Circadian regulation of sleep–wake behaviour in nocturnal rats requires multiple signals from suprachiasmatic nucleus

Abstract

The dynamics of sleep and wake are strongly linked to the circadian clock. Many models have accurately predicted behaviour resulting from dynamic interactions between these two systems without specifying physiological substrates for these interactions. By contrast, recent experimental work has identified much of the relevant physiology for circadian and sleep-wake regulation, but interaction dynamics are difficult to study experimentally. To bridge these approaches, we developed a neuronal population model for the dynamic, bidirectional, neurotransmitter-mediated interactions of the sleepwake and circadian regulatory systems in nocturnal rats. This model proposes that the central circadian pacemaker, located within the suprachiasmatic nucleus (SCN) of the hypothalamus, promotes sleep through single neurotransmitter-mediated signalling to sleep-wake regulatory populations. Feedback projections from these populations to the SCN alter SCN firing patterns and fine-tune this modulation. Although this model reproduced circadian variation in sleep-wake dynamics in nocturnal rats, it failed to describe the sleep-wake dynamics observed in SCN-lesioned rats. We thus propose two alternative, physiologically based models in which neurotransmitter-and neuropeptidemediated signalling from the SCN to sleep-wake populations introduces mechanisms to account for the behaviour of both the intact and SCN-lesioned rat. These models generate testable predictions and offer a new framework for modelling sleep-wake and circadian interactions.

Adolescent sleep patterns in humans and laboratory animals

“…The daily rhythm in sleep is generated by the circadian timekeeping system, which alternately promotes wake or sleep depending on the time of day (Fleshner et al, 2011; Mistlberger, 2005; although see Edgar et al, 1993). In order for this system to tell time accurately, internally-generated rhythms are “entrained” by environmental time cues such as sunlight.…”

The sleeping brain as a complex system

“…This approach leads to so-called neural field models and is used in this issue by Bojak et al [38], Fleshner et al [39] and Robinson et al [40]. It ignores the precise firing times of neurons, which can be a reasonable approximation in neural populations for processes that are slow compared with that of the spike dynamics.…”

“…There the activity of the specific neural populations involved in sleep regulation is modelled by coupled nonlinear ordinary differential equations that can produce limit cycles, show hysteresis effects and undergo bifurcations. In this issue, Fleshner et al [39] concentrate on the interaction between the circadian and the homeostatic regulatory mechanisms by modelling the neurotransmitter-mediated interactions between the corresponding neural populations, whereas Robinson et al [40] focus on the reaction of the regulatory dynamics to external influences, such as auditory stimuli, sleep deprivation or caffeine.…”

“…Both Robinson et al [40] and Fleshner et al [39] model homeostasis in the framework of the adenosinergic system. In these models, the homeostatic component, however, has no link to neuronal substrates generating slow waves and thus has no relation to slow-wave activity.…”

Computer Simulation of Noise Effects of the Neighborhood of Stimulus Threshold for a Mathematical Model of Homeostatic Regulation of Sleep-Wake Cycles

“…This noise can influence the transmission and integration of signals from other neurons and alter the firing activity of neurons in isolation [2][3][4], and there are some significant effects near bifurcation points [5,6], the weak neural noise, that seem to be less relevant when the neurons operate in spike generating regime for a suprathreshold; however, the situation is completely different in the neighborhood of threshold where noise can induce significant changes in the impulse patterns; furthermore, in the central neural system, the neurons often work in the neighborhood of threshold, but neurons are heterogeneous and noise is inevitable [7]. Sleep is essential for the maintenance of the brain and the body, yet many features of sleep are poorly understood and mathematical models are an important tool for probing proposed biological mechanisms; in addition, noise is an inevitable factor in real neuronal systems, which plays an important role in spatiotemporal dynamics of neuronal networks, for nearly a century of study; some regulation nonlinear sleep models about circadian [8], diversity-induced resonance [9], temporal dynamics [10], physiological substrates [11,12], and more have been proposed to investigate the neural regulatory mechanism for sleep-wake cycle; however, sleep and its underlying processes still hold many mysteries; it remains unclear how identified brain regions interact to bring about the different stages of sleep and wakefulness, how the timing of sleep depends on the length of time spent awake and work load, and how pathologies associated with sleep, such as narcolepsy, arise [13]. As we all know, there are homeostatic formation mechanism and biological function 2 Complexity between connection neurons [14,15]; in this work, we study the spatiotemporal behaviors of noise effects in the neighborhood of stimulus threshold for a mathematical model of homeostatic regulation of sleep-wake cycles proposed by Postnova et al [16].…”