Subjective sleepiness correlates negatively with global alpha (8-12 Hz) and positively with central frontal theta (4-8 Hz) frequencies in the human resting awake electroencephalogram

The beneficial influence of night-shift napping on brain core cognition networks in nurses experiencing sleep deprivation: A preliminary resting-state fMRI study

PURPOSE

This study investigated the restorative effects of napping on cognitive brain networks in night-shift nurses experiencing sleep deprivation (SD).

METHODS

Functional magnetic resonance imaging data and neurocognitive assessments were collected from 20 nurses during three sessions (rested wakefulness (RW), SD, and night-shift napping (NS-NAP)). Functional connectivity (FC) was performed in three core cognitive networks, including the default-mode network (DMN), central executive network (CEN), and salience network (SN).

RESULTS

The SD session showed decreased FC across almost the entire DMN, while only showed increased FC in several key nodes of the CEN and SN. Napping partially mitigated SD-related FC alterations within the DMN and essentially restored FC abnormities in both the CEN and SN. Changes in neurocognitive performance observed between SD and NS-NAP sessions were correlated with alterations in FC within the DMN.

CONCLUSION

The functional integration of core neurocognitive networks can be restored to varying degrees through appropriate NS-NAP practices, potentially improving neurocognitive performance in nurses experiencing SD.

CLINICAL TRIAL NUMBER

not applicable.

EEG-based assessment of long-term vigilance and lapses of attention using a user-centered frequency-tagging approach

Objective.Sustaining vigilance over extended periods is crucial for many critical operations but remains challenging due to the cognitive resources required. Fatigue and other factors contribute to fluctuations in vigilance, causing attentional focus to drift from task-relevant information. Such lapses of attention, common in prolonged tasks, lead to decreased performance and missed critical information, with potentially serious consequences. Identifying physiological markers that predict inattention is key to developing preventive strategies.Approach.Previous research has established electroencephalography (EEG) responses to periodic visual stimuli, known as steady-state visual evoked potentials (SSVEP), as sensitive markers of attention. In this study, we evaluated a minimally intrusive SSVEP-based approach for tracking vigilance in healthy participants (N= 16) during two sessions of a 45 min sustained visual attention task (Mackworth's clock task). A 14 Hz frequency-tagging flicker was either superimposed on the task or absent.Main results.Results revealed that SSVEP responses were lower prior to lapses of attention, while other spectral EEG markers, such as frontal theta and parietal alpha activity, did not reliably distinguish between detected and missed attention probes. Importantly, the flicker did not affect task performance or participant experience.Significance.This non-intrusive frequency-tagging method provides a continuous measure of vigilance, effectively detecting attention lapses in prolonged tasks. It holds promise for integration into passive brain-computer interfaces, offering a practical solution for real-time vigilance monitoring in high-stakes settings like air traffic control or driving.

Neurofeedback Reduces P300 Amplitudes to Intensely Emotive Pictures in Depressed Cancer Patients

Objective. Electroencephalographic neurofeedback (EEG NF) or its effects on event-related potentials (ERPs) in quantitative EEG have not yet been systematically studied in cancer patients. The aim of this study was to investigate the emotional arousal and valence effects on the event-related P300 in a visual oddball paradigm by an individualized EEG alpha and theta/beta NF intervention in cancer patients and survivors (N = 18, age between 31 and 73 years). Methods. ERPs to low and high arousal target stimuli with either emotional positive or negative content and depressive state were obtained in cancer patients before and after a five-week NF intervention in a waitlist paradigm, following the consensus on the reporting and experimental design of clinical and cognitive-behavioral NF studies (CRED-nf checklist). Results. Overall, P300 amplitudes decreased significantly (p < .05) from pre to post therapy. Effects concerning high arousal stimuli with negative and positive valences were on the border to significance. Moreover, patients achieved significant relief of depressive symptoms (p < .05). Especially younger participants (<55 yrs.) benefited. Conclusions. P300 observations could reflect a therapeutic effect on brain activity level. EEG NF alleviates depressive symptoms in cancer patients. Significance. Based on these findings, further studies are needed to investigate the effects on event-related potentials by NF therapy.

Impact of expectancy on fatigue by exposure to the fifth generation of mobile communication signals

There is a long-standing debate about the relationship between Radio Frequency Electromagnetic Field (RF-EMF) exposure and fatigue. Past studies primarily rely on self-report scales to assess fatigue, but these methods are often susceptible to personal biases. Notably, the role of psychological factors in the fatigue response induce by RF-EMF exposure remains unclear. Therefore, our study focuses on exploring the impact of 5 G signal exposure on human fatigue, particularly considering the influence of expectancy induced by psychological priming on the outcomes. In this study, we recruited 21 healthy subjects who were tested in three sessions. Each session included two 30-min exposures to either real or sham 5 G signals, with the order randomized. The experiment was conducted under varying informational conditions: subjects were provided with correct, false, or no information about the order of exposure. Additionally, subjects completed a fatigue scoring questionnaire and underwent Electroencephalogram (EEG) measurements during the experiment. The statistical comparison indicates that 5 G RF-EMF exposure at routine levels does not lead to changes in EEG power. The finding reveals that the report of fatigue can be altered by the conveyed information of being exposed by 5 G signals although there is no real exposure and no detectable electrophysiological indicator. Our findings suggest that it is necessary to prevent psychological priming in any kind or to take its possible consequence into consideration, to reveal this effect of RF-EMF exposure.

Evaluation of alpha neurofeedback training to enhance sleep in remitted depression and anxiety sufferers with persistent insomnia

This study evaluates whether neurofeedback training (NFT) to boost alpha wave activity in the central brain may effectively mitigate persistent insomnia in patients with remitted depression and anxiety. Thirty-two participants in clinical remission from depression or anxiety were enrolled and evaluated for insomnia severity. Individuals were randomly assigned in a single-blinded manner to either NFT or the sham treatment. The effectiveness of the intervention was measured using recognized scales for depression, anxiety and sleep quality. While subjective sleep quality, measured by the PSQI, showed significant improvements in the active group compared to the sham group at post training, 1-month, 3-month, and 6-month follow-up, objective measures of sleep quality largely remained within the normal range, with few significant changes observed. Specifically, the active group exhibited notable improvements in alpha amplitude and duration during NFT sessions, which were not seen in the sham group. This highlights the potential of NFT as a complementary approach for improving sleep perception in this population, but further research is needed to confirm its effects on actual sleep architecture and long-term outcomes.

Neural indicators of sleep loss and sleep propensity in male military trainees: Insights from dry-electrode EEG-An exploratory study

This study examined the impact of reduced sleep on electroencephalogram (EEG) activity during cognitive tasks in Military Clearance Diver trainees using a novel dry-electrode EEG system. Seven male participants underwent two 5-day periods: a baseline and a "live-in" phase with increased workload and reduced sleep (5.4 ± 0.1 vs. 7.4 ± 0.7 h). EEG was recorded daily in the early morning (am) and late afternoon (pm) during a Psychomotor Vigilance Test (PVT), two oculography tests (am: n = 4; pm: n = 3), and 2 min of eyes-closed rest. Significant increases in theta (t (29) = 2.308, p = 0.028, d = 0.421) and alpha (t (29) = 2.124, p = 0.042, d = 0.388) power spectrum densities were observed in the "live-in" phase during the PVT. These findings align with increased lower frequency activity over time awake, reflecting heightened sleep propensity. Sleep loss was further confirmed by declining Odds Ratio Product (ORP) values. This study demonstrates the feasibility of dry-electrode EEG in detecting fatigue-related neural changes and highlights the potential of ORP as a quantifiable fatigue marker. These insights may inform operational settings, such as military diver performance monitoring and fatigue management strategies.

Using passive BCI for personalization of assistive wearable devices: a proof-of-concept study

Assistive wearable devices can significantly enhance the quality of life for individuals with movement impairments, aid the rehabilitation process, and augment movement abilities of healthy users. However, personalizing the assistance to individual preferences and needs remains a challenge. Brain-Computer Interface (BCI) offers a promising solution for this personalization problem. The overarching goal of this study is to investigate the feasibility of utilizing passive BCI technology to personalize the assistance provided by a knee exoskeleton. Participants performed seated knee flexion-extension tasks while wearing a one-degree-of-freedom knee exoskeleton with varying levels of applied force. Their brain activities were recorded throughout the movements using electroencephalography (EEG). EEG spectral bands from several brain regions were compared between the conditions with the lowest and highest exoskeleton forces to identify statistically significant changes. A Naive Bayes classifier was trained on these spectral features to distinguish between the two conditions. Statistical analysis revealed significant increases in δ and θ activity and decreases in α and β activity in the frontal, motor, and occipital cortices. These changes suggest heightened attention, concentration, and motor engagement when the task became more difficult. The trained Naive Bayes classifier achieved an average accuracy of approximately 72% in distinguishing between the two conditions. The outcomes of our study demonstrate the potential of passive BCI in personalizing assistance provided by wearable devices. Future research should further explore integrating passive BCI into assistive wearable devices to enhance user experience.

Impact of sleep deprivation on dynamic functional connectivity states

Sleep deprivation (SD) is an experimental procedure to study the effects of sleep loss on the human brain. Neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), have been pivotal in studying these effects. The present chapter aims to retrace the state of the art regarding the literature that examines the SD effects on the brain through functional connectivity (FC) evaluated in fMRI and EEG settings, separately. Specifically, we focused on the cognitive domains mainly affected by sleep loss and the underlying brain connectivity alterations. SD disrupts homeostatic and circadian processes, negatively affecting cognitive and cerebral functionality explored through FC. All evidence confirms the detrimental role of SD on brain connectivity impacting several resting-state networks and resulting in cognitive impairments. To conclude, SD may offer useful insights into pathogenic mechanisms likely resembling those induced by chronic sleep loss that might find their application in the clinical context.

Closed-loop auditory stimulation targeting alpha and theta oscillations during rapid eye movement sleep induces phase-dependent power and frequency changes

STUDY OBJECTIVES

Alpha and theta oscillations characterize the waking human electroencephalogram (EEG) and can be modulated by closed-loop auditory stimulation (CLAS). These oscillations also occur during rapid eye movement (REM) sleep, but their function here remains elusive. CLAS represents a promising tool to pinpoint how these brain oscillations contribute to brain function in humans. Here we investigate whether CLAS can modulate alpha and theta oscillations during REM sleep in a phase-dependent manner.

METHODS

We recorded high-density EEG during an extended overnight sleep period in 18 healthy young adults. Auditory stimulation was delivered during both phasic and tonic REM sleep in alternating 6-second ON and 6-second OFF windows. During the ON windows, stimuli were phase-locked to four orthogonal phases of ongoing alpha or theta oscillations detected in a frontal electrode.

RESULTS

The phases of ongoing alpha and theta oscillations were targeted with high accuracy during REM sleep. Alpha and theta CLAS induced phase-dependent changes in power and frequency at the target location. Frequency-specific effects were observed for alpha trough (speeding up) and rising (slowing down) and theta trough (speeding up) conditions. CLAS-induced phase-dependent changes were observed during both REM sleep substages, even though auditory evoked potentials were very much reduced in phasic compared to tonic REM sleep.

CONCLUSIONS

This study provides evidence that faster REM sleep rhythms can be modulated by CLAS in a phase-dependent manner. This offers a new approach to investigating how modulation of REM sleep oscillations affects the contribution of this vigilance state to brain function.

Novel biomarkers derived from the Maintenance of Wakefulness Test as predictors of sleepiness and response to treatment

The Maintenance of Wakefulness Test (MWT) is a widely accepted objective test used to evaluate daytime somnolence and is commonly used in clinical studies evaluating novel therapeutics for excessive daytime sleepiness. In the latter, sleep onset latency (SOL) is typically the sole MWT endpoint. Here, we explored microsleeps, sleep probability measures derived from automated sleep scoring, and quantitative electroencephalography (qEEG) features as additional MWT biomarkers of daytime sleepiness, using data from a phase 1B trial of the selective orexin receptor 2 agonist danavorexton (TAK-925) in people with narcolepsy type 1 (NT1) or type 2 (NT2). Danavorexton treatment reduced the rate and duration of microsleeps during the MWT in NT1 (days 1 and 7; p ≤ .005) and microsleep rate in NT2 (days 1 and 7; p < .0001). The use of an EEG-sleep-staging - derived measure to determine the probability of wakefulness for each minute revealed a novel metric to track changes in daytime sleepiness, which were consistent with the θ/α ratio, a known biomarker of drowsiness. The slopes of line-fits to both the log-transformed sleepiness score or log-transformed θ/α ratio correlated well to (inverse) MWT SOL for NT1 (R = 0.93 and R = 0.83, respectively) and NT2 (R = 0.97 and R = 0.84, respectively), suggesting that individuals with narcolepsy have increased sleepiness immediately after lights-off. These analyses demonstrate that novel EEG-based biomarkers can augment SOL as predictors of sleepiness and its response to treatment and provide a novel framework for the analysis of wake EEG in hypersomnia disorders.

Extended wakefulness alters the relationship between EEG oscillations and performance in a sustained attention task

During drowsiness, maintaining consistent attention becomes difficult, leading to behavioural lapses. Bursts of oscillations in the electroencephalogram (EEG) might predict such lapses, given that alpha bursts increase during inattention and theta bursts increase with time spent awake. Paradoxically, however, alpha bursts decrease with time awake and theta bursts increase during focussed attention and cognitive tasks. Therefore, we investigated to what extent theta and alpha bursts predicted performance in a sustained attention task, either when well rested (baseline, BL) or following 20 h of extended wakefulness (EW). High-density EEG was measured in 18 young adults, and the timing of bursts was related to trial outcomes (fast, slow, and lapse trials). To increase the likelihood of lapses, the task was performed under soporific conditions. Against expectations, alpha bursts were more likely before fast trials and less likely before lapses at baseline, although the effect was substantially reduced during extended wakefulness. Theta bursts showed no significant relationship to behavioural outcome either at baseline or extended wakefulness. However, following exploratory analyses, we found that large-amplitude theta and alpha bursts were more likely to be followed by lapse trials during extended wakefulness but not baseline. In summary, alpha bursts during baseline anticipated better trial outcomes, whereas large-amplitude theta and alpha bursts during extended wakefulness anticipated worse outcomes. Therefore, neither theta nor alpha bursts maintain a consistent relationship with behaviour under different levels of overall vigilance.

Associating EEG functional networks and the effect of sleep deprivation as measured using psychomotor vigilance tests

People are routinely forced to undertake cognitive challenges under the effect of sleep deprivation, due to professional and social obligations forcing them to ignore their circadian clock. However, low intra-individual and high inter-individual differences in behavioural outcomes are known to occur when people are sleep deprived, leading to the conclusion that trait-like differences to sleep deprivation could explain the differing levels of resilience. Within this study we consider if trait-like resilience to sleep deprivation, measured using psychomotor vigilance tests over a 40 h protocol, could be associated with graph metrics (mean node strength, clustering coefficient, characteristic path length and stability) calculated from EEG functional networks acquired when participants ([Formula: see text]) are well rested (baseline). Furthermore, we investigated how stability (the consistency of a participant's functional network over time measured using 2-D correlation) changed over the constant routine. We showed evidence of strong significant correlations between high mean node strength, low characteristic path length and high stability at baseline with a general resilience to extended sleep deprivation, although the same features lead to vulnerability during the period of natural sleep onset, highlighting non-uniform correlations over time. We also show significant differences in the levels of stability between resilient and vulnerable groups.

Impact of sleep deprivation on aperiodic activity: a resting-state EEG study

Sleep deprivation (SD) has been shown to have a negative impact on alertness, as evidenced by behavioral and electroencephalographic studies. Nevertheless, in prior studies utilizing conventional fixed-bandwidth spectral analysis the aperiodic and periodic components were often confused, and some important periodic parameters (i.e., center frequency, bandwidth) were ignored. Here, based on a large open-access dataset of SD, we employed a standardized process for multiple-electrode analysis and group inference. We found that, compared to the healthy sleep control state (SC), the aperiodic offset shifted overall after SD, primarily in the occipital region. This shift was associated with a reduction in subjective alertness. Regarding periodic components, we did not find any power change in the alpha rhythm, but there was an increase in bandwidth of alpha within different regions distributed in the occipital and temporal lobes. These findings highlight the potential significance and value of aperiodic parameters in behavioral and electrophysiological research.NEW & NOTEWORTHY Aperiodic and periodic components were separated in a large open-access EEG dataset of sleep deprivation. Aperiodic offsets increase after deprivation, particularly in the occipital region, reflecting a decline in self-reported vigilance. Parameterized alpha bandwidth, which was ignored in previous studies, is found to be relevant to sleep deprivation. Increase in bandwidth of alpha was focused in the occipital and temporal lobes.

Neuro-motor controlled wearable augmentations: current research and emerging trends

Wearable augmentations (WAs) designed for movement and manipulation, such as exoskeletons and supernumerary robotic limbs, are used to enhance the physical abilities of healthy individuals and substitute or restore lost functionality for impaired individuals. Non-invasive neuro-motor (NM) technologies, including electroencephalography (EEG) and sufrace electromyography (sEMG), promise direct and intuitive communication between the brain and the WA. After presenting a historical perspective, this review proposes a conceptual model for NM-controlled WAs, analyzes key design aspects, such as hardware design, mounting methods, control paradigms, and sensory feedback, that have direct implications on the user experience, and in the long term, on the embodiment of WAs. The literature is surveyed and categorized into three main areas: hand WAs, upper body WAs, and lower body WAs. The review concludes by highlighting the primary findings, challenges, and trends in NM-controlled WAs. This review motivates researchers and practitioners to further explore and evaluate the development of WAs, ensuring a better quality of life.

Differential effects of mindfulness treatment and mobile neurofeedback on event-related potentials in early posterior negativity in cancer patients: a clinical-experimental parallel group design

Introduction

Cancer frequently leads to psychological challenges, among them emotion regulation problems. These can be alleviated with the help of mindfulness therapies or neurofeedback (NF) interventions. Possible intervention effects on emotion procession can be detected in clinical EEG studies by exploring event-related potentials, e.g., early posterior negativity (EPN), which recently has been established to investigate emotional processing and represents very early attention to affective stimuli. Therefore, this clinical-experimental study investigated the efficacy of mindfulness and NF (10 sessions each) on the EPN in oncology patients.

Method

The study enrolled 42 cancer patients (age: 31-73 years; gender: 28 female, 14 male). The study design was an RCT with a parallel group [NF (n = 21) versus mindfulness (n = 21)] waitlist paradigm. EEG recordings in an oddball task with neutral, rare positive and negative valence and high and low arousal stimuli were performed at three measurement time points (T0 = before waitlist, T1 = before intervention, T2 = after intervention). Following preprocessing, data from electrodes O1, Oz and O2 were analyzed for EPN amplitudes.

Results

Response time did not differ across groups and conditions. Comparing EPN at T1 and T2, there was a significant interaction of time, valence, and intervention (p = 0.042). Descriptive statistics showed increased EPN for negative stimuli after the NF intervention (T1 to T2), while EPN for positive stimuli only slightly increased. For mindfulness, positive stimuli evoked stronger amplitudes after the intervention, while EPN for negative stimuli increased from T1 to T2.

Conclusion

Distinct effects were observed for the EPN for pictures with negative valence. Here, it is presumed that mindfulness treatment led to a refocusing of attention with a focus on positive valence, whereas NF seems to entail a different processing of images with negative valence and is therefore to be seen more in the sense of a confrontational approach. Our results suggest that both interventions are suitable for modulating EPN. However, it is not clear to what extent the effects are due to the interventions alone and how other factors might have affected the amplitudes, which highlights the need for further research in this area.

Phase-Amplitude Coupling in Theta and Beta Bands: A Potential Electrophysiological Marker for Obstructive Sleep Apnea

Background

Phase-amplitude coupling (PAC) between the phase of low-frequency signals and the amplitude of high-frequency activities plays many physiological roles and is involved in the pathological processed of various neurological disorders. However, how low-frequency and high-frequency neural oscillations or information synchronization activities change under chronic central hypoxia in OSA patients and whether these changes are closely associated with OSA remains largely unexplored. This study arm to elucidate the long-term consequences of OSA-related oxygen deprivation on central nervous system function.

Methods

: We screened 521 patients who were clinically suspected of having OSA at our neurology and sleep centers. Through polysomnography (PSG) and other clinical examinations, 103 patients were ultimately included in the study and classified into mild, moderate, and severe OSA groups based on the severity of hypoxia determined by PSG. We utilized the phase-amplitude coupling (PAC) method to analyze the modulation index (MI) trends between different frequency bands during NREM (N1/N2/N3), REM, and wakefulness stages in OSA patients with varying severity levels. We also examined the correlation between the MI index and OSA hypoxia indices.

Results

Apart from reduced N2 sleep duration and increased microarousal index, the sleep architecture remained largely unchanged among OSA patients with varying severity levels. Compared to the mild OSA group, patients with moderate and severe OSA exhibited higher MI values of PAC in the low-frequency theta phase and high-frequency beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. No significant differences in the MI of phase-amplitude coupling were observed during N2/3 and REM sleep. Moreover, the MI of phase-amplitude coupling in theta and beta bands positively correlated with hypoxia-related indices, including the apnea-hypopnea index (AHI) and oxygenation desaturation index (ODI), and the percentage of oxygen saturation below 90% (SaO2<90%).

Conclusion

OSA patients demonstrated increased MI values of theta phase and beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. This suggests that cortical coupling is prevalent and exhibits sleep-stage-specific patterns in OSA. Theta-beta PAC during N1 and wakefulness was positively correlated with hypoxia-related indices, suggesting a potential relationship between these neural oscillations and OSA severity. The present study provides new insights into the relationship between neural oscillations and respiratory hypoxia in OSA patients.

How to quantify sleepiness during an attempt to sleep?

Background. Sleepiness assessment tools were mostly developed for detection of an elevated sleepiness level in the condition of sleep deprivation and several medical conditions. However, sleepiness occurs in various other conditions including the transition from wakefulness to sleep during an everyday attempt to get sleep.Objective. We examined whether objective sleepiness indexes can be implicated in detection of fluctuations in sleepiness level during the polysomnographically-monitored attempt to sleep, i.e. in the absence of self-reports on perceived sleepiness level throughout such an attempt.Approach. The polysomnographic signals were recorded in the afternoon throughout 106 90 min napping attempts of 53 university students (28 females). To calculate two objective sleepiness indexes, the electroencephalographic (EEG) spectra were averaged on 30 s epochs of each record, assigned to one of 5 sleep-wake stages, and scored using either the frequency weighting curve for sleepiness substate of wake state or loadings of each frequency on the 2nd principal component of variation in the EEG spectrum (either sleepiness score or PC2 score, respectively).Main results. We showed that statistically significant fluctuations in these two objective sleepiness indexes during epochs assigned to wake stage can be described in terms of the changes in verbally anchored levels of subjective sleepiness assessed by scoring on the 9-step Karolinska Sleepiness Scale.Significance. The results afford new opportunities to elaborate importance of intermediate substates between wake and sleep states for sleep-wake dynamics in healthy individuals and patients with disturbed sleep.

Timing and cortical region matter: theta power differences between teenagers affected by Major Depression and healthy controls

In adults affected by Major Depressive Disorder (MDD), most findings point to higher electroencephalographic (EEG) theta power during wake compared to healthy controls (HC) as a potential biomarker aiding the diagnostic process or subgrouping for stratified treatment. Besides these group differences, theta power is modulated by time of day, sleep/wake history, and age. Thus, we aimed at assessing if the time of recording alters theta power in teenagers affected by MDD or HC. Standardized wake EEG power was assessed with high-density EEG in 15 children and adolescents with MDD and in 15 age- and sex-matched HC in the evening and morning. Using a two-way ANOVA, group, time, and their interaction were tested. In patients, the current severity of depression was rated using the Children's Depression Rating Scale. Broadband EEG power was lower in the morning after sleep, with a significant interaction (group x time) in central regions in the 4-6 Hz range. In MDD relative to HC, theta power was decreased over occipital areas in the evening and increased over frontal areas in the morning. A higher frontal theta power was correlated with more severe depressive mood in the morning but not in the evening. This was a cross-sectional study design, including patients on antidepressant medication. In conclusion, depending on time of recording, region-specific opposite differences of theta power were found between teenagers with MDD and HC. These findings stress the importance of the time of the recording when investigating theta power's relationship to psychopathology.

Validation of the Karolinska Sleepiness Scale in Korean

BACKGROUND AND PURPOSE

The Karolinska Sleepiness Scale (KSS) is widely used for assessing current level of sleepiness, but it has not been validated in South Korea. This study aimed to validate the KSS using the Stanford Sleepiness Scale (SSS), polysomnography (PSG), and electroencephalography (EEG).

METHODS

The sample consisted of 27 adult participants in this study aged 40.5±7.7 years (mean±standard deviation) and included 22 males. They completed questionnaires and underwent EEG recording and overnight PSG. The KSS was completed from 18:00 to 24:00 every 2 hours and following PSG (at 07:00). KSS scores changed over time and in particular increased with the time since waking, with the score peaking at 24:00.

RESULTS

Convergent validity of the KSS was verified by performing a Spearman correlation analysis between the KSS and SSS (r=0.742, p<0.01). Concurrent validity of the KSS was verified by performing a Spearman correlation analysis between the KSS administered before sleep and the sleep onset latency measured using PSG (r=-0.456, p<0.05). Alpha waves were measured 5 minutes before administering the KSS, and the KSS scores were compared with these alpha waves. There were no significant correlations observed between the KSS scores and alpha waves measured in the left occipital area (O1), left frontal area (F3), or left central area (C3). In addition, Spearman correlation analyses of the difference between KSS scores and alpha waves measured at O1, F3, and C3 produced no significant results.

CONCLUSIONS

This study verified the convergent validity and concurrent validity of the KSS, and confirmed the capabilities of this scale in assessing sleepiness changes over time.

Neural rhythms of narcissism: Facets of narcissism are associated with different neural sources in resting-state EEG

Trait narcissism is characterized by significant heterogeneity across individuals. Despite advances in the conceptualization of narcissism, including the increasing recognition that narcissism is a multidimensional construct, the sources of this heterogeneity remain poorly understood. Here, we used a neural trait approach to help better understand "how," and shed light on "why," individuals vary in facets of trait narcissism. Participants (N = 58) first completed personality measures, including the Narcissistic Personality Inventory (NPI), and then in a second session sat passively while resting-state electroencephalography (rs-EEG) was recorded. We then regressed source-localized rs-EEG activity on the distinct facets of narcissism: Grandiose Exhibitionism (GE), Entitlement/Exploitativeness (EE), and Leadership/Authority (LA). Results revealed that each facet was associated with different (though sometimes overlapping) neural sources. Specifically, GE was associated with reduced activation in the dorsomedial prefrontal cortex (DMPFC). EE was associated with reduced activation in the DMPFC and right lateral PFC. LA was associated with increased activation in the left anterior temporal cortex. These findings support the idea that trait narcissism is a multidimensional construct undergirded by individual differences in neural regions related to social cognition (the DMPFC), self-regulation (right lateral PFC), and self-referential processing (left anterior temporal cortex).

Diurnal biological effects of correlated colour temperature and its exposure timing on alertness, cognition, and mood in an enclosed environment

Artificial lighting, which profits from the non-visual effects of light, is a potentially promising solution to support residents' psychophysiological health and performance at specific times of the day in enclosed environments. However, few studies have investigated the non-visual effects of daytime correlated colour temperature (CCT) and its exposure timing on human alertness, cognition, and mood. However, the neural mechanisms underlying these effects are largely unknown. The current study evaluated the effects of daytime CCT and its exposure timing on markers of subjective experience, cognitive performance, and cerebral activity in a simulated enclosed environment. Forty-two participants participated a single-blind laboratory study with a 4 within (CCT: 4000 K vs. 6500 K vs. 8500 K vs. 12,000 K) × 2 between (exposure timing: morning vs. afternoon) mixed design. The results showed time of the day dependent benefits of the daytime CCT on subjective experience, vigilant attention, response inhibition, working memory, emotional perception, and risk decisions. The results of the electroencephalogram (EEG) revealed that lower-frequency EEG bands, including theta, alpha, and alpha-theta, were quite sensitive to daytime CCT intervention, which provides a valuable reference for trying to establish the underlying mechanisms that support the performance-enhancement effects of exposure to CCT in the daytime. However, the results revealed no consistent intervention pattern across these measurements. Therefore, future studies should consider personalised optimisation of daytime CCT for different cognitive demands.

Behavioral and Electrophysiological Markers of Attention Fluctuations in Children with Hypersomnolence

Background. No device is yet available to effectively capture the attentional repercussions of hypersomnolence (HYP). The present study aimed to compare attentional performance of children with HYP, attention deficit hyperactivity disorder (ADHD), and controls using behavioral and electrophysiological (EEG) markers, and to assess their relationship with conventional sleepiness measurements. Methods. Children with HYP underwent a multiple sleep latency test (MSLT) and completed the adapted Epworth sleepiness scale (AESS). Along with age-matched children with ADHD, they were submitted to a resting EEG followed by the Bron-Lyon Attention Stability Test (BLAST). The control group only performed the BLAST. Multivariate models compared reaction time (RT), error percentage, BLAST-Intensity, BLAST-Stability, theta activity, and theta/beta ratio between groups. Correlations between these measures and conventional sleepiness measurements were conducted in children with HYP. Results. Children with HYP had lower RT and BLAST-Stability than controls but showed no significant difference in BLAST/EEG markers compared to children with ADHD. The AESS was positively correlated with the percentage of errors and negatively with BLAST-Intensity. Conclusions. Children with HYP showed impulsivity and attention fluctuations, without difference from children with ADHD for BLAST/EEG markers. The BLAST-EEG protocol could be relevant for the objective assessment of attentional fluctuations related to hypersomnolence.

Resting-state electroencephalography (EEG) microstates of healthy individuals following mild sleep deprivation

Mild sleep deprivation is widespread in many societies worldwide. Electroencephalography (EEG) microstate analysis provides information on spatial and temporal characteristics of resting brain network, serving as an indicator of neurophysiological activities at rest. This study seeks to investigate potential neural markers in EEG following mild sleep deprivation of a single night using EEG microstate analysis. Six-minute resting EEG was conducted on thirty healthy adults within 6 hours of waking in the morning and after at least 18 h of sleep deprivation. Translated and validated Malay language Karolinska Sleepiness Scale was used to assess the participants' degree of sleepiness. Microstate characteristics analysis was conducted on the final 24 subjects based on four standard microstate maps. Microstate C shows a significant increase in mean duration, coverage and occurrence, while microstate D has significantly higher occurrence after sleep deprivation. This study demonstrates notable changes in resting state EEG microstates following mild sleep deprivation. Present findings deepen our understanding of the brain's spatiotemporal dynamics under this condition and suggest the potential utility of neural markers in this domain as components of composite markers for sleep deprivation.

A randomized controlled trial of alpha phase-locked auditory stimulation to treat symptoms of sleep onset insomnia

Sleep onset insomnia is a pervasive problem that contributes significantly to the poor health outcomes associated with insufficient sleep. Auditory stimuli phase-locked to slow-wave sleep oscillations have been shown to augment deep sleep, but it is unknown whether a similar approach can be used to accelerate sleep onset. The present randomized controlled crossover trial enrolled adults with objectively verified sleep onset latencies (SOLs) greater than 30 min to test the effect of auditory stimuli delivered at specific phases of participants' alpha oscillations prior to sleep onset. During the intervention week, participants wore an electroencephalogram (EEG)-enabled headband that delivered acoustic pulses timed to arrive anti-phase with alpha for 30 min (Stimulation). During the Sham week, the headband silently recorded EEG. The primary outcome was SOL determined by blinded scoring of EEG records. For the 21 subjects included in the analyses, stimulation had a significant effect on SOL according to a linear mixed effects model (p = 0.0019), and weekly average SOL decreased by 10.5 ± 15.9 min (29.3 ± 44.4%). These data suggest that phase-locked acoustic stimulation can be a viable alternative to pharmaceuticals to accelerate sleep onset in individuals with prolonged sleep onset latencies. Trial Registration: This trial was first registered on clinicaltrials.gov on 24/02/2023 under the name Sounds Locked to ElectroEncephalogram Phase For the Acceleration of Sleep Onset Time (SLEEPFAST), and assigned registry number NCT05743114.

Aperiodic and periodic components of oscillatory brain activity in relation to cognition and symptoms in pediatric ADHD

Children with attention-deficit/hyperactivity disorder show deficits in processing speed, as well as aberrant neural oscillations, including both periodic (oscillatory) and aperiodic (1/f-like) activity, reflecting the pattern of power across frequencies. Both components were suggested as underlying neural mechanisms of cognitive dysfunctions in attention-deficit/hyperactivity disorder. Here, we examined differences in processing speed and resting-state-Electroencephalogram neural oscillations and their associations between 6- and 12-year-old children with (n = 33) and without (n = 33) attention-deficit/hyperactivity disorder. Spectral analyses of the resting-state EEG signal using fast Fourier transform revealed increased power in fronto-central theta and beta oscillations for the attention-deficit/hyperactivity disorder group, but no differences in the theta/beta ratio. Using the parameterization method, we found a higher aperiodic exponent, which has been suggested to reflect lower neuronal excitation-inhibition, in the attention-deficit/hyperactivity disorder group. While fast Fourier transform-based theta power correlated with clinical symptoms for the attention-deficit/hyperactivity disorder group only, the aperiodic exponent was negatively correlated with processing speed across the entire sample. Finally, the aperiodic exponent was correlated with fast Fourier transform-based beta power. These results highlight the different and complementary contribution of periodic and aperiodic components of the neural spectrum as metrics for evaluation of processing speed in attention-deficit/hyperactivity disorder. Future studies should further clarify the roles of periodic and aperiodic components in additional cognitive functions and in relation to clinical status.

Purkinje cell dysfunction causes disrupted sleep in ataxic mice

Purkinje cell dysfunction disrupts movement and causes disorders such as ataxia. Recent evidence suggests that Purkinje cell dysfunction may also alter sleep regulation. Here, we used an ataxic mouse model generated by silencing Purkinje cell neurotransmission (L7Cre;Vgatfx/fx) to better understand how cerebellar dysfunction impacts sleep physiology. We focused our analysis on sleep architecture and electrocorticography (ECoG) patterns based on their relevance to extracting physiological measurements during sleep. We found that circadian activity was unaltered in the mutant mice, although their sleep parameters and ECoG patterns were modified. The L7Cre;Vgatfx/fx mutant mice had decreased wakefulness and rapid eye movement (REM) sleep, whereas non-REM sleep was increased. The mutants had an extended latency to REM sleep, which is also observed in human patients with ataxia. Spectral analysis of ECoG signals revealed alterations in the power distribution across different frequency bands defining sleep. Therefore, Purkinje cell dysfunction may influence wakefulness and equilibrium of distinct sleep stages in ataxia. Our findings posit a connection between cerebellar dysfunction and disrupted sleep and underscore the importance of examining cerebellar circuit function in sleep disorders.

Multimodal Vigilance Estimation With Modality-Pairwise Contrastive Loss

Nowadays, how to estimate vigilance with higher accuracy has become a hot field of research direction. Although the increasing available modalities opens the door for amazing new possibilities to achieve good performance, the uncertain cross-modal interaction still poses a real challenge to the multimodal fusion. In this paper, a cross-modality alignment method has been proposed based on the contrastive learning for extracting shared but not the same information among modalities. The contrastive learning is adopted to minimize the intermodal differences by maximizing the similarity of semantic representation of modalities. Applying our proposed modeling framework, we evaluated our approach on SEED-VIG dataset consisting of EEG and EOG signals. Experiments showed that our study achieved state-of-the-art multimodal vigilance estimation performance both in intra-subject and inter-subject situations, the average of RMSE/CORR were improved to 0.092/0.893 and 0.144/0.887, respectively. In addition, analysis on the frequency bands showed that theta and alpha activities contain valuable information for vigilance estimation, and the correlation between them and PERCLOS can be significantly improved by contrastive learning. We argue that the proposed method in the inter-subject case could offer the possibility of reducing the high-cost of data annotation, and further analysis may provide an idea for the application of multimodal vigilance regression.

Driving fatigue detection based on brain source activity and ARMA model

Fatigue among drivers is a significant issue in society, and according to organizational reports, it substantially contributes to accidents. So accurate fatigue detection in drivers plays a crucial role in reducing the number of people fatalities or injured resulting from accidents. Several methods are proposed for fatigue driver recognition among which electroencephalography (EEG) is one. This paper proposed a method for fatigue recognition by EEG signals with extracted features from source and sensor spaces. The proposed method starts with preprocessing by applying filtering and artifact rejection. Then source localization methods are applied to EEG signals for active source extraction. A multivariate autoregressive (MVAR) model is fitted to selected sources, and a dual Kalman filter is applied to estimate the source activity and their relationships. Then multivariate autoregressive moving average (ARMA) is fitted between EEG and source activity signals. Features are extracted from model parameters, source relationship matrix, and wavelet transform of EEG and source activity signals. The novelty of this approach is the use of ARMA model between source activities (as input) and EEG signals (as output) and feature extraction from source relations. Relevant features are selected using a combination of RelifF and neighborhood component analysis (NCA) methods. Three classifiers, namely k-nearest neighbor (KNN), support vector machine (SVM), and naive Bayesian (NB) classifiers, are employed to classify drivers. To improve performance, the final label for fatigue detection is calculated by combining these classifiers using the voting method. The results demonstrate that the proposed method accurately recognizes and classifies fatigued drivers with the ensemble classifiers in comparison with other methods.

Reliability of Spectral Features of Resting-State Brain Activity: A Magnetoencephalography Study

Background Cognition is a vital sign and its deterioration is a major concern in clinical medicine. It is usually evaluated using neuropsychological assessments, which have innate limitations such as the practice effect. To compensate for these assessments, the oscillatory power of resting-state brain activity has recently become available. The power is obtained noninvasively using magnetoencephalography and is summarized by spectral parameters such as the median frequency (MF), individual alpha frequency (IAF), spectral edge frequency 95 (SEF95), and Shannon's spectral entropy (SSE). As these parameters are less sensitive to practice effects, they are suitable for longitudinal studies. However, their reliability remains unestablished, hindering their proactive use in clinical practice. Therefore, we aimed to quantify the within-participant reliability of these parameters using repeated measurements of healthy participants to facilitate their clinical use and to evaluate the observed changes/differences in these parameters reported in previous studies. Methodology Resting-state brain activity with eyes closed was recorded using magnetoencephalography for five minutes from 15 healthy individuals (29.3 ± 4.6 years old: ranging from 23 to 28 years old). The following four spectral parameters were calculated: MF, IAF, SEF95, and SSE. To quantify reliability, the minimal detectable change (MDC) and intraclass correlation coefficient (ICC) were computed for each parameter. In addition, we used MDCs to evaluate the changes and differences in the spectral parameters reported in previous longitudinal and cross-sectional studies. Results The MDC at 95% confidence interval (MDC95) of MF, IAF, SEF95, and SSE were 0.61 Hz, 0.44 Hz, 2.91 Hz, and 0.028, respectively. The ICCs of these parameters were 0.96, 0.92, 0.94, and 0.83, respectively. The MDC95 of these parameters was smaller than the mean difference in the parameters between cognitively healthy individuals and patients with dementia, as reported in previous studies. Conclusions The spectral parameter changes/differences observed in prior studies were not attributed to measurement errors but rather reflected genuine effects. Furthermore, all spectral parameters exhibited high ICCs (>0.8), underscoring their robust within-participant reliability. Our results support the clinical use of these parameters, especially in the longitudinal monitoring and evaluation of the outcomes of interventions.

Region-specific changes in brain activity and memory after continuous positive airway pressure therapy in obstructive sleep apnea: a pilot high-density electroencephalography study

STUDY OBJECTIVES

Limited channel electroencephalography (EEG) investigations in obstructive sleep apnea (OSA) have revealed deficits in slow wave activity (SWA) and spindles during sleep and increased EEG slowing during resting wakefulness. High-density EEG (Hd-EEG) has also detected local parietal deficits in SWA (delta power) during NREM. It is unclear whether effective continuous positive airway pressure (CPAP) treatment reverses regional SWA deficits, and other regional sleep and wake EEG abnormalities, and whether any recovery relates to improved overnight memory consolidation.

METHODS

A clinical sample of men with moderate-severe OSA underwent sleep and resting wake recordings with 256-channel Hd-EEG before and after 3 months of CPAP. Declarative and procedural memory tasks were administered pre- and post-sleep. Topographical spectral power maps and differences between baseline and treatment were compared using t-tests and statistical nonparametric mapping (SnPM).

RESULTS

In 11 compliant CPAP users (5.2 ± 1.1 hours/night), total sleep time did not differ after CPAP but N1 and N2 sleep were lower and N3 was higher. Centro-parietal gamma power during N3 increased and fronto-central slow spindle activity during N2 decreased (SnPM < 0.05). No other significant differences in EEG power were observed. When averaged specifically within the parietal region, N3 delta power increased after CPAP (p = 0.0029) and was correlated with the change in overnight procedural memory consolidation (rho = 0.79, p = 0.03). During resting wakefulness, there were trends for reduced delta and theta power.

CONCLUSIONS

Effective CPAP treatment of OSA may correct regional EEG abnormalities, and regional recovery of SWA may relate to procedural memory improvements in the short term.

Multi-modal analysis of infant cry types characterization: Acoustics, body language and brain signals

BACKGROUND

Infant crying is the first attempt babies use to communicate during their initial months of life. A misunderstanding of the cry message can compromise infant care and future neurodevelopmental process.

METHODS

An exploratory study collecting multimodal data (i.e., crying, electroencephalography (EEG), near-infrared spectroscopy (NIRS), facial expressions, and body movements) from 38 healthy full-term newborns was conducted. Cry types were defined based on different conditions (i.e., hunger, sleepiness, fussiness, need to burp, and distress). Statistical analysis, Machine Learning (ML), and Deep Learning (DL) techniques were used to identify relevant features for cry type classification and to evaluate a robust DL algorithm named Acoustic MultiStage Interpreter (AMSI).

RESULTS

Significant differences were found across cry types based on acoustics, EEG, NIRS, facial expressions, and body movements. Acoustics and body language were identified as the most relevant ML features to support the cause of crying. The DL AMSI algorithm achieved an accuracy rate of 92%.

CONCLUSIONS

This study set a precedent for cry analysis research by highlighting the complexity of newborn cry expression and strengthening the potential use of infant cry analysis as an objective, reliable, accessible, and non-invasive tool for cry interpretation, improving the infant-parent relationship and ensuring family well-being.

Assessing attentional task-related electroencephalogram signal variations by using mobile electroencephalogram technology: An experimental study

BACKGROUND

A better understanding of the network responses of cortical activities during rest and cognitive tasks is necessary. Therefore, in this study, we aimed to evaluate cerebral activities during attentional tasks by using mobile electroencephalography, identifying the types of attentional components and brain waves.

METHODS

In this experimental study, we enrolled 12 healthy young adults. The attentional tasks comprised parts A and B of the Trail-Making Test (TMT). Nineteen electroencephalography electrodes were placed over various brain regions. The Wilcoxon signed-rank test was used to examine the differences in power levels between the rest and TMT conditions.

RESULTS

During TMT part A, the electroencephalography power level of the delta waves was significantly higher in the right frontal, left central, left occipital, left inferior frontal, right mid-temporal, right posterior temporal, and middle parietal areas (P < .05) than those during the resting state; that of the alpha waves was significantly lower in the left posterior temporal area (P = .006); and that of the high gamma waves was significantly lower in the left parietal (P = .05) and left occipital (P = .002) areas. During TMT part B, the electroencephalography power level of the beta waves was significantly higher in the right frontal area (P = .041) than that during the resting state, and that of the low gamma waves was significantly higher in the left frontal pole, right frontal, and right inferior frontal areas (P < .05). During the focused attentional task, the power level of the delta waves increased and that of the alpha waves decreased, and during the alternating attentional task, those of both the beta and gamma waves increased. The delta waves were related to the whole brain, the alpha and high gamma waves to the left posterior lobe, and the beta and low gamma waves to both frontal lobes.

CONCLUSION

These findings contribute to the basic knowledge necessary to develop new attentional assessment methods for clinical situations.

Acute hypoxia elicits prefrontal oxygenation asymmetry in young adults

Significance

Cerebrovascular reactivity can be evaluated by prefrontal cortex (PFC) hemodynamic responses and oxygenation changes secondary to hypoxia using near-infrared spectroscopy (NIRS). However, whether there are hemispheric differences in these NIRS-determined PFC hemodynamic responses and oxygenation changes remains unknown.

Aim

This study was performed to determine whether there are differences in the PFC hemodynamic responses and oxygenation changes secondary to hypoxia between the left and right frontal poles (FPL and FPR, respectively).

Approach

Fifteen young men participated in the study. During conduction of an isocapnic hypoxia protocol with a 10-min hypoxic phase at partial pressure of end-tidal oxygen (PET O 2 ) of 45 Torr, hemodynamic and oxygenation indices comprising oxygenated hemoglobin (oxy-Hb), deoxygenated Hb (deoxy-Hb), total Hb (total-Hb), and tissue oxygen saturation (StO 2 ) over FPL and FPR were measured by NIRS. The heart rate (HR) was evaluated by electrocardiography.

Results

In response to hypoxia, the HR increased, oxy-Hb decreased, deoxy-Hb increased, total-Hb increased above baseline, and StO 2 decreased. There was no difference in the change in total-Hb between FPL and FPR. However, there were greater changes in oxy-Hb, deoxy-Hb, and StO 2 over FPL than over FPR, indicating that PFC oxygenation asymmetry occurs in response to hypoxia. Moreover, the change in total-Hb over FPL was associated with the increase in HR.

Conclusions

NIRS-determined hemodynamic responses and oxygenation changes secondary to hypoxia might not simply reflect the direct effect of hypoxia on cerebral vessels. Although there is no hemispheric difference in the PFC hemodynamic responses to hypoxia as in total-Hb, PFC oxygenation asymmetry occurs in young adults.

Cerebral electrometabolic coupling in disordered and normal states of consciousness

We assess cerebral integrity with cortical and subcortical FDG-PET and cortical electroencephalography (EEG) within the mesocircuit model framework in patients with disorders of consciousness (DoCs). The mesocircuit hypothesis proposes that subcortical activation facilitates cortical function. We find that the metabolic balance of subcortical mesocircuit areas is informative for diagnosis and is associated with four EEG-based power spectral density patterns, cortical metabolism, and α power in healthy controls and patients with a DoC. Last, regional electrometabolic coupling at the cortical level can be identified in the θ and α ranges, showing positive and negative relations with glucose uptake, respectively. This relation is inverted in patients with a DoC, potentially related to altered orchestration of neural activity, and may underlie suboptimal excitability states in patients with a DoC. By understanding the neurobiological basis of the pathophysiology underlying DoCs, we foresee translational value for diagnosis and treatment of patients with a DoC.

How and when EEG reflects changes in neuronal connectivity due to time awake

Being awake means forming new memories, primarily by strengthening neuronal synapses. The increase in synaptic strength results in increasing neuronal synchronicity, which should result in higher amplitude electroencephalography (EEG) oscillations. This is observed for slow waves during sleep but has not been found for wake oscillations. We hypothesized that this was due to a limitation of spectral power analysis, which does not distinguish between changes in amplitudes from changes in number of occurrences of oscillations. By using cycle-by-cycle analysis instead, we found that theta and alpha oscillation amplitudes increase as much as 30% following 24 h of extended wake. These increases were interrupted during the wake maintenance zone (WMZ), a window just before bedtime when it is difficult to fall asleep. We found that pupil diameter increased during this window, suggesting the ascending arousal system is responsible. In conclusion, wake oscillation amplitudes reflect increased synaptic strength, except during the WMZ.

Purkinje cell dysfunction causes disrupted sleep in ataxic mice

Purkinje cell dysfunction causes movement disorders such as ataxia, however, recent evidence suggests that Purkinje cell dysfunction may also alter sleep regulation. Here, we used an ataxia mouse model generated by silencing Purkinje cell neurotransmission ( L7 Cre ;Vgat fx/fx ) to better understand how cerebellar dysfunction impacts sleep physiology. We focused our analysis on sleep architecture and electrocorticography (ECoG) patterns based on their relevance to extracting physiological measurements during sleep. We found that circadian activity is unaltered in the mutant mice, although their sleep parameters and ECoG patterns are modified. The L7 Cre ;Vgat fx/fx mutant mice have decreased wakefulness and rapid eye movement (REM) sleep, while non-rapid eye movement (NREM) sleep is increased. The mutant mice have an extended latency to REM sleep, which is also observed in human ataxia patients. Spectral analysis of ECoG signals revealed alterations in the power distribution across different frequency bands defining sleep. Therefore, Purkinje cell dysfunction may influence wakefulness and equilibrium of distinct sleep stages in ataxia. Our findings posit a connection between cerebellar dysfunction and disrupted sleep and underscore the importance of examining cerebellar circuit function in sleep disorders.

Summary Statement

Utilizing a precise genetic mouse model of ataxia, we provide insights into the cerebellum's role in sleep regulation, highlighting its potential as a therapeutic target for motor disorders-related sleep disruptions.

Reduced Resting-State EEG Power Spectra and Functional Connectivity after 24 and 36 Hours of Sleep Deprivation

Total sleep deprivation (TSD) leads to cognitive decline; however, the neurophysiological mechanisms underlying resting-state electroencephalogram (EEG) changes after TSD remain unclear. In this study, 42 healthy adult participants were subjected to 36 h of sleep deprivation (36 h TSD), and resting-state EEG data were recorded at baseline, after 24 h of sleep deprivation (24 h TSD), and after 36 h TSD. The analysis of resting-state EEG at baseline, after 24 h TSD, and after 36 h TSD using source localization analysis, power spectrum analysis, and functional connectivity analysis revealed a decrease in alpha-band power and a significant increase in delta-band power after TSD and impaired functional connectivity in the default mode network, precuneus, and inferior parietal lobule. The cortical activities of the precuneus, inferior parietal lobule, and superior parietal lobule were significantly reduced, but no difference was found between the 24 h and 36 h TSD groups. This may indicate that TSD caused some damage to the participants, but this damage temporarily slowed during the 24 h to 36 h TSD period.

Genuine beta bursts in human working memory: controlling for the influence of lower-frequency rhythms

Human working memory is associated with significant modulations in oscillatory brain activity. However, the functional role of brain rhythms at different frequencies is still debated. Modulations in the beta frequency range (15-40 Hz) are especially difficult to interpret because they could be artifactually produced by (more prominent) oscillations in lower frequencies that show non-sinusoidal properties. In this study, we investigate beta oscillations during working memory while controlling for the possible influence of lower frequency rhythms. We collected electroencephalography (EEG) data in 31 participants who performed a spatial working-memory task with two levels of cognitive load. In order to rule out the possibility that observed beta activity was affected by non-sinusoidalities of lower frequency rhythms, we developed an algorithm that detects transient beta oscillations that do not coincide with more prominent lower frequency rhythms in time and space. Using this algorithm, we show that the amplitude and duration of beta bursts decrease with memory load and during memory manipulation, while their peak frequency and rate increase. In addition, interindividual differences in performance were significantly associated with beta burst rates. Together, our results show that beta rhythms are functionally modulated during working memory and that these changes cannot be attributed to lower frequency rhythms with non-sinusoidal properties.

The effect of TENS on sleep: A pilot study

BACKGROUND

Insomnia is the second most common neuropsychiatric disorder, but the current treatments are not very effective. There is therefore an urgent need to develop better treatments. Transcutaneous electrical nerve stimulation (TENS) may be a promising means of treating insomnia.

OBJECTIVE

This work aims to explore whether and how TENS modulate sleep and the effect of stimulation waveforms on sleep.

METHODS

Forty-five healthy subjects participated in this study. Electroencephalography (EEG) data were recorded before and after four mode low-frequency (1 Hz) TENS with different waveforms, which were formed by superimposing sine waves of different high frequencies (60-210 Hz) and low frequencies (1-6 Hz). The four waveform modes are formed by combining sine waves of varying frequencies. Mode 1 (M1) consists of a combination of high frequencies (60-110 Hz) and low frequencies (1-6 Hz). Mode 2 (M2) is made up of high frequencies (60-210 Hz) and low frequencies (1-6 Hz). Mode 3 (M3) consists of high frequencies (110-160 Hz) and low frequencies (1-6 Hz), while mode 4 (M4) is composed of high frequencies (160-210 Hz) and low frequencies (1-6 Hz). For M1, M3 and M4, the high frequency portions of the stimulus waveforms account for 50%, while for M2, the high frequency portion of the waveform accounts for 65%. For each mode, the current intensities ranged from 4 mA to 7 mA, with values for each participant adjusted according to individual tolerance. During stimulation, the subjects were stimulated at the greater occipital nerve by the four mode TENS.

RESULTS

M1, M3, and M4 slowed down the frequency of neural activity, broadened the distribution of theta waves, and caused a decrease in activity in wakefulness-related regions and an increase in activity in sleep-related regions. However, M2 has the opposite modulation effect.

CONCLUSION

These results indicated that low-frequency TENS (1 Hz) may facilitate sleep in a waveform-specific manner. Our findings provide new insights into the mechanisms of sleep modulation by TENS and the design of effective insomnia treatments.

What is autonomous sensory meridian response (ASMR)? A narrative review and comparative analysis of related phenomena

A narrative review of autonomous sensory meridian response (ASMR) was carried out. Definitional factors relevant to ASMR were canvassed. Related, but distinctly unique, sensorial phenomena, including frisson, synaesthesia, and misophonia were considered. Finally, the status of literature with respect to clinical outcomes, individual differences, and current research applications was evaluated. ASMR is a nascent phenomenon that has rapidly progressed in scope and depth of study throughout the past decade; a notable shift from brief-form studies to an increase in formalised trials is noted. Yet, critical questions remain unaddressed, including expectancy and placebo effects, that future research should interrogate.

Novel Objective Measures of Hypersomnolence

Purpose of review

To provide a brief overview of current objective measures of hypersomnolence, discuss proposed measure modifications, and review emerging measures.

Recent findings

There is potential to optimize current tools using novel metrics. High-density and quantitative EEG-based measures may provide discriminative informative. Cognitive testing may quantify cognitive dysfunction common to hypersomnia disorders, particularly in attention, and objectively measure pathologic sleep inertia. Structural and functional neuroimaging studies in narcolepsy type 1 have shown considerable variability but so far implicate both hypothalamic and extra-hypothalamic regions; fewer studies of other CDH have been performed. There is recent renewed interest in pupillometry as a measure of alertness in the evaluation of hypersomnolence.

Summary

No single test captures the full spectrum of disorders and use of multiple measures will likely improve diagnostic precision. Research is needed to identify novel measures and disease-specific biomarkers, and to define combinations of measures optimal for CDH diagnosis.

Links between excessive daytime sleepiness and EEG power and activation in two subtypes of ADHD

OBJECTIVES

This study aimed to replicate previously reported EEG characteristics between typically developing (TD) children and two subtypes of Attention Deficit Hyperactivity Disorder (ADHD) using a frontal, single-channel, dry-sensor portable EEG device, and explore whether differences are moderated by excessive daytime sleepiness (EDS).

METHODS

Children with ADHD Inattentive (ADHD-I) and ADHD Combined presentation (ADHD-C) and typically-developing (TD) children (N = 34 in each group) had frontal EEG recorded during eyes-closed resting, eyes-open resting, and focus tasks. Participants also completed the Children's Self-Report Sleep Patterns - Sleepiness Scale as a measure of EDS.

RESULTS

Consistent with previous literature, there were increases in frontal delta and theta power in the ADHD-C compared to ADHD-I and TD groups, in all conditions. Novel power and activation effects in ADHD subtypes, as well as significant group and EDS interactions for alpha and beta power were also found.

CONCLUSIONS

These findings highlight the importance of considering ADHD subtypes and EDS when exploring EEG characteristics, and have important implications for the diagnosis and treatment of children with ADHD.

The neurophysiology of intraoperative error: An EEG study of trainee surgeons during robotic-assisted surgery simulations

Surgeons operate in mentally and physically demanding workspaces where the impact of error is highly consequential. Accurately characterizing the neurophysiology of surgeons during intraoperative error will help guide more accurate performance assessment and precision training for surgeons and other teleoperators. To better understand the neurophysiology of intraoperative error, we build and deploy a system for intraoperative error detection and electroencephalography (EEG) signal synchronization during robot-assisted surgery (RAS). We then examine the association between EEG data and detected errors. Our results suggest that there are significant EEG changes during intraoperative error that are detectable irrespective of surgical experience level.

Neurofeedback Treatment Affects Affective Symptoms, But Not Perceived Cognitive Impairment in Cancer Patients: Results of an Explorative Randomized Controlled Trial

BACKGROUND

EEG biofeedback (NF) is an established therapy to enable individuals to influence their own cognitive-emotional state by addressing changes in brainwaves. Psycho-oncological approaches of NF in cancer patients are rare and effects are hardly studied.

OBJECTIVE

The aim of this explorative, randomized controlled trial was to test the effectiveness of an alpha and theta NF training protocol, compared to mindfulness based therapy as an established psycho-oncological treatment.

METHODS

Of initially 62 screened patients, 56 were included (inclusion criteria were cancer independent of tumor stage, age >18 years, German speaking; exclusion criteria suicidal ideation, brain tumor). Randomization and stratification (tumor stage) was conducted by a computer system. Participants got 10 sessions over 5 weeks, in (a) an NF intervention (n = 21; 13 female, 8 male; MAge = 52.95(10 519); range = 31 to 73 years)) or (b) a mindfulness group therapy as control condition (CG; n = 21; ie, 15 female, 6 male; MAge = 50.33(8708); range = 32 to 67 years)). Outcome parameters included self-reported cognitive impairment (PCI) as primary outcome, and secondary outcomes of emotional distress (DT, PHQ-8, GAD-7), fatigue (MFI-20), rumination (RSQ), quality of life (QoL, EORTC-30 QoL), self-efficacy (GSE), and changes in EEG alpha, and theta-beta band performance in the NF condition.

RESULTS

No changes in cognitive impairment were found (P = .079), neither in NF nor CG. High affective distress was evident, with 70.7% showing elevated distress and 34.1% showing severe depressive symptoms. Affective symptoms of distress (P ≤ .01), depression (P ≤ .05) and generalized anxiety (P ≤ .05) decreased significantly over time. No differences between NF and CG were found. There was a significant increase of the alpha band (P ≤ .05; N = 15) over the NF sessions. Self-efficacy predicted QoL increase in NF with P ≤ .001 and an explained variance of 48.2%.

CONCLUSION

This is the first study to investigate NF technique with regard to basic mechanisms of effectiveness in a sample of cancer patients, compared to an established psycho-oncological intervention in this field. Though there were no changes in cognitive impairment, present data show that NF improves affective symptoms comparably to mindfulness-based therapy and even more pronounced in QoL and self-efficacy.Trial registration: ID: DRKS00015773.

Sleep Deprivation-Induced Changes in Baseline Brain Activity and Vigilant Attention Performance

Sleep deprivation (SD) negatively affects several aspects of cognitive performance, and one of the most widely-used tools to evaluate these effects is the Psychomotor Vigilance Test (PVT). The present study investigated the possibility of predicting changes induced by SD in vigilant attention performance by evaluating the baseline electroencephalographic (EEG) activity immediately preceding the PVT stimuli onset. All participants (n = 10) underwent EEG recordings during 10 min of PVT before and after a night of SD. For each participant, the root mean square (RMS) of the baseline EEG signal was evaluated for each 1 s time window, and the respective average value was computed. After SD, participants showed slower (and less accurate) performance in the PVT task. Moreover, a close relationship between the changes in the baseline activity with those in cognitive performance was identified at several electrodes (Fp2, F7, F8, P3, T6, O1, Oz, O2), with the highest predictive power at the occipital derivations. These results indicate that vigilant attention impairments induced by SD can be predicted by the pre-stimulus baseline activity changes.

Cancer Patients’ Age-Related Benefits from Mobile Neurofeedback-Therapy in Quality of Life and Self-efficacy: A Clinical Waitlist Control Study

Electroencephalographic neurofeedback (EEG NF) can improve quality of life (QoL) and reduce distress by modifying the amplitude of selected brain frequencies. This study aims to investigate the effects of NF therapy on QoL and self-efficacy in cancer patients and to explore age-related reactions. In a waitlist control paradigm, psychometric data (EORTC QLQ-C30, General Self-Efficacy Scale) of 20 patients were collected at three different time points, each five weeks apart. An outpatient 10-session NF intervention (mobile) was conducted between the second and third measurement point. QoL and self-efficacy changed significantly over time (QoL: F(2,36) = 5.294, p < .05, η2 = .227; Self-efficacy: F(2,26) = 8.178, p < .05, η2 = .386). While QoL increased in younger patients, older patients initially showed a decrease in QoL, which then increased during intervention. Younger patients did not differ from older patients in QoL in both waitlist control (T0-T1) and intervention phase (T1–T2). QoL in older patients significantly differed between waitlist control and intervention phase (Z = − 2.023, p < .05, d = 1.085). Self-efficacy increased in both age categories. Younger and older patients did not differ in self-efficacy in waitlist control, but in intervention phase (F(1,16) = 7.014, p < .05, η2 = .319). The current findings suggest that NF therapy is a promising treatment modality for improving QoL in cancer patients. Our study reveals NF being a tool to influence self-efficacy, which should receive more appreciation in clinical care. However, the effect of NF in different age groups as well as the influence on further cancer-related symptoms should be investigated in future research.

Alteration of Resting Electroencephalography by Acute Caffeine Consumption in Early Phase Psychosis

Individuals with schizophrenia use twice as much caffeine on average when compared to healthy controls. Knowing the high rates of consumption, and the potential negative effects of such, it is important we understand the cortical mechanisms that underlie caffeine use, and the consequences of caffeine use on neural circuits in this population. Using a randomized, placebo controlled, double-blind, repeated measures design, the current study examines caffeine's effects on resting electroencephalography (EEG) power in those who have been recently diagnosed with schizophrenia (SZ) compared to regular-using healthy controls (HC). Correlations between average caffeine consumption, withdrawal symptoms, drug related symptoms and clinical psychosis symptoms were measured and significant correlations with neurophysiological data were examined. Results showed caffeine had no effect on alpha asymmetry in the SZ group, although caffeine produced a more global effect on the reduction of alpha₂ power in the SZ group. Further, those with more positive symptoms were found to have a greater reduction in alpha₂ power following caffeine administration. Caffeine also reduced beta power during eyes closed and eyes open resting in HC, but only during eyes closed resting conditions in the SZ group. These findings provide a descriptive profile of the resting EEG state following caffeine administration in individuals with schizophrenia. The findings ultimately suggest caffeine does not affect alpha or beta power as readily in this population and a higher dose may be needed to achieve the desired effects, which may elucidate motivational factors for high caffeine use.

Electroencephalography Theta/Beta Ratio Decreases in Patients with Severe Obstructive Sleep Apnea

Purpose

Accumulating evidence suggests that theta/beta ratio (TBR), an electroencephalographic (EEG) frequency band parameter, might serve as an objective marker of executive cognitive control in healthy adults. Obstructive sleep apnea (OSA) has a detrimental impact on patients' behavior and cognitive performance while whether TBR is different in OSA population has not been reported. This study aimed to explore the difference in relative EEG spectral power and TBR during sleep between patients with severe OSA and non-OSA groups.

Patients and Methods

142 participants with in-laboratory nocturnal PSG recording were included, among which 100 participants suffered severe OSA (apnea hypopnea index, AHI > 30 events/hour; OSA group) and 42 participants had no OSA (AHI ≤ 5 events/h; control group). The fast Fourier transformation was used to compute the EEG power spectrum for total sleep duration within contiguous 30-second epochs of sleep. The demographic and polysomnographic characteristics, relative EEG spectral power and TBR of the two groups were compared.

Results

It was found that the beta band power during NREM sleep and total sleep was significantly higher in the OSA group than controls (p < 0.001, p = 0.012, respectively), and the theta band power during NREM sleep and total sleep was significantly lower in the OSA group than controls (p = 0.019, p = 0.014, respectively). TBR during NREM sleep, REM sleep and total sleep was significantly lower in the OSA group compared to the control group (p < 0.001 for NREM sleep and total sleep, p = 0.015 for REM sleep). TBR was negatively correlated with AHI during NREM sleep (r=-0.324, p < 0.001) and total sleep (r=-0. 312, p < 0.001).

Conclusion

TBR was significantly decreased in severe OSA patients compared to the controls, which was attributed to both increased beta power and decreased theta power. TBR may be a stable EEG-biomarker of OSA patients, which may accurately and reliably identify phenotype of patients.

Data-Driven EEG Theta and Alpha Components Are Associated with Subjective Experience during Resting State

The resting-state paradigm is frequently applied to study spontaneous activity of the brain in normal and clinical conditions. However, the relationship between the ongoing experience of mind wandering and the individual biological signal is still unclear. We aim to estimate associations between subjective experiences measured with the Amsterdam Resting-State Questionnaire and data-driven components of an electroencephalogram extracted by frequency principal component analysis (f-PCA). Five minutes of resting multichannel EEG was recorded in 226 participants and six EEG data-driven components were extracted-three components in the alpha range (peaking at 9, 10.5, and 11.5 Hz) and one each in the delta (peaking at 0.5 Hz), theta (peaking at 5.5 Hz) and beta (peaking at 17 Hz) ranges. Bayesian Pearson's correlation revealed a positive association between the individual loadings of the theta component and ratings for Sleepiness (r = 0.200, BF10 = 7.676), while the individual loadings on one of the alpha components correlated positively with scores for Comfort (r = 0.198, BF10 = 7.115). Our study indicates the relevance of assessments of spontaneous thought occurring during the resting-state for the understanding of the individual intrinsic electrical brain activity.