Cyclic alternating pattern in sleep and its relationship to creativity

Embracing sleep-onset complexity

Sleep is crucial for many vital functions and has been extensively studied. By contrast, the sleep-onset period (SOP), often portrayed as a mere prelude to sleep, has been largely overlooked and remains poorly characterized. Recent findings, however, have reignited interest in this transitional period and have shed light on its neural mechanisms, cognitive dynamics, and clinical implications. This review synthesizes the existing knowledge about the SOP in humans. We first examine the current definition of the SOP and its limits, and consider the dynamic and complex electrophysiological changes that accompany the descent to sleep. We then describe the interplay between internal and external processing during the wake-to-sleep transition. Finally, we discuss the putative cognitive benefits of the SOP and identify novel directions to better diagnose sleep-onset disorders.

Automatic classification of sleep stages using EEG signals and convolutional neural networks

Sleep stages classification is one of the new topics in studying human life quality because it plays a crucial role in getting a healthy lifestyle. Abnormal changes or absence of normal sleep may lead to different diseases such as heart-related diseases, diabetes, and obesity. In general, sleep staging analysis can be performed using electroencephalography (EEG) signals. This study proposes a convolutional neural network (CNN) based methodology for sleep stage classification using EEG signals taken by six channels and transformed into time-frequency analysis images. The proposed methodology consists of three major steps: (i) segment the EEG signal into epochs with 30 seconds in length, (ii) convert epochs into 2D representation using time-frequency analysis, and (iii) feed the 2D time-frequency analysis to the 2D CNN. The results showed that the proposed methodology is robust and achieved a very high accuracy of 99.39% for channel C4-A1. All other channels have accuracy values above 98.5%, which indicates that any channel can be used for sleep stage classification with high accuracy. The proposed methodology outperformed the methods in the literature in terms of overall accuracy or single channel accuracy. It is expected to provide a great benefit for physicians, especially neurologists; by providing them with a new powerful tool to support the clinical diagnosis of sleep-related diseases.

Sleep electroencephalography biomarkers of cognition in obstructive sleep apnea

Obstructive sleep apnea has been associated with cognitive impairment and may be linked to disorders of cognitive function. These associations may be a result of intermittent hypoxaemia, sleep fragmentation and changes in sleep microstructure in obstructive sleep apnea. Current clinical metrics of obstructive sleep apnea, such as the apnea-hypopnea index, are poor predictors of cognitive outcomes in obstructive sleep apnea. Sleep microstructure features, which can be identified on sleep electroencephalography of traditional overnight polysomnography, are increasingly being characterized in obstructive sleep apnea and may better predict cognitive outcomes. Here, we summarize the literature on several major sleep electroencephalography features (slow-wave activity, sleep spindles, K-complexes, cyclic alternating patterns, rapid eye movement sleep quantitative electroencephalography, odds ratio product) identified in obstructive sleep apnea. We will review the associations between these sleep electroencephalography features and cognition in obstructive sleep apnea, and examine how treatment of obstructive sleep apnea affects these associations. Lastly, evolving technologies in sleep electroencephalography analyses will also be discussed (e.g. high-density electroencephalography, machine learning) as potential predictors of cognitive function in obstructive sleep apnea.

Sleep and Athletic Performance: Impacts on Physical Performance, Mental Performance, Injury Risk and Recovery, and Mental Health: An Update

Sleep health is an important consideration for athletic performance. Athletes are at high risk of insufficient sleep duration, poor sleep quality, daytime sleepiness and fatigue, suboptimal sleep schedules, irregular sleep schedules, and sleep and circadian disorders. These issues likely have an impact on athletic performance via several domains. Sleep loss and/or poor sleep quality can impair muscular strength, speed, and other aspects of physical performance. Sleep issues can also increase risk of concussions and other injuries and impair recovery after injury. Cognitive performance is also impacted in several domains, including vigilance, learning and memory, decision making, and creativity.

Sleep spindles in children with restless sleep disorder, restless legs syndrome and normal controls

OBJECTIVE

To analyze and identify differences in sleep spindles in children with restless sleep disorder (RSD), restless legs syndrome (RLS) and normal controls.

METHODS

PSG (polysomnography) from children with RSD, RLS and normal controls were analyzed. Sleep spindle activity was detected on one frontal and one central electrode, for each epoch of N2 and N3 sleep. Sleep spindle density, duration and intensity (density × duration) were then obtained and used for analysis.

RESULTS

Thirty-eight children with RSD, twenty-three children with RLS and twenty-nine controls were included. The duration of frontal spindles in sleep stage N2 was longer in children with RSD than in controls. Frontal spindle density and intensity tended to be increased in RSD children. No significant differences were found for central spindles.

CONCLUSION

Children with RSD had longer frontal spindles. This finding may contribute to explain the occurrence of excessive movement activity during sleep and the presence of daytime symptoms.

SIGNIFICANCE

Recent research has demonstrated that children with RSD have increased NREM instability and sympathetic activation during sleep. Analyzing sleep spindles in children with RSD in comparison with children with RLS and controls adds to our understanding of the pathophysiology or RSD and its effects on daytime impairment.

Sleep’s Role in Schema Learning and Creative Insights

Purpose of Review

A recent resurgence of interest in schema theory has influenced research on sleep-dependent memory consolidation and led to a new understanding of how schemata might be activated during sleep and play a role in the reorganisation of memories. This review is aimed at synthesising recent findings into a coherent narrative and draw overall conclusions.

Recent Findings

Rapid consolidation of schematic memories has been shown to benefit from an interval containing sleep. These memories have shown reduced reliance on the hippocampus following consolidation in both humans and rodents. Using a variety of methodologies, notably including the DRM paradigm, it has been shown that activation of a schema can increase the rate of false memory as a result of activation of semantic associates during slow wave sleep (SWS). Memories making use of a schema have shown increased activity in the medial prefrontal cortex, which may reflect both the schematic activation itself and a cognitive control component selecting an appropriate schema to use. SWS seems to be involved in assimilation of new memories within existing semantic frameworks and in making memories more explicit, while REM sleep may be more associated with creating entirely novel associations while keeping memories implicit.

Summary

Sleep plays an important role in schematic memory consolidation, with more rapid consolidation, reduced hippocampal involvement, and increased prefrontal involvement as the key characteristics. Both SWS and REM sleep may have a role to play.

Ill-Defined Problem Solving Does Not Benefit From Daytime Napping

The main goal of the present study was to explore the role of sleep in the process of ill-defined problem solving. The results of previous studies indicate that various cognitive processes are largely dependent on the quality and quantity of sleep. However, while sleep-related memory consolidation seems to be well-grounded, with regard to the impact of sleep on problem solving, existing research yields mixed and rather inconclusive results. Moreover, this effect has been mainly tested using simple and well-defined, common laboratory problems, such as the remote associate test (RAT), crossword and anagram puzzles, numeric and logic problems, etc. What is lacking is research on the effect of sleep on solving more complex and more real-life oriented ill-defined problems. In the present study, we hypothesized that sleep can improve performance in solving this kind of problems. The study involved 40 participants, randomly assigned to two experimental conditions: sleep group and waking group. The experimental protocol comprised three stages: problem presentation, retention interval, and testing stage. The problem was presented to the participants in the form of an interactive computer game concerning a complex, elaborate crime story. During the retention interval, the participants—depending on the condition—took a nap or stayed awake; sleeping participants underwent polysomnography recording, while waking participants performed activities not related to the experimental problem. In the testing stage, participants tried to solve the presented problem. The solutions generated were assessed both for quality (reasonableness, consistency, and story recall) and creativity (fluency, flexibility, originality, and elaboration). Contrary to expectations, we found no effect of sleep on ill-defined problem solving. Neither quality nor creativity of the solutions generated by the participants was higher in the nap group than in the waking group. There were also no performance improvements with regard to any sleep stage or incidence of dreams. Our study adds to a growing body of evidence that sleep probably might provide an incubation gap, but not a facilitating environment serving the purpose of problem solving, at least with regard to ill-defined problems.

Sleep and Athletic Performance: Impacts on Physical Performance, Mental Performance, Injury Risk and Recovery, and Mental Health

Research has characterized the sleep of elite athletes and attempted to identify factors associated with athletic performance, cognition, health, and mental well-being. Sleep is a fundamental component of performance optimization among elite athletes, yet only recently embraced by sport organizations as an important part of training and recovery. Sleep plays a crucial role in physical and cognitive performance and is an important factor in reducing risk of injury. This article aims to highlight the prevalence of poor sleep, describe its impacts, and address the issue of sport culture surrounding healthy sleep.

Increased cortical involvement and synchronization during CAP A1 slow waves

Slow waves recorded with EEG in NREM sleep are indicative of the strength and spatial extent of synchronized firing in neuronal assemblies of the cerebral cortex. Slow waves often appear in the A1 part of the cyclic alternating patterns (CAP), which correlate with a number of behavioral and biological parameters, but their physiological significance is not adequately known. We automatically detected slow waves from the scalp recordings of 37 healthy patients, visually identified CAP A1 events and compared slow waves during CAP A1 with those during NCAP. For each slow wave, we computed the amplitude, slopes, frequency, synchronization (synchronization likelihood) between specific cortical areas, as well as the location of origin and scalp propagation of individual waves. CAP A1 slow waves were characterized by greater spatial extent and amplitude, steeper slopes and greater cortical synchronization, but a similar prominence in frontal areas and similar propagation patterns to other areas on the scalp. Our results indicate that CAP A1 represents a period of highly synchronous neuronal firing over large areas of the cortical mantle. This feature may contribute to the role CAP A1 plays in both normal synaptic homeostasis and in the generation of epileptiform phenomena in epileptic patients.

Sleep microstructure dynamics and neurocognitive performance in obstructive sleep apnea syndrome patients

The present study examined the relationship between the increment in cyclic alternating patterns (CAPs) in sleep electroencephalography and neurocognitive decline in obstructive Sleep Apnea Syndrome (OSAS) patients through source localization of the phase-A of CAPs. All-night polysomnographic recordings of 10 OSAS patients and 4 control subjects along with their cognitive profile using the Addenbrooke's Cognitive Examination (ACE) test were acquired. The neuropsychological assessment involved five key domains including attention and orientation, verbal fluency, memory, language and visuo-spatial skills. The standardized low-resolution brain electromagnetic tomography (sLORETA) tool was used to source-localize the phase-A of CAPs in sleep EEG aiming to investigate the correlation between CAP phase-A and cognitive functions. Our findings suggested a significant increase in CAP rates among OSAS subjects versus control subjects. Moreover, sLORETA revealed that CAP phase-A is mostly activated in frontoparietal cortices. As CAP rate increases, the activity of phase-A in such areas is dramatically enhanced leading to arousal instability, lower sleep efficiency and a possibly impaired cortical capacity to consolidate cognitive inputs in frontal and parietal areas during sleep. As such, cognitive domains including verbal fluency, memory and visuo-spatial skills which predominantly relate to frontoparietal areas tend to be affected. Based on our findings, CAP activity may possibly be considered as a predictor of cognitive decline among OSAS patients.

After being challenged by a video game problem, sleep increases the chance to solve it

In the past years many studies have demonstrated the role of sleep on memory consolidation. It is known that sleeping after learning a declarative or non-declarative task, is better than remaining awake. Furthermore, there are reports of a possible role for dreams in consolidation of declarative memories. Other studies have reported the effect of naps on memory consolidation. With similar protocols, another set of studies indicated that sleep has a role in creativity and problem-solving. Here we hypothesised that sleep can increase the likelihood of solving problems. After struggling to solve a video game problem, subjects who took a nap (n = 14) were almost twice as likely to solve it when compared to the wake control group (n = 15). It is interesting to note that, in the nap group 9 out 14 subjects engaged in slow-wave sleep (SWS) and all solved the problem. Surprisingly, we did not find a significant involvement of Rapid Eye Movement (REM) sleep in this task. Slow-wave sleep is believed to be crucial for the transfer of memory-related information to the neocortex and implement intentions. Sleep can benefit problem-solving through the generalisation of newly encoded information and abstraction of the gist. In conclusion, our results indicate that sleep, even a nap, can potentiate the solution of problems that involve logical reasoning. Thus, sleep's function seems to go beyond memory consolidation to include managing of everyday-life events.

Sleep cyclic alternating pattern and cognition in children: a review

Several studies have been recently focused on the relationship between sleep cyclic alternating pattern (CAP) and daytime cognitive performance, supporting the idea that the CAP slow components may play a role in sleep-related cognitive processes. Based on the results of these reports, it can be hypothesized that the analysis of CAP might be helpful in characterizing sleep microstructure patterns of different phenotypes of intellectual disability and a series of studies has been carried out that are reviewed in this paper. First the studies exploring the correlations between CAP and cognitive performance in normal adults and children are described; then, those analyzing the correlation between CAP and cognitive patterns of several developmental conditions with neurocognitive dysfunction (with or without mental retardation) are reported in detail in order to achieve a unitary view of the role of CAP in these conditions that allows to detect a particular "sleep microstructure phenotype" of children with neurologic/neuropsychiatric disorders.

Effects of replacement therapy on sleep architecture in children with growth hormone deficiency

OBJECTIVE

Children with GH deficiency (GHD) show a general decrease in electroencephalographic (EEG) arousability represented by a significant global decrease in Cyclic Alternating Pattern (CAP). The aim of the present study was to evaluate if sleep structure is influenced by GH substitutive therapy by analyzing the classical sleep architecture parameters and sleep microstructure by means of CAP.

SUBJECTS AND METHODS

Laboratory polysomnographic sleep recordings were obtained from five children affected by GHD (two girls and three boys; mean age: 4.6 ± 3.1 years), at baseline and after GH therapy, and from 10 normal healthy children (four girls and six boys, mean age: 5.6 ± 2.2 years).

RESULTS

Compared to controls, GHD subjects showed a reduced total sleep time with increased wakefulness and a consequent decrease in sleep efficiency; GH therapy was associated with an increase of the awakenings/hour and a large effect size was evident for sleep latency, sleep efficiency, and stage N3, which were decreased, and for stage W, which was increased. CAP appeared to be globally reduced and all phase A subtypes and CAP cycle showed a longer duration in GHD children vs. controls. GH substitutive treatment was followed by an increase in CAP rate (total, in N2, and in N3); additionally, A1 index was also significantly increased, especially during stage N3, with a very large effect size. On the other hand, A2 and A3 index and CAP cycle mean duration were reduced.

CONCLUSION

Sleep stage architecture seems to be influenced by the GH status, but the analysis of sleep microstructure by means of CAP reveals an enhancement of EEG slow oscillations in GHD patients (demonstrated by an increase in CAP rate and A1 index during N3) after the start of GH replacement therapy. These findings deserve to be verified in a larger trial.

Cyclic alternating pattern (CAP): the marker of sleep instability

Cyclic alternating pattern CAP is the EEG marker of unstable sleep, a concept which is poorly appreciated among the metrics of sleep physiology. Besides, duration, depth and continuity, sleep restorative properties depend on the capacity of the brain to create periods of sustained stable sleep. This issue is not confined only to the EEG activities but reverberates upon the ongoing autonomic activity and behavioral functions, which are mutually entrained in a synchronized oscillation. CAP can be identified both in adult and children sleep and therefore represents a sensitive tool for the investigation of sleep disorders across the lifespan. The present review illustrates the story of CAP in the last 25 years, the standardized scoring criteria, the basic physiological properties and how the dimension of sleep instability has provided new insight into pathophysiolology and management of sleep disorders.