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.

Intracerebral Dynamics of Sleep Arousals: A Combined Scalp-Intracranial EEG Study.

As an intrinsic component of sleep architecture, sleep arousals represent an intermediate state between sleep and wakefulness and are important for sleep-wake regulation. They are defined in an all-or-none manner, whereas they actually present a wide range of scalp-electroencephalography (EEG) activity patterns. It is poorly understood how these arousals differ in their mechanisms. Stereo-EEG (SEEG) provides the unique opportunity to record intracranial activities in superficial and deep structures in humans. Using combined polysomnography and SEEG, we quantitatively categorized arousals during nonrapid eye movement sleep into slow wave (SW) and non-SW arousals based on whether they co-occurred with a scalp-EEG SW event. We then investigated their intracranial correlates in up to 26 brain regions from 26 patients (12 females). Across both arousal types, intracranial theta, alpha, sigma, and beta activities increased in up to 25 regions (p < 0.05; d = 0.06-0.63), while gamma and high-frequency (HF) activities decreased in up to 18 regions across the five brain lobes (p < 0.05; d = 0.06-0.44). Intracranial delta power widely increased across five lobes during SW arousals (p < 0.05 in 22 regions; d = 0.10-0.39), while it widely decreased during non-SW arousals (p < 0.05 in 19 regions; d = 0.10-0.30). Despite these main patterns, unique activities were observed locally in some regions such as the hippocampus and middle cingulate cortex, indicating spatial heterogeneity of arousal responses. Our results suggest that non-SW arousals correspond to a higher level of brain activation than SW arousals. The decrease in HF activities could potentially explain the absence of awareness and recollection during arousals.

Oscillatory and nonoscillatory sleep electroencephalographic biomarkers of the epileptic network.

OBJECTIVE: In addition to the oscillatory brain activity, the nonoscillatory (scale-free) components of the background electroencephalogram (EEG) may provide further information about the complexity of the underlying neuronal network. As epilepsy is considered a network disease, such scale-free metrics might help to delineate the epileptic network. Here, we performed an analysis of the sleep oscillatory (spindle, slow wave, and rhythmic spectral power) and nonoscillatory (H exponent) intracranial EEG using multiple interictal features to estimate whether and how they deviate from normalcy in 38 adults with drug-resistant epilepsy. METHODS: To quantify intracranial EEG abnormalities within and outside the seizure onset areas, patients' values were adjusted based on normative maps derived from the open-access Montreal Neurological Institute open iEEG Atlas. In a subset of 29 patients who underwent resective surgery, we estimated the predictive value of these features to identify the epileptogenic zone in those with a good postsurgical outcome. RESULTS: We found that distinct sleep oscillatory and nonoscillatory metrics behave differently across the epileptic network, with the strongest differences observed for (1) a reduction in spindle activity (spindle rates and rhythmic sigma power in the 10-16 Hz band), (2) a higher rhythmic gamma power (30-80 Hz), and (3) a higher H exponent (steeper 1/f slope). As expected, epileptic spikes were also highest in the seizure onset areas. Furthermore, in surgical patients, the H exponent achieved the highest performance (balanced accuracy of .76) for classifying resected versus nonresected channels in good outcome patients. SIGNIFICANCE: This work suggests that nonoscillatory components of the intracranial EEG signal could serve as promising interictal sleep candidates of epileptogenicity in patients with drug-resistant epilepsy. Our findings further advance the understanding of epilepsy as a disease, whereby absence or loss of sleep physiology may provide information complementary to pathological epileptic processes.

Interictal stereo-electroencephalography features below 45 Hz are sufficient for correct localization of the epileptogenic zone and postsurgical outcome prediction.

OBJECTIVE: Evidence suggests that the most promising results in interictal localization of the epileptogenic zone (EZ) are achieved by a combination of multiple stereo-electroencephalography (SEEG) biomarkers in machine learning models. These biomarkers usually include SEEG features calculated in standard frequency bands, but also high-frequency (HF) bands. Unfortunately, HF features require extra effort to record, store, and process. Here we investigate the added value of these HF features for EZ localization and postsurgical outcome prediction. METHODS: In 50 patients we analyzed 30 min of SEEG recorded during non-rapid eye movement sleep and tested a logistic regression model with three different sets of features. The first model used broadband features (1-500 Hz); the second model used low-frequency features up to 45 Hz; and the third model used HF features above 65 Hz. The EZ localization by each model was evaluated by various metrics including the area under the precision-recall curve (AUPRC) and the positive predictive value (PPV). The differences between the models were tested by the Wilcoxon signed-rank tests and Cliff's Delta effect size. The differences in outcome predictions based on PPV values were further tested by the McNemar test. RESULTS: The AUPRC score of the random chance classifier was .098. The models (broad-band, low-frequency, high-frequency) achieved median AUPRCs of .608, .582, and .522, respectively, and correctly predicted outcomes in 38, 38, and 33 patients. There were no statistically significant differences in AUPRC or any other metric between the three models. Adding HF features to the model did not have any additional contribution. SIGNIFICANCE: Low-frequency features are sufficient for correct localization of the EZ and outcome prediction with no additional value when considering HF features. This finding allows significant simplification of the feature calculation process and opens the possibility of using these models in SEEG recordings with lower sampling rates, as commonly performed in clinical routines.

Psychobehavioural profile in narcolepsy type 1 with and without REM sleep behaviour disorder.

REM sleep behaviour disorder (RBD) is common in narcolepsy type 1 (NT1). Abnormalities in the reward system have been observed in NT1, possibly related to impaired orexin projections towards the mesolimbic reward system, but also in RBD when associated with Parkinson's disease. Our study aimed to explore the psychobehavioural profile of NT1 patients with and without RBD compared with healthy controls (HC). Forty patients with NT1 were compared with 20 sex- and age-matched HC. All patients with NT1 underwent a video-polysomnography including a measure of REM sleep without atonia (RSWA). The following neuropsychobehavioural variables were assessed: apathy, impulsivity, depression, cognition, subjective and objective attention, sensation-seeking, and behavioural addictions. The patient population included 22 patients with NT1-RBD and 18 patients with NT1-noRBD. Compared with the healthy controls, patients with NT1 had higher scores of apathy, impulsivity, and depression; a lower score on global cognition, and poorer self-perceived attention. No differences were found between patients with NT1 with and without RBD in all neuropsychological variables, except for impaired objective attention in patients with NT1-RBD. In patients with NT1, a positive correlation was observed between RSWA and both apathy and impulsivity subscale. Moreover, in patients with NT1-RBD, RSWA was positively correlated with depression. Patients with NT1 showed higher depression, apathy, and impulsivity compared with controls. These measures correlate with the severity of RSWA, suggesting a transdiagnostic association between RBD and abnormalities of the reward system at least for patients with NT1.

Revisiting the maintenance of wakefulness test: from intra-/inter-scorer agreement to normative values in patients treated for obstructive sleep apnea.

The Maintenance of Wakefulness Test is widely used to objectively assess sleepiness and make safety-related decisions, but its interpretation is subjective and normative values remain debated. Our work aimed to determine normative thresholds in non-subjectively sleepy patients with well-treated obstructive sleep apnea, and to assess intra- and inter-scorer variability. We included maintenance of wakefulness tests of 141 consecutive patients with treated obstructive sleep apnea (90% men, mean (SD) age 47.5 (9.2) years, mean (SD) pre-treatment apnea-hypopnea index of 43.8 (20.3) events/h). Sleep onset latencies were independently scored by two experts. Discordant scorings were reviewed to reach a consensus and half of the cohort was double-scored by each scorer. Intra- and inter-scorer variability was assessed using Cohen's kappa for 40, 33, and 19 min mean sleep latency thresholds. Consensual mean sleep latencies were compared between four groups according to subjective sleepiness (Epworth Sleepiness Scale score < versus ≥11) and residual apnea-hypopnea index (< versus ≥15 events/h). In well-treated non-sleepy patients (n = 76), the consensual mean (SD) sleep latency was 38.4 (4.2) min (lower normal limit [mean - 2SD] = 30 min), and 80% of them did not fall asleep. Intra-scorer agreement on mean sleep latency was high but inter-scorer was only fair (Cohen's kappa 0.54 for 33-min threshold, 0.27 for 19-min threshold), resulting in changes in latency category in 4%-12% of patients. A higher sleepiness score but not the residual apnea-hypopnea index was significantly associated with a lower mean sleep latency. Our findings suggest a higher than usually accepted normative threshold (30 min) in this context and emphasise the need for more reproducible scoring approaches.

Sleep and epilepsy: A snapshot of knowledge and future research lines.

Sleep and epilepsy have a reciprocal relationship, and have been recognized as bedfellows since antiquity. However, research on this topic has made a big step forward only in recent years. In this narrative review we summarize the most stimulating discoveries and insights reached by the "European school." In particular, different aspects concerning the sleep-epilepsy interactions are analysed: (a) the effects of sleep on epilepsy; (b) the effects of epilepsy on sleep structure; (c) the relationship between epilepsy, sleep and epileptogenesis; (d) the impact of epileptic activity during sleep on cognition; (e) the relationship between epilepsy and the circadian rhythm; (f) the history and features of sleep hypermotor epilepsy and its differential diagnosis; (g) the relationship between epilepsy and sleep disorders.

Rapid Eye Movement Sleep Sawtooth Waves Are Associated with Widespread Cortical Activations.

Sawtooth waves (STW) are bursts of frontocentral slow oscillations recorded in the scalp electroencephalogram (EEG) during rapid eye movement (REM) sleep. Little is known about their cortical generators and functional significance. Stereo-EEG performed for presurgical epilepsy evaluation offers the unique possibility to study neurophysiology in situ in the human brain. We investigated intracranial correlates of scalp-detected STW in 26 patients (14 women) undergoing combined stereo-EEG/polysomnography. We visually marked STW segments in scalp EEG and selected stereo-EEG channels exhibiting normal activity for intracranial analyses. Channels were grouped in 30 brain regions. The spectral power in each channel and frequency band was computed during STW and non-STW control segments. Ripples (80-250 Hz) were automatically detected during STW and control segments. The spectral power in the different frequency bands and the ripple rates were then compared between STW and control segments in each brain region. An increase in 2-4 Hz power during STW segments was found in all brain regions, except the occipital lobe, with large effect sizes in the parietotemporal junction, the lateral and orbital frontal cortex, the anterior insula, and mesiotemporal structures. A widespread increase in high-frequency activity, including ripples, was observed concomitantly, involving the sensorimotor cortex, associative areas, and limbic structures. This distribution showed a high spatiotemporal heterogeneity. Our results suggest that STW are associated with widely distributed, but locally regulated REM sleep slow oscillations. By driving fast activities, STW may orchestrate synchronized reactivations of multifocal activities, allowing tagging of complex representations necessary for REM sleep-dependent memory consolidation.SIGNIFICANCE STATEMENT Sawtooth waves (STW) present as scalp electroencephalographic (EEG) bursts of slow waves contrasting with the low-voltage fast desynchronized activity of REM sleep. Little is known about their cortical origin and function. Using combined stereo-EEG/polysomnography possible only in the human brain during presurgical epilepsy evaluation, we explored the intracranial correlates of STW. We found that a large set of regions in the parietal, frontal, and insular cortices shows increases in 2-4 Hz power during scalp EEG STW, that STW are associated with a strong and widespread increase in high frequencies, and that these slow and fast activities exhibit a high spatiotemporal heterogeneity. These electrophysiological properties suggest that STW may be involved in cognitive processes during REM sleep.

Dynamics of hippocampus and orbitofrontal cortex activity during arousing reactions from sleep: An intracranial electroencephalographic study.

Sleep is punctuated by transient elevations of vigilance level called arousals or awakenings depending on their durations. Understanding the dynamics of brain activity modifications during these transitional phases could help to better understand the changes in cognitive functions according to vigilance states. In this study, we investigated the activity of memory-related areas (hippocampus and orbitofrontal cortex) during short (3 s to 2 min) arousing reactions detected from thalamic activity, using intracranial recordings in four drug-resistant epilepsy patients. The average power of the signal between 0.5 and 128 Hz was compared across four time windows: 10 s of preceding sleep, the first part and the end of the arousal/awakening, and 10 s of wakefulness. We observed that (a) in most frequency bands, the spectral power during hippocampal arousal/awakenings is intermediate between wakefulness and sleep whereas frontal cortex shows an early increase in low and fast activities during non-rapid-eye-movement (NREM) sleep arousals/awakenings; (b) this pattern depends on the preceding sleep stage with fewer modifications for REM than for non-REM sleep arousal/awakenings, potentially reflecting the EEG similarities between REM sleep and wakefulness; (c) a greater activation at the arousing reaction onset in the prefrontal cortex predicts longer arousals/awakenings. Our findings suggest that hippocampus and prefrontal arousals/awakenings are progressive phenomena modulated by sleep stage, and, in the neocortex, by the intensity of the early activation. This pattern of activity could underlie the link between sleep stage, arousal/awakening duration and restoration of memory abilities including dream recall.

Sleep Disruption in Epilepsy: Ictal and Interictal Epileptic Activity Matter.

OBJECTIVE: Disturbed sleep is common in epilepsy. The direct influence of nocturnal epileptic activity on sleep fragmentation remains poorly understood. Stereo-electroencephalography paired with polysomnography is the ideal tool to study this relationship. We investigated whether sleep-related epileptic activity is associated with sleep disruption. METHODS: We visually marked sleep stages, arousals, seizures, and epileptic bursts in 36 patients with focal drug-resistant epilepsy who underwent combined stereo-electroencephalography/polysomnography during presurgical evaluation. Epileptic spikes were detected automatically. Spike and burst indices (n/sec/channel) were computed across four 3-second time windows (baseline sleep, pre-arousal, arousal, and post-arousal). Sleep stage and anatomic localization were tested as modulating factors. We assessed the intra-arousal dynamics of spikes and their relationship with the slow wave component of non-rapid eye-movement sleep (NR) arousals. RESULTS: The vast majority of sleep-related seizures (82.4%; 76.5% asymptomatic) were followed by awakenings or arousals. The epileptic burst index increased significantly before arousals as compared to baseline and postarousal, irrespective of sleep stage or brain area. A similar pre-arousal increase was observed for the spike index in NR stage 2 and rapid eye-movement sleep. In addition, the spike index increased during the arousal itself in neocortical channels, and was strongly correlated with the slow wave component of NR arousals (r = 0.99, p < 0.0001). INTERPRETATION: Sleep fragmentation in focal drug-resistant epilepsy is associated with ictal and interictal epileptic activity. The increase in interictal epileptic activity before arousals suggests its participation in sleep disruption. An additional increase in the spike rate during arousals may result from a sleep-wake boundary instability, suggesting a bidirectional relationship. ANN NEUROL 2020;88:907-920.

Telehealth-delivered CBT-I programme enhanced by acceptance and commitment therapy for insomnia and hypnotic dependence: A pilot randomized controlled trial.

Cognitive behavioural therapy for insomnia is the recommended treatment for chronic insomnia. However, up to a quarter of patients dropout from cognitive behavioural therapy for insomnia programmes. Acceptance, mindfulness and values-based actions may constitute complementary therapeutic tools to cognitive behavioural therapy for insomnia. The current study sought to evaluate the efficacy of a remotely delivered programme combining the main components of cognitive behavioural therapy for insomnia (sleep restriction and stimulus control) with the third-wave cognitive behavioural therapy acceptance and commitment therapy in adults with chronic insomnia and hypnotic dependence on insomnia symptoms and quality of life. Thirty-two participants were enrolled in a pilot randomized controlled trial: half of them were assigned to a 3-month waiting list before receiving the four "acceptance and commitment therapy-enhanced cognitive behavioural therapy for insomnia" treatment sessions using videoconference. The primary outcome was sleep quality as measured by the Insomnia Severity Index and the Pittsburgh Sleep Quality Index. All participants also filled out questionnaires about quality of life, use of hypnotics, depression and anxiety, acceptance, mindfulness, thought suppression, as well as a sleep diary at baseline, post-treatment and 6-month follow-up. A large effect size was found for Insomnia Severity Index and Pittsburgh Sleep Quality Index, but also daytime improvements, with increased quality of life and acceptance at post-treatment endpoint in acceptance and commitment therapy-enhanced cognitive behavioural therapy for insomnia participants. Improvement in Insomnia Severity Index and Pittsburgh Sleep Quality Index was maintained at the 6-month follow-up. Wait-list participants increased their use of hypnotics, whereas acceptance and commitment therapy-enhanced cognitive behavioural therapy for insomnia participants evidenced reduced use of them. This pilot study suggests that web-based cognitive behavioural therapy for insomnia incorporating acceptance and commitment therapy processes may be an efficient option to treat chronic insomnia and hypnotic dependence.

The human K-complex: Insights from combined scalp-intracranial EEG recordings.

Sleep spindles and K-complexes (KCs) are a hallmark of N2 sleep. While the functional significance of spindles is comparatively well investigated, there is still ongoing debate about the role of the KC: it is unclear whether it is a cortical response to an arousing stimulus (either external or internal) or whether it has sleep-promoting properties. Invasive intracranial EEG recordings from individuals with drug-resistant epilepsy offer a unique opportunity to study in-situ human brain physiology. To better understand the function of the KC, we aimed to (i) investigate the intracranial correlates of spontaneous scalp KCs, and (ii) compare the intracranial activity of scalp KCs associated or not with arousals. Whole-night recordings from adults with drug-resistant focal epilepsy who underwent combined intracranial-scalp EEG for pre-surgical evaluation at the Montreal Neurological Institute between 2010 and 2018 were selected. KCs were visually marked in the scalp and categorized according to the presence of microarousals: (i) Pre-microarousal KCs; (ii) KCs during an ongoing microarousal; and (iii) KCs without microarousal. Power in different spectral bands was computed to compare physiological intracranial EEG activity at the time of scalp KCs relative to the background, as well as to compare microarousal subcategories. A total of 1198 scalp KCs selected from 40 subjects were analyzed, resulting in 32,504 intracranial KC segments across 992 channels. Forty-seven percent of KCs were without microarousal, 30% were pre-microarousal, and 23% occurred during microarousals. All scalp KCs were accompanied by widespread cortical increases in delta band power (0.3-4 â€‹Hz) relative to the background: the highest percentages were observed in the parietal (60-65%) and frontal cortices (52-58%). Compared to KCs without microarousal, pre-microarousal KCs were accompanied by increases (66%) in beta band power (16-30 â€‹Hz) in the motor cortex, which was present before the peak of the KC. In addition, spatial distribution of spectral power changes following each KC without microarousal revealed that certain brain regions were associated with increases in delta power (25-62%) or decreases in alpha/beta power (11-24%), suggesting a sleep-promoting pattern, whereas others were accompanied by increases of higher frequencies (12-27%), suggesting an arousal-related pattern. This study shows that KCs can be generated across widespread cortical areas. Interestingly, the motor cortex shows awake-like EEG activity before the onset of KCs followed by microarousals. Our findings also highlight region-specific sleep- or arousal-promoting responses following KCs, suggesting a dual role for the human KC.

Rapid eye movement sleep behaviour disorder symptomatic of a brain stem cavernoma.

A 75-year-old man complained of excessive daytime sleepiness (EDS), difficulty falling asleep and nocturnal agitation during sleep. Restless legs syndrome (RLS) was diagnosed and treated. Because of persistent EDS, snoring and nycturia, a nocturnal polysomnography (PSG) was performed. PSG showed high sleep fragmentation related to a moderate to severe obstructive sleep apnea syndrome. Continuous positive airway pressure treatment (CPAP) was proposed. Because of the persistence of abnormal nocturnal behaviours, characterized by screaming, punching and falling out of bed, a video-PSG with CPAP treatment was performed. The recording showed typical chin electromyography (EMG) activity increase associated with violent movements during rapid eye movement (REM) sleep, suggesting REM sleep behaviour disorders (RBD). Clinical neurological examination found no parkinsonian syndrome, no dysautonomic sign and no neurological focal sign. Dopamine transporter imaging [123I-FP-CIT single photon emission computed tomography (SPECT)] did not find any presynaptic dopaminergic pathways degeneration. Brain magnetic resonance imaging showed a vascular lesion suggestive of cavernoma located in the pons. The present case illustrates the complexity of sleep disturbance diagnosis with a possible entanglement of aetiologies responsible for nocturnal agitation, and confirms that an isolated pons cavernoma should be considered among the rare causes of RBD.

Sleep Disturbances and Osteoarthritis.

Sleep disturbances are particularly troublesome in patients with painful rheumatic disease. This article reviews the literature specifically published on sleep disturbances in osteoarthritis, a prevalent pathology and leading cause of disability. Several aspects of the relationship between sleep and osteoarthritis are discussed, including epidemiology, pathophysiological hypotheses, and treatment outcomes. Sleep is of central importance in the well-being of patients and should systematically be assessed in patients with osteoarthritis. When needed, a specific treatment of sleep disorders should be associated with an optimal management of pain to achieve synergistic improvements in quality of life. More large-scale studies are needed to identify predictive factors of sleep impairment in osteoarthritis.

Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study.

Wakefulness, non-rapid eye movement (NREM), and rapid eye movement (REM) sleep are characterized by specific brain activities. However, recent experimental findings as well as various clinical conditions (parasomnia, sleep inertia) have revealed the presence of transitional states. Brief intrusions of wakefulness into sleep, namely, arousals, appear as relevant phenomena to characterize how brain commutes from sleep to wakefulness. Using intra-cerebral recordings in 8 drug-resistant epileptic patients, we analyzed electroencephalographic (EEG) activity during spontaneous or nociceptive-induced arousals in NREM and REM sleep. Wavelet spectral analyses were performed to compare EEG signals during arousals, sleep, and wakefulness, simultaneously in the thalamus, and primary, associative, or high-order cortical areas. We observed that 1) thalamic activity during arousals is stereotyped and its spectral composition corresponds to a state in-between wakefulness and sleep; 2) patterns of cortical activity during arousals are heterogeneous, their manifold spectral composition being related to several factors such as sleep stages, cortical areas, arousal modality ("spontaneous" vs nociceptive-induced), and homeostasis; 3) spectral compositions of EEG signals during arousal and wakefulness differ from each other. Thus, stereotyped arousals at the thalamic level seem to be associated with different patterns of cortical arousals due to various regulation factors. These results suggest that the human cortex does not shift from sleep to wake in an abrupt binary way. Arousals may be considered more as different states of the brain than as "short awakenings." This phenomenon may reflect the mechanisms involved in the negotiation between two main contradictory functional necessities, preserving the continuity of sleep, and maintaining the possibility to react.

The timing of sleep spindles is modulated by the respiratory cycle in humans.

OBJECTIVE: Coupling of sleep spindles with cortical slow waves and hippocampus sharp-waves ripples is crucial for sleep-related memory consolidation. Recent literature evidenced that nasal respiration modulates neural activity in large-scale brain networks. In rodents, this respiratory drive strongly varies according to vigilance states. Whether sleep oscillations are also respiration-modulated in humans remains open. In this work, we investigated the influence of breathing on sleep spindles during non-rapid-eye-movement sleep in humans. METHODS: Full night polysomnography of twenty healthy participants were analysed. Spindles and slow waves were automatically detected during N2 and N3 stages. Spindle-related sigma power as well as spindle and slow wave events were analysed according to the respiratory phase. RESULTS: We found a significant coupling between both slow and fast spindles and the respiration cycle, with enhanced sigma activity and occurrence probability of spindles during the middle part of the expiration phase. A different coupling was observed for slow waves negative peaks which were rather distributed around the two respiration phase transitions. CONCLUSION: Our findings suggest that breathing cycle influences the dynamics of brain activity during non-rapid-eye-movement sleep. SIGNIFICANCE: This coupling may enable sleep spindles to synchronize with other sleep oscillations and facilitate information transfer between distributed brain networks.

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.

Phenotyping patients treated for obstructive sleep apnea with persistent objective impaired alertness or subjective sleepiness.

BACKGROUND AND OBJECTIVES: Sleepiness in patients with obstructive sleep apnea (OSA) is associated with accidental and economic burden, as well as cardiovascular risk. Despite OSA treatment, 10-28 % of patients report residual sleepiness. Its determinants, as well as those of objective impaired alertness remain poorly known. In this study, we investigated factors associated with residual subjective sleepiness and objective impaired alertness in patients treated for OSA. METHODS: Consecutive OSA treated patients referred for maintenance of wakefulness tests (MWT) at a tertiary university center were recruited between 2017 and 2020. Clinical data and polysomnography parameters were compared between patients with vs without subjective sleepiness (Epworth Sleepiness Scale, ESS≥11) and those with vs without impaired alertness (at least one trial with sleep onset on MWT). A multivariate logistic model was used to assess explanatory variables of MWT and ESS results. RESULTS: We included 141 patients, of whom 12.8 % had both subjective sleepiness and objective impaired alertness, 17.7 % objective impaired alertness only and 9.2 % subjective sleepiness only. Self-reported history of car accident/near miss, smoking history and ESS≥11 were significantly associated with objective impaired alertness whereas residual Apnea-hypopnea Index and CPAP use were not. The only significant variable associated with ESS at the time of MWT evaluation was initial ESS. Patients with objective impaired alertness only were more often smokers (52 % vs 19 %, p = 0.01), had a higher body mass index (BMI) (32 vs 29 kg/m2, p = 0.05), and showed lower initial ESS (11 vs 13, p < 0.01). CONCLUSIONS: More than one third of OSA treated patients referred for MWT have objective impaired alertness and/or subjective sleepiness. Our findings highlight the need for a comprehensive medical assessment including accident history, subjective sleepiness and comorbidities. Particular attention should be paid to smoking patients with high BMI, who are at risk of impaired alertness with no report of subjective sleepiness.

Sleepiness should be reinvestigated through the lens of clinical neurophysiology: A mixed expertal and big-data Natural Language Processing approach.

Historically, the field of sleep medicine has revolved around electrophysiological tools. However, the use of these tools as a neurophysiological method of investigation seems to be underrepresented today, from both international recommendations and sleep centers, in contrast to behavioral and psychometric tools. The aim of this article is to combine a data-driven approach and neurophysiological and sleep medicine expertise to confirm or refute the hypothesis that neurophysiology has declined in favor of behavioral or self-reported dimensions in sleep medicine for the investigation of sleepiness, despite the use of electrophysiological tools. Using Natural Language Processing methods, we analyzed the abstracts of the 18,370 articles indexed by PubMed containing the terms 'sleepiness' or 'sleepy' in the title, abstract, or keywords. For this purpose, we examined these abstracts using two methods: a lexical network, enabling the identification of concepts (neurophysiological or clinical) related to sleepiness in these articles and their interconnections; furthermore, we analyzed the temporal evolution of these concepts to extract historical trends. These results confirm the hypothesis that neurophysiology has declined in favor of behavioral or self-reported dimensions in sleep medicine for the investigation of sleepiness. In order to bring sleepiness measurements closer to brain functioning and to reintroduce neurophysiology into sleep medicine, we discuss two strategies: the first is reanalyzing electrophysiological signals collected during the standard sleep electrophysiological test; the second takes advantage of the current trend towards dimensional models of sleepiness to situate clinical neurophysiology at the heart of the redefinition of sleepiness.