Habitual short sleep impacts frontal switch mechanism in attention to novelty

Electroencephalography Microstate Class D is a Brain Marker of Subjective Sleep Quality for College Students with High Habitual Sleep Efficiency

Subjective sleep quality is an individual's subjective sleep feeling, and its effective evaluation is the premise of improving sleep quality. However, people with autism or mental disorders often experience difficulties in verbally expressing their subjective sleep quality. To solve the above problem, this study provides a non-verbal and convenient brain feature to assess subjective sleep quality. Reportedly, microstates are often used to characterize the patterns of functional brain activity in humans. The occurrence frequency of microstate class D is an important feature in the insomnia population. We therefore hypothesize that the occurrence frequency of microstate class D is a physiological indicator of subjective sleep quality. To test this hypothesis, we recruited college students from China as participants [N = 61, mean age = 20.84 years]. The Chinese version of the Pittsburgh Sleep Quality Index scale was used to measure subjective sleep quality and habitual sleep efficiency, and the state characteristics of the brain at this time were assessed using closed eyes resting-state brain microstate class D. The occurrence frequency of EEG microstate class D was positively associated with subjective sleep quality (r = 0.32, p < 0.05). Further analysis of the moderating effect showed that the occurrence frequency of microstate class D was significantly and positively correlated with subjective sleep quality in the high habitual sleep efficiency group. However, the relationship was not significant in the low sleep efficiency group (βsimple = 0.63, p < 0.001). This study shows that the occurrence frequency of microstate class D is a physiological indicator of assessing subjective sleep quality levels in the high sleep efficiency group. This study provides brain features for assessing subjective sleep quality of people with autism and mental disorders who cannot effectively describe their subjective feelings.

Total sleep deprivation impairs visual selective attention and triggers a compensatory effect: evidence from event-related potentials

Many studies have demonstrated the impairment of sustained attention due to total sleep deprivation (TSD). However, it remains unclear whether and how TSD affects the processing of visual selective attention. In the current study, 24 volunteers performed a visual search task before and after TSD over a period of 36 h while undergoing spontaneous electroencephalography. Paired-sample t-tests of behavioral performance revealed that, compared with baseline values, the participants showed lower accuracy and higher variance in response time in visual search tasks performed after TSD. Analysis of the event-related potentials (ERPs) showed that the mean amplitude of the N2-posterior-contralateral (N2pc) difference wave after TSD was less negative than that at baseline and the mean amplitude of P3 after TSD was more positive than that at baseline. Our findings suggest that TSD significantly attenuates attentional direction/orientation processing and triggers a compensatory effect in the parietal brain to partially offset the impairments. These findings provide new evidence and improve our understanding of the effects of sleep loss.

Electrophysiological Evidence of Local Sleep During Yoga Nidra Practice

Background and Objectives

Yoga nidra is a technique sages use to self-induce sleep. Classically, sleep is characterized by three cardinal electrophysiological features, namely, electroencephalography (EEG), electromyography (EMG), and electrooculography (EOG). As the literature on electrophysiological characterization of Yoga nidra is lacking, it is not known whether it is a sleep or awake state. The objective of the study was to electrophysiologically characterize yoga nidra practice.

Materials and Methods

Thirty subjects underwent five initial supervised yoga nidra sessions and then continued practice on their own. The subjects completed their sleep diaries for 2 weeks before and during the intervention. The electrophysiological characterization was done after 2 weeks of yoga nidra practice using 19 EEG channels polysomnography for pre-yoga nidra, yoga nidra practice and post-yoga nidra. Polysomnographic data were scored for sleep-wake stages as per standard criteria. Power spectral density (PSD) was calculated from various frequency bands in different time bins. EEG data were grouped by areas, namely, central, frontal, prefrontal, parietal, temporal, and occipital in time bins. Sleep diary parameters were also compared for pre-post-yoga nidra training.

Results

After 2 weeks of yoga nidra practice, awake was scored throughout the session (n = 26). PSD results (mean difference in dB between different time bins; P value) showed significant changes. When compared to pre-yoga nidra, there was an increase in delta power in the central area (1.953; P = 0.033) and a decrease in the prefrontal area (2.713; P = 0.041) during yoga nidra. Sleep diary showed improvement in sleep duration (P = 0.0001), efficiency (P = 0.0005), quality (P = 0.0005), and total wake duration (P = 0.00005) after 2 weeks of practice.

Interpretations and Conclusions

Yoga nidra practice in novices is electrophysiologically an awake state with signs of slow waves locally, often referred to as local sleep.

Clinical Trial

Clinical Trial Registry of India, http://www.ctri.nic.in/Clinicaltrials/pmaindet2.php? trialid = 6253, 2013/05/003682.

Performance of an Ambulatory Dry-EEG Device for Auditory Closed-Loop Stimulation of Sleep Slow Oscillations in the Home Environment

Recent research has shown that auditory closed-loop stimulation can enhance sleep slow oscillations (SO) to improve N3 sleep quality and cognition. Previous studies have been conducted in lab environments. The present study aimed to validate and assess the performance of a novel ambulatory wireless dry-EEG device (WDD), for auditory closed-loop stimulation of SO during N3 sleep at home. The performance of the WDD to detect N3 sleep automatically and to send auditory closed-loop stimulation on SO were tested on 20 young healthy subjects who slept with both the WDD and a miniaturized polysomnography (part 1) in both stimulated and sham nights within a double blind, randomized and crossover design. The effects of auditory closed-loop stimulation on delta power increase were assessed after one and 10 nights of stimulation on an observational pilot study in the home environment including 90 middle-aged subjects (part 2).The first part, aimed at assessing the quality of the WDD as compared to a polysomnograph, showed that the sensitivity and specificity to automatically detect N3 sleep in real-time were 0.70 and 0.90, respectively. The stimulation accuracy of the SO ascending-phase targeting was 45 ± 52°. The second part of the study, conducted in the home environment, showed that the stimulation protocol induced an increase of 43.9% of delta power in the 4 s window following the first stimulation (including evoked potentials and SO entrainment effect). The increase of SO response to auditory stimulation remained at the same level after 10 consecutive nights. The WDD shows good performances to automatically detect in real-time N3 sleep and to send auditory closed-loop stimulation on SO accurately. These stimulation increased the SO amplitude during N3 sleep without any adaptation effect after 10 consecutive nights. This tool provides new perspectives to figure out novel sleep EEG biomarkers in longitudinal studies and can be interesting to conduct broad studies on the effects of auditory stimulation during sleep.

A single night of sleep loss impairs objective but not subjective working memory performance in a sex-dependent manner

Acute sleep deprivation can lead to judgement errors and thereby increases the risk of accidents, possibly due to an impaired working memory. However, whether the adverse effects of acute sleep loss on working memory are modulated by auditory distraction in women and men are not known. Additionally, it is unknown whether sleep loss alters the way in which men and women perceive their working memory performance. Thus, 24 young adults (12 women using oral contraceptives at the time of investigation) participated in two experimental conditions: nocturnal sleep (scheduled between 22:30 and 06:30 hours) versus one night of total sleep loss. Participants were administered a digital working memory test in which eight‐digit sequences were learned and retrieved in the morning after each condition. Learning of digital sequences was accompanied by either silence or auditory distraction (equal distribution among trials). After sequence retrieval, each trial ended with a question regarding how certain participants were of the correctness of their response, as a self‐estimate of working memory performance. We found that sleep loss impaired objective but not self‐estimated working memory performance in women. In contrast, both measures remained unaffected by sleep loss in men. Auditory distraction impaired working memory performance, without modulation by sleep loss or sex. Being unaware of cognitive limitations when sleep‐deprived, as seen in our study, could lead to undesirable consequences in, for example, an occupational context. Our findings suggest that sleep‐deprived young women are at particular risk for overestimating their working memory performance.

The sleep-deprived human brain

How does a lack of sleep affect our brains? In contrast to the benefits of sleep, frameworks exploring the impact of sleep loss are relatively lacking. Importantly, the effects of sleep deprivation (SD) do not simply reflect the absence of sleep and the benefits attributed to it; rather, they reflect the consequences of several additional factors, including extended wakefulness. With a focus on neuroimaging studies, we review the consequences of SD on attention and working memory, positive and negative emotion, and hippocampal learning. We explore how this evidence informs our mechanistic understanding of the known changes in cognition and emotion associated with SD, and the insights it provides regarding clinical conditions associated with sleep disruption.

Performance of a Portable Sleep Monitoring Device in Individuals with High Versus Low Sleep Efficiency

STUDY OBJECTIVES

Portable and automated sleep monitoring technology is becoming widely available to consumers, and one wireless system (WS) has recently surfaced as a research tool for sleep and sleep staging assessment outside the hospital/laboratory; however, previous research findings indicate low sensitivity for wakefulness detection. Because difficulty discriminating between wake and sleep is likely to affect staging performance, we sought to further evaluate the WS by comparing it to the gold-standard polysomnography (PSG) and actigraphy (ACT) for overall sleep/wakefulness detection and sleep staging, within high and low sleep efficiency sleepers.

METHODS

Twenty-nine healthy adults (eight females) underwent concurrent WS, PSG, and ACT assessment in an overnight laboratory study. Epoch-by-epoch agreement was determined by comparing sleep/wakefulness decisions between the WS to both PSG and ACT, and for detection of light, deep, and rapid eye movement (REM) sleep stages between the WS and PSG.

RESULTS

Sensitivity for wakefulness was low (40%), and an overestimation of total sleep time and underestimation of wake after sleep onset was observed. Prevalence and bias adjusted kappa statistic indicated moderate-to-high agreement between the WS and PSG for sleep staging. However, upon further inspection, WS performance varied by sleep efficiency, with the best performance during high sleep efficiency.

CONCLUSIONS

The benefit of the WS as a sleep monitoring device over ACT is the ability to assess sleep stages, and our findings suggest this benefit is only realized within high sleep efficiency. Care should be taken to collect data under conditions where this is expected.

Less Efficient Neural Processing Related to Irregular Sleep and Less Sustained Attention in Toddlers

The current study used event-related potentials to examine a candidate process through which sleep difficulties affect attentional processing in toddlers. Fifteen toddlers participated in an auditory Oddball task while neurophysiological data were collected. Sleep deficits were assessed using actigraphs, and attention was examined with a sustained attention task. A P3-like component was elicited from the toddlers, and longer target P3 latencies were associated with poorer sustained attention and irregular sleep. Findings suggest that irregular sleep is associated with less efficient attentional processing as reflected by the P3 component, and that longer target P3 latencies are associated with poorer sustained attention.

Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity

STUDY OBJECTIVES

We examined whether interindividual differences in habitual sleep patterns, quantified as the cumulative habitual total sleep time (cTST) over a 2-w period, were reflected in waking measurements of intranetwork and internetwork functional connectivity (FC) between major nodes of three intrinsically connected networks (ICNs): default mode network (DMN), salience network (SN), and central executive network (CEN).

METHODS

Resting state functional magnetic resonance imaging (fMRI) study using seed-based FC analysis combined with 14-d wrist actigraphy, sleep diaries, and subjective questionnaires (N = 33 healthy adults, mean age 34.3, standard deviation ± 11.6 y). Data were statistically analyzed using multiple linear regression. Fourteen consecutive days of wrist actigraphy in participant's home environment and fMRI scanning on day 14 at the Birmingham University Imaging Centre. Seed-based FC analysis on ICNs from resting-state fMRI data and multiple linear regression analysis performed for each ICN seed and target. cTST was used to predict FC (controlling for age).

RESULTS

cTST was specific predictor of intranetwork FC when the mesial prefrontal cortex (MPFC) region of the DMN was used as a seed for FC, with a positive correlation between FC and cTST observed. No significant relationship between FC and cTST was seen for any pair of nodes not including the MPFC. Internetwork FC between the DMN (MPFC) and SN (right anterior insula) was also predicted by cTST, with a negative correlation observed between FC and cTST.

CONCLUSIONS

This study improves understanding of the relationship between intranetwork and internetwork functional connectivity of intrinsically connected networks (ICNs) in relation to habitual sleep quality and duration. The cumulative amount of sleep that participants achieved over a 14-d period was significantly predictive of intranetwork and inter-network functional connectivity of ICNs, an observation that may underlie the link between sleep status and cognitive performance.

Beneficial impact of sleep extension on fasting insulin sensitivity in adults with habitual sleep restriction

STUDY OBJECTIVES

A link between sleep loss and increased risk for the development of diabetes is now well recognized. The current study investigates whether sleep extension under real-life conditions is a feasible intervention with a beneficial impact on glucose metabolism in healthy adults who are chronically sleep restricted.

DESIGN

Intervention study.

PARTICIPANTS

Sixteen healthy non-obese volunteers (25 [23, 27.8] years old, 3 men).

INTERVENTIONS

Two weeks of habitual time in bed followed by 6 weeks during which participants were instructed to increase their time in bed by one hour per day.

MEASUREMENTS AND RESULTS

Continuous actigraphy monitoring and daily sleep logs during the entire study. Glucose and insulin were assayed on a single morning blood sample at the end of habitual time in bed and at the end of sleep extension. Home polysomnography was performed during one weekday of habitual time in bed and after 40 days of sleep extension. Sleep time during weekdays increased (mean actigraphic data: +44 ± 34 minutes, P < 0.0001; polysomnographic data: +49 ± 68 minutes, P = 0.014), without any significant change during weekends. Changes from habitual time in bed to the end of the intervention in total sleep time correlated with changes in glucose (r = +0.53, P = 0.041) and insulin levels (r = -0.60, P = 0.025), as well as with indices of insulin sensitivity (r = +0.76, P = 0.002).

CONCLUSIONS

In healthy adults who are chronically sleep restricted, a simple low cost intervention such as sleep extension is feasible and is associated with improvements in fasting insulin sensitivity.

Insomnia in shift work disorder relates to occupational and neurophysiological impairment

STUDY OBJECTIVES

To determine whether occupational and neurophysiological decrements within shift work disorder (SWD) are differentially related to its two diagnostic symptoms, insomnia and excessive sleepiness.

METHODS

Thirty-four permanent night workers participated in an overnight lab protocol including a multiple sleep latency test (MSLT) and an event-related brain potential (ERP) task testing auditory target detection (P3a and P3b). At 16:00, each subject completed an Endicott Work Productivity Scale (EWPS), two Insomnia Severity Indices (ISI-Day, ISI-Night), and an Epworth Sleepiness Scale (ESS). Subjects were grouped by ISI and ESS scores into clinical phenotypes. This study compared EWPS and ERP results between alert insomniacs ("AI," reporting insomnia without sleepiness), sleepy insomniacs ("SI," reporting both insomnia and sleepiness), and controls.

RESULTS

The AI group was most impaired on the EWPS, significantly more impaired than controls (25.8 ± 14.8 vs. 12.3 ± 9.4, p < 0.05). SI were not statistically different from controls (19.5 ± 8.7 vs. 12.3 ± 9.4, p > 0.05). Compared to controls, AI showed significantly attenuated P3a response (Fcz, Czp, Cpz, mean difference [MD] 1.62-1.77, p < 0.05) and target-detection P3b response (Fcz, Czp, Cpz, MD 1.28-1.64, p < 0.05). P3b in SI was not different from controls (p > 0.10), and P3a was only different at one electrode site (Cpz, MD 1.43, p < 0.01). Neither the MSLT nor the ESS correlated with EWPS scores or ERP (P3a/P3b) amplitudes (p > 0.10). However, the mean of the ISI measurements correlated with the EWPS (r = 0.409, p < 0.01) and the attention-to-novelty P3a (r = -0.410, p < 0.01).

CONCLUSIONS

Among shift work disorder patients, insomnia is linked to functional and cognitive impairments. Insomniacs with normal sleepiness showed more severe impairments than insomniacs who also reported excessive sleepiness.

Validation of an automated wireless system for sleep monitoring during daytime naps

An automated wireless system (WS) for sleep monitoring was recently developed and validated for assessing nighttime sleep. Here, we aimed to evaluate the validity of the WS to correctly monitor daytime sleep during naps compared to polysomnography (PSG). We found that the WS underestimated wake, sleep onset latency, and wake after sleep onset. Meanwhile, it overestimated total sleep time, sleep efficiency, and duration of REM sleep. Sensitivity was moderate for wake (58.51%) and light sleep (66.92%) and strong for deep sleep (83.46%) and REM sleep (82.12%). These results demonstrated that the WS had a low ability to detect wake and systematically overscored REM sleep, implicating the WS as an inadequate substitute for PSG in diagnosing sleep disorders or for research in which sleep staging is essential.

Caffeine effects on sleep taken 0, 3, or 6 hours before going to bed

STUDY OBJECTIVE

Sleep hygiene recommendations are widely disseminated despite the fact that few systematic studies have investigated the empirical bases of sleep hygiene in the home environment. For example, studies have yet to investigate the relative effects of a given dose of caffeine administered at different times of day on subsequent sleep.

METHODS

This study compared the potential sleep disruptive effects of a fixed dose of caffeine (400 mg) administered at 0, 3, and 6 hours prior to habitual bedtime relative to a placebo on self-reported sleep in the home. Sleep disturbance was also monitored objectively using a validated portable sleep monitor.

RESULTS

Results demonstrated a moderate dose of caffeine at bedtime, 3 hours prior to bedtime, or 6 hours prior to bedtime each have significant effects on sleep disturbance relative to placebo (p < 0.05 for all).

CONCLUSION

The magnitude of reduction in total sleep time suggests that caffeine taken 6 hours before bedtime has important disruptive effects on sleep and provides empirical support for sleep hygiene recommendations to refrain from substantial caffeine use for a minimum of 6 hours prior to bedtime.

Sleep extension normalizes ERP of waking auditory sensory gating in healthy habitually short sleeping individuals

Chronic sleep loss has been associated with increased daytime sleepiness, as well as impairments in memory and attentional processes. In the present study, we evaluated the neuronal changes of a pre-attentive process of wake auditory sensory gating, measured by brain event-related potential (ERP) – P50 in eight normal sleepers (NS) (habitual total sleep time (TST) 7 h 32 m) vs. eight chronic short sleeping individuals (SS) (habitual TST ≤6 h). To evaluate the effect of sleep extension on sensory gating, the extended sleep condition was performed in chronic short sleeping individuals. Thus, one week of time in bed (6 h 11 m) corresponding to habitual short sleep (hSS), and one week of extended time (∼ 8 h 25 m) in bed corresponding to extended sleep (eSS), were counterbalanced in the SS group. The gating ERP assessment was performed on the last day after each sleep condition week (normal sleep and habitual short and extended sleep), and was separated by one week with habitual total sleep time and monitored by a sleep diary. We found that amplitude of gating was lower in SS group compared to that in NS group (0.3 µV vs. 1.2 µV, at Cz electrode respectively). The results of the group × laterality interaction showed that the reduction of gating amplitude in the SS group was due to lower amplitude over the left hemisphere and central-midline sites relative to that in the NS group. After sleep extension the amplitude of gating increased in chronic short sleeping individuals relative to their habitual short sleep condition. The sleep condition × frontality interaction analysis confirmed that sleep extension significantly increased the amplitude of gating over frontal and central brain areas compared to parietal brain areas.

Sleep, memory, and aging: the link between slow-wave sleep and episodic memory changes from younger to older adults

In younger adults, recently learned episodic memories are reactivated and consolidated during slow-wave sleep (SWS). It is interesting that SWS declines across the life span, but little research has examined whether sleep-dependent memory consolidation occurs in older adults. In this study, younger adults and healthy older adults encoded word pairs in the morning or evening and then returned following a sleep or no-sleep interval. Sleep-stage scoring was obtained by using a home sleep-stage monitoring system. In the younger adult group, there was a positive correlation between word retention and amount of SWS during the retention interval. In contrast, the older adults demonstrated no significant positive correlations but one significant negative correlation between memory and SWS. These findings suggest that the link between episodic memory and SWS that is typically observed in younger adults may be weakened or otherwise changed in the healthy older adult population.

Variable sleep schedules and outcomes in children with psychopathological problems: preliminary observations

BACKGROUND

Night-to-night variability in sleep of children with attention deficit hyperactivity disorder (ADHD) may be a mediator of behavioral phenotype. We examined the potential association between alertness, sleep, and eating behaviors in children with ADHD and comorbid problems.

METHODS

Sleep was monitored by actigraphy for 7 days. Questionnaires were used to assess sleep complaints, habits and food patterns by parental report, and sleep complaints and sleepiness by child report.

RESULTS

The group comprised 18 children, including 15 boys, aged 9.4 ± 1.7 years, 88.9% Caucasian, who took one or multiple medications. Children slept on average for 6 hours and 58 minutes with a variability of 1 hour 3 minutes relative to the mean, and their sleepiness scores were highly variable from day to day. Most children had a normal body mass index (BMI). Sleepiness and BMI were associated with sleep schedules and food patterns, such that they accounted for 76% of variance, predominantly by the association of BMI with mean wake after sleep onset and by bedtime sleepiness, with wake after sleep onset variability. Similarly, 97% of variance was shared with eating behaviors, such as desserts and snacks, and fast food meals were associated with morning sleepiness.

CONCLUSION

Disrupted sleep and sleepiness appears to favor unhealthy food patterns and may place children with ADHD at increased risk for obesity.