Cecilia G. Diniz Behn

Impact of Sleep and Circadian Disruption on Energy Balance and Diabetes: A Summary of Workshop Discussions

A workshop was held at the National Institute for Diabetes and Digestive and Kidney Diseases with a focus on the impact of sleep and circadian disruption on energy balance and diabetes. The workshop identified a number of key principles for research in this area and a number of specific opportunities. Studies in this area would be facilitated by active collaboration between investigators in sleep/circadian research and investigators in metabolism/diabetes. There is a need to translate the elegant findings from basic research into improving the metabolic health of the American public. There is also a need for investigators studying the impact of sleep/circadian disruption in humans to move beyond measurements of insulin and glucose and conduct more in-depth phenotyping. There is also a need for the assessments of sleep and circadian rhythms as well as assessments for sleep-disordered breathing to be incorporated into all ongoing cohort studies related to diabetes risk. Studies in humans need to complement the elegant short-term laboratory-based human studies of simulated short sleep and shift work etc. with studies in subjects in the general population with these disorders. It is conceivable that chronic adaptations occur, and if so, the mechanisms by which they occur needs to be identified and understood. Particular areas of opportunity that are ready for translation are studies to address whether CPAP treatment of patients with pre-diabetes and obstructive sleep apnea (OSA) prevents or delays the onset of diabetes and whether temporal restricted feeding has the same impact on obesity rates in humans as it does in mice.

Simulating Microinjection Experiments in a Novel Model of the Rat Sleep-Wake Regulatory Network

This study presents a novel mathematical modeling framework that is uniquely suited to investigating the structure and dynamics of the sleep-wake regulatory network in the brain stem and hypothalamus. It is based on a population firing rate model formalism that is modified to explicitly include concentration levels of neurotransmitters released to postsynaptic populations. Using this framework, interactions among primary brain stem and hypothalamic neuronal nuclei involved in rat sleep-wake regulation are modeled. The model network captures realistic rat polyphasic sleep-wake behavior consisting of wake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep states. Network dynamics include a cyclic pattern of NREM sleep, REM sleep, and wake states that is disrupted by simulated variability of neurotransmitter release and external noise to the network. Explicit modeling of neurotransmitter concentrations allows for simulations of microinjections of neurotransmitter agonists and antagonists into a key wake-promoting population, the locus coeruleus (LC). Effects of these simulated microinjections on sleep-wake states are tracked and compared with experimental observations. Agonist/antagonist pairs, which are presumed to have opposing effects on LC activity, do not generally induce opposing effects on sleep-wake patterning because of multiple mechanisms for LC activation in the network. Also, different agents, which are presumed to have parallel effects on LC activity, do not induce parallel effects on sleep-wake patterning because of differences in the state dependence or independence of agonist and antagonist action. These simulation results highlight the utility of formal mathematical modeling for constraining conceptual models of the sleep-wake regulatory network.

Physiologically-based modeling of sleep–wake regulatory networks

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

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

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 sleep–wake 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 neuropeptide-mediated 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.

Enhanced stability and polyadenylation of select mRNAs support rapid thermogenesis in the brown fat of a hibernator

During hibernation, animals cycle between torpor and arousal. These cycles involve dramatic but poorly understood mechanisms of dynamic physiological regulation at the level of gene expression. Each cycle, Brown Adipose Tissue (BAT) drives periodic arousal from torpor by generating essential heat. We applied digital transcriptome analysis to precisely timed samples to identify molecular pathways that underlie the intense activity cycles of hibernator BAT. A cohort of transcripts increased during torpor, paradoxical because transcription effectively ceases at these low temperatures. We show that this increase occurs not by elevated transcription but rather by enhanced stabilization associated with maintenance and/or extension of long poly(A) tails. Mathematical modeling further supports a temperature-sensitive mechanism to protect a subset of transcripts from ongoing bulk degradation instead of increased transcription. This subset was enriched in a C-rich motif and genes required for BAT activation, suggesting a model and mechanism to prioritize translation of key proteins for thermogenesis. DOI: http://dx.doi.org/10.7554/eLife.04517.001

A Fast-Slow Analysis of the Dynamics of REM Sleep

Waking and sleep states are regulated by the coordinated activity of a number of neuronal populations in the brainstem and hypothalamus whose synaptic interactions compose a sleep-wake regulatory network. Physiologically based mathematical models of the sleep-wake regulatory network contain mechanisms operating on multiple time scales including relatively fast synaptic-based interactions between neuronal populations, and much slower homeostatic and circadian processes that modulate sleep-wake temporal patterning. In this study, we exploit the naturally arising slow time scale of the homeostatic sleep drive in a reduced sleep-wake regulatory network model to utilize fast-slow analysis to investigate the dynamics of rapid eye movement (REM) sleep regulation. The network model consists of a reduced number of wake-, non-REM (NREM) sleep-, and REM sleep-promoting neuronal populations with synaptic interactions reflecting the mutually inhibitory flip-flop conceptual model for sleep-wake regulation and the recip...

Dynamic interactions between orexin and dynorphin may delay onset of functional orexin effects: a modeling study.

Orexin (also known as hypocretin) neurons play a key role in regulating sleep-wake behavior, but the links between orexin neuron electrophysiology and function have not been explored. Orexin neurons are wake-active, and spiking activity in orexin neurons may anticipate transitions to wakefulness by several seconds. However, it is suggested that while the orexin system is necessary to maintain sustained wake bouts, orexin has little effect on brief wake bouts. In vitro experiments investigating the actions of orexin and dynorphin, a colocalized neuropeptide, on orexin neurons indicate that the dynamics of desensitization to dynorphin may represent a mechanism for modulating local network activity and resolving the apparent discrepancy between the onset of firing in orexin neurons and the onset of functional orexin effects. To investigate the role of dynorphin on orexin neuron activity, a Hodgkin-Huxley—type model orexin neuron was developed in which baseline electrophysiology, orexin/dynorphin action, and dynorphin desensitization were closely tied to experimental data. In this model framework, model orexin neuron responses to orexin/dynorphin action were calibrated by simulating the physiologic effects of static orexin and dynorphin bath application on orexin neurons. Then behavior in a small network of model orexin neurons was simulated with pure orexin, pure dynorphin, or combined orexin and dynorphin coupling based on the mechanisms established in the static case. It was found that the dynamics of desensitization to dynorphin can mediate a clear shift from a network in which firing is suppressed by dynorphin-mediated inhibition to a network of neurons with high firing rates sustained by orexin-mediated excitation. The findings suggest that dynamic interactions between orexin and dynorphin at transitions from sleep to wake may delay onset of functional orexin effects.

Contrasting Existence and Robustness of REM/Non-REM Cycling in Physiologically Based Models of REM Sleep Regulatory Networks

Typical human sleep throughout the night consists of alternating periods of rapid eye movement (REM) sleep and non-REM (NREM) sleep. This ultradian rhythm of NREM/REM cycling is thought to be produced by the state-dependent activity of “REM-on” and “REM-off” brainstem and hypothalamic neuronal populations that, respectively, promote or suppress REM sleep. Synaptic interactions among these populations define REM sleep regulatory networks; however, the identity of the key neuronal populations in these networks and the dynamics of interactions among them are disputed and cannot be addressed comprehensively with current experimental techniques. The purpose of this study is to use physiologically based mathematical models to explore the dynamic implications associated with competing hypotheses for network-based REM sleep regulation. Generally, putative REM sleep regulatory networks fall into two categories: a reciprocal interaction network consisting of an excitatory REM-on population interacting with an inhib...

Modeling Interindividual Differences in Spontaneous Internal Desynchrony Patterns

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

Modeling the temporal architecture of rat sleep-wake behavior

The fine architecture of sleep-wake behavior shows a distinct dynamic structure with distributions of rat sleep and wake bout durations displaying qualitatively different profiles. Wake bout durations follow a power-law relation whereas sleep bout durations are exponentially distributed. We show that a physiologically-based sleep-wake regulatory network model with an underlying deterministic structure governing neuronal interactions can generate realistic rat sleep-wake behavior as assessed by both standard summary statistics and survival analysis of bout distributions. Obtaining appropriate bout duration distributions depended on stochastic elements included in the model, the existence of multiple mechanisms for state transitions, and specific relationships among time constants governing state maintenance. This model provides a novel framework for exploring the disruptions of sleep-wake architecture associated with pharmacological, genetic, and disease states.