Local awakening: Regional reorganizations of brain oscillations after sleep

Local wakefulness-like activity of layer 5 cortex under general anaesthesia

Consciousness, defined as being aware of and responsive to one's surroundings, is characteristic of normal waking life and typically is lost during sleep and general anaesthesia. The traditional view of consciousness as a global brain state has evolved toward a more sophisticated interplay between global and local states, with the presence of local sleep in the awake brain and local wakefulness in the sleeping brain. However, this interplay is not clear for general anaesthesia, where loss of consciousness was recently suggested to be associated with a global state of brain-wide synchrony that selectively involves layer 5 cortical pyramidal neurons across sensory, motor and associative areas. According to this global view, local wakefulness of layer 5 cortex should be incompatible with deep anaesthesia, a hypothesis that deserves to be scrutinised with causal manipulations. Here, we show that unilateral chemogenetic activation of layer 5 pyramidal neurons in the sensorimotor cortex of isoflurane-anaesthetised mice induces a local state transition from slow-wave activity to tonic firing in the transfected hemisphere. This wakefulness-like activity dramatically disrupts layer 5 interhemispheric synchrony with mirror-image locations in the contralateral hemisphere, but does not reduce the level of unconsciousness under deep anaesthesia, nor in the transitions to/from anaesthesia. Global layer 5 synchrony may thus be a sufficient condition for anaesthesia-induced unconsciousness, but is not a necessary one, at least under isoflurane anaesthesia. Local wakefulness-like activity of layer 5 cortex can be induced and maintained under deep anaesthesia, encouraging further investigation into the local vs. global aspects of anaesthesia-induced unconsciousness. KEY POINTS: The neural correlates of consciousness have evolved from global brain states to a nuanced interplay between global and local states, evident in terms of local sleep in awake brains and local wakefulness in sleeping brains. The concept of local wakefulness remains unclear for general anaesthesia, where the loss of consciousness has been recently suggested to involve brain-wide synchrony of layer 5 cortical neurons. We found that local wakefulness-like activity of layer 5 cortical can be chemogenetically induced in anaesthetised mice without affecting the depth of anaesthesia or the transitions to and from unconsciousness. Global layer 5 synchrony may thus be a sufficient but not necessary feature for the unconsciousness induced by general anaesthesia. Local wakefulness-like activity of layer 5 neurons is compatible with general anaesthesia, thus promoting further investigation into the local vs. global aspects of anaesthesia-induced unconsciousness.

Considerations towards a neurobiologically-informed EEG measurement of sleepiness

Sleep is a daily experience across humans and other species, yet our understanding of how and why we sleep is presently incomplete. This is particularly prevalent in research examining the neurophysiological measurement of sleepiness in humans, where several electroencephalogram (EEG) phenomena have been linked with prolonged wakefulness. This leaves researchers without a solid basis for the measurement of homeostatic sleep need and complicates our understanding of the nature of sleep. Recent theoretical and technical advances may allow for a greater understanding of the neurobiological basis of homeostatic sleep need: this may result from increases in neuronal excitability and shifts in excitation/inhibition balance in neuronal circuits and can potentially be directly measured via the aperiodic component of the EEG. Here, we review the literature on EEG-derived markers of sleepiness in humans and argue that changes in these electrophysiological markers may actually result from neuronal activity represented by changes in aperiodic markers. We argue for the use of aperiodic markers derived from the EEG in predicting sleepiness and suggest areas for future research based on these.

The subcortical default mode network and Alzheimer's disease: a systematic review and meta-analysis

The default mode network is a central cortical brain network suggested to play a major role in several disorders and to be particularly vulnerable to the neuropathological hallmarks of Alzheimer's disease. Subcortical involvement in the default mode network and its alteration in Alzheimer's disease remains largely unknown. We performed a systematic review, meta-analysis and empirical validation of the subcortical default mode network in healthy adults, combined with a systematic review, meta-analysis and network analysis of the involvement of subcortical default mode areas in Alzheimer's disease. Our results show that, besides the well-known cortical default mode network brain regions, the default mode network consistently includes subcortical regions, namely the thalamus, lobule and vermis IX and right Crus I/II of the cerebellum and the amygdala. Network analysis also suggests the involvement of the caudate nucleus. In Alzheimer's disease, we observed a left-lateralized cluster of decrease in functional connectivity which covered the medial temporal lobe and amygdala and showed overlap with the default mode network in a portion covering parts of the left anterior hippocampus and left amygdala. We also found an increase in functional connectivity in the right anterior insula. These results confirm the consistency of subcortical contributions to the default mode network in healthy adults and highlight the relevance of the subcortical default mode network alteration in Alzheimer's disease.

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.

Somatotopic disruption of the functional connectivity of the primary sensorimotor cortex in complex regional pain syndrome type 1

In complex regional pain syndrome (CRPS), the representation area of the affected limb in the primary sensorimotor cortex (SM1) reacts abnormally during sensory stimulation and motor actions. We recorded 3T functional magnetic resonance imaging resting-state data from 17 upper-limb CRPS type 1 patients and 19 healthy control subjects to identify alterations of patients' SM1 function during spontaneous pain and to find out how the spatial distribution of these alterations were related to peripheral symptoms. Seed-based correlations and independent component analyses indicated that patients' upper-limb SM1 representation areas display (i) reduced interhemispheric connectivity, associated with the combined effect of intensity and spatial extent of limb pain, (ii) increased connectivity with the right anterior insula that positively correlated with the duration of CRPS, (iii) increased connectivity with periaqueductal gray matter, and (iv) disengagement from the other parts of the SM1 network. These findings, now reported for the first time in CRPS, parallel the alterations found in patients suffering from other chronic pain conditions or from limb denervation; they also agree with findings in healthy persons who are exposed to experimental pain or have used their limbs asymmetrically. Our results suggest that CRPS is associated with a sustained and somatotopically specific alteration of SM1 function, that has correspondence to the spatial distribution of the peripheral manifestations and to the duration of the syndrome.

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.

Time Course of Motor Sleep Inertia Dissipation According to Age

Sleep inertia (SI) refers to a complex psychophysiological phenomenon observed after morning awakening that can be described as the gradual recovery of waking-like status after a night of sleep. The time course of SI dissipation in an everyday life condition is little studied. The present study aims to investigate the SI dissipation in motor activity, as a function of age, upon spontaneous morning awakening after a usual night-time sleep. To this end, we performed a retrospective study in a naturalistic setting in a wide life span sample: 382 healthy participants (219 females) from middle childhood (9 years old) to late adulthood (70 years old). Participants were required to wear the actigraph on the non-dominant wrist for at least seven consecutive nights. Results show that SI of motor activity is dissipated in 70 min. Mean motor activity in such a time window was significantly modulated by age: lower age corresponded to higher motor activity.

Anterior precuneus related to the recovery of consciousness

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Degree centrality of anterior precuneus correlated with Glasgow Outcome Scale scores.

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Anterior precuneus was shown as a hub in multiple recoverable unconscious states.

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Anterior precuneus had similar connectivity pattern in recoverable unconscious states.

The neural mechanism that enables the recovery of consciousness in patients with unresponsive wakefulness syndrome (UWS) remains unclear. The aim of the current study is to characterize the cortical hub regions related to the recovery of consciousness. In the current fMRI study, voxel-wise degree centrality analysis was adopted to identify the cortical hubs related to the recovery of consciousness, for which a total of 27 UWS patients were recruited, including 13 patients who emerged from UWS (UWS-E), and 14 patients who remained in UWS (UWS-R) at least three months after the experiment performance. Furthermore, other recoverable unconscious states were adopted as validation groups, including three independent N3 sleep datasets (n = 12, 9, 9 respectively) and three independent anesthesia datasets (n = 27, 14, 6 respectively). Spatial similarity of the hub characteristic with the validation groups between the UWS-E and UWS-R was compared using the dice coefficient. Finally, with the cortical regions persistently shown as hubs across UWS-E and validation states, functional connectivity analysis was further performed to explore the connectivity patterns underlying the recovery of consciousness. The results identified four cortical hubs in the UWS-E, which showed significantly higher degree centrality for UWS-E than UWS-R, including the anterior precuneus, left inferior parietal lobule, left inferior frontal gyrus, and left middle frontal gyrus, of which the degree centrality value also positively correlated with the patients’ Glasgow Outcome Scale (GOS) score that assessed global brain functioning outcome after a brain injury. Furthermore, the anterior precuneus was found with significantly higher similarity of hub characteristics as well as functional connectivity patterns between UWS-E and the validation groups. The results suggest that the recovery of consciousness may be relevant to the integrity of cortical hubs in the recoverable unconscious states, especially the anterior precuneus. The identified cortical hub regions could serve as potential treatment targets for patients with UWS.

Localizing Spectral Interactions in the Resting State Network Using the Hilbert-Huang Transform

Brain synchronizations are orchestrated from neuronal oscillations through frequency interactions, such as the alpha rhythm during relaxation. Nevertheless, how the intrinsic interaction forges functional integrity across brain segregations remains elusive, thereby motivating recent studies to localize frequency interactions of resting-state fMRI (rs-fMRI). To this point, we aim to unveil the fMRI-based spectral interactions using the time-frequency (TF) analysis; however, Fourier-based TF analyses impose restrictions on revealing frequency interactions given the limited time points in fMRI signals. Instead of using the Fourier-based wavelet analysis to identify the fMRI frequency of interests, we employed the Hilbert-Huang transform (HHT) for probing the specific frequency contribution to the functional integration, called ensemble spectral interaction (ESI). By simulating data with time-variant frequency changes, we demonstrated the Hilbert TF maps with high spectro-temporal resolution and full accessibility in comparison with the wavelet TF maps. By detecting amplitude-to-amplitude frequency couplings (AAC) across brain regions, we elucidated the ESI disparity between the eye-closed (EC) and eye-open (EO) conditions in rs-fMRI. In the visual network, the strength of the spectral interaction within 0.03-0.04 Hz was amplified in EC compared with that in EO condition, whereas a canonical connectivity analysis did not present differences between conditions. Collectively, leveraging from the instantaneous frequency of HHT, we firstly addressed the ESI technique to map the fMRI-based functional connectivity in a brand-new AAC perspective. The ESI possesses potential in elucidating the functional connectivity at specific frequency bins, thereby providing additional diagnostic merits for future clinical neuroscience.

Changes of Brain Functional Connectivity in End-Stage Renal Disease Patients Receiving Peritoneal Dialysis Without Cognitive Decline

Background: Functional connectivity detected by resting-state functional MRI (R-fMRI) helps to discover the subtle changes in brain activities. Patients with end-stage renal disease (ESRD) on hemodialysis (HD) have impaired brain networks. However, the functional changes of brain networks in patients with ESRD undergoing peritoneal dialysis (PD) have not been fully delineated, especially among those with preserved cognitive function. Therefore, it is worth knowing about the brain functional connectivity in patients with PD by using R-fMRI.

Methods: This case-control study prospectively enrolled 19 patients with ESRD receiving PD and 24 age- and sex- matched controls. All participants without a history of cognitive decline received mini-mental status examination (MMSE) and brain 3-T R-fMRI. Comprehensive R-fMRI analyses included graph analysis for connectivity and seed-based correlation networks. Independent t-tests were used for comparing the graph parameters and connectivity networks between patients with PD and controls.

Results: All subjects were cognitively intact (MMSE > 24). Whole-brain connectivity by graph analysis revealed significant differences between the two groups with decreased global efficiency (E_glob, p < 0.05), increased betweenness centrality (BC) (p < 0.01), and increased characteristic path length (L, p < 0.01) in patients with PD. The functional connections of the default-mode network (DMN), sensorimotor network (SMN), salience network (SN), and hippocampal network (HN) were impaired in patients with PD. Meanwhile, in DMN and SN, elevated connectivity was observed in certain brain regions of patients with PD.

Conclusion: Patients with ESRD receiving PD had specific disruptions in functional connectivity. In graph analysis, E_glob, BC, and L showed significant connectivity changes compared to the controls. DMN and SN had the most prominent alterations among the observed networks, with both decreased and increased connectivity regions. Our study confirmed that significant changes in cerebral connections existed in cognitively intact patients with PD.

fMRI lag structure during waking up from early sleep stages

The brain mechanisms by which we transition from sleep to a conscious state remain largely unknown in humans, partly because of methodological challenges. Here we study a pre-existing dataset of waking up participants originally designed for a study of dreaming (Horikawa, Tamaki, Miyawaki, & Kamitani, 2013) and suggest that suddenly awakening from early sleep stages results from a two-stage process that involves a sequence of cortical and subcortical brain activity. First, subcortical and sensorimotor structures seem to be recruited before most cortical regions, followed by fast, ignition-like whole-brain activation-with frontal regions engaging a little after the rest of the brain. Second, a comparably slower and possibly mirror-reversed stage might take place, with cortical regions activating before subcortical structures and the cerebellum. This pattern of activation points to a key role of subcortical structures for the initiation and maintenance of conscious states.

Sleep inertia measurement with the psychomotor vigilance task in idiopathic hypersomnia

STUDY OBJECTIVES

Sleep inertia is a frequent and disabling symptom in idiopathic hypersomnia (IH), but poorly defined and without objective measures. The study objective was to determine whether the psychomotor vigilance task (PVT) can reliably measure sleep inertia in patients with IH or other sleep disorders (non-IH).

METHODS

Sixty-two (51 women, mean age: 27.7±9.2) patients with IH and 140 (71 women, age: 33.3±12.1) with non-IH (narcolepsy=29, non-specified hypersomnolence NSH=47, obstructive sleep apnea=39, insomnia=25) were included. Sleep inertia and sleep drunkenness in the last month (M-sleep inertia) and on PVT day (D-sleep inertia) were assessed with three items of the Idiopathic Hypersomnia Severity Scale (IHSS), in drug-free conditions. The PVT was performed four times (7:00 PM, and 7:00, 7:30 and 11:00 AM) and three metrics were used: lapses, mean 1/Reaction Time (RT), slowest 10% 1/RT.

RESULTS

Sleep inertia was more frequent in patients with IH than non-IH (56.5% and 43.6% with severe sleep inertia in the past month, including 24% and 12% with sleep drunkenness). Lapse number increase and slowest 10% 1/RT decrease, particularly at 7:00 and 7:30AM, were proportional with M-sleep inertia severity, but regardless of sleep drunkenness and sleep disorders. Similar results were obtained when PVT results were compared in patients with/without D-sleep inertia, with the largest increase of the lapse number at 7:00 and 7:30AM associated with severe sleep inertia and sleep drunkenness.

CONCLUSION

PVT is a reliable and objective measure of sleep inertia that might be useful for its characterization, management and follow-up in patients with IH.

[Sleep and neurophysiological correlates of consciousness activation upon awakening]

The authors discuss modern ideas about the neurophysiological mechanisms of awakening from sleep and the results of own EEG studies of the spatio-temporal dynamics of the activity of the cerebral hemispheres using the own experimental model for studying consciousness in the sleep-wake paradigm. This model is based on continuous execution of a monotonous psychomotor test performed lying down with eyes closed and allows observing several short-term sleep episodes during a 1-hour experiment, followed by spontaneous awakening and restoration of the psychomotor test. A necessary condition for the restoration of activity during spontaneous awakening is the emergence of the EEG alpha rhythm, the parameters of which determine the effectiveness of the restoration of the psychomotor test and, accordingly, the achievement of a certain level of consciousness, and therefore can be considered as a neurophysiological correlate of consciousness activation upon awakening. The considered experimental model of consciousness can be useful for analyzing the neurophysiological mechanisms of consciousness activation in patients with chronic impairments of consciousness and for searching for effective methods for the rehabilitation of such patients.

Higher-order sensorimotor circuit of the brain's global network supports human consciousness

Consciousness is a mental characteristic of the human mind, whose exact neural features remain unclear. We aimed to identify the critical nodes within the brain's global functional network that support consciousness. To that end, we collected a large fMRI resting state dataset with subjects in at least one of the following three consciousness states: preserved (including the healthy awake state, and patients with a brain injury history (BI) that is fully conscious), reduced (including the N1-sleep state, and minimally conscious state), and lost (including the N3-sleep state, anesthesia, and unresponsive wakefulness state). We also included a unique dataset of subjects in rapid eye movement sleep state (REM-sleep) to test for the presence of consciousness with minimum movements and sensory input. To identify critical nodes, i.e., hubs, within the brain's global functional network, we used a graph-theoretical measure of degree centrality conjoined with ROI-based functional connectivity. Using these methods, we identified various higher-order sensory and motor regions including the supplementary motor area, bilateral supramarginal gyrus (part of inferior parietal lobule), supragenual/dorsal anterior cingulate cortex, and left middle temporal gyrus, that could be important hubs whose degree centrality was significantly reduced when consciousness was reduced or absent. Additionally, we identified a sensorimotor circuit, in which the functional connectivity among these regions was significantly correlated with levels of consciousness across the different groups, and remained present in the REM-sleep group. Taken together, we demonstrated that regions forming a higher-order sensorimotor integration circuit are involved in supporting consciousness within the brain's global functional network. That offers novel and more mechanism-guided treatment targets for disorders of consciousness.

Does maladaptive cardiovagal modulation extend to gastric modulation in women with chronic pelvic pain?

BACKGROUND

Women with chronic pelvic pain (CPP) have poor cardiovagal modulation. It is unclear whether this finding reflects a broader abnormality across many systems such as gastro-vagal modulation.

AIM

To determine if maladaptive cardiovagal activity in females with CPP is accompanied by maladaptive gastric myoelectric activity.

METHODS

A total of 36 health controls (HC) and 75 CPP underwent supine (10 min), then upright (tilted 70° head up; 30 min), and back to supine (10 min) positions. High-frequency heart rate variability (HF-HRV; 0.15-0.4 Hz) was measured as an index of cardiovagal activity. Cutaneous electrogastrography (EGG) assessed gastric myoelectric activity pre- and during-upright tilt. EGG measures from 16 HC and 31 CPP patients were available for analysis and included relative percentage of gastric activity within the normal (2-4 cpm) and tachygastria (4-10 cpm) ranges, plus ratio of normal/tachygastria.

RESULTS

HF-HRV was lower in CPP individuals at all time points (each p < .05). CPP individuals showed lesser decrease in HF-HRV from supine to upright, and poorer HF-HRV recovery from upright back to supine (F[1, 106] = 4.62, p = .034). HC showed increase in tachygastria activity (t[15] = -2.09, p = .054) while the CPP group showed no change in tachygastria activity from pre-upright to upright (t[30] = -0.62, p = .537).

CONCLUSIONS

Individuals with CPP going from supine to upright demonstrate an impairment in both tachygastria and the parallel decrement in HRV. These results support the hypothesis of a generalized blunting in the physiological modulation in CPP individuals affecting both cardiovascular and gastric systems.

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.

Dynamic functional connectivity states characterize NREM sleep and wakefulness

According to recent neuroimaging studies, temporal fluctuations in functional connectivity patterns can be clustered into dynamic functional connectivity (DFC) states and correspond to fluctuations in vigilance. However, whether there consistently exist DFC states associated with wakefulness and sleep stages and what are the characteristics and electrophysiological origin of these states remain unclear. The aims of the current study were to investigate the properties of DFC in different sleep stages and to explore the relationship between the characteristics of DFC and slow‐wave activity. We collected both eyes‐closed wakefulness and sleep data from 48 healthy young volunteers with simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. EEG data were employed as the gold standard of sleep stage scoring, and DFC states were estimated based on fMRI data. The results demonstrated that DFC states of the fMRI signals consistently corresponded to wakefulness and nonrapid eye movement sleep stages independent of the number of clusters. Furthermore, the mean dwell time of these states significantly correlated with slow‐wave activity. The inclusion or omission of regression of the global signal and the selection of parcellation schemes exerted minimal effects on the current findings. These results provide strong evidence that DFC states underlying fMRI signals match the fluctuations of vigilance and suggest a possible electrophysiological source of DFC states corresponding to vigilance states.

Microsleep episodes in the borderland between wakefulness and sleep

Study objectives

The wake-sleep transition zone represents a poorly defined borderland, containing, for example, microsleep episodes (MSEs), which are of potential relevance for diagnosis and may have consequences while driving. Yet, the scoring guidelines of the American Academy of Sleep Medicine (AASM) completely neglect it. We aimed to explore the borderland between wakefulness and sleep by developing the Bern continuous and high-resolution wake-sleep (BERN) criteria for visual scoring, focusing on MSEs visible in the electroencephalography (EEG), as opposed to purely behavior- or performance-defined MSEs.

Methods

Maintenance of Wakefulness Test (MWT) trials of 76 randomly selected patients were retrospectively scored according to both the AASM and the newly developed BERN scoring criteria. The visual scoring was compared with spectral analysis of the EEG. The quantitative EEG analysis enabled a reliable objectification of the visually scored MSEs. For less distinct episodes within the borderland, either ambiguous or no quantitative patterns were found.

Results

As expected, the latency to the first MSE was significantly shorter in comparison to the sleep latency, defined according to the AASM criteria. In certain cases, a large difference between the two latencies was observed and a substantial number of MSEs occurred between the first MSE and sleep. Series of MSEs were more frequent in patients with shorter sleep latencies, while isolated MSEs were more frequent in patients who did not reach sleep.

Conclusion

The BERN criteria extend the AASM criteria and represent a valuable tool for in-depth analysis of the wake-sleep transition zone, particularly important in the MWT.

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.

Spatio-temporal structure of sleep slow oscillations on the electrode manifold and its relation to spindles

Electrophysiological sleep rhythms have been shown to impact human waking cognition, but their spatio-temporal dynamics are not understood. We investigated how slow oscillations (SOs; 0.5-4 Hz) are organized during a night of polysomnographically-recorded sleep, focusing on the scalp electrode manifold. We detected troughs of SOs at all electrodes independently and analyzed the concurrent SO troughs found in every other electrode within ±400 ms. We used a k-clustering algorithm to categorize the spatial patterns of SO trough co-occurrence into three types (Global, Local or Frontal) depending on their footprint on the electrode manifold during the considered time window. When comparing the clusters across non-rapid eye movement (NREM) sleep stages, we found a relatively larger fraction of Local SOs in slow wave sleep (SWS) compared to stage 2, and larger fraction of Global SOs in stage 2 compared to SWS. The probability of SO detection in time between two electrodes showed that SO troughs of all types co-occurred at some nearby electrodes, but only Global troughs had traveling wave profiles, moving anteriorly to posteriorly. Global SOs also had larger amplitudes at frontal electrodes and stronger coupling with fast spindles (12.5-16 Hz). Indeed, SO-spindle complexes were more likely to be detected following a Global SO trough compared to SOs in other clusters. Also, the phase-amplitude modulation of SOs over spindles (modulation vector) was higher for Global SOs across the electrode manifold. Given the recent evidence of a link between thalamocortical coupling and cognition, our findings suggest stronger cognitive relevance of Global SOs as compared to other SO types in sleep memory processing.

Clinical Trials

No clinical trial is related to this study.

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.

[18F]Fludeoxyglucose-Positron Emission Tomography Evidence for Cerebral Hypermetabolism in the Awake State in Narcolepsy and Idiopathic Hypersomnia

Background

Changes in structural and functional central nervous system have been reported in narcolepsy, with large discrepancies between studies. No study has investigated yet spontaneous brain activity at wake in idiopathic hypersomnia (IH). We compared relative changes in regional brain metabolism in two central hypersomnia conditions with different clinical features, namely narcolepsy type 1 (NT1) and IH, and in healthy controls.

Methods

Sixteen patients [12 males, median age 30 years (17–78)] with NT1, nine patients [2 males, median age 27 years (20–60)] with IH and 19 healthy controls [16 males, median age 36 years (17–78)] were included. ¹⁸F-fludeoxyglucose positron emission tomography (PET) was performed in all drug-free subjects under similar conditions and instructions to stay in a wake resting state.

Results

We found increased metabolism in the anterior and middle cingulate and the insula in the two pathological conditions as compared to healthy controls. The reverse contrast failed to evidence hypometabolism in patients vs. controls. Comparisons between patient groups were non-significant. At sub-statistical threshold, we found higher right superior occipital gyrus glucose metabolism in narcolepsy and higher middle orbital cortex and supplementary motor area metabolism in IH, findings that require further confirmation.

Conclusion

There is significant hypermetabolism in narcolepsy and IH in the wake resting state in a set of brain regions constitutive of the salience cortical network that may reflect a compensatory neurocircuitry activity secondary to sleepiness. Metabolic differences between the two disorders within the executive-control network may be a signature of abnormally functioning neural system leading to persistent drowsiness typical of IH.

Effect of DRD4 receptor -616 C/G polymorphism on brain structure and functional connectivity density in pediatric primary nocturnal enuresis patients

The dopamine D4 receptor (DRD4) promoter (-616; rs747302) has been associated with primary nocturnal enuresis (PNE); however, its relationship with neuroimaging has not been investigated. Therefore, we assessed the effects of the DRD4 -616 C/G single nucleotide polymorphism on the gray matter volume (GMV) and functional connectivity density (FCD) during resting-state functional magnetic resonance imaging in children with PNE using voxel-based morphometry and FCD methods. Genomic and imaging data were obtained from 97 children with PNE and 105 healthy controls. DRD4 -616 C/G was genotyped. Arousal from sleep (AS) was assessed on a scale of 1-8. Both the main effect of genotype and the group (PNE/control)-by-genotype interaction on GMV and FCD were calculated. Our results showed that C-allele carriers were associated with a higher AS, decreased GMV and FCD in the pregenual anterior cingulate cortex; children with PNE carrying the C allele exhibit decreased GMV and FCD in the thalamus; however, controls carrying the C allele exhibit increased FCD in the posterior cingulate cortex. These effects of genetic variation of the DRD4 locus may help us understand the genetic susceptibility of the DRD4 -616 C allele to PNE.