Real-Time Monitoring of Slow-Wave Sleep by Electroencephalogram Variance

Based on statistical variance as an index of electroencephalogram (EEG) parameters, we monitored slow-wave sleep in both humans and rats in real time and on-line with a widely used personal computer. This EEG variance method may be a useful tool to carry out biological rhythm research, including sleep studies.     

Changes in Brain Glycogen During Slow-Wave Sleep in the Rat

Abstract: During slow-wave sleep, rat brain glycogen increases within a few minutes to about 70% above waking levels. Upon awakening, the increment is lost within 2–5 min. After repeated episodes of sleep, brain glycogen levels are comparable to those observed after only a single episode of sleep. Liver glycogen is unaffected by slow-wave sleep.     

Reduced Slow-Wave Rebound during Daytime Recovery Sleep in Middle-Aged Subjects

Cortical synchronization during NREM sleep, characterized by electroencephalographic slow waves (SW <4Hz and >75 μV), is strongly related to the number of hours of wakefulness prior to sleep and to the quality of the waking experience. Whether a similar increase in wakefulness length leads to a comparable enhancement in NREM sleep cortical synchronization in young and older subjects is still a matter of debate in the literature. Here we evaluated the impact of 25-hours of wakefulness on SW during a daytime recovery sleep episode in 29 young (27y ±5), and 34 middle-aged (51y ±5) subjects. We also assessed whether age-related changes in NREM sleep cortical synchronization predicts the ability to maintain sleep during daytime recovery sleep. Compared to baseline sleep, sleep efficiency was lower during daytime recovery sleep in both age-groups but the effect was more prominent in the middle-aged than in the young subjects. In both age groups, SW density, amplitude, and slope increased whereas SW positive and negative phase duration decreased during daytime recovery sleep compared to baseline sleep, particularly in anterior brain areas. Importantly, compared to young subjects, middle-aged participants showed lower SW density rebound and SW positive phase duration enhancement after sleep deprivation during daytime recovery sleep. Furthermore, middle-aged subjects showed lower SW amplitude and slope enhancements after sleep deprivation than young subjects in frontal and prefrontal derivations only. None of the SW characteristics at baseline were associated with daytime recovery sleep efficiency. Our results support the notion that anterior brain areas elicit and may necessitate more intense recovery and that aging reduces enhancement of cortical synchronization after sleep loss, particularly in these areas. Age-related changes in the quality of wake experience may underlie age-related reduction in markers of cortical synchronization enhancement after sustained wakefulness.     

Hippocampal Ripple Coordinates Retrosplenial Inhibitory Neurons during Slow-Wave Sleep

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Network-Specific Synchronization of Electrical Slow-Wave Oscillations Regulates Sleep Drive in Drosophila

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Elevated Variance in Heart Rate During Slow-Wave Sleep After Late-Night Physical Activity

This study investigates the effect of mild physical activity before bedtime on the sleep pattern and heart rate during the night. Nine healthy subjects underwent a habituation night, a reference night, and a physical induction night. The physical induction night did not alter the sleep pattern. Physical activity before bedtime resulted in higher heart rate variance during slow-wave sleep. The low-frequency/high-frequency component (LF/HF) ratio during slow-wave sleep in the physical induction night was significantly higher than during the reference night. Increased mean heart rate and higher LF/HF ratio are related to decreased parasympathetic dominance. Exercise up to 1?h before bedtime thus seems to modify the quality of sleep. (Author correspondence: Daniel.Berckmans@biw.kuleuven.be)     

Functional Structure of Spontaneous Sleep Slow Oscillation Activity in Humans

Background

During non-rapid eye movement (NREM) sleep synchronous neural oscillations between neural silence (down state) and neural activity (up state) occur. Sleep Slow Oscillations (SSOs) events are their EEG correlates. Each event has an origin site and propagates sweeping the scalp. While recent findings suggest a SSO key role in memory consolidation processes, the structure and the propagation of individual SSO events, as well as their modulation by sleep stages and cortical areas have not been well characterized so far.

Methodology/Principal Findings

We detected SSO events in EEG recordings and we defined and measured a set of features corresponding to both wave shapes and event propagations. We found that a typical SSO shape has a transition to down state, which is steeper than the following transition from down to up state. We show that during SWS SSOs are larger and more locally synchronized, but less likely to propagate across the cortex, compared to NREM stage 2. Also, the detection number of SSOs as well as their amplitudes and slopes, are greatest in the frontal regions. Although derived from a small sample, this characterization provides a preliminary reference about SSO activity in healthy subjects for 32-channel sleep recordings.

Conclusions/Significance

This work gives a quantitative picture of spontaneous SSO activity during NREM sleep: we unveil how SSO features are modulated by sleep stage, site of origin and detection location of the waves. Our measures on SSOs shape indicate that, as in animal models, onsets of silent states are more synchronized than those of neural firing. The differences between sleep stages could be related to the reduction of arousal system activity and to the breakdown of functional connectivity. The frontal SSO prevalence could be related to a greater homeostatic need of the heteromodal association cortices.     

Scale-Free Fluctuations in Behavioral Performance: Delineating Changes in Spontaneous Behavior of Humans with Induced Sleep Deficiency

The timing and dynamics of many diverse behaviors of mammals, e.g., patterns of animal foraging or human communication in social networks exhibit complex self-similar properties reproducible over multiple time scales. In this paper, we analyze spontaneous locomotor activity of healthy individuals recorded in two different conditions: during a week of regular sleep and a week of chronic partial sleep deprivation. After separating activity from rest with a pre-defined activity threshold, we have detected distinct statistical features of duration times of these two states. The cumulative distributions of activity periods follow a stretched exponential shape, and remain similar for both control and sleep deprived individuals. In contrast, rest periods, which follow power-law statistics over two orders of magnitude, have significantly distinct distributions for these two groups and the difference emerges already after the first night of shortened sleep. We have found steeper distributions for sleep deprived individuals, which indicates fewer long rest periods and more turbulent behavior. This separation of power-law exponents is the main result of our investigations, and might constitute an objective measure demonstrating the severity of sleep deprivation and the effects of sleep disorders.     

Sleep in mammals

Quiet sleep (QS) was correlated with a different set of constitutional variables from those associated with active sleep (AS), in a sample of 69 species of mammals. The time spent in quiet sleep was negatively correlated with body size and basal metabolic rate. The latter relationship remained even after controlling for the effects of body weight. Neither the total time spent in active sleep, nor active sleep as a percentage of total sleep time was significantly correlated with body weight or metabolic rate. Altricial species spend more time in active sleep than do precocial species. The time between the onset of successive episodes of active sleep, the AS-QS cycle length, was positively correlated with body weight. For their body sizes, species that live in temperate regions have shorter AS-QS cycles than those living in tropical or sub-tropical regions. Correlations between patterns of sleep and adult brain weight probably result from the confounding effects of body weight. These findings were used to evaluate several explanations for interspecific differences in patterns of sleep among mammals.     

Sleep in brain development

With the discovery of rapid eye movement (REM) sleep, sleep was no longer considered a homogeneous state of passive rest for the brain. On the contrary, sleep, and especially REM sleep, appeared as an active condition of intense cerebral activity. The fact that we get large amounts of sleep in early life suggested that sleep may play a role in brain maturation. This idea has been investigated for many years through a large number of animal and human studies, but evidence remains fragmented. The hypothesis proposed was that REM sleep would provide an endogenous source of activation, possibly critical for structural maturation of the central nervous system. This proposal led to a series of experiments looking at the role of REM sleep in brain development. In particular, the influence of sleep in developing the visual system has been highlighted. More recently, non-REM (NREM) sleep state has become a major focus of attention. The current data underscore the importance of both REM sleep and NREM sleep states in normal synaptic development and lend support to their functional roles in brain maturation. Both sleep states appear to be important for neuronal development, but the corresponding contribution is likely to be different.