The electroencephalographic substratum of the awakening

From physiological awakening to pathological sleep inertia: Neurophysiological and behavioural characteristics of the sleep-to-wake transition

Sleep inertia refers to the transient physiological state of hypoarousal upon awakening, associated with various degrees of impaired neurobehavioral performance, confusion, a desire to return to sleep and often a negative emotional state. Scalp and intracranial electro-encephalography as well as functional imaging studies have provided evidence that the sleep inertia phenomenon is underpinned by an heterogenous cerebral state mixing local sleep and local wake patterns of activity, at the neuronal and network levels. Sleep inertia is modulated by homeostasis and circadian processes, sleep stage upon awakening, and individual factors; this translates into a huge variability in its intensity even under physiological conditions. In sleep disorders, especially in hypersomnolence disorders such as idiopathic hypersomnia, sleep inertia may be a daily, serious and long-lasting symptom leading to severe impairment. To date, few tools have been developed to assess sleep inertia in clinical practice. They include mainly questionnaires and behavioral tests such as the psychomotor vigilance task. Only one neurophysiological protocol has been evaluated in hypersomnia, the forced awakening test which is based on an event-related potentials paradigm upon awakening. This contrasts with the major functional consequences of sleep inertia and its potentially dangerous consequences in subjects required to perform safety-critical tasks soon after awakening. There is a great need to identify reproducible biomarkers correlated with sleep inertia-associated cognitive and behavioral impairment. These biomarkers will aim at better understanding and measuring sleep inertia in physiological and pathological conditions, as well as objectively evaluating wake-promoting treatments or non-pharmacological countermeasures to reduce this phenomenon.

Traces of EEG-fMRI coupling reveals neurovascular dynamics on sleep inertia

Upon emergence from sleep, individuals experience temporary hypo-vigilance and grogginess known as sleep inertia. During the transient period of vigilance recovery from prior nocturnal sleep, the neurovascular coupling (NVC) may not be static and constant as assumed by previous neuroimaging studies. Stemming from this viewpoint of sleep inertia, this study aims to probe the NVC changes as awakening time prolongs using simultaneous EEG-fMRI. The time-lagged coupling between EEG features of vigilance and BOLD-fMRI signals, in selected regions of interest, was calculated with one pre-sleep and three consecutive post-awakening resting-state measures. We found marginal changes in EEG theta/beta ratio and spectral slope across post-awakening sessions, demonstrating alterations of vigilance during sleep inertia. Time-varying EEG-fMRI coupling as awakening prolonged was evidenced by the changing time lags of the peak correlation between EEG alpha-vigilance and fMRI-thalamus, as well as EEG spectral slope and fMRI-anterior cingulate cortex. This study provides the first evidence of potential dynamicity of NVC occurred in sleep inertia and opens new avenues for non-invasive neuroimaging investigations into the neurophysiological mechanisms underlying brain state transitions.

Regional variability in intracerebral properties of NREM to REM sleep transitions in humans

Transitions between wake and sleep states show a progressive pattern underpinned by local sleep regulation. In contrast, little evidence is available on non-rapid eye movement (NREM) to rapid eye movement (REM) sleep boundaries, considered as mainly reflecting subcortical regulation. Using polysomnography (PSG) combined with stereoelectroencephalography (SEEG) in humans undergoing epilepsy presurgical evaluation, we explored the dynamics of NREM-to-REM transitions. PSG was used to visually score transitions and identify REM sleep features. SEEG-based local transitions were determined automatically with a machine learning algorithm using features validated for automatic intra-cranial sleep scoring (10.5281/zenodo.7410501). We analyzed 2988 channel-transitions from 29 patients. The average transition time from all intracerebral channels to the first visually marked REM sleep epoch was 8 s ± 1 min 58 s, with a great heterogeneity between brain areas. Transitions were observed first in the lateral occipital cortex, preceding scalp transition by 1 min 57 s ± 2 min 14 s (d = -0.83), and close to the first sawtooth wave marker. Regions with late transitions were the inferior frontal and orbital gyri (1 min 1 s ± 2 min 1 s, d = 0.43, and 1 min 1 s ± 2 min 5 s, d = 0.43, after scalp transition). Intracranial transitions were earlier than scalp transitions as the night advanced (last sleep cycle, d = -0.81). We show a reproducible gradual pattern of REM sleep initiation, suggesting the involvement of cortical mechanisms of regulation. This provides clues for understanding oneiric experiences occurring at the NREM/REM boundary.

Face validation and pharmacologic analysis of Sik3Sleepy mutant mouse as a possible model of idiopathic hypersomnia

Idiopathic hypersomnia (IH) is a chronic neurologic disorder with unknown mechanisms that result in long night-time sleep, daytime sleepiness, long non-refreshing naps, and difficult awakening presenting as sleep drunkenness. IH patients are typically diagnosed by shorter sleep latency on multiple sleep latency test (MSLT) along with long sleep time. Only symptomatic drug treatments are currently available for IH and no animal model to study it. Sleepy mice carry a splicing mutation in the Sik3 gene, leading to increased sleep time and sleep need. Here we used a mouse version of MSLT and a decay analysis of wake EEG delta power to validate the Sleepy mutant mouse as an animal model for IH. Sleepy mice had shorter sleep latency in the dark (active) phase than wild-type mice. They also showed lower decay of EEG delta density during wakefulness, possibly reflecting increased sleep inertia. These data indicate that the Sleepy mouse may have partial face validity as a mouse model for idiopathic hypersomnia. We then investigated the effect of orexin-A and the orexin receptor 2-selective agonist YNT-185 on the sleepiness symptoms of the Sleepy mouse. Intracerebroventricular orexin-A promoted wakefulness for 3 h and decreased wake EEG delta density after injection in Sleepy mice and wild-type mice. Moreover, Sleepy mice but not wild-type mice showed a sleep rebound after the orexin-A-induced wakefulness. Intraperitoneal YNT-185 promoted wakefulness for 3 h after injection in Sleepy mice, indicating the potential of using orexin agonists to treat not only orexin deficiency but hypersomnolence of various etiologies.

Temporal consistency of neurovascular components on awakening: preliminary evidence from electroencephalography, cerebrovascular reactivity, and functional magnetic resonance imaging

Sleep inertia (SI) is a time period during the transition from sleep to wakefulness wherein individuals perceive low vigilance with cognitive impairments; SI is generally identified by longer reaction times (RTs) in attention tasks immediately after awakening followed by a gradual RT reduction along with waking time. The sluggish recovery of vigilance in SI involves a dynamic process of brain functions, as evidenced in recent functional magnetic resonance imaging (fMRI) studies in within-network and between-network connectivity. However, these fMRI findings were generally based on the presumption of unchanged neurovascular coupling (NVC) before and after sleep, which remains an uncertain factor to be investigated. Therefore, we recruited 12 young participants to perform a psychomotor vigilance task (PVT) and a breath-hold task of cerebrovascular reactivity (CVR) before sleep and thrice after awakening (A1, A2, and A3, with 20 min intervals in between) using simultaneous electroencephalography (EEG)-fMRI recordings. If the NVC were to hold in SI, we hypothesized that time-varying consistencies could be found between the fMRI response and EEG beta power, but not in neuron-irrelevant CVR. Results showed that the reduced accuracy and increased RT in the PVT upon awakening was consistent with the temporal patterns of the PVT-induced fMRI responses (thalamus, insula, and primary motor cortex) and the EEG beta power (Pz and CP1). The neuron-irrelevant CVR did not show the same time-varying pattern among the brain regions associated with PVT. Our findings imply that the temporal dynamics of fMRI indices upon awakening are dominated by neural activities. This is the first study to explore the temporal consistencies of neurovascular components on awakening, and the discovery provides a neurophysiological basis for further neuroimaging studies regarding SI.

Reconfigurations in brain networks upon awakening from slow wave sleep: Interventions and implications in neural communication

Sleep inertia is the brief period of impaired alertness and performance experienced immediately after waking. Little is known about the neural mechanisms underlying this phenomenon. A better understanding of the neural processes during sleep inertia may offer insight into the awakening process. We observed brain activity every 15 min for 1 hr following abrupt awakening from slow wave sleep during the biological night. Using 32-channel electroencephalography, a network science approach, and a within-subject design, we evaluated power, clustering coefficient, and path length across frequency bands under both a control and a polychromatic short-wavelength-enriched light intervention condition. We found that under control conditions, the awakening brain is typified by an immediate reduction in global theta, alpha, and beta power. Simultaneously, we observed a decrease in the clustering coefficient and an increase in path length within the delta band. Exposure to light immediately after awakening ameliorated changes in clustering. Our results suggest that long-range network communication within the brain is crucial to the awakening process and that the brain may prioritize these long-range connections during this transitional state. Our study highlights a novel neurophysiological signature of the awakening brain and provides a potential mechanism by which light improves performance after waking.

The impact of a short burst of exercise on sleep inertia

STUDY OBJECTIVES

Determine whether 30 s (s) of exercise performed upon waking can reduce sleep inertia and accelerate an increase in the cortisol awakening response (CAR) and core body temperature (CBT), compared to when sedentary.

METHODS

Fifteen participants (mean age ± SD, 25.9 ± 5.9 years; six females) completed a counterbalanced, repeated measures, in-laboratory study involving three single experimental nights, each separated by a four-night recovery period. Participants were woken following a 2-h nap (2400-0200) and completed a cycling bout of high-intensity (30-s sprint), low-intensity (30 s at 60% maximum heart rate), or no exercise (sedentary). Sleep inertia testing (eight batteries, 15-min intervals) began immediately following and included measures of subjective sleepiness (Karolinska Sleepiness Scale) and cognitive performance tasks (psychomotor vigilance, serial addition and subtraction, and spatial configuration). CBT was measured continuously via an ingestible telemetric capsule. The CAR was determined using salivary cortisol samples collected at 0, 30 and 45 min post-waking. Data were analysed using mixed effects analysis of variance.

RESULTS

There was no difference in cognitive performance or CBT between conditions. Participants felt less sleepy in the high-intensity condition, followed by the low-intensity and sedentary conditions (p = .003). The CAR was greatest in the high-intensity condition, followed by the sedentary condition, and low-intensity condition (p < 0.001), with no differences between the low-intensity and sedentary conditions.

CONCLUSIONS

Those who exercise upon waking should be aware that while they may feel more alert, they may not be performing better than if they had not exercised. Future research should investigate whether exercise of different duration or timing may impact sleep inertia.

The Inert Brain: Explaining Neural Inertia as Post-anaesthetic Sleep Inertia

"Neural inertia" is the brain's tendency to resist changes in its arousal state: it is manifested as emergence from anaesthesia occurring at lower drug doses than those required for anaesthetic induction, a phenomenon observed across very different species, from invertebrates to mammals. However, the brain is also subject to another form of inertia, familiar to most people: sleep inertia, the feeling of grogginess, confusion and impaired performance that typically follows awakening. Here, we propose a novel account of neural inertia, as the result of sleep inertia taking place after the artificial sleep induced by anaesthetics. We argue that the orexinergic and noradrenergic systems may be key mechanisms for the control of these transition states, with the orexinergic system exerting a stabilising effect through the noradrenergic system. This effect may be reflected at the macroscale in terms of altered functional anticorrelations between default mode and executive control networks of the human brain. The hypothesised link between neural inertia and sleep inertia could explain why different anaesthetic drugs induce different levels of neural inertia, and why elderly individuals and narcoleptic patients are more susceptible to neural inertia. This novel hypothesis also enables us to generate several empirically testable predictions at both the behavioural and neural levels, with potential implications for clinical practice.

The Inert Brain: Explaining Neural Inertia as Post-anaesthetic Sleep Inertia

"Neural inertia" is the brain's tendency to resist changes in its arousal state: it is manifested as emergence from anaesthesia occurring at lower drug doses than those required for anaesthetic induction, a phenomenon observed across very different species, from invertebrates to mammals. However, the brain is also subject to another form of inertia, familiar to most people: sleep inertia, the feeling of grogginess, confusion and impaired performance that typically follows awakening. Here, we propose a novel account of neural inertia, as the result of sleep inertia taking place after the artificial sleep induced by anaesthetics. We argue that the orexinergic and noradrenergic systems may be key mechanisms for the control of these transition states, with the orexinergic system exerting a stabilising effect through the noradrenergic system. This effect may be reflected at the macroscale in terms of altered functional anticorrelations between default mode and executive control networks of the human brain. The hypothesised link between neural inertia and sleep inertia could explain why different anaesthetic drugs induce different levels of neural inertia, and why elderly individuals and narcoleptic patients are more susceptible to neural inertia. This novel hypothesis also enables us to generate several empirically testable predictions at both the behavioural and neural levels, with potential implications for clinical practice.

Post-ictal Generalized EEG Suppression is reduced by Enhancing Dorsal Raphe Serotonergic Neurotransmission

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death in patients with refractory epilepsy. A proposed risk marker for SUDEP is the duration of post-ictal generalized EEG suppression (PGES). The mechanisms underlying PGES are unknown. Serotonin (5-HT) has been implicated in SUDEP pathophysiology. Seizures suppress activity of 5-HT neurons in the dorsal raphe nucleus (DRN). We hypothesized that suppression of DRN 5-HT neuron activity contributes to PGES and increasing 5-HT neurotransmission or stimulating the DRN before a seizure would decrease PGES duration. Adult C57BL/6J and Pet1-Cre mice received EEG/EMG electrodes, a bipolar stimulating/recording electrode in the right basolateral amygdala, and either a microdialysis guide cannula or an injection of adeno-associated virus (AAV) allowing expression of channelrhodopsin2 plus an optic fiber into the DRN. Systemic application of the selective 5-HT reuptake inhibitor citalopram (20 mg/kg) decreased PGES duration from seizures induced during wake (n = 23) and non-rapid eye movement (NREM) sleep (n = 13) whereas fluoxetine (10 mg/kg) pretreatment decreased PGES duration following seizures induced from wake (n = 11), but not NREM sleep (n = 9). Focal chemical (n = 6) or optogenetic (n = 8) stimulation of the DRN reduced PGES duration following seizures in kindled mice induced during wake. During PGES, animals exhibited immobility and suppression of EEG activity that was reduced by citalopram pretreatment. These results suggest 5-HT and the DRN may regulate PGES.

Loss of frontal regulator of vigilance during sleep inertia: A simultaneous EEG-fMRI study

Sleep inertia refers to a distinct physiological state of waking up from sleep accompanied by performance impairments and sleepiness. The neural substrates of sleep inertia are unknown, but growing evidence suggests that this inertia state maintains certain sleep features. To investigate the neurophysiological mechanisms of sleep inertia, a comparison of pre-sleep and post-sleep wakefulness with eyes-open resting-state was performed using simultaneous EEG-fMRI, which has the potential to reveal the dynamic details of neuroelectric and hemodynamic responses with high temporal resolution. Our data suggested sleep-like features of slow EEG power and decreased BOLD activity were persistent during sleep inertia. In the pre-sleep phase, participants with stronger EEG vigilance showed stronger activity in the fronto-parietal network (FPN), but this phenomenon disappeared during sleep inertia. A time course analysis confirmed a decreased correlation between EEG vigilance and the FPN activity during sleep inertia. This simultaneous EEG-fMRI study advanced our understanding of sleep inertia and revealed the importance of the FPN in maintaining awareness. This is the first study to reveal the dynamic brain network changes from multi-modalities perspective during sleep inertia.

Sleep Inertia Countermeasures in Automated Driving: A Concept of Cognitive Stimulation

When highly automated driving is realized, the role of the driver will change dramatically. Drivers will even be able to sleep during the drive. However, when awaking from sleep, drivers often experience sleep inertia, meaning they are feeling groggy and are impaired in their driving performance―which can be an issue with the concept of dual-mode vehicles that allow both manual and automated driving. Proactive methods to avoid sleep inertia like the widely applied ‘NASA nap’ are not immediately practicable in automated driving. Therefore, a reactive countermeasure, the sleep inertia counter-procedure for drivers (SICD), has been developed with the aim to activate and motivate the driver as well as to measure the driver’s alertness level. The SICD is evaluated in a study with N = 21 drivers in a level highly automation driving simulator. The SICD was able to activate the driver after sleep and was perceived as “assisting” by the drivers. It was not capable of measuring the driver’s alertness level. The interpretation of the findings is limited due to a lack of a comparative baseline condition. Future research is needed on direct comparisons of different countermeasures to sleep inertia that are effective and accepted by drivers.

Dream Recall upon Awakening from Non-Rapid Eye Movement Sleep in Older Adults: Electrophysiological Pattern and Qualitative Features

Several findings support the activation hypothesis, positing that cortical arousal promotes dream recall (DR). However, most studies have been carried out on young participants, while the electrophysiological (EEG) correlates of DR in older people are still mostly unknown. We aimed to test the activation hypothesis on 20 elders, focusing on the Non-Rapid Eye Movement (NREM) sleep stage. All the subjects underwent polysomnography, and a dream report was collected upon their awakening from NREM sleep. Nine subjects were recallers (RECs) and 11 were non-RECs (NRECs). The delta and beta EEG activity of the last 5 min and the total NREM sleep was calculated by Fast Fourier Transform. Statistical comparisons (RECs vs. NRECs) revealed no differences in the last 5 min of sleep. Significant differences were found in the total NREM sleep: the RECs showed lower delta power over the parietal areas than the NRECs. Consistently, statistical comparisons on the activation index (delta/beta power) revealed that RECs showed a higher level of arousal in the fronto-temporal and parieto-occipital regions than NRECs. Both visual vividness and dream length are positively related to the level of activation. Overall, our results are consistent with the view that dreaming and the storage of oneiric contents depend on the level of arousal during sleep, highlighting a crucial role of the temporo-parietal-occipital zone.

Later School Start Time: The Impact of Sleep on Academic Performance and Health in the Adolescent Population

The crucial role of sleep in physical and mental health is well known, especially during the developmental period. In recent years, there has been a growing interest in examining the relationship between sleep patterns and school performance in adolescents. At this stage of life, several environmental and biological factors may affect both circadian and homeostatic regulation of sleep. A large part of this population does not experience adequate sleep, leading to chronic sleep restriction and/or disrupted sleep–wake cycles. Studies investigating the effects of different sleep–wake schedules on academic achievement showed that impaired sleep quality and quantity are associated with decreased learning ability and compromised daytime functioning. This review focuses on the most recent studies that evaluated the effects of modified school start time on sleep patterns and related outcomes. Moreover, based on the available empirical evidence, we intend to propose a direction for future studies targeted to implement prevention or treatment programs by modifying sleep timing.

Exercising Caution Upon Waking-Can Exercise Reduce Sleep Inertia?

Sleep inertia, the transitional state of reduced alertness and impaired cognitive performance upon waking, is a safety risk for on-call personnel who can be required to perform critical tasks soon after waking. Sleep inertia countermeasures have previously been investigated; however, none have successfully dissipated sleep inertia within the first 15 min following waking. During this time, on-call personnel could already be driving, providing advice, or performing other safety-critical tasks. Exercise has not yet been investigated as a sleep inertia countermeasure but has the potential to stimulate the key physiological mechanisms that occur upon waking, including changes in cerebral blood flow, the cortisol awakening response, and increases in core body temperature. Here, we examine these physiological processes and hypothesize how exercise can stimulate them, positioning exercise as an effective sleep inertia countermeasure. We then propose key considerations for research investigating the efficacy of exercise as a sleep inertia countermeasure, including the need to determine the intensity and duration of exercise required to reduce sleep inertia, as well as testing the effectiveness of exercise across a range of conditions in which the severity of sleep inertia may vary. Finally, practical considerations are identified, including the recommendation that qualitative field-based research be conducted with on-call personnel to determine the potential constraints in utilizing exercise as a sleep inertia countermeasure in real-world scenarios.

Alarm tones, music and their elements: Analysis of reported waking sounds to counteract sleep inertia

Sleep inertia is a potentially dangerous reduction in human alertness and occurs 0-4 hours after waking. The type of sound people set as their alarm for waking has been shown to reduce the effects of sleep inertia, however, the elemental musical factors that underpin these waking sounds and their relationships remain unclear. The goal of this research is to understand how a particular sound or music chosen to assist waking may counteract sleep inertia, and more specifically, what elements of these sounds may contribute to its reduction. Through an anonymous, self-report online questionnaire, fifty participants (N = 50) reported attributes of their preferred waking sound, their feeling towards the waking sound, and perceived sleep inertia after waking. This data enabled the analysis and comparison between these responses to identify statistically significant relationships. Our results did not return any significant association between sleep inertia and the reported waking sound type, nor the subject's feeling towards their sound. However, the analysis did reveal that a sound which is ranked as melodic by participants shows a significant relationship to reports of reductions in perceived sleep inertia, and in contrast, sound rated as neutral (neither unmelodic nor melodic) returns a significant relationship to the reports of increases in perceived sleep inertia. Additionally, our secondary analysis revealed that a sound rated as melodic is considered to be more rhythmic than a melodically neutral interpretation. Together these findings raise questions regarding the impact melody and rhythm may hold with respect to sleep inertia intensity. Considering that the implementation of auditory assisted awakening is a common occurrence, the musical elements of a chosen waking sound may be an area to further interrogate with respect to counteracting sleep inertia.

Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep

The modern understanding of sleep is based on the classification of sleep into stages defined by their electroencephalography (EEG) signatures, but the underlying brain dynamics remain unclear. Here we aimed to move significantly beyond the current state-of-the-art description of sleep, and in particular to characterise the spatiotemporal complexity of whole-brain networks and state transitions during sleep. In order to obtain the most unbiased estimate of how whole-brain network states evolve through the human sleep cycle, we used a Markovian data-driven analysis of continuous neuroimaging data from 57 healthy participants falling asleep during simultaneous functional magnetic resonance imaging (fMRI) and EEG. This Hidden Markov Model (HMM) facilitated discovery of the dynamic choreography between different whole-brain networks across the wake-non-REM sleep cycle. Notably, our results reveal key trajectories to switch within and between EEG-based sleep stages, while highlighting the heterogeneities of stage N1 sleep and wakefulness before and after sleep.

Sleep is composed of a number of different stages, each associated with a different pattern of brain activity. Here, using a data-driven Hidden Markov Model (HMM) of fMRI data, the authors discover a more complex set of neural activity states underlying the conventional stages of non-REM sleep.

Sleep inertia: current insights

Sleep inertia, or the grogginess felt upon awakening, is associated with significant cognitive performance decrements that dissipate as time awake increases. This impairment in cognitive performance has been observed in both tightly controlled in-laboratory studies and in real-world scenarios. Further, these decrements in performance are exaggerated by prior sleep loss and the time of day in which a person awakens. This review will examine current insights into the causes of sleep inertia, factors that may positively or negatively influence the degree of sleep inertia, the consequences of sleep inertia both in the laboratory and in real-world settings, and lastly discuss potential countermeasures to lessen the impact of sleep inertia.

Waking up is the hardest thing I do all day: Sleep inertia and sleep drunkenness

The transition from sleep to wake is marked by sleep inertia, a distinct state that is measurably different from wakefulness and manifests as performance impairments and sleepiness. Although the precise substrate of sleep inertia is unknown, electroencephalographic, evoked potential, and neuroimaging studies suggest the persistence of some features of sleep beyond the point of awakening. Forced desynchrony studies have demonstrated that sleep inertia impacts cognition differently than do homeostatic and circadian drives and that sleep inertia is most intense during awakenings from the biological night. Recovery sleep after sleep deprivation also amplifies sleep inertia, although the effects of deep sleep vary based on task and timing. In patients with hypersomnolence disorders, especially but not exclusively idiopathic hypersomnia, a more pronounced period of confusion and sleepiness upon awakening, known as "sleep drunkenness", is common and problematic. Optimal treatment of sleep drunkenness is unknown, although several medications have been used with benefit in small case series. Difficulty with awakening is also commonly endorsed by individuals with mood disorders, disproportionately to the general population. This may represent an important treatment target, but evidence-based treatment guidance is not yet available.

Local aspects of sleep and wakefulness

Slow waves, the hallmark of NREM (Non Rapid Eye Movement) sleep, are not uniformly distributed across the cortical surface, but can occur locally and asynchronously across brain regions. Their regional distribution and amplitude is affected by brain maturation and by time spent awake, mediated in part by experience-dependent changes in synaptic strength. Recent studies have shown that local low-frequency oscillations (<10Hz) can also occur in REM sleep and during wakefulness, leading to region-specific cognitive errors. Local decreases and increases of slow wave activity in posterior brain regions have been linked to the occurrence of dreaming and to unconscious sleep, respectively. Finally, the coexistence of local sleep-like and wake-like patterns in different brain areas is characteristic of several sleep disorders and may offer insights into these conditions.

Increased Evoked Potentials to Arousing Auditory Stimuli during Sleep: Implication for the Understanding of Dream Recall

High dream recallers (HR) show a larger brain reactivity to auditory stimuli during wakefulness and sleep as compared to low dream recallers (LR) and also more intra-sleep wakefulness (ISW), but no other modification of the sleep macrostructure. To further understand the possible causal link between brain responses, ISW and dream recall, we investigated the sleep microstructure of HR and LR, and tested whether the amplitude of auditory evoked potentials (AEPs) was predictive of arousing reactions during sleep. Participants (18 HR, 18 LR) were presented with sounds during a whole night of sleep in the lab and polysomnographic data were recorded. Sleep microstructure (arousals, rapid eye movements (REMs), muscle twitches (MTs), spindles, KCs) was assessed using visual, semi-automatic and automatic validated methods. AEPs to arousing (awakenings or arousals) and non-arousing stimuli were subsequently computed. No between-group difference in the microstructure of sleep was found. In N2 sleep, auditory arousing stimuli elicited a larger parieto-occipital positivity and an increased late frontal negativity as compared to non-arousing stimuli. As compared to LR, HR showed more arousing stimuli and more long awakenings, regardless of the sleep stage but did not show more numerous or longer arousals. These results suggest that the amplitude of the brain response to stimuli during sleep determine subsequent awakening and that awakening duration (and not arousal) is the critical parameter for dream recall. Notably, our results led us to propose that the minimum necessary duration of an awakening during sleep for a successful encoding of dreams into long-term memory is approximately 2 min.

Optimizing the Detection of Wakeful and Sleep-Like States for Future Electrocorticographic Brain Computer Interface Applications

Previous studies suggest stable and robust control of a brain-computer interface (BCI) can be achieved using electrocorticography (ECoG). Translation of this technology from the laboratory to the real world requires additional methods that allow users operate their ECoG-based BCI autonomously. In such an environment, users must be able to perform all tasks currently performed by the experimenter, including manually switching the BCI system on/off. Although a simple task, it can be challenging for target users (e.g., individuals with tetraplegia) due to severe motor disability. In this study, we present an automated and practical strategy to switch a BCI system on or off based on the cognitive state of the user. Using a logistic regression, we built probabilistic models that utilized sub-dural ECoG signals from humans to estimate in pseudo real-time whether a person is awake or in a sleep-like state, and subsequently, whether to turn a BCI system on or off. Furthermore, we constrained these models to identify the optimal anatomical and spectral parameters for delineating states. Other methods exist to differentiate wake and sleep states using ECoG, but none account for practical requirements of BCI application, such as minimizing the size of an ECoG implant and predicting states in real time. Our results demonstrate that, across 4 individuals, wakeful and sleep-like states can be classified with over 80% accuracy (up to 92%) in pseudo real-time using high gamma (70-110 Hz) band limited power from only 5 electrodes (platinum discs with a diameter of 2.3 mm) located above the precentral and posterior superior temporal gyrus.

Distinctive features of NREM parasomnia behaviors in parkinson's disease and multiple system atrophy

OBJECTIVE

To characterize parasomnia behaviors on arousal from NREM sleep in Parkinson's Disease (PD) and Multiple System Atrophy (MSA).

METHODS

From 30 patients with PD, Dementia with Lewy Bodies/Dementia associated with PD, or MSA undergoing nocturnal video-polysomnography for presumed dream enactment behavior, we were able to select 2 PD and 2 MSA patients featuring NREM Parasomnia Behviors (NPBs). We identified episodes during which the subjects seemed to enact dreams or presumed dream-like mentation (NPB arousals) versus episodes with physiological movements (no-NPB arousals). A time-frequency analysis (Morlet Wavelet Transform) of the scalp EEG signals around each NPB and no- NPB arousal onset was performed, and the amplitudes of the spectral frequencies were compared between NPB and no-NPB arousals.

RESULTS

19 NPBs were identified, 12 of which consisting of 'elementary' NPBs while 7 resembling confusional arousals. With quantitative EEG analysis, we found an amplitude reduction in the 5-6 Hz band 40 seconds before NPBs arousal as compared to no-NPB arousals at F4 and C4 derivations (p<0.01).

CONCLUSIONS

Many PD and MSA patients feature various NREM sleep-related behaviors, with clinical and electrophysiological differences and similarities with arousal parasomnias in the general population.

SIGNIFICANCE

This study help bring to attention an overlooked phenomenon in neurodegenerative diseases.

The dynamics of cortical neuronal activity in the first minutes after spontaneous awakening in rats and mice

STUDY OBJECTIVE

Upon awakening from sleep, a fully awake brain state is not reestablished immediately, but the origin and physiological properties of the distinct brain state during the first min after awakening are unclear. To investigate whether neuronal firing immediately upon arousal is different from the remaining part of the waking episode, we recorded and analyzed the dynamics of cortical neuronal activity in the first 15 min after spontaneous awakenings in freely moving rats and mice.

DESIGN

Intracortical recordings of the local field potential and neuronal activity in freely-moving mice and rats.

SETTING

Basic sleep research laboratory.

PATIENTS OR PARTICIPANTS

WKY adult male rats, C57BL/6 adult male mice.

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

In both species the average population spiking activity upon arousal was initially low, though substantial variability in the dynamics of firing activity was apparent between individual neurons. A distinct population of neurons was found that was virtually silent in the first min upon awakening. The overall lower population spiking initially after awakening was associated with the occurrence of brief periods of generalized neuronal silence (OFF periods), whose frequency peaked immediately after awakening and then progressively declined. OFF periods incidence upon awakening was independent of ongoing locomotor activity but was sensitive to immediate preceding sleep/wake history. Notably, in both rats and mice if sleep before a waking episode was enriched in rapid eye movement sleep, the incidence of OFF periods was initially higher as compared to those waking episodes preceded mainly by nonrapid eye movement sleep.

CONCLUSION

We speculate that an intrusion of sleep-like patterns of cortical neuronal activity into the wake state immediately after awakening may account for some of the changes in the behavior and cognitive function typical of what is referred to as sleep inertia.

CITATION

Vyazovskiy VV, Cui N, Rodriguez AV, Funk C, Cirelli C, Tononi G. The dynamics of cortical neuronal activity in the first minutes after spontaneous awakening in rats and mice.

[Reliability and validity of the 3 Dimensional Sleep Scale (3DSS)--day workers version--in assessing sleep phase, quality, and quantity]

OBJECTIVES

Most sleep scales assess sleep quantity (e.g., sleep duration and daytime sleepiness) or sleep quality (e.g., sleep latency and maintenance); the Pittsburgh Sleep Quality Index (PSQI) is an exceptional example. However, the prevalence of 24-hour operations presents the need for a scale that can also measure sleep phase (e.g., sleep onset and offset). Furthermore, we have to assess the phase, quality and quantity respectively to understand which of them has a problem. Thus, the 3 Dimensional Sleep Scale (3DSS) - day workers version - was developed to assess each of them related to sleep, and this study attempted to verify its reliability and validity.

METHODS

Subjects were 635 day workers (461 men, 174 women; average age = 40.5 years) from the manufacturing and service industries. A scale was created based on a pre-study and discussions with specialists. The scale consisted of 17 sleep-related items. The skew of the data was assessed, and the construct validity and reliability were verified using exploratory and confirmatory factor analysis and Cronbach's alpha, respectively. The scale was scored and G-P analysis was performed. The items measuring phase, quality, and quantity of sleep were selected from the PSQI and SDS, and their correlation with the three scales of 3DSS were measured to verify the convergent and discriminant validity. In addition, the total scores obtained on the PSQI were compared with each scale of the 3DSS.

RESULTS

No skew was found in the data. Exploratory factor analysis revealed a three-factor structure--quality, quantity, and phase. Each factor consisted of five items, therefore two items were excluded. The fitness of the 15-item model was better than that of the 17-item model according to confirmatory factor analysis. Cronbach's alpha for phase, quality and quantity score were 0.685, 0.768 and 0.716, respectively. The hypothesis tests were almost accepted, therefore convergent and discriminant validity were sufficiently established.

CONCLUSIONS

The present study established the reliability and validity of the 3DSS; however, further studies using larger samples are needed to standardize the test and to establish a cut-off value.

Dissociated wake-like and sleep-like electro-cortical activity during sleep

Sleep is traditionally considered a global process involving the whole brain. However, recent studies have shown that sleep depth is not evenly distributed within the brain. Sleep disorders, such as sleepwalking, also suggest that EEG features of sleep and wakefulness might be simultaneously present in different cerebral regions. In order to probe the coexistence of dissociated (wake-like and sleep-like) electrophysiological behaviors within the sleeping brain, we analyzed intracerebral electroencephalographic activity drawn from sleep recordings of five patients with pharmacoresistant focal epilepsy without sleep disturbances, who underwent pre-surgical intracerebral electroencephalographic investigation. We applied spectral and wavelet transform analysis techniques to electroencephalographic data recorded from scalp and intracerebral electrodes localized within the Motor cortex (Mc) and the dorso-lateral Prefrontal cortex (dlPFc). The Mc showed frequent Local Activations (lasting from 5 to more than 60s) characterized by an abrupt interruption of the sleep electroencephalographic slow waves pattern and by the appearance of a wake-like electroencephalographic high frequency pattern (alpha and/or beta rhythm). Local activations in the Mc were paralleled by a deepening of sleep in other regions, as expressed by the concomitant increase of slow waves in the dlPFc and scalp electroencephalographic recordings. These results suggest that human sleep can be characterized by the coexistence of wake-like and sleep-like electroencephalographic patterns in different cortical areas, supporting the hypothesis that unusual phenomena, such as NREM parasomnias, could result from an imbalance of these two states.

The cortisol awakening response: more than a measure of HPA axis function

In most healthy people morning awakening is associated with a burst of cortisol secretion: the cortisol awakening response (CAR). It is argued that the CAR is subject to a range physiological regulatory influences that facilitate this rapid increase in cortisol secretion. Evidence is presented for reduced adrenal sensitivity to rising levels of ACTH in the pre-awakening period, mediated by an extra-pituitary pathway to the adrenal from the suprachiasmatic nucleus (SCN). A role for the hippocampus in this pre-awakening regulation of cortisol secretion is considered. Attainment of consciousness is associated with 'flip-flop' switching of regional brain activation, which, it is argued, initiates a combination of processes: (1) activation of the hypothalamic pituitary adrenal (HPA) axis; (2) release of pre-awakening reduced adrenal sensitivity to ACTH; (3) increased post-awakening adrenal sensitivity to ACTH in response to light, mediated by a SCN extra-pituitary pathway. An association between the CAR and the ending of sleep inertia is discussed.