EEG functional connectivity prior to sleepwalking : evidence of interplay between sleep and wakefulness

Study Objectives: Although sleepwalking (somnambulism) affects up to 4% of adults, its pathophysiology remains poorly understood. Sleepwalking can be preceded by fluctuations in slow-wave sleep EEG signals, but the significance of these pre-episode changes remains unknown and methods based on EEG functional connectivity have yet to be used to better comprehend the disorder. Methods: We investigated the sleep EEG of 27 adult sleepwalkers (mean age: 29 ± 7.6 years) who experienced a somnambulistic episode during slow-wave sleep. The 20-second segment of sleep EEG immediately preceding each patient’s episode was compared with the 20-second segment occurring 2 minutes prior to episode onset. Results: Results from spectral analyses revealed increased delta and theta spectral power in the 20 seconds preceding the episodes’ onset as compared to the 20 seconds occurring 2 minutes before the episodes. The imaginary part of the coherence immediately prior to episode onset revealed (1) decreased delta EEG functional connectivity in parietal and occipital regions, (2) increased alpha connectivity over a fronto-parietal network, and (3) increased beta connectivity involving symmetric inter-hemispheric networks implicating frontotemporal, parietal and occipital areas. Conclusions: Taken together, these modifications in EEG functional connectivity suggest that somnambulistic episodes are preceded by brain processes characterized by the co-existence of arousal and deep slee

Sleep-related epileptic behaviors and non-REM-related parasomnias: Insights from stereo-EEG

During the last decade, many clinical and pathophysiological aspects of sleep-related epileptic and non-epileptic paroxysmal behaviors have been clarified. Advances have been achieved in part through the use of intracerebral recording methods such as stereo-electroencephalography (S-EEG), which has allowed a unique "in vivo" neurophysiological insight into focal epilepsy. Using S-EEG, the local features of physiological and pathological EEG activity in different cortical and subcortical structures have been better defined during the entire sleep-wake spectrum. For example, S-EEG has contributed to clarify the semiology of sleep-related seizures as well as highlight the specific epileptogenic networks involved during ictal activity. Moreover, intracerebral EEG recordings derived from patients with epilepsy have been valuable to study sleep physiology and specific sleep disorders. The occasional co-occurrence of NREM-related parasomnias in epileptic patients undergoing S-EEG investigation has permitted the recordings of such events, highlighting the presence of local electrophysiological dissociated states and clarifying the underlying pathophysiological substrate of such NREM sleep disorders. Based on these recent advances, the authors review and summarize the current and relevant S-EEG literature on sleep-related hypermotor epilepsies and NREM-related parasomnias. Finally, novel data and future research hypothesis will be discussed

Acetylcholine neuromodulation in normal and abnormal learning and memory: vigilance control in waking, sleep, autism, amnesia, and Alzheimer's disease

This article provides a unified mechanistic neural explanation of how learning, recognition, and cognition break down during Alzheimer's disease, medial temporal amnesia, and autism. It also clarifies whey there are often sleep disturbances during these disorders. A key mechanism is how acetylcholine modules vigilance control in cortical layer

Cognitive and Physiologic Impacts of the Infraslow Oscillation

Brain states are traditionally recognized via sleep-wake cycles, but modern neuroscience is beginning to identify many sub-states within these larger arousal types. Multiple lines of converging evidence now point to the infraslow oscillation (ISO) as a mediator of brain sub-states, with impacts ranging from the creation of resting state networks (RSNs) in awake subjects to interruptions in neural activity during sleep. This review will explore first the basic characteristics of the ISO in human subjects before reviewing findings in sleep and in animals. Networks of consistently correlated brain regions known as RSNs seen in human functional neuroimaging studies oscillate together at infraslow frequencies. The infraslow rhythm subdivides nonREM in a manner that may correlate with plasticity. The mechanism of this oscillation may be found in the thalamus and may ultimately come from glial cells. Finally, I review the functional impacts of ISOs on brain phenomena ranging from higher frequency oscillations, to brain networks, to information representation and cognitive performance. ISOs represent a relatively understudied phenomenon with wide effects on the brain and behavior

Physiopathologie du somnambulisme : étude de l’activité cérébrale en sommeil lent profond via la Tomographie d’Émission Monophotonique (TEMP) et l'analyse de connectivité fonctionnelle cérébrale

Le somnambulisme se caractérise par des comportements moteurs complexes au cours du sommeil, dans un état où persiste une altération des fonctions cognitives, du jugement et de la conscience. Bien que cette parasomnie affecte jusqu’à 4% des adultes, sa physiopathologie demeure peu documentée à ce jour. Conceptualisé au départ comme un trouble reflétant une transition incomplète du sommeil vers l’éveil, le somnambulisme est maintenant aussi considéré comme un trouble reflétant des anomalies au niveau du sommeil lent profond (SLP). L’objectif de la thèse est de documenter la physiopathologie du trouble à la lumière de ces conceptualisations, en caractérisant l’activité cérébrale de somnambules à l’éveil et en sommeil lent profond à l’aide de deux techniques novatrices : les analyses de connectivité fonctionnelle cérébrale et la tomographie par émission monophotonique. Ces deux techniques sont particulièrement indiquées pour l’étude du sommeil et, bien que largement utilisées pour décrire le sommeil régulier, celles-ci n’avaient jamais encore été utilisées pour décrire le SLP de somnambules. Dans une première étude, des analyses de connectivité fonctionnelle cérébrale ont permis d’investiguer les changements d’interdépendance et de synchronisation des signaux EEG de 27 somnambules. La période de 20 secondes immédiatement avant le déclenchement d’un épisode de somnambulisme a été comparée à la période survenant 2 minutes avant leur déclenchement. Les résultats montrent que les épisodes sont précédés par des changements dans la connectivité fonctionnelle cérébrale qui suggèrent le passage vers un état plus près de l’éveil: une diminution de la connectivité locale dans la bande delta, caractéristique du sommeil, ainsi qu’une augmentation de la connectivité dans la bande beta, caractéristique de l’éveil, sur de longs réseaux inter-hémisphériques impliquant les régions frontales, pariétales et occipitales. Ces résultats soulignent que la coexistence entre le sommeil et l’éveil qui sous-tend les épisodes se manifeste également sous forme de changements au niveau des réseaux de connectivité cérébrale et que des marqueurs de cette coexistence s’installent avant même les manifestations comportementales des épisodes. Cette coexistence suggérant des anomalies du processus de transition vers l’éveil, elle appuie par ailleurs la classification du somnambulisme dans la catégorie des troubles de l’éveil. Dans une deuxième étude, la tomographie par émission monophotonique a été utilisée afin de caractériser le SLP et l’éveil, suivant 24 heures de privation de sommeil, de 10 somnambules et 10 participants contrôles. Les résultats révèlent que les somnambules, lorsque comparés aux participants contrôles, montrent une diminution de la perfusion en SLP dans plusieurs régions frontales et pariétales, régions qui ont préalablement été associées à la génération du SLP et à l’occurrence d’épisodes. De plus, les résultats en SLP montrent une diminution de la perfusion dans le cortex préfrontal dorsolatéral et l’insula, ce qui est congruent avec des manifestations cliniques des épisodes. À l’éveil, une diminution de la perfusion est observée chez les somnambules dans plusieurs régions frontales et pariétales, ce qui peut être mis en lien avec les dysfonctions cognitives et fonctionnelles diurnes observées chez cette population. En résumé, cette thèse suggère que le somnambulisme est associé à des anomalies fonctionnelles cérébrales qui s’étendent au-delà des épisodes eux-mêmes, affectant la période précédant leur déclenchement, de même que le SLP et l’éveil suivant privation de sommeil. Ainsi, elle souligne l’importance d’en arriver à une compréhension de la physiopathologie du somnambulisme qui prenne en considération la façon dont ce trouble se manifeste en dehors des épisodes comportementaux.Somnambulism is characterized by the occurrence of complex motor behaviours during NREM sleep in a state in which consciousness, judgement and cognitive functions are altered. Although the disorder affects up to 4% of adults, its pathophysiology remains poorly understood. Initially viewed as a disorder reflecting an incomplete transition from sleep to wakefulness, sleepwalking is now also conceptualized as reflecting key anomalies in slow-wave sleep. The main objective of this thesis was to characterize the cerebral activity of sleepwalkers during wakefulness and during slow-wave sleep in order to elucidate the nature of episode occurrence as well as the disorder’s pathophysiology. EEG functional connectivity analysis and single-photon emission computed tomography (SPECT) are two innovative methods that have been widely used to describe normal sleep. However, these methods had not yet been used to investigate sleepwalkers’ slow wave sleep. In study 1, EEG functional connectivity analyses were used to investigate changes in EEG signal synchronization and interdependency in a group of 27 sleepwalkers who experienced a somnambulistic episode during slow-wave sleep. The 20-sec segment of sleep EEG immediately preceding each patient’s episode was compared with the 20-sec segment occurring two minutes prior to episode onset. Results show that episode onset is preceded by changes in EEG functional connectivity, including decreased delta connectivity in parietal and occipital regions and increased beta connectivity in symmetric inter-hemispheric networks implicating frontal, parietal and occipital areas. These results indicate that somnambulistic episodes are preceded by brain processes characterized by the co-existence of arousal and deep sleep and provide new insights into sleepwalking’s pathophysiology while bolstering its conceptualization as a disorder of arousal. In study 2, SPECT was used to investigate recovery slow-wave sleep and wakefulness following sleep deprivation in 10 sleepwalkers and 10 matched controls. When compared to controls, sleepwalkers showed decreased rCBF in frontal and parietal areas, regions previously associated with slow-wave sleep generation and episode occurrence. Additionally, reduced rCBF was found in the dorsolateral prefrontal cortex and insula during recovery slow-wave sleep, which is consistent with several clinical features of somnambulistic episodes. Reduced rCBF found during sleepwalkers’ resting-state wakefulness in frontal and parietal regions may be related to daytime cognitive and functional anomalies previously described in this population. Taken as a whole, the results from this thesis suggest that sleepwalking is characterized by cerebral functional anomalies that extend well beyond the episodes themselves. In fact, not only are such anomalies observed immediately preceding episode onset, but also more generally during sleepwalkers’ recovery slow-wave sleep and resting-state wakefulness following sleep deprivation. These findings highlight the importance of conceptualizing sleepwalking’s pathophysiology in a way that adequately accounts for how the disorder manifests itself outside of actual behavioural episodes

Increased Global Functional Connectivity Correlates with LSD-Induced Ego Dissolution.

Lysergic acid diethylamide (LSD) is a non-selective serotonin-receptor agonist that was first synthesized in 1938 and identified as (potently) psychoactive in 1943. Psychedelics have been used by indigenous cultures for millennia [1]; however, because of LSD's unique potency and the timing of its discovery (coinciding with a period of major discovery in psychopharmacology), it is generally regarded as the quintessential contemporary psychedelic [2]. LSD has profound modulatory effects on consciousness and was used extensively in psychological research and psychiatric practice in the 1950s and 1960s [3]. In spite of this, however, there have been no modern human imaging studies of its acute effects on the brain. Here we studied the effects of LSD on intrinsic functional connectivity within the human brain using fMRI. High-level association cortices (partially overlapping with the default-mode, salience, and frontoparietal attention networks) and the thalamus showed increased global connectivity under the drug. The cortical areas showing increased global connectivity overlapped significantly with a map of serotonin 2A (5-HT2A) receptor densities (the key site of action of psychedelic drugs [4]). LSD also increased global integration by inflating the level of communication between normally distinct brain networks. The increase in global connectivity observed under LSD correlated with subjective reports of "ego dissolution." The present results provide the first evidence that LSD selectively expands global connectivity in the brain, compromising the brain's modular and "rich-club" organization and, simultaneously, the perceptual boundaries between the self and the environment.This research received financial support from the Safra Foundation (who fund DJN as the Edmond J. Safra Professor of Neuropsychopharmacology) and the Beckley Foundation (it was conducted as part of the Beckley-Imperial research programme). ET is supported by a postdoctoral fellowship of the AXA Research Fund. RCH is supported by an MRC clinical development scheme grant. SDM is supported by a Royal Society of New Zealand Rutherford Discovery Fellowship. KM is supported by a Wellcome Trust Fellowship (WT090199). The researchers would like to thank supporters of the Walacea.com crowd-funding campaign for helping to secure the funds required to complete the study. This report presents independent research carried out at the NIHR/Wellcome Trust Imperial Clinical Research Facility. Authors declare no conflict of interest.This is the author accepted manuscript. The final version is available from Cell Press via http://dx.doi.org/10.1016/j.cub.2016.02.01

Tracking brain dynamics across transitions of consciousness

How do we lose and regain consciousness? The space between healthy wakefulness and unconsciousness encompasses a series of gradual and rapid changes in brain activity. In this thesis, I investigate computational measures applicable to the electroencephalogram to quantify the loss and recovery of consciousness from the perspective of modern theoretical frameworks. I examine three different transitions of consciousness caused by natural, pharmacological and pathological factors: sleep, sedation and coma. First, I investigate the neural dynamics of falling asleep. By combining the established methods of phase-lag brain connectivity and EEG microstates in a group of healthy subjects, a unique microstate is identified, whose increased duration predicts behavioural unresponsiveness to auditory stimuli during drowsiness. This microstate also uniquely captures an increase in frontoparietal theta connectivity, a putative marker of the loss of consciousness prior to sleep onset. I next examine the loss of behavioural responsiveness in healthy subjects undergoing mild and moderate sedation. The Lempel-Ziv compression algorithm is employed to compute signal complexity and symbolic mutual information to assess information integration. An intriguing dissociation between responsiveness and drug level in blood during sedation is revealed: responsiveness is best predicted by the temporal complexity of the signal at single- channel and low-frequency integration, whereas drug level is best predicted by the complexity of spatial patterns and high-frequency integration. Finally, I investigate brain connectivity in the overnight EEG recordings of a group of patients in acute coma. Graph theory is applied on alpha, theta and delta networks to find that increased variability in delta network integration early after injury predicts the eventual coma recovery score. A case study is also described where the re-emergence of frontoparietal connectivity predicted a full recovery long before behavioural improvement. The findings of this thesis inform prospective clinical applications for tracking states of consciousness and advance our understanding of the slow and fast brain dynamics underlying its transitions. Collating these findings under a common theoretical framework, I argue that the diversity of dynamical states, in particular in temporal domain, and information integration across brain networks are fundamental in sustaining consciousness.My PhD was funded by the Cambridge Trust and a MariaMarina award from Lucy Cavendish College

The Feasibility for Whole-Night Sleep Brain Network Research Using Synchronous EEG-fMRI

Objectives: Synchronous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) has been used to explore sleep stage dependent functional brain networks. Despite a growing number of sleep studies using EEG-fMRI, few stud- ies have conducted network analysis on whole night sleep due to dif culty in data acquisition, artifacts, and sleep management within the MRI scanner. Methods: In order to perform network analysis for whole night sleep, we proposed experimental procedures and data process- ing techniques for EEG-fMRI. We acquired 6-7 hours of EEG-fMRI data per participant and conducted signal processing to re- duce artifacts in both EEG and fMRI. We then generated a functional brain atlas with 68 brain regions using independent com- ponent analysis of sleep fMRI data. Using this functional atlas, we constructed sleep level dependent functional brain networks. Results: When we evaluated functional connectivity distribution, sleep showed signi cantly reduced functional connectivity for the whole brain compared to that during wakefulness. REM sleep showed statistically different connectivity patterns compared to non-REM sleep in sleep-related subcortical brain circuits. Conclusion: This study suggests the feasibility of exploring functional brain networks using sleep EEG-fMRI for whole night sleep via appropriate experimental procedures and signal processing techniques for fMRI and EEG.ope

Effects of Sleep Deprivation on Functional Connectivity and Integration During Cognitive Tasks

Introduction: We previously demonstrated that sleep deprivation (SD) alters the balance of integration and segregation of brain activity in cortical networks, which was correlated to cognitive impairment following SD. The objectives of this study is to examine the effects of total sleep deprivation and recovery nap on (i) cognitive performances, (ii) functional connectivity, (iii) integration and (iv) compare changes in integration with cognitive changes during different cognitive tasks individually. We hypothesized that sleep deprivation will lead to increase integration within-networks relative to between-networks and associated with cognitive impairment for all three tasks. Methods: 20 healthy adults (MAGE=21.32, 12 females) were scanned using simultaneous EEG-fMRI during three cognitive tasks (attention, working memory, vigilance) in three conditions: following a normal night of sleep, 24-hour of total SD, and 1-hour recovery nap. A general linear model was performed to compare functional connectivity between the three conditions. Functional clustering ratio (FCR) was used to calculate integration and Pearson’s correlations was used to compare the changes in integration and cognitive changes between each conditions. Results: SD was associated with increased FCR, driven by a rise of integration within cortical networks which was associated with deficits in performance of working memory and attention tasks, but not vigilance task. Restoration of balance between integration and segregation of cortical activity was related with performance following recovery nap demonstrating bidirectional effect. Conclusions: These results demonstrate intra- and interindividual differences in cortical network integration and segregation during task performance may play a critical role in vulnerability to cognitive impairment in the SD state