EEG and behavioural correlates of mild sleep deprivation and vigilance

"Counting sheep PSG": EEGLAB-compatible open-source matlab software for signal processing, visualization, event marking and staging of polysomnographic data

BACKGROUND

Progress in advancing sleep research employing polysomnography (PSG) has been negatively impacted by the limited availability of widely available, open-source sleep-specific analysis tools.

NEW METHOD

Here, we introduce Counting Sheep PSG, an EEGLAB-compatible software for signal processing, visualization, event marking and manual sleep stage scoring of PSG data for MATLAB.

RESULTS

Key features include: (1) signal processing tools including bad channel interpolation, down-sampling, re-referencing, filtering, independent component analysis, artifact subspace reconstruction, and power spectral analysis, (2) customizable display of polysomnographic data and hypnogram, (3) event marking mode including manual sleep stage scoring, (4) automatic event detections including movement artifact, sleep spindles, slow waves and eye movements, and (5) export of main descriptive sleep architecture statistics, event statistics and publication-ready hypnogram.

COMPARISON WITH EXISTING METHODS

Counting Sheep PSG was built on the foundation created by sleepSMG (https://sleepsmg.sourceforge.net/). The scope and functionalities of the current software have made significant advancements in terms of EEGLAB integration/compatibility, preprocessing, artifact correction, event detection, functionality and ease of use. By comparison, commercial software can be costly and utilize proprietary data formats and algorithms, thereby restricting the ability to distribute and share data and analysis results.

CONCLUSIONS

The field of sleep research remains shackled by an industry that resists standardization, prevents interoperability, builds-in planned obsolescence, maintains proprietary black-box data formats and analysis approaches. This presents a major challenge for the field of sleep research. The need for free, open-source software that can read open-format data is essential for scientific advancement to be made in the field.

Simultaneous MEG and EEG source imaging of electrophysiological activity in response to acute transcranial photobiomodulation

Introduction

Transcranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique that improves human cognition. The effects of tPBM of the right forehead on neurophysiological activity have been previously investigated using EEG in sensor space. However, the spatial resolution of these studies is limited. Magnetoencephalography (MEG) is known to facilitate a higher spatial resolution of brain source images. This study aimed to image post-tPBM effects in brain space based on both MEG and EEG measurements across the entire human brain.

Methods

MEG and EEG scans were concurrently acquired for 6 min before and after 8-min of tPBM delivered using a 1,064-nm laser on the right forehead of 25 healthy participants. Group-level changes in both the MEG and EEG power spectral density with respect to the baseline (pre-tPBM) were quantified and averaged within each frequency band in the sensor space. Constrained modeling was used to generate MEG and EEG source images of post-tPBM, followed by cluster-based permutation analysis for family wise error correction (p < 0.05).

Results

The 8-min tPBM enabled significant increases in alpha (8-12 Hz) and beta (13-30 Hz) powers across multiple cortical regions, as confirmed by MEG and EEG source images. Moreover, tPBM-enhanced oscillations in the beta band were located not only near the stimulation site but also in remote cerebral regions, including the frontal, parietal, and occipital regions, particularly on the ipsilateral side.

Discussion

MEG and EEG results shown in this study demonstrated that tPBM modulates neurophysiological activity locally and in distant cortical areas. The EEG topographies reported in this study were consistent with previous observations. This study is the first to present MEG and EEG evidence of the electrophysiological effects of tPBM in the brain space, supporting the potential utility of tPBM in treating neurological diseases through the modulation of brain oscillations.

Sleep deprivation changes frequency-specific functional organization of the resting human brain

Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies have widely explored the temporal connection changes in the human brain following long-term sleep deprivation (SD). However, the frequency-specific topological properties of sleep-deprived functional networks remain virtually unclear. In this study, thirty-seven healthy male subjects underwent resting-state fMRI during rested wakefulness (RW) and after 36 hours of SD, and we examined frequency-specific spectral connection changes (0.01-0.08 Hz, interval = 0.01 Hz) caused by SD. First, we conducted a multivariate pattern analysis combining linear SVM classifiers with a robust feature selection algorithm, and the results revealed that accuracies of 74.29%-84.29% could be achieved in the classification between RW and SD states in leave-one-out cross-validation at different frequency bands, moreover, the spectral connection at the lowest and highest frequency bands exhibited higher discriminative power. Connection involving the cingulo-opercular network increased most, while connection involving the default-mode network decreased most following SD. Then we performed a graph-theoretic analysis and observed reduced low-frequency modularity and high-frequency global efficiency in the SD state. Moreover, hub regions, which were primarily situated in the cerebellum and the cingulo-opercular network after SD, exhibited high discriminative power in the aforementioned classification consistently. The findings may indicate the frequency-dependent effects of SD on the functional network topology and its efficiency of information exchange, providing new insights into the impact of SD on the human brain.

Impact of one night of sleep restriction on sleepiness and cognitive function: A systematic review and meta-analysis

Detrimental consequences of chronic sleep restriction on cognitive function are well established in the literature. However, effects of a single night of sleep restriction remain equivocal. Therefore, we synthesized data from 44 studies to investigate effects of sleep restriction to 2-6 h sleep opportunity on sleepiness and cognition in this meta-analysis. We investigated subjective sleepiness, sustained attention, choice reaction time, cognitive throughput, working memory, and inhibitory control. Results revealed a significant increase in subjective sleepiness following one night of sleep restriction (Standardized Mean Difference (SMD) = 0.986, p < 0.001), while subjective sleepiness was not associated with sleep duration during sleep restriction (β = -0.214, p = 0.039, significance level 0.01). Sustained attention, assessed via common 10-min tasks, was impaired, as demonstrated through increased reaction times (SMD = 0.512, p < 0.001) and attentional lapses (SMD = 0.489, p < 0.001). However, the degree of impaired attention was not associated with sleep duration (ps > 0.090). We did not find significant effects on choice reaction time, cognitive throughput, working memory, or inhibitory control. Overall, results suggest that a single night of restricted sleep can increase subjective sleepiness and impair sustained attention, a cognitive function crucial for everyday tasks such as driving.

A resting-state EEG dataset for sleep deprivation

To investigate the impact of sleep deprivation (SD) on mood, alertness, and resting-state electroencephalogram (EEG), we present an eyes-open resting-state EEG dataset. The dataset comprises EEG recordings and cognitive data from 71 participants undergoing two testing sessions: one involving SD and the other normal sleep. In each session, participants engaged in eyes-open resting-state EEG. The Psychomotor Vigilance Task (PVT) was employed for alertness measurement. Emotional and sleepiness were measured using Positive and Negative Affect Scale (PANAS) and Stanford Sleepiness Scale (SSS). Additionally, to examine the influence of individual sleep quality and traits on SD, Pittsburgh Sleep Quality Index (PSQI) and Buss-Perry Aggression Questionnaire (BPAQ) were utilized. This dataset's sharing may contribute to open EEG measurements in the field of SD.

Changes in electroencephalography microstates are associated with reduced levels of vigilance after sleep deprivation

Total sleep deprivation (TSD) negatively affects cognitive functions, especially vigilance attention, but studies on vigilance changes in terms of electroencephalography (EEG) microstates after TSD are limited. This study investigates the impact of TSD on vigilance attention, EEG microstates and its relationship. Thirty healthy adult males completed a psychomotor vigilance task (PVT) before, 24 h after, and 36 h after TSD while their EEG was recorded during rest. Microstate analysis revealed significant changes in the occurrence and contribution of microstate class B after TSD. Moreover, changes in the probability of transitioning between microstate classes A and D were observed, correlating with decreased vigilance. Specifically, a positive correlation was found between transitioning from class B to class C and vigilance, while a trend of negative correlation was observed between transitioning between classes A and D and vigilance. These findings indicate abnormal activity in the salience network and dorsal attention network following sleep deprivation. TSD impairs vigilance attention, as demonstrated by the effects on EEG microstate class B and the transitions between classes A and D. The study suggests its potential as an early warning indicator for predicting vigilance attention after sleep deprivation.

The evaluation of cEEGrids for fatigue detection in aviation

Operator fatigue poses a major concern in safety-critical industries such as aviation, potentially increasing the chances of errors and accidents. To better understand this risk, there is a need for noninvasive objective measures of fatigue. This study aimed to evaluate the performance of cEEGrids, a type of ear-EEG, for fatigue detection by analyzing the alpha and theta power before and after sleep restriction in four sessions on two separate days, employing a within-participants design. Results were compared to traditional, highly validated methods: the Karolinska Sleepiness Scale (KSS) and Psychomotor Vigilance Task (PVT). After sleep restriction and an office workday, 12 participants showed increased alpha band power in multiple electrode channels, but no channels correlated with KSS scores and PVT response speed. These findings indicate that cEEGrids can detect differences in alpha power following mild sleep loss. However, it should be noted that this capability was limited to specific channels, and no difference in theta power was observed. The study shows the potential and limitations of ear-EEG for fatigue detection as a less invasive alternative to cap-EEG. Further design and electrode configuration adjustments are necessary before ear-EEG can be implemented for fatigue detection in the field.

The measurement of mental fatigue following an overnight on-call duty among doctors using electroencephalogram

This study aimed to measure the spectral power differences in the brain rhythms among a group of hospital doctors before and after an overnight on-call duty. Thirty-two healthy doctors who performed regular on-call duty in a tertiary hospital in Sarawak, Malaysia were voluntarily recruited into this study. All participants were interviewed to collect relevant background information, followed by a self-administered questionnaire using Chalder Fatigue Scale and electroencephalogram test before and after an overnight on-call duty. The average overnight sleep duration during the on-call period was 2.2 hours (p<0.001, significantly shorter than usual sleep duration) among the participants. The mean (SD) Chalder Fatigue Scale score of the participants were 10.8 (5.3) before on-call and 18.4 (6.6) after on-call (p-value < 0.001). The theta rhythm showed significant increase in spectral power globally after an overnight on-call duty, especially when measured at eye closure. In contrast, the alpha and beta rhythms showed reduction in spectral power, significantly at temporal region, at eye closure, following an overnight on-call duty. These effects are more statistically significant when we derived the respective relative theta, alpha, and beta values. The finding of this study could be useful for development of electroencephalogram screening tool to detect mental fatigue.

The Effect of Transcranial Electrical Stimulation on the Recovery of Sleep Quality after Sleep Deprivation Based on an EEG Analysis

Acute sleep deprivation can reduce the cognitive ability and change the emotional state in humans. However, little is known about how brain EEGs and facial expressions change during acute sleep deprivation (SD). Herein, we employed 34 healthy adult male subjects to undergo acute SD for 36 h, during which, their emotional states and brain EEG power were measured. The subjects were divided randomly into electronic stimulation and control groups. We performed TDCS on the left dorsolateral prefrontal cortex for 2 mA and 30 min in the TDCS group. These results indicated that the proportion of disgusted expressions in the electrical stimulation group was significantly less than the controls after 36 h post-acute SD, while the proportion of neutral expressions was increased post-restorative sleep. Furthermore, the electrical stimulation group presented a more significant impact on slow wave power (theta and delta) than the controls. These findings indicated that emotional changes occurred in the subjects after 36 h post-acute SD, while electrical stimulation could effectively regulate the cortical excitability and excitation inhibition balance after acute SD.

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.

Decreased Functional Connectivity of Brain Networks in the Alpha Band after Sleep Deprivation Is Associated with Decreased Inhibitory Control in Young Male Adults

Sleep deprivation leads to reduced inhibitory control in individuals. However, the underlying neural mechanisms are poorly understood. Accordingly, this study aimed to investigate the effects of total sleep deprivation (TSD) on inhibitory control and their neuroelectrophysiological mechanisms from the perspective of the time course of cognitive processing and brain network connectivity, using event-related potential (ERP) and resting-state functional connectivity techniques. Twenty-five healthy male participants underwent 36 h of TSD (36-h TSD), completing Go/NoGo tasks and resting-state data acquisition before and after TSD; their behavioral and electroencephalogram data were recorded. Compared to baseline, participants' false alarms for NoGo stimuli increased significantly (t = -4.187, p < 0.001) after 36-h TSD. ERP results indicated that NoGo-N2 negative amplitude increased and latency was prolonged (t = 4.850, p < 0.001; t = -3.178, p < 0.01), and NoGo-P3 amplitude significantly decreased and latency was prolonged (t = 5.104, p < 0.001; t = -2.382, p < 0.05) after 36-h TSD. Functional connectivity analysis showed that the connectivity of the default mode and visual networks in the high alpha band was significantly reduced after TSD (t = 2.500, p = 0.030). Overall, the results suggest that the negative amplitude increase in N2 after 36-h TSD may reveal that more attention and cognitive resources are invested after TSD; the significant decrease in P3 amplitude may indicate the impairment of advanced cognitive processing. Further functional connectivity analysis indicated impairment of the brain's default mode network and visual information processing after TSD.

Total sleep deprivation selectively impairs motor preparation sub-stages in visual search task: Evidence from lateralized readiness potentials

Introduction

Many studies have provided evidence of a damage effect triggered by total sleep deprivation (TSD). However, it remains unclear whether the motor preparation processing is affected by TSD.

Methods

In the current study, 23 volunteers performed a stimulus-response compatibility visual search task before and after TSD while undergoing spontaneous electroencephalography (EEG).

Results

Repeated-measures analysis of variance revealed that: Compared with that at baseline, the visual search task's accuracy decreased after TSD, while the response time variance increased significantly. The peak amplitude of the stimulus-locked lateralized readiness potential (LRP) induced by a compatible stimulus was significantly more negative than that induced by an incompatible stimulus before TSD, whereas this difference was not significant after TSD. However, when taking sleep status into consideration, there were no significant main or interaction effects on response-locked LRPs.

Discussion

Our findings suggest that TSD damages visual search behavior, selectively impairs the earlier sub-stages of motor preparation (sensory integration). These findings will provide a new perspective for understanding the effects of sleep loss.

Vigilance described by the time-on-task effect in EEG activity during a cued Go/NoGo task

Vigilance refers to the ability to maintain attention and to remain alert to stimuli in prolonged and monotonous tasks. Vigilance decrement describes the decline in performance in the course of such sustained attention tasks. Time-related alterations in attention have been found to be associated with changes in EEG. We investigated these time-on-task effects on the basis of changes in the conventional EEG spectral bands with the aim of finding a compound measure of vigilance. 148 healthy adults performed a cued Go/NoGo task that lasted approximately 21 min. Behavioural performance was examined by comparing the number of errors in the first and last quarters of the task using paired t-test. EEG data were epoched per trial, and time-on-task effects were modelled by using multiple linear regression, with frequency spectra band power values as independent variables and trial number as the dependent variable. Behavioural performance decreased in terms of omission errors only. Performance of the models, expressed by predicted R-squared, was between 0.10 and 0.27, depending on the particular task condition. The time-on-task EEG spectral changes were characterized by broad changes in the alpha and frontal changes in the beta and gamma bands. We were able to identify a set of EEG spectral features that predict time-on-task. Our output is considered to be a measure of vigilance, reflecting the allocation of mental resources for the maintenance of attention.

The EEG correlates and dangerous behavioral consequences of drowsy driving after a single night of mild sleep deprivation

OBJECTIVE

Here, we investigated the behavioral, cognitive, and electrophysiological impact of mild, acute sleep loss via simultaneously recorded behavioral and electrophysiological measures of vigilance during a "real-world", simulated driving task.

METHODS

Participants (N = 34) visited the lab for two testing days where their brain activity and vigilance were simultaneously recorded during a driving simulator task. The driving task lasted approximately 70 mins and consisted of tailgating the lead car at high speed, which braked randomly, requiring participants to react quickly to avoid crashing. The night before testing, participants either slept from 12am-9am (Normally Rested), or 1am-6am (Sleep Restriction).

RESULTS

After a single night of mild sleep restriction, sleepiness was increased, participants took longer to brake, missed more braking events, and crashed more often. Brain activity showed more intense alpha burst activity and significant changes in EEG spectral power frequencies related to arousal (e.g., delta, theta, alpha). Importantly, increases in amplitude and number of alpha bursts predicted delays in reaction time when braking.

CONCLUSIONS

The findings of this study suggest that a single night of mild sleep loss has significant, negative consequences on driving performance and vigilance, and a clear impact on the physiology of the brain in ways that reflect reduced arousal.

SIGNIFICANCE

Understanding neural and cognitive changes associated with sleep loss may lead to important advancements in identifying and preventing potentially dangerous sleep-related lapses in vigilance.

Total Sleep Deprivation Triggers Greater Activation in the Parietal Brain in the Visual Working Memory Updating Processes: An Event-Related Potentials Study

Working memory functions are known to be altered after total sleep deprivation (TSD). However, few studies have explored the deficits of working memory updating (WMU) after TSD, or the underlying electrophysiological mechanisms of these alterations. In the current exploratory study, we enrolled 14 young male volunteers who performed two kinds of WMU tasks—spatial and object two-back tasks—with simultaneous electroencephalography recordings under two sleep conditions: a normal sleep baseline condition and after 36 h of TSD. Repeated-measures analysis of variance showed that compared with those at baseline, the rates of correct responses in the WMU tasks decreased significantly after TSD. Analysis of event-related potentials revealed that the average amplitude of P3 components decreased significantly in the frontal and central brain regions and increased significantly in the parietal brain regions. Our findings suggest that TSD damages WMU behavior, impairs cognitive functions in the frontal and central brain regions, and triggers greater activation in the parietal brain regions. This is the first study to report the existence of event-related compensatory neural activity. This event-related compensatory effect may provide a new perspective for understanding the mechanisms underlying the influences triggered by sleep loss.

Observing changes in human functioning during induced sleep deficiency and recovery periods

Prolonged periods of sleep restriction seem to be common in the contemporary world. Sleep loss causes perturbations of circadian rhythmicity and degradation of waking alertness as reflected in attention, cognitive efficiency and memory. Understanding whether and how the human brain recovers from chronic sleep loss is important not only from a scientific but also from a public health perspective. In this work we report on behavioral, motor, and neurophysiological correlates of sleep loss in healthy adults in an unprecedented study conducted in natural conditions and comprising 21 consecutive days divided into periods of 4 days of regular life (a baseline), 10 days of chronic partial sleep restriction (30% reduction relative to individual sleep need) and 7 days of recovery. Throughout the whole experiment we continuously measured the spontaneous locomotor activity by means of actigraphy with 1-minute resolution. On a daily basis the subjects were undergoing EEG measurements (64-electrodes with 500 Hz sampling frequency): resting state with eyes open and closed (8 minutes long each) followed by Stroop task lasting 22 minutes. Altogether we analyzed actigraphy (distributions of rest and activity durations), behavioral measures (reaction times and accuracy from Stroop task) and EEG (amplitudes, latencies and scalp maps of event-related potentials from Stroop task and power spectra from resting states). We observed unanimous deterioration in all the measures during sleep restriction. Further results indicate that a week of recovery subsequent to prolonged periods of sleep restriction is insufficient to recover fully. Only one measure (mean reaction time in Stroop task) reverted to baseline values, while the others did not.