The Transition Between Slow-Wave Sleep and REM Sleep Constitutes an Independent Sleep Stage Organized by Cholinergic Mechanisms in the Rostrodorsal Pontine Tegmentum

Out-of-body experiences in relation to lucid dreaming and sleep paralysis: A theoretical review and conceptual model

Out-of-body experiences (OBEs) are characterized by the subjective experience of being located outside the physical body. Little is known about the neurophysiology of spontaneous OBEs, which are often reported by healthy individuals as occurring during states of reduced vigilance, particularly in proximity to or during sleep (sleep-related OBEs). In this paper, we review the current state of research on sleep-related OBEs and hypothesize that maintaining consciousness during transitions from wakefulness to REM sleep (sleep-onset REM periods) may facilitate sleep-related OBEs. Based on this hypothesis, we propose a new conceptual model that potentially describes the relationship between OBEs and sleep states. The model sheds light on the phenomenological differences between sleep-related OBEs and similar states of consciousness, such as lucid dreaming (the realization of being in a dream state) and sleep paralysis (feeling paralyzed while falling asleep or waking up), and explores the potential polysomnographic features underlying sleep-related OBEs. Additionally, we apply the predictive coding framework and suggest a connecting link between sleep-related OBEs and OBEs reported during wakefulness.

The Ponto-Geniculo-Occipital (PGO) Waves in Dreaming: An Overview

Rapid eye movement (REM) sleep is the main sleep correlate of dreaming. Ponto-geniculo-occipital (PGO) waves are a signature of REM sleep. They represent the physiological mechanism of REM sleep that specifically limits the processing of external information. PGO waves look just like a message sent from the pons to the lateral geniculate nucleus of the visual thalamus, the occipital cortex, and other areas of the brain. The dedicated visual pathway of PGO waves can be interpreted by the brain as visual information, leading to the visual hallucinosis of dreams. PGO waves are considered to be both a reflection of REM sleep brain activity and causal to dreams due to their stimulation of the cortex. In this review, we summarize the role of PGO waves in potential neural circuits of two major theories, i.e., (1) dreams are generated by the activation of neural activity in the brainstem; (2) PGO waves signaling to the cortex. In addition, the potential physiological functions during REM sleep dreams, such as memory consolidation, unlearning, and brain development and plasticity and mood regulation, are discussed. It is hoped that our review will support and encourage research into the phenomenon of human PGO waves and their possible functions in dreaming.

Plasticity of the hypocretinergic/orexinergic system after a chronic treatment with suvorexant in rats. Role of the hypocretinergic/orexinergic receptor 1 as an autoreceptor

The hypothalamic hypocretinergic/orexinergic (Hcrt/Ox) system is involved in many physiological and pathophysiological processes. Malfunction of Hcrt/Ox transmission results in narcolepsy, a sleep disease caused in humans by progressive neurodegeneration of hypothalamic neurons containing Hcrt/Ox. To explore the Hcrt/Ox system plasticity we systemically administered suvorexant (a dual Hcrt/Ox receptor antagonist) in rats to chronically block Hcrt/Ox transmission without damaging Hcrt/Ox cells. Three groups of eight rats (four males and four females) received daily i.p. injections of suvorexant (10 or 30 mg/kg) or vehicle (DMSO) over a period of 7 days in which the body weight was monitored. After the treatments cerebrospinal fluid (CSF) Hcrt1/OxA concentration was measured by ELISA, and hypothalamic Hcrt/OxR1 and Hcrt/OxR2 levels by western blot. The systemic blockade of the Hcrt/Ox transmission with the suvorexant high dose produced a significant increase in body weight at the end of the treatment, and a significant decrease in CSF Hcrt1/OxA levels, both features typical in human narcolepsy type 1. Besides, a significant overexpression of hypothalamic Hcrt/OxR1 occurred. For the Hcrt/OxR2 two very close bands were detected, but they did not show significant changes with the treatment. Thus, the plastic changes observed in the Hcrt/Ox system after the chronic blockade of its transmission were a decrease in CSF Hcrt1/OXA levels and an overexpression of hypothalamic Hcrt/OxR1. These findings support an autoregulatory role of Hcrt/OxR1 within the hypothalamus, which would induce the synthesis/release of Hcrt/Ox, but also decrease its own availability at the plasma membrane after binding Hcrt1/OxA to preserve Hcrt/Ox system homeostasis.

Development and validation of a clinical model to predict hypertension in consecutive patients with obstructive sleep apnea hypopnea syndrome: a hospital-based study and nomogram analysis

BACKGROUND

To screen for risk predictors of hypertension in patients with Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) and develop and validate a clinical model for individualized prediction of hypertension in consecutive patients with OSAHS.

METHODS

114 consecutive patients with OSAHS confirmed by PSG monitoring participated in this study. Those individuals were divided into two sets at a ratio of 7:3, using computer-generated random numbers: 82 individuals were assigned to the training set and 32 to the validation set. Important risk predictors of hypertension in individuals with OSAHS were confirmed using the LASSO method and a clinical nomogram constructed. The predictive accuracy was assessed by unadjusted concordance index (C-index) and calibration plot.

RESULTS

Univariate and multivariate regression analysis identified BMI, REM-AHI, REM-MSpO₂ and T90% as predictive risk factors of OSAHS. Those risk factors were used to construct a clinical predictive nomogram. The calibration curves for hypertension in patients with OSAHS risk revealed excellent accuracy of the predictive nomogram model, internally and externally. The unadjusted concordance index (C-index) for the training and validation set was 0.897 [95% CI 0.795-0.912] and 0.894 [95% CI 0.788-0.820] respectively. The AUC of the training and validation set was 0.8175882 and 0.8031522, respectively. Decision curve analysis showed that the predictive model could be applied clinically when the threshold probability was 20 to 80%.

CONCLUSION

We constructed and validated a clinical nomogram to individually predict the occurrence of hypertension in patients with OSAHS. We determined that BMI, REM-AHI, REM-MSpO₂ and T90% were independent risk predictors for hypertension in patients with OSAHS. This practical prognostic nomogram may help improve clinical decision making.

Spatiotemporal Patterns of Adaptation-Induced Slow Oscillations in a Whole-Brain Model of Slow-Wave Sleep

During slow-wave sleep, the brain is in a self-organized regime in which slow oscillations (SOs) between up- and down-states travel across the cortex. While an isolated piece of cortex can produce SOs, the brain-wide propagation of these oscillations are thought to be mediated by the long-range axonal connections. We address the mechanism of how SOs emerge and recruit large parts of the brain using a whole-brain model constructed from empirical connectivity data in which SOs are induced independently in each brain area by a local adaptation mechanism. Using an evolutionary optimization approach, good fits to human resting-state fMRI data and sleep EEG data are found at values of the adaptation strength close to a bifurcation where the model produces a balance between local and global SOs with realistic spatiotemporal statistics. Local oscillations are more frequent, last shorter, and have a lower amplitude. Global oscillations spread as waves of silence across the undirected brain graph, traveling from anterior to posterior regions. These traveling waves are caused by heterogeneities in the brain network in which the connection strengths between brain areas determine which areas transition to a down-state first, and thus initiate traveling waves across the cortex. Our results demonstrate the utility of whole-brain models for explaining the origin of large-scale cortical oscillations and how they are shaped by the connectome.

Pathway-Dependent Regulation of Sleep Dynamics in a Network Model of the Sleep-Wake Cycle

Sleep is a fundamental homeostatic process within the animal kingdom. Although various brain areas and cell types are involved in the regulation of the sleep-wake cycle, it is still unclear how different pathways between neural populations contribute to its regulation. Here we address this issue by investigating the behavior of a simplified network model upon synaptic weight manipulations. Our model consists of three neural populations connected by excitatory and inhibitory synapses. Activity in each population is described by a firing-rate model, which determines the state of the network. Namely wakefulness, rapid eye movement (REM) sleep or non-REM (NREM) sleep. By systematically manipulating the synaptic weight of every pathway, we show that even this simplified model exhibits non-trivial behaviors: for example, the wake-promoting population contributes not just to the induction and maintenance of wakefulness, but also to sleep induction. Although a recurrent excitatory connection of the REM-promoting population is essential for REM sleep genesis, this recurrent connection does not necessarily contribute to the maintenance of REM sleep. The duration of NREM sleep can be shortened or extended by changes in the synaptic strength of the pathways from the NREM-promoting population. In some cases, there is an optimal range of synaptic strengths that affect a particular state, implying that the amount of manipulations, not just direction (i.e., activation or inactivation), needs to be taken into account. These results demonstrate pathway-dependent regulation of sleep dynamics and highlight the importance of systems-level quantitative approaches for sleep-wake regulatory circuits.