight into how the properties of the SCN clock influence individual differences in behavioural rhythms. First, individual differences in the timing of locomotor activity rhythms were positively correlated with the timing of SCN rhythms. Second, slower adjustment during simulated jetlag was associated with a larger degree of phase heterogeneity among SCN neurons. Collectively, these findings highlight the role of the SCN network in determining individual differences in circadian behaviour. Furthermore, these results reveal novel ways that the network organization of the SCN influences plasticity at the behavioural level, and lend insight into potential interventions designed to modulate the rate of resynchronization during transmeridian travel and shift work.     

Seasonal encoding by the circadian pacemaker of the SCN

The circadian pacemaker of the suprachiasmatic nucleus (SCN) functions as a seasonal clock through its ability to encode day length [1-6]. To investigate the mechanism by which SCN neurons code for day length, we housed mice under long (LD 16:8) and short (LD 8:16) photoperiods. Electrophysiological recordings of multiunit activity (MUA) in the SCN of freely moving mice revealed broad activity profiles in long days and compressed activity profiles in short days. The patterns remained consistent after release of the mice in constant darkness. Recordings of MUA in acutely prepared hypothalamic slices showed similar differences between the SCN electrical activity patterns in vitro in long and short days. In vitro recordings of neuronal subpopulations revealed that the width of the MUA activity profiles was determined by the distribution of phases of contributing units within the SCN. The subpopulation patterns displayed a significantly broader distribution in long days than in short days. Long-term recordings of single-unit activity revealed short durations of elevated activity in both short and long days (3.48 and 3.85 hr, respectively). The data indicate that coding for day length involves plasticity within SCN neuronal networks in which the phase distribution of oscillating neurons carries information on the photoperiod's duration.     

Fractal Stochastic Modeling of Spiking Activity in Suprachiasmatic Nucleus Neurons

Individual neurons in the suprachiasmatic nucleus (SCN), the master biological clock in mammals, autonomously produce highly complex patterns of spikes. We have shown that most (~90%) SCN neurons exhibit truly stochastic interspike interval (ISI) patterns. The aim of this study was to understand the stochastic nature of the firing patterns in SCN neurons by analyzing the ISI sequences of 150 SCN neurons in hypothalamic slices. Fractal analysis, using the periodogram, Fano factor, and Allan factor, revealed the presence of a 1/f-type power-law (fractal) behavior in the ISI sequences. This fractal nature was persistent after the application of the GABA_A receptor antagonist bicuculline, suggesting that the fractal stochastic activity is an intrinsic property of individual SCN neurons. Based on these physiological findings, we developed a computational model for the stochastic SCN neurons to find that their stochastic spiking activity was best described by a gamma point process whose mean firing rate was modulated by a fractal binomial noise. Taken together, we suggest that SCN neurons generate temporal spiking patterns using the fractal stochastic point process.Action Editor: Carson C. Chow     

Fos expression within vasopressin-containing neurons in the suprachiasmatic nucleus of diurnal rodents compared to nocturnal rodents

The underlying neural causes of the differences between nocturnal and diurnal animals with respect to their patterns of rhythmicity have not yet been identified. These differences could be due to differences in some subpopulation of neurons within the suprachiasmatic nucleus (SCN) or to differences in responsiveness to signals emanating from the SCN. The experiments described in this article were designed to address the former hypothesis by examining Fos expression within vasopressin (VP) neurons in the SCN of nocturnal and diurnal rodents. Earlier work has shown that within the SCN of the diurnal rodent Arvicanthis niloticus, approximately 30% of VP-immunoreactive (IR) neurons express Fos during the day, whereas Fos rarely is expressed in VP-IR neurons in the SCN of nocturnal rats. However, in earlier studies, rats were housed in constant darkness and pulsed with light, whereas Arvicanthis were housed in a light:dark (LD) cycle. To provide data from rats that would permit comparisons with A. niloticus, the first experiment examined VP/Fos double labeling in the SCN of rats housed in a 12:12 LD cycle and perfused 4 h into the light phase or 4 h into the dark phase. Fos was significantly elevated in the SCN of animals sacrificed during the light compared to the dark phase, but virtually no Fos at either time was found in VP-IR neurons, confirming that the SCN of rats and diurnal Arvicanthis are significantly different in this regard. The authors also evaluated the relationship between this aspect of SCN function and diurnality by examining Fos-IR and VP-IR in diurnal and nocturnal forms of Arvicanthis. In this species, most individuals exhibit diurnal wheel-running rhythms, but some exhibit a distinctly different and relatively nocturnal pattern. The authors have bred their laboratory colony for this trait and used animals with both patterns in this experiment. They examined Fos expression within VP-IR neurons in the SCN of both nocturnal and diurnal A. niloticus kept on a 12:12 LD cycle and perfused 4 h into the light phase or 4 h into the dark phase, and brains were processed for immunohistochemical identification of Fos and VP. Both the total number of Fos-IR cells and the proportion of VP-IR neurons containing Fos (20%) were higher during the day than during the night. Neither of these parameters differed between nocturnal and diurnal animals. The implications of these findings are discussed.     

The suprachiasmatic nucleus in the sheep: retinal projections and cytoarchitectural organization

The retinal innervation, cytoarchitectural, and immunohistochemical organization of the suprachiasmatic nucleus (SCN) was studied in the domestic sheep. The SCN is a large elongated nucleus extending rostrocaudally for roughly 3 mm in the hypothalamus. The morphology is unusual in that the rostral part of the nucleus extends out of the main mass of the hypothalamus onto the dorsal aspect of the optic chiasm. Following intraocular injection of wheat-germ agglutininhorseradish peroxidase or tritiated amino acids, anterograde label is distributed throughout the SCN. Retinal innervation of the SCN is bilaterally symmetric or predominantly ipsilateral. Quantitative image analysis demonstrates that, although the amount of autoradiographic label is greatest in the ventral and central parts of the nucleus, density varies progressively between different regions. In addition to the SCN, retinal fibers are also seen in the medial preoptic area, the anterior and lateral hypothalamic areas, the dorsomedial hypothalamus, the retrochiasmatic area, and the basal telencephalon. Whereas the SCN can be identified using several techniques, complete delineation of the nucleus requires combined tract tracing, cytoarchitectural, and histochemical criteria. Compared with the surrounding hypothalamic regions, the SCN contains smaller, more densely packed neurons, and is largely devoid of myelinated fibers. Cell soma sizes are smaller in the ventral SCN than in the dorsal or lateral parts, but an obvious regional transition is lacking. Using Nissl, myelin, acetylcholinesterase, and cytochrome oxidase staining, the SCN can be clearly distinguished in the rostral and medial regions, but is less differentiated toward the caudal pole. Immunohistochemical demonstration of several neuropeptides shows that the neurochemical organization of the sheep SCN is heterogeneous, but that it lacks a distinct compartmental organization. Populations of different neuropeptide-containing cells are found throughout the nucleus, although perikarya positive for vasoactive intestinal polypeptide and fibers labeled for methionine-enkephalin are predominant ventrally; neurophysine-immunoreactive cells are more prominent in the dorsal region and toward the caudal pole. The results suggest that the intrinsic organization of the sheep SCN is characterized by gradual regional transitions between different zones.     

Seasonal Rhythms of Neuronal Activity in the Human Biological Clock: A Mathematical Model

The mammalian suprachiasmatic nucleus (SCN) is implicated in the temporal organization of circadian and seasonal processes. Photic information may have a synchronizing effect on the endogenous clock of the SCN by inducing periodic changes in the functional activity of specific groups of neurons. The present study was performed to analyze the annual profiles of the arginine vasopressin (AVP)- and vasoactive intestinal polypeptide (VIP)-producing neurons in the human SCN. The populations of AVP- and VIP-expressing neurons in the SCN showed marked annual rhythms with an asymmetrical, bimodal waveform. Time series analysis indicated that these annual cycles in peptidergic activity could be described by a statistical model consisting of multiple-harmonic regression and ARMA components. The annual AVP cycle was adequately described by a two-harmonic model and a third-order autoregressive noise component, whereas the properties of the VIP cycle were best characterized by a two-harmonic model and a first-order autoregressive noise component. The models of both annual cycles reached a maximum in September–October and a minimum in May–June, and their estimated amplitudes, relative to the annual mean, were similar in size. These findings indicate that the biosynthesis of vasopressin and VIP in the human SCN exhibits an annual rhythmicity, and that the temporal organization of these processes is mainly controlled by environmental lighting conditions.     

Seasonal Rhythms of Neuronal Activity in the Human Biological Clock: A Mathematical Model

The mammalian suprachiasmatic nucleus (SCN) is implicated in the temporal organization of circadian and seasonal processes. Photic information may have a synchronizing effect on the endogenous clock of the SCN by inducing periodic changes in the functional activity of specific groups of neurons. The present study was performed to analyze the annual profiles of the arginine vasopressin (AVP)- and vasoactive intestinal polypeptide (VIP)-producing neurons in the human SCN. The populations of AVP- and VIP-expressing neurons in the SCN showed marked annual rhythms with an asymmetrical, bimodal waveform. Time series analysis indicated that these annual cycles in peptidergic activity could be described by a statistical model consisting of multiple-harmonic regression and ARMA components. The annual AVP cycle was adequately described by a two-harmonic model and a third-order autoregressive noise component, whereas the properties of the VIP cycle were best characterized by a two-harmonic model and a first-order autoregressive noise component. The models of both annual cycles reached a maximum in September-October and a minimum in May-June, and their estimated amplitudes, relative to the annual mean, were similar in size. These findings indicate that the biosynthesis of vasopressin and VIP in the human SCN exhibits an annual rhythmicity, and that the temporal organization of these processes is mainly controlled by environmental lighting conditions.     

Gates and oscillators: a network model of the brain clock

The suprachiasmatic nuclei (SCN) control circadian oscillations of physiology and behavior. Measurements of electrical activity and of gene expression indicate that these heterogeneous structures are composed of both rhythmic and nonrhythmic cells. A fundamental question with regard to the organization of the circadian system is how the SCN achieve a coherent output while their constituent independent cellular oscillators express a wide range of periods. Previously, the consensus output of individual oscillators had been attributed to coupling among cells. The authors propose a model that incorporates nonrhythmic "gate" cells and rhythmic oscillator cells with a wide range of periods, that neither requires nor excludes a role for interoscillator coupling. The gate provides daily input to oscillator cells and is in turn regulated (directly or indirectly) by the oscillator cells. In the authors' model, individual oscillators with initial random phases are able to self-assemble so as to maintain cohesive rhythmic output. In this view, SCN circuits are important for self-sustained oscillation, and their network properties distinguish these nuclei from other tissues that rhythmically express clock genes. The model explains how individual SCN cells oscillate independently and yet work together to produce a coherent rhythm.     

Gates and oscillators II: zeitgebers and the network model of the brain clock

Circadian rhythms in physiology and behavior are regulated by the SCN. When assessed by expression of clock genes, at least 2 distinct functional cell types are discernible within the SCN: nonrhythmic, light-inducible, retinorecipient cells and rhythmic autonomous oscillator cells that are not directly retinorecipient. To predict the responses of the circadian system, the authors have proposed a model based on these biological properties. In this model, output of rhythmic oscillator cells regulates the activity of the gate cells. The gate cells provide a daily organizing signal that maintains phase coherence among the oscillator cells. In the absence of external stimuli, this arrangement yields a multicomponent system capable of producing a self-sustained consensus rhythm. This follow-up study considers how the system responds when the gate cells are activated by an external stimulus, simulating a response to an entraining (or phase-setting) signal. In this model, the authors find that the system can be entrained to periods within the circadian range, that the free-running system can be phase shifted by timed activation of the gate, and that the phase response curve for activation is similar to that observed when animals are exposed to a light pulse. Finally, exogenous triggering of the gate over a number of days can organize an arrhythmic system, simulating the light-dependent reappearance of rhythmicity in a population of disorganized, independent oscillators. The model demonstrates that a single mechanism (i.e., the output of gate cells) can account for not only free-running and entrained rhythmicity but also other circadian phenomena, including limits of entrainment, a PRC with both delay and advance zones, and the light-dependent reappearance of rhythmicity in an arrhythmic animal.     

GABA synchronizes clock cells within the suprachiasmatic circadian clock

The master clock in the suprachiasmatic nuclei (SCN) is composed of multiple, single-cell circadian clocks. We test the postulate that these individual "clock cells" can be synchronized to each other by the inhibitory transmitter gamma-aminobutyric acid (GABA). For these experiments, we monitored the firing rate rhythm of individual clock cells on fixed multielectrode plates in culture and tested the effects of GABA. The results show that the daily variation in responsiveness of the SCN to phase-shifting agents is manifested at the level of individual neurons. Moreover, GABA, acting through A-type receptors, can both phase shift and synchronize clock cells. We propose that GABA is an important synchronizer of SCN neurons in vivo.     

Dissociation between circadian Per1 and neuronal and behavioral rhythms following a shifted environmental cycle

The suprachiasmatic nucleus (SCN) of the anterior hypothalamus contains a major circadian pacemaker that imposes or entrains rhythmicity on other structures by generating a circadian pattern in electrical activity. The identification of "clock genes" within the SCN and the ability to dynamically measure their rhythmicity by using transgenic animals open up new opportunities to study the relationship between molecular rhythmicity and other well-documented rhythms within the SCN. We investigated SCN circadian rhythms in Per1-luc bioluminescence, electrical activity in vitro and in vivo, as well as the behavioral activity of rats exposed to a 6-hr advance in the light-dark cycle followed by constant darkness. The data indicate large and persisting phase advances in Per1-luc bioluminescence rhythmicity, transient phase advances in SCN electrical activity in vitro, and an absence of phase advances in SCN behavioral or electrical activity measured in vivo. Surprisingly, the in vitro phase-advanced electrical rhythm returns to the phase measured in vivo when the SCN remains in situ. Our study indicates that hierarchical levels of organization within the circadian timing system influence SCN output and suggests a strong and unforeseen role of extra-SCN areas in regulating pacemaker function.     

Rhythm-induced spike-timing patterns characterized by 1D firing maps

We explore patterns in the spike timing of neurons receiving periodic inputs, with an emphasis on stable characteristics which are realized in both models and in-vitro whole-cell recordings. We report on whole-cell recordings of pyramidal CA1 cells from rat hippocampus and entorhinal cortex and compare this data to model simulations. Cells were injected with a constant current to induce a steady firing rate and then a modest rhythm was added which altered the spike times and their corresponding phases relative to the rhythm. For both experiment and theory the relationship between consecutive spike phases is characterized by a probability distribution with peaks concentrated near a one-dimensional firing map. As is well-known, stable fixed points of this map correspond to the neuron phase-locking to the rhythm. We show that the interaction between noise and sufficiently steep maps can also cause a new kind of spike-time organization, in which consecutive spike time pairs organize into discrete clusters, with transitions between these clusters proceeding in a fixed sequence. This structure is not just a vestige of the noise-free dynamics. This slow dynamics and temporal organization in the relationship between consecutive spike phases is not evident in either the neuron’s voltage traces or single phase or interspike interval histograms. Furthermore, the consecutive spike relationship is also evident in consecutive ISIs, and hence this ordering can be observed without detailed knowledge of the rhythm (e.g. without concurrent LFP recordings).