A physiologically based model of orexinergic stabilization of sleep and wake

Objective evaluation of excessive daytime sleepiness

Excessive daytime sleepiness (EDS) is multifactorial. It combines, among other things, an excessive propensity to fall asleep ("physiological sleepiness") and a continuous non-imperative sleepiness (or drowsiness/hypo-arousal) leading to difficulties remaining awake and maintaining sustained attention and vigilance over the long term ("manifest sleepiness"). There is no stand-alone biological measure of EDS. EDS measures can either capture the severity of physiological sleepiness, which corresponds to the propensity to fall asleep, or the severity of manifest sleepiness, which corresponds to behavioral consequences of sleepiness and reduced vigilance. Neuropsychological tests (The psychomotor vigilance task (PVT), Oxford Sleep Resistance Test (OSLeR), Sustained Attention to Response Task (SART)) explore manifest sleepiness through several sustained attention tests but the lack of normative values and standardized protocols make the results difficult to interpret and use in clinical practice. Neurophysiological tests explore the two main aspects of EDS, i.e. the propensity to fall asleep (Multiple sleep latency test, MSLT) and the capacity to remain awake (Maintenance of wakefulness test, MWT). The MSLT and the MWT are widely used in clinical practice. The MSLT is recognized as the "gold standard" test for measuring the severity of the propensity to fall asleep and it is a diagnostic criterion for narcolepsy. The MWT measures the ability to stay awake. The MWT is not a diagnostic test as it is recommended only to evaluate the evolution of EDS and efficacy of EDS treatment. Even if some efforts to standardize the protocols for administration of these tests have been ongoing, MSLT and MWT have numerous limitations: age effect, floor or ceiling effects, binding protocol, no normal or cutoff value (or determined in small samples), and no or low test-retest values in some pathologies. Moreover, the recommended electrophysiological set-up and the determination of sleep onset using the 30‑sec epochs scoring rule show some limitations. New, more precise neurophysiological techniques should aim to detect very brief periods of physiological sleepiness and, in the future, the brain local phenomenon of sleepiness likely to underpin drowsiness, which could be called "physiological drowsiness".

Pilot feasibility testing of biomathematical model recommendations for personalising sleep timing in shift workers

Sleep disturbances and circadian disruption play a central role in adverse health, safety, and performance outcomes in shift workers. While biomathematical models of sleep and alertness can be used to personalise interventions for shift workers, their practical implementation is undertested. This study tested the feasibility of implementing two biomathematical models-the Phillips-Robinson Model and the Model for Arousal Dynamics-in 28 shift-working nurses, 14 in each group. The study examined the overlap and adherence between model recommendations and sleep behaviours, and changes in sleep following the implementation of recommendations. For both groups combined, the mean (SD) percentage overlap between when a model recommended an individual to sleep and when sleep was obtained was 73.62% (10.24%). Adherence between model recommendations and sleep onset and offset times was significantly higher with the Model of Arousal Dynamics compared to the Phillips-Robinson Model. For the Phillips-Robinson model, 27% of sleep onset and 35% of sleep offset times were within ± 30 min of model recommendations. For the Model of Arousal Dynamics, 49% of sleep onset, and 35% of sleep offset times were within ± 30 min of model recommendations. Compared to pre-study, significant improvements were observed post-study for sleep disturbance (Phillips-Robinson Model), and insomnia severity and sleep-related impairments (Model of Arousal Dynamics). Participants reported that using a digital, automated format for the delivery of sleep recommendations would enable greater uptake. These findings provide a positive proof-of-concept for using biomathematical models to recommend sleep in operational contexts.

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

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

Disrupted nighttime sleep and sleep instability in narcolepsy

STUDY OBJECTIVES

This review aimed to summarize current knowledge about disrupted nighttime sleep (DNS) and sleep instability in narcolepsy, including self-reported and objective assessments, potential causes of sleep instability, health consequences and functional burden, and management.

METHODS

One hundred two peer-reviewed publications from a PubMed search were included.

RESULTS

DNS is a key symptom of narcolepsy but has received less attention than excessive daytime sleepiness and cataplexy. There has been a lack of clarity regarding the definition of DNS, as many sleep-related symptoms and conditions disrupt sleep quality in narcolepsy (eg, hallucinations, sleep paralysis, rapid eye movement sleep behavior disorder, nightmares, restless legs syndrome/periodic leg movements, nocturnal eating, sleep apnea, depression, anxiety). In addition, the intrinsic sleep instability of narcolepsy results in frequent spontaneous wakings and sleep stage transitions, contributing to DNS. Sleep instability likely emerges in the setting of orexin insufficiency/deficiency, but its exact pathophysiology remains unknown. DNS impairs quality of life among people with narcolepsy, and more research is needed to determine its contributions to cardiovascular risk. Multimodal treatment is appropriate for DNS management, including behavioral therapies, counseling on sleep hygiene, and/or medication. There is strong evidence showing improvement in self-reported sleep quality and objective sleep stability measures with sodium oxybate, but rigorous clinical trials with other pharmacotherapies are needed. Treatment may be complicated by comorbidities, concomitant medications, and mood disorders.

CONCLUSIONS

DNS is a common symptom of narcolepsy deserving consideration in clinical care and future research.

CITATION

Maski K, Mignot E, Plazzi G, Dauvilliers Y. Disrupted nighttime sleep and sleep instability in narcolepsy. J Clin Sleep Med. 2022;18(1):289-304.

Sleep in Normal Aging, Homeostatic and Circadian Regulation and Vulnerability to Sleep Deprivation

In the context of geriatric research, a growing body of evidence links normal age-related changes in sleep with many adverse health outcomes, especially a decline in cognition in older adults. The most important sleep alterations that continue to worsen after 60 years involve sleep timing, (especially early wake time, phase advance), sleep maintenance (continuity of sleep interrupted by numerous awakenings) and reduced amount of sigma activity (during non-rapid eye movement (NREM) sleep) associated with modifications of sleep spindle characteristics (density, amplitude, frequency) and spindle-Slow Wave coupling. After 60 years, there is a very clear gender-dependent deterioration in sleep. Even if there are degradations of sleep after 60 years, daytime wake level and especially daytime sleepiness is not modified with age. On the other hand, under sleep deprivation condition, older adults show smaller cognitive impairments than younger adults, suggesting an age-related lower vulnerability to extended wakefulness. These sleep and cognitive age-related modifications would be due to a reduced homeostatic drive and consequently a reduced sleep need, an attenuation of circadian drive (reduction of sleep forbidden zone in late afternoon and wake forbidden zone in early morning), a modification of the interaction of the circadian and homeostatic processes and/or an alteration of subcortical structures involved in generation of circadian and homeostatic drive, or connections to the cerebral cortex with age. The modifications and interactions of these two processes with age are still uncertain, and still require further investigation. The understanding of the respective contribution of circadian and homeostatic processes in the regulation of neurobehavioral function with aging present a challenge for improving health, management of cognitive decline and potential early chronobiological or sleep-wake interventions.

Regulation of microRNA Expression in Sleep Disorders in Patients with Epilepsy

The effects of epilepsy on sleep and the activating effects of sleep on seizures are well documented in the literature. To date, many sleep-related and awake-associated epilepsy syndromes have been described. The relationship between sleep and epilepsy has led to the recognition of polysomnographic testing as an important diagnostic tool in the diagnosis of epilepsy. The authors analyzed the available medical database in search of other markers that assess correlations between epilepsy and sleep. Studies pointing to microRNAs, whose abnormal expression may be common to epilepsy and sleep disorders, are promising. In recent years, the role of microRNAs in the pathogenesis of epilepsy and sleep disorders has been increasingly emphasized. MicroRNAs are a family of single-stranded, non-coding, endogenous regulatory molecules formed from double-stranded precursors. They are typically composed of 21–23 nucleotides, and their main role involves post-transcriptional downregulation of expression of numerous genes. Learning more about the role of microRNAs in the pathogenesis of sleep disorder epilepsy may result in its use as a biomarker in these disorders and application in therapy.

Stability of nocturnal wake and sleep stages defines central nervous system disorders of hypersomnolence

STUDY OBJECTIVES

We determine if young people with narcolepsy type 1 (NT1), narcolepsy type 2 (NT2), and idiopathic hypersomnia (IH) have distinct nocturnal sleep stability phenotypes compared to subjectively sleepy controls.

METHODS

Participants were 5- to 21-year old and drug-naïve or drug free: NT1 (n = 46), NT2 (n = 12), IH (n = 18), and subjectively sleepy controls (n = 48). We compared the following sleep stability measures from polysomnogram recording between each hypersomnolence disorder to subjectively sleepy controls: number of wake and sleep stage bouts, Kaplan-Meier survival curves for wake and sleep stages, and median bout durations.

RESULTS

Compared to the subjectively sleepy control group, NT1 participants had more bouts of wake and all sleep stages (p ≤ .005) except stage N3. NT1 participants had worse survival of nocturnal wake, stage N2, and rapid eye movement (REM) bouts (p < .005). In the first 8 hours of sleep, NT1 participants had longer stage N1 bouts but shorter REM (all ps < .004). IH participants had a similar number of bouts but better survival of stage N2 bouts (p = .001), and shorter stage N3 bouts in the first 8 hours of sleep (p = .003). In contrast, NT2 participants showed better stage N1 bout survival (p = .006) and longer stage N1 bouts (p = .02).

CONCLUSIONS

NT1, NT2, and IH have unique sleep physiology compared to subjectively sleepy controls, with only NT1 demonstrating clear nocturnal wake and sleep instability. Overall, sleep stability measures may aid in diagnoses and management of these central nervous system disorders of hypersomnolence.

Review of the Efficacy and Safety of Lemborexant, a Dual Receptor Orexin Antagonist (DORA), in the Treatment of Adults With Insomnia Disorder

OBJECTIVE

To provide an overview of the efficacy and safety of lemborexant in the treatment of insomnia disorder by assessing the currently available literature.

DATA SOURCES

A literature search of PubMed was performed (2010 to March 2021) using the following search terms: lemborexant, sleep, orexin.

STUDY SELECTION AND DATA EXTRACTION

All relevant English-language studies were reviewed and considered, with a focus on phase 3 trials.

DATA SYNTHESIS

The efficacy and safety of lemborexant in the treatment of insomnia disorder in adults was demonstrated in 2 phase 3 trials. Lemborexant significantly reduced latency to persistent sleep compared with placebo. The first study also demonstrated a significant reduction compared with the active control zolpidem ER. Somnolence and headache were relatively common, but the marked adverse effects associated with other medications commonly used to treat insomnia, such as cognitive and psychomotor impairment and complex sleep-related behaviors, were not observed.

RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE

Although nonpharmacological therapy is considered first-line treatment for insomnia disorder, pharmacological treatment is most commonly utilized. Lemborexant is a viable pharmacological treatment option for patients who are unable to tolerate the adverse effects associated with the most commonly prescribed medications for insomnia, such as benzodiazepines and sedative-hypnotics (Z drugs). This is especially true for geriatric patients, who may be more sensitive to these adverse effects.

CONCLUSION

Lemborexant can be recommended to treat insomnia disorder when pharmacological treatment is warranted. It has demonstrated efficacy in clinical trials and is likely better tolerated than most currently available treatment options.

The Inert Brain: Explaining Neural Inertia as Post-anaesthetic Sleep Inertia

"Neural inertia" is the brain's tendency to resist changes in its arousal state: it is manifested as emergence from anaesthesia occurring at lower drug doses than those required for anaesthetic induction, a phenomenon observed across very different species, from invertebrates to mammals. However, the brain is also subject to another form of inertia, familiar to most people: sleep inertia, the feeling of grogginess, confusion and impaired performance that typically follows awakening. Here, we propose a novel account of neural inertia, as the result of sleep inertia taking place after the artificial sleep induced by anaesthetics. We argue that the orexinergic and noradrenergic systems may be key mechanisms for the control of these transition states, with the orexinergic system exerting a stabilising effect through the noradrenergic system. This effect may be reflected at the macroscale in terms of altered functional anticorrelations between default mode and executive control networks of the human brain. The hypothesised link between neural inertia and sleep inertia could explain why different anaesthetic drugs induce different levels of neural inertia, and why elderly individuals and narcoleptic patients are more susceptible to neural inertia. This novel hypothesis also enables us to generate several empirically testable predictions at both the behavioural and neural levels, with potential implications for clinical practice.

The Inert Brain: Explaining Neural Inertia as Post-anaesthetic Sleep Inertia

"Neural inertia" is the brain's tendency to resist changes in its arousal state: it is manifested as emergence from anaesthesia occurring at lower drug doses than those required for anaesthetic induction, a phenomenon observed across very different species, from invertebrates to mammals. However, the brain is also subject to another form of inertia, familiar to most people: sleep inertia, the feeling of grogginess, confusion and impaired performance that typically follows awakening. Here, we propose a novel account of neural inertia, as the result of sleep inertia taking place after the artificial sleep induced by anaesthetics. We argue that the orexinergic and noradrenergic systems may be key mechanisms for the control of these transition states, with the orexinergic system exerting a stabilising effect through the noradrenergic system. This effect may be reflected at the macroscale in terms of altered functional anticorrelations between default mode and executive control networks of the human brain. The hypothesised link between neural inertia and sleep inertia could explain why different anaesthetic drugs induce different levels of neural inertia, and why elderly individuals and narcoleptic patients are more susceptible to neural inertia. This novel hypothesis also enables us to generate several empirically testable predictions at both the behavioural and neural levels, with potential implications for clinical practice.

Recent advances in modeling sleep: from the clinic to society and disease

In the past few decades, advances in understanding sleep-wake neurophysiology have occurred hand-in-hand with advances in mathematical modeling of sleep and wake. In this review, we summarize recent updates in modeling the timing and durations of sleep and wake, the underlying neurophysiology of sleep and wake, and the application of these models in understanding cognition and disease. Throughout, we highlight the role modeling has played in developing our understanding of sleep and its underlying mechanisms. We present open questions and controversies in the field and propose the utility of individualized models of sleep for precision sleep medicine.

On-the-road driving performance the morning after bedtime administration of lemborexant in healthy adult and elderly volunteers

Study Objectives

To assess potential effects of lemborexant on next-morning driving performance in adult and elderly healthy volunteers.

Methods

Randomized, double-blind, double-dummy, placebo and active-controlled, four period incomplete crossover study in 48 healthy volunteers (22 females), 23–78 years old. Participants were treated at bedtime for eight consecutive nights with two of three dose levels of lemborexant (2.5, 5, or 10 mg), zopiclone 7.5 mg (on the first and last night with placebo on intervening nights), or placebo. Driving performance was assessed in the morning on days 2 and 9 using a standardized highway driving test in normal traffic, measuring standard deviation of lateral position (SDLP). Drug–placebo differences in SDLP >2.4 cm were considered to reflect clinically meaningful driving impairment.

Results

Mean drug–placebo differences in SDLP following lemborexant 2.5, 5, and 10 mg on days 2 and 9 were 0.74 cm or less. The upper bound of the 95% confidence intervals (CIs) for lemborexant treatment groups were all below 2.4 cm and the 95% CIs included zero, indicating that the effects were neither clinically meaningful nor statistically significant. Symmetry analysis further supported the lack of clinically meaningful impairment with lemborexant.

Conclusions

When assessed starting ~9 h after lemborexant administration at bedtime the previous night, there was no statistically significant or clinically meaningful effect on driving performance in healthy adults and elderly, as assessed by either mean differences in SDLP relative to placebo or symmetry analysis. In this study, lemborexant at doses up to 10 mg was well-tolerated.

Clinical Trial Registration

clinicaltrials.gov, NCT02583451. https://clinicaltrials.gov/ct2/show/NCT02583451.

Sleep Modelling across Physiological Levels

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

Neuroendocrine Control of Sleep

Sleep is a phenomenon in animal behavior as enigmatic as it is ubiquitous, and one deeply tied to endocrine function. Though there are still many unanswered questions about the neurochemical basis of sleep and its functions, extensive interactions have been identified between sleep and the endocrine system, in both the endocrine system's effect on sleep and sleep's effect on the endocrine system. Unfortunately, until recent years, much research on sleep behavior largely disregarded its connections with the endocrine system. Use of both clinical studies and rodent models to investigate interactions between neuroendocrine function, including biological sex, and sleep therefore presents a promising area of further exploration. Further investigation of the neurobiological and neuroendocrine basis of sleep could have wide impact on a number of clinical and basic science fields. In this review, we summarize the state of basic sleep biology and its connections to the field of neuroendocrine biology, as well as suggest key future directions for the neuroendocrine regulation of sleep that may significantly impact new therapies for sleep disorders in women and men.

Spiking patterns and synchronization of thalamic neurons along the sleep-wake cycle

Spiking patterns and synchronization dynamics of thalamic neurons along the sleep-wake cycle are studied in a minimal model of four coupled conductance-based neurons. The model simulates two thalamic neurons coupled via a gap junction and driven by a synaptic input from a two-neuron model of sleep regulation by the hypothalamus. In accord with experimental data, the model shows that during sleep, when hypothalamic wake-active neurons are silent, the thalamic neurons discharge bursts of spikes. During wake, the excitatory synaptic input from the hypothalamus drives the coupled thalamic neurons to a state of tonic firing (single spikes). In the deterministic case, the thalamic neurons synchronize in-phase in the bursting regime but demonstrate multi-stability of out-of-phase, in-phase, and asynchronous states in the tonic firing. However, along the sleep-wake cycle, once the neurons synchronize in-phase during sleep (bursting), they stay synchronized in wake (tonic firing). It is thus found that noise is needed to reproduce the experimentally observed transitions between synchronized bursting during sleep and asynchronous tonic firing during wake. Overall, synchronization of bursting is found to be more robust to noise than synchronization of tonic firing, where a small disturbance is sufficient to desynchronize the thalamic neurons. The model predicts that the transitions between sleep and wake happen via chaos because a single thalamic neuron exhibits chaos between regular bursting and tonic activity. The results of this study suggest that the sleep- and wake-related dynamics in the thalamus may be generated at a level of gap junction-coupled clusters of thalamic neurons driven from the hypothalamus which would then propagate throughout the thalamus and cortex via axonal long-range connections.

Numerical study of entrainment of the human circadian system and recovery by light treatment

Background

While the effects of light as a zeitgeber are well known, the way the effects are modulated by features of the sleep-wake system still remains to be studied in detail.

Methods

A mathematical model for disturbance and recovery of the human circadian system is presented. The model combines a circadian oscillator and a sleep-wake switch that includes the effects of orexin. By means of simulations, we characterize the period-locking zone of the model, where a stable 24-hour circadian rhythm exists, and the occurrence of circadian disruption due to both insufficient light and imbalance in orexin. We also investigate how daily bright light treatments of short duration can recover the normal circadian rhythm.

Results

It is found that the system exhibits continuous phase advance/delay at lower/higher orexin levels. Bright light treatment simulations disclose two optimal time windows, corresponding to morning and evening light treatments. Among the two, the morning light treatment is found effective in a wider range of parameter values, with shorter recovery time.

Conclusions

This approach offers a systematic way to determine the conditions under which circadian disruption occurs, and to evaluate the effects of light treatment. In particular, it could potentially offer a way to optimize light treatments for patients with circadian disruption, e.g., sleep and mood disorders, in clinical settings.

Modeling the adenosine system as a modulator of cognitive performance and sleep patterns during sleep restriction and recovery

Sleep loss causes profound cognitive impairments and increases the concentrations of adenosine and adenosine A1 receptors in specific regions of the brain. Time courses for performance impairment and recovery differ between acute and chronic sleep loss, but the physiological basis for these time courses is unknown. Adenosine has been implicated in pathways that generate sleepiness and cognitive impairments, but existing mathematical models of sleep and cognitive performance do not explicitly include adenosine. Here, we developed a novel receptor-ligand model of the adenosine system to test the hypothesis that changes in both adenosine and A1 receptor concentrations can capture changes in cognitive performance during acute sleep deprivation (one prolonged wake episode), chronic sleep restriction (multiple nights with insufficient sleep), and subsequent recovery. Parameter values were estimated using biochemical data and reaction time performance on the psychomotor vigilance test (PVT). The model closely fit group-average PVT data during acute sleep deprivation, chronic sleep restriction, and recovery. We tested the model's ability to reproduce timing and duration of sleep in a separate experiment where individuals were permitted to sleep for up to 14 hours per day for 28 days. The model accurately reproduced these data, and also correctly predicted the possible emergence of a split sleep pattern (two distinct sleep episodes) under these experimental conditions. Our findings provide a physiologically plausible explanation for observed changes in cognitive performance and sleep during sleep loss and recovery, as well as a new approach for predicting sleep and cognitive performance under planned schedules.

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

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

Wake-sleep transition as a noisy bifurcation

A recent physiologically based model of the ascending arousal system is used to analyze the dynamics near the transition from wake to sleep, which corresponds to a saddle-node bifurcation at a critical point. A normal form is derived by approximating the dynamics by those of a particle in a parabolic potential well with dissipation. This mechanical analog is used to calculate the power spectrum of fluctuations in response to a white noise drive, and the scalings of fluctuation variance and spectral width are derived versus distance from the critical point. The predicted scalings are quantitatively confirmed by numerical simulations, which show that the variance increases and the spectrum undergoes critical slowing, both in accord with theory. These signals can thus serve as potential precursors to indicate imminent wake-sleep transition, with potential application to safety-critical occupations in transport, air-traffic control, medicine, and heavy industry.

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

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

A Neurophysiological Approach for Evaluating Noise-Induced Sleep Disturbance: Calculating the Time Constant of the Dynamic Characteristics in the Brainstem

Chronic sleep disturbance induced by traffic noise is considered to cause environmental sleep disorder, which increases the risk of cardiovascular disease, stroke, diabetes and other stress-related diseases. However, noise indices for the evaluation of sleep disturbance are not based on the neurophysiological process of awakening regulated by the brainstem. In this study, through the neurophysiological approach, we attempted (1) to investigate the thresholds of awakening due to external stimuli in the brainstem; (2) to evaluate the dynamic characteristics in the brainstem and (3) to verify the validity of existing noise indices. Using the mathematical Phillips-Robinson model, we obtained thresholds of awakening in the brainstem for different durations of external stimuli. The analysis revealed that the brainstem seemed insensitive to short stimuli and that the response to external stimuli in the brainstem could be approximated by a first-order lag system with a time constant of 10-100 s. These results suggest that the brainstem did not integrate sound energy as external stimuli, but neuroelectrical signals from auditory nerve. To understand the awakening risk accumulated in the brainstem, we introduced a new concept of "awakening potential" instead of sound energy.

Exponential state transition dynamics in the rest-activity architecture of patients with bipolar disorder

OBJECTIVE

Our goal was to model the temporal dynamics of sleep-wake transitions, represented by transitions between rest and activity obtained from actigraphic data, in patients with bipolar disorder using a probabilistic state transition approach.

METHODS

We collected actigraphic data for 14 days from 20 euthymic patients with bipolar disorder, who had been characterized clinically, demographically, and with respect to their circadian preferences (chronotype). We processed each activity record to generate a series of transitions in both directions between the states of rest (R) and activity (A) and plotted the estimated transition probabilities (pRA and pAR). Each 24-hour period was also divided into a rest phase consisting of the eight consecutive least active hours in each day and an active phase consisting of the 16 consecutive most active hours in each day. We then calculated separate transition probabilities for each of these phases for each participant. We subsequently modeled the rest phase data to find the best fit for rest-activity transitions using maximum likelihood estimation. We also examined the association of transition probabilities with clinical and demographic variables.

RESULTS

The best-fit model for rest-activity transitions during the rest phase was a mixture (bimodal) of exponential functions. Of those patients with rapid cycling, 75% had an evening-type chronotype. Patients with bipolar II disorder taking antidepressants had a lower probability of transitioning back to rest than those not on antidepressants [mean ± SD = 0.050 ± 0.006 versus 0.141 ± 0.058, F(1,15) = 3.40, p < 0.05].

CONCLUSIONS

The dynamics of transitions between rest and activity in bipolar disorder can be accounted for by a mixture (bimodal) of exponential functions. Patients taking antidepressants had a reduced probability of sustaining and returning to sleep.

On-the-road driving performance the morning after bedtime use of suvorexant 15 and 30 mg in healthy elderly

RATIONALE

Suvorexant is a first-in-class orexin receptor antagonist for treating insomnia. There is a general concern that hypnotics may impair next-morning driving ability.

OBJECTIVE

The objective of this study was to evaluate next-morning driving performance in older adults after single and repeated doses of suvorexant.

METHODS

Double-blind, randomized, placebo-controlled, 4-period crossover study in 24 healthy volunteers (10 females), aged 65-80 years. Subjects were treated with suvorexant (15 and 30 mg) for eight consecutive nights, zopiclone 7.5 mg nightly on days 1 and 8, and placebo. Driving performance was assessed on days 2 and 9 (9 h after dosing) using a 1-h standardized highway driving test in normal traffic, measuring standard deviation of lateral position (SDLP). Drug-placebo differences in SDLP >2.4 cm were considered to reflect clinically meaningful driving impairment.

RESULTS

Driving performance as measured by SDLP was not impaired following suvorexant. Mean drug-placebo differences in SDLP following suvorexant 15 and 30 mg on day 2 and 9 were 0.6 cm or less. Their 90 % CIs were all below the threshold of 2.4 cm for clinical relevance and included zero, indicating effects were not clinically meaningful or statistically significant. Symmetry analysis showed no significant differences between the number of participants who had SDLP differences >2.4 cm and those who had SDLP differences <-2.4 cm following suvorexant.

CONCLUSIONS

There was no clinically meaningful residual effect of suvorexant 15 and 30 mg on next-morning driving (9 h after bedtime dosing) in healthy older adults, as assessed by mean changes in SDLP and by the number of participants on drug versus placebo that exceeded a predetermined threshold for clinically meaningful impairment.

A Framework for Quantitative Modeling of Neural Circuits Involved in Sleep-to-Wake Transition

Identifying the neuronal circuits and dynamics of sleep-to-wake transition is essential to understanding brain regulation of behavioral states, including sleep–wake cycles, arousal, and hyperarousal. Recent work by different laboratories has used optogenetics to determine the role of individual neuromodulators in state transitions. The optogenetically driven data do not yet provide a multi-dimensional schematic of the mechanisms underlying changes in vigilance states. This work presents a modeling framework to interpret, assist, and drive research on the sleep-regulatory network. We identify feedback, redundancy, and gating hierarchy as three fundamental aspects of this model. The presented model is expected to expand as additional data on the contribution of each transmitter to a vigilance state becomes available. Incorporation of conductance-based models of neuronal ensembles into this model and existing models of cortical excitability will provide more comprehensive insight into sleep dynamics as well as sleep and arousal-related disorders.

Effects of reciprocal inhibitory coupling in model neurons

Central pattern generators are neuron networks that produce vital rhythmic motor outputs such as those observed in mastication, walking and breathing. Their activity patterns depend on the tuning of their intrinsic ionic conductances, their synaptic interconnectivity and entrainment by extrinsic neurons. The influence of two commonly found synaptic connectivities--reciprocal inhibition and electrical coupling--are investigated here using a neuron model with subthreshold oscillation capability, in different firing and entrainment regimes. We study the dynamics displayed by a network of a pair of neurons with various firing regimes, coupled by either (i) only reciprocal inhibition or by (ii) electrical coupling first and then reciprocal inhibition. In both scenarios a range of coupling strengths for the reciprocal inhibition is tested, and in general the neuron with the lower firing rate stops spiking for strong enough inhibitory coupling, while the faster neuron remains active. However, in scenario (ii) the originally slower neuron stops spiking at weaker inhibitory coupling strength, suggesting that the electrical coupling introduces an element of instability to the two-neuron network.

A unifying computational framework for stability and flexibility of arousal

Arousal and consciousness flexibly adjust to salient cues, but remain stable despite noise and disturbance. Diverse, highly interconnected neural networks govern the underlying transitions of behavioral state; these networks are robust but very complex. Frameworks from systems engineering provide powerful tools for understanding functional logic behind component complexity. From a general systems viewpoint, a minimum of three communicating control modules may enable flexibility and stability to coexist. Comparators would subtract current arousal from desired arousal, producing an error signal. Regulators would compute control signals from this error. Generators would convert control signals into arousal, which is fed back to comparators, to make the system noise-proof through self-correction. Can specific neurons correspond to these control elements? To explore this, here we consider the brain-wide orexin/hypocretin network, which is experimentally established to be vital for flexible and stable arousal. We discuss whether orexin neurons may act as comparators, and their target neurons as regulators and generators. Experiments are proposed for testing such predictions, based on computational simulations showing that comparators, regulators, and generators have distinct temporal signatures of activity. If some regulators integrate orexin-communicated errors, robust arousal control may be achieved via integral feedback (a basic engineering strategy for tracking a set-point despite noise). An integral feedback view also suggests functional roles for specific molecular aspects, such as differing life-spans of orexin peptides. The proposed framework offers a unifying logic for molecular, cellular, and network details of arousal systems, and provides insight into behavioral state transitions, complex behavior, and bases for disease.