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Annarumma L, Reda F, Scarpelli S, D'Atri A, Alfonsi V, Salfi F, Viselli L, Pazzaglia M, De Gennaro L, Gorgoni M. Spatiotemporal EEG dynamics of the sleep onset process in preadolescence. Sleep Med 2024; 119:438-450. [PMID: 38781667 DOI: 10.1016/j.sleep.2024.05.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 05/15/2024] [Accepted: 05/16/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND During preadolescence the sleep electroencephalography undergoes massive qualitative and quantitative modifications. Despite these relevant age-related peculiarities, the specific EEG pattern of the wake-sleep transition in preadolescence has not been exhaustively described. METHODS The aim of the present study is to characterize regional and temporal electrophysiological features of the sleep onset (SO) process in a group of 23 preadolescents (9-14 years) and to compare the topographical pattern of slow wave activity and delta/beta ratio of preadolescents with the EEG pattern of young adults. RESULTS Results showed in preadolescence the same dynamics known for adults, but with peculiarities in the delta and beta activity, likely associated with developmental cerebral modifications: the delta power showed a widespread increase during the SO with central maxima, and the lower bins of the beta activity showed a power increase after SO. Compared to adults, preadolescents during the SO exhibited higher delta power only in the slowest bins of the band: before SO slow delta activity was higher in prefrontal, frontal and occipital areas in preadolescents, and, after SO the younger group had higher slow delta activity in occipital areas. In preadolescents delta/beta ratio was higher in more posterior areas both before and after the wake-sleep transition and, after SO, preadolescents showed also a lower delta/beta ratio in frontal areas, compared to adults. CONCLUSION Results point to a general higher homeostatic drive for the developing areas, consistently with plastic-related maturational modifications, that physiologically occur during preadolescence.
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Affiliation(s)
- Ludovica Annarumma
- Body and Action Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina 306, 00179, Rome, Italy
| | - Flaminia Reda
- SIPRE, Società Italiana di psicoanalisi Della Relazione, Italy
| | - Serena Scarpelli
- Department of Psychology, Sapienza University of Rome, Via Dei Marsi 78, 00185, Rome, Italy
| | - Aurora D'Atri
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 67100, L'Aquila, Italy
| | - Valentina Alfonsi
- Department of Psychology, Sapienza University of Rome, Via Dei Marsi 78, 00185, Rome, Italy
| | - Federico Salfi
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 67100, L'Aquila, Italy
| | - Lorenzo Viselli
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 67100, L'Aquila, Italy
| | - Mariella Pazzaglia
- Body and Action Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina 306, 00179, Rome, Italy; Department of Psychology, Sapienza University of Rome, Via Dei Marsi 78, 00185, Rome, Italy
| | - Luigi De Gennaro
- Body and Action Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina 306, 00179, Rome, Italy; Department of Psychology, Sapienza University of Rome, Via Dei Marsi 78, 00185, Rome, Italy
| | - Maurizio Gorgoni
- Body and Action Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina 306, 00179, Rome, Italy; Department of Psychology, Sapienza University of Rome, Via Dei Marsi 78, 00185, Rome, Italy.
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Marsh BM, Navas-Zuloaga MG, Rosen BQ, Sokolov Y, Delanois JE, González OC, Krishnan GP, Halgren E, Bazhenov M. Emergent effects of synaptic connectivity on the dynamics of global and local slow waves in a large-scale thalamocortical network model of the human brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.15.562408. [PMID: 38617301 PMCID: PMC11014475 DOI: 10.1101/2023.10.15.562408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Slow-wave sleep (SWS), characterized by slow oscillations (SO, <1Hz) of alternating active and silent states in the thalamocortical network, is a primary brain state during Non-Rapid Eye Movement (NREM) sleep. In the last two decades, the traditional view of SWS as a global and uniform whole-brain state has been challenged by a growing body of evidence indicating that SO can be local and can coexist with wake-like activity. However, the understanding of how global and local SO emerges from micro-scale neuron dynamics and network connectivity remains unclear. We developed a multi-scale, biophysically realistic human whole-brain thalamocortical network model capable of transitioning between the awake state and slow-wave sleep, and we investigated the role of connectivity in the spatio-temporal dynamics of sleep SO. We found that the overall strength and a relative balance between long and short-range synaptic connections determined the network state. Importantly, for a range of synaptic strengths, the model demonstrated complex mixed SO states, where periods of synchronized global slow-wave activity were intermittent with the periods of asynchronous local slow-waves. Increase of the overall synaptic strength led to synchronized global SO, while decrease of synaptic connectivity produced only local slow-waves that would not propagate beyond local area. These results were compared to human data to validate probable models of biophysically realistic SO. The model producing mixed states provided the best match to the spatial coherence profile and the functional connectivity estimated from human subjects. These findings shed light on how the spatio-temporal properties of SO emerge from local and global cortical connectivity and provide a framework for further exploring the mechanisms and functions of SWS in health and disease.
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Affiliation(s)
- Brianna M Marsh
- Department of Medicine, University of California, San Diego
- Neuroscience Graduate Program, University of California, San Diego
| | | | - Burke Q Rosen
- Neuroscience Graduate Program, University of California, San Diego
| | - Yury Sokolov
- Department of Medicine, University of California, San Diego
| | - Jean Erik Delanois
- Department of Medicine, University of California, San Diego
- Department of Computer Science and Engineering, University of California, San Diego
| | | | | | - Eric Halgren
- Neuroscience Graduate Program, University of California, San Diego
- Department of Radiology and Neuroscience, University of California, San Diego
| | - Maxim Bazhenov
- Department of Medicine, University of California, San Diego
- Neuroscience Graduate Program, University of California, San Diego
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3
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Tononi G, Boly M, Cirelli C. Consciousness and sleep. Neuron 2024; 112:1568-1594. [PMID: 38697113 PMCID: PMC11105109 DOI: 10.1016/j.neuron.2024.04.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 04/04/2024] [Accepted: 04/10/2024] [Indexed: 05/04/2024]
Abstract
Sleep is a universal, essential biological process. It is also an invaluable window on consciousness. It tells us that consciousness can be lost but also that it can be regained, in all its richness, when we are disconnected from the environment and unable to reflect. By considering the neurophysiological differences between dreaming and dreamless sleep, we can learn about the substrate of consciousness and understand why it vanishes. We also learn that the ongoing state of the substrate of consciousness determines the way each experience feels regardless of how it is triggered-endogenously or exogenously. Dreaming consciousness is also a window on sleep and its functions. Dreams tell us that the sleeping brain is remarkably lively, recombining intrinsic activation patterns from a vast repertoire, freed from the requirements of ongoing behavior and cognitive control.
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Affiliation(s)
- Giulio Tononi
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719, USA.
| | - Melanie Boly
- Department of Neurology, University of Wisconsin, Madison, WI 53719, USA
| | - Chiara Cirelli
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719, USA
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4
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Lacaux C, Strauss M, Bekinschtein TA, Oudiette D. Embracing sleep-onset complexity. Trends Neurosci 2024; 47:273-288. [PMID: 38519370 DOI: 10.1016/j.tins.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 01/17/2024] [Accepted: 02/07/2024] [Indexed: 03/24/2024]
Abstract
Sleep is crucial for many vital functions and has been extensively studied. By contrast, the sleep-onset period (SOP), often portrayed as a mere prelude to sleep, has been largely overlooked and remains poorly characterized. Recent findings, however, have reignited interest in this transitional period and have shed light on its neural mechanisms, cognitive dynamics, and clinical implications. This review synthesizes the existing knowledge about the SOP in humans. We first examine the current definition of the SOP and its limits, and consider the dynamic and complex electrophysiological changes that accompany the descent to sleep. We then describe the interplay between internal and external processing during the wake-to-sleep transition. Finally, we discuss the putative cognitive benefits of the SOP and identify novel directions to better diagnose sleep-onset disorders.
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Affiliation(s)
- Célia Lacaux
- Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, Geneva, Switzerland; Institut du Cerveau (Paris Brain Institute), Institut du Cerveau et de la Moelle Épinière (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche Scientifique (CNRS), Sorbonne Université, Paris 75013, France.
| | - Mélanie Strauss
- Neuropsychology and Functional Neuroimaging Research Group (UR2NF), Center for Research in Cognition and Neurosciences (CRCN), Université Libre de Bruxelles, B-1050 Brussels, Belgium; Departments of Neurology, Psychiatry, and Sleep Medicine, Hôpital Universitaire de Bruxelles, Site Erasme, Université Libre de Bruxelles, B-1070 Brussels, Belgium
| | - Tristan A Bekinschtein
- Cambridge Consciousness and Cognition Laboratory, Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Delphine Oudiette
- Institut du Cerveau (Paris Brain Institute), Institut du Cerveau et de la Moelle Épinière (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche Scientifique (CNRS), Sorbonne Université, Paris 75013, France; Assistance Publique - Hopitaux de Paris (AP-HP), Hôpital Pitié-Salpêtrière, Service des Pathologies du Sommeil, National Reference Centre for Narcolepsy, Paris 75013, France.
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5
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Andrillon T, Taillard J, Strauss M. Sleepiness and the transition from wakefulness to sleep. Neurophysiol Clin 2024; 54:102954. [PMID: 38460284 DOI: 10.1016/j.neucli.2024.102954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 02/02/2024] [Accepted: 02/03/2024] [Indexed: 03/11/2024] Open
Abstract
The transition from wakefulness to sleep is a progressive process that is reflected in the gradual loss of responsiveness, an alteration of cognitive functions, and a drastic shift in brain dynamics. These changes do not occur all at once. The sleep onset period (SOP) refers here to this period of transition between wakefulness and sleep. For example, although transitions of brain activity at sleep onset can occur within seconds in a given brain region, these changes occur at different time points across the brain, resulting in a SOP that can last several minutes. Likewise, the transition to sleep impacts cognitive and behavioral levels in a graded and staged fashion. It is often accompanied and preceded by a sensation of drowsiness and the subjective feeling of a need for sleep, also associated with specific physiological and behavioral signatures. To better characterize fluctuations in vigilance and the SOP, a multidimensional approach is thus warranted. Such a multidimensional approach could mitigate important limitations in the current classification of sleep, leading ultimately to better diagnoses and treatments of individuals with sleep and/or vigilance disorders. These insights could also be translated in real-life settings to either facilitate sleep onset in individuals with sleep difficulties or, on the contrary, prevent or control inappropriate sleep onsets.
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Affiliation(s)
- Thomas Andrillon
- Paris Brain Institute, Sorbonne Université, Inserm-CNRS, Paris 75013, France; Monash Centre for Consciousness & Contemplative Studies, Monash University, Melbourne, VIC 3800, Australia
| | - Jacques Taillard
- Univ. Bordeaux, CNRS, SANPSY, UMR 6033, F-33000 Bordeaux, France
| | - Mélanie Strauss
- Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), CUB Hôpital Érasme, Services de Neurologie, Psychiatrie et Laboratoire du sommeil, Route de Lennik 808 1070 Bruxelles, Belgium; Neuropsychology and Functional Neuroimaging Research Group (UR2NF), Center for Research in Cognition and Neurosciences (CRCN), Université Libre de Bruxelles, B-1050 Brussels, Belgium.
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6
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Cui Y, Li Y, Li Q, Huang J, Tan X, Zhan CA. Alpha anteriorization and theta posteriorization during deep sleep. J Neurosci Res 2024; 102:e25325. [PMID: 38562056 DOI: 10.1002/jnr.25325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 03/06/2024] [Accepted: 03/17/2024] [Indexed: 04/04/2024]
Abstract
Brain states (wake, sleep, general anesthesia, etc.) are profoundly associated with the spatiotemporal dynamics of brain oscillations. Previous studies showed that the EEG alpha power shifted from the occipital cortex to the frontal cortex (alpha anteriorization) after being induced into a state of general anesthesia via propofol. The sleep research literature suggests that slow waves and sleep spindles are generated locally and propagated gradually to different brain regions. Since sleep and general anesthesia are conceptualized under the same framework of consciousness, the present study examines whether alpha anteriorization similarly occurs during sleep and how the EEG power in other frequency bands changes during different sleep stages. The results from the analysis of three polysomnography datasets of 234 participants show consistent alpha anteriorization during the sleep stages N2 and N3, beta anteriorization during stage REM, and theta posteriorization during stages N2 and N3. Although it is known that the neural circuits responsible for sleep are not exactly the same for general anesthesia, the findings of alpha anteriorization in this study suggest that, at macro level, the circuits for alpha oscillations are organized in the similar cortical areas. The spatial shifts of EEG power in different frequency bands during sleep may offer meaningful neurophysiological markers for the level of consciousness.
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Affiliation(s)
- Yue Cui
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Yu Li
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Qiqi Li
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Jing Huang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
| | - Xiaodan Tan
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
| | - Chang'an A Zhan
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China
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7
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Bugnon T, Mayner WGP, Cirelli C, Tononi G. Sleep and wake in a model of the thalamocortical system with Martinotti cells. Eur J Neurosci 2024; 59:703-736. [PMID: 36215116 PMCID: PMC10083195 DOI: 10.1111/ejn.15836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 08/26/2022] [Accepted: 10/05/2022] [Indexed: 12/14/2022]
Abstract
The mechanisms leading to the alternation between active (UP) and silent (DOWN) states during sleep slow waves (SWs) remain poorly understood. Previous models have explained the transition to the DOWN state by a progressive failure of excitation because of the build-up of adaptation currents or synaptic depression. However, these models are at odds with recent studies suggesting a role for presynaptic inhibition by Martinotti cells (MaCs) in generating SWs. Here, we update a classical large-scale model of sleep SWs to include MaCs and propose a different mechanism for the generation of SWs. In the wake mode, the network exhibits irregular and selective activity with low firing rates (FRs). Following an increase in the strength of background inputs and a modulation of synaptic strength and potassium leak potential mimicking the reduced effect of acetylcholine during sleep, the network enters a sleep-like regime in which local increases of network activity trigger bursts of MaC activity, resulting in strong disfacilitation of the local network via presynaptic GABAB1a -type inhibition. This model replicates findings on slow wave activity (SWA) during sleep that challenge previous models, including low and skewed FRs that are comparable between the wake and sleep modes, higher synchrony of transitions to DOWN states than to UP states, the possibility of triggering SWs by optogenetic stimulation of MaCs, and the local dependence of SWA on synaptic strength. Overall, this work points to a role for presynaptic inhibition by MaCs in the generation of DOWN states during sleep.
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Affiliation(s)
- Tom Bugnon
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719 USA
- Neuroscience Training Program, University of Wisconsin, Madison
| | - William G. P. Mayner
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719 USA
- Neuroscience Training Program, University of Wisconsin, Madison
| | - Chiara Cirelli
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719 USA
| | - Giulio Tononi
- Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719 USA
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Bergamo D, Handjaras G, Petruso F, Talami F, Ricciardi E, Benuzzi F, Vaudano AE, Meletti S, Bernardi G, Betta M. Maturation-dependent changes in cortical and thalamic activity during sleep slow waves: Insights from a combined EEG-fMRI study. Sleep Med 2024; 113:357-369. [PMID: 38113618 DOI: 10.1016/j.sleep.2023.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 11/24/2023] [Accepted: 12/02/2023] [Indexed: 12/21/2023]
Abstract
INTRODUCTION Studies using scalp EEG have shown that slow waves (0.5-4 Hz), the most prominent hallmark of NREM sleep, undergo relevant changes from childhood to adulthood, mirroring brain structural modifications and the acquisition of cognitive skills. Here we used simultaneous EEG-fMRI to investigate the cortical and subcortical correlates of slow waves in school-age children and determine their relative developmental changes. METHODS We analyzed data from 14 school-age children with self-limited focal epilepsy of childhood who fell asleep during EEG-fMRI recordings. Brain regions associated with slow-wave occurrence were identified using a voxel-wise regression that also modelled interictal epileptic discharges and sleep spindles. At the group level, a mixed-effects linear model was used. The results were qualitatively compared with those obtained from 2 adolescents with epilepsy and 17 healthy adults. RESULTS Slow waves were associated with hemodynamic-signal decreases in bilateral somatomotor areas. Such changes extended more posteriorly relative to those in adults. Moreover, the involvement of areas belonging to the default mode network changes as a function of age. No significant hemodynamic responses were observed in subcortical structures. However, we identified a significant correlation between age and thalamic hemodynamic changes. CONCLUSIONS Present findings indicate that the somatomotor cortex may have a key role in slow-wave expression throughout the lifespan. At the same time, they are consistent with a posterior-to-anterior shift in slow-wave distribution mirroring brain maturational changes. Finally, our results suggest that slow-wave changes may not reflect only neocortical modifications but also the maturation of subcortical structures, including the thalamus.
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Affiliation(s)
- Damiana Bergamo
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | | | - Flavia Petruso
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy; Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Francesca Talami
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Dept., Azienda Ospedaliera Universitaria di Modena, Italy
| | | | - Francesca Benuzzi
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Anna Elisabetta Vaudano
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Dept., Azienda Ospedaliera Universitaria di Modena, Italy
| | - Stefano Meletti
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Dept., Azienda Ospedaliera Universitaria di Modena, Italy
| | - Giulio Bernardi
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Monica Betta
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy.
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Fabus MS, Sleigh JW, Warnaby CE. Effect of Propofol on Heart Rate and Its Coupling to Cortical Slow Waves in Humans. Anesthesiology 2024; 140:62-72. [PMID: 37801625 PMCID: PMC7615371 DOI: 10.1097/aln.0000000000004795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/08/2023]
Abstract
BACKGROUND Propofol causes significant cardiovascular depression and a slowing of neurophysiological activity. However, literature on its effect on the heart rate remains mixed, and it is not known whether cortical slow waves are related to cardiac activity in propofol anesthesia. METHODS The authors performed a secondary analysis of electrocardiographic and electroencephalographic data collected as part of a previously published study where n = 16 healthy volunteers underwent a slow infusion of propofol up to an estimated effect-site concentration of 4 µg/ml. Heart rate, heart rate variability, and individual slow electroencephalographic waves were extracted for each subject. Timing between slow-wave start and the preceding R-wave was tested against a uniform random surrogate. Heart rate data were further examined as a post hoc analysis in n = 96 members of an American Society of Anesthesiologists Physical Status II/III older clinical population collected as part of the AlphaMax trial. RESULTS The slow propofol infusion increased the heart rate in a dose-dependent manner (mean ± SD, increase of +4.2 ± 1.5 beats/min/[μg ml-1]; P < 0.001). The effect was smaller but still significant in the older clinical population. In healthy volunteers, propofol decreased the electrocardiogram R-wave amplitude (median [25th to 75th percentile], decrease of -83 [-245 to -28] μV; P < 0.001). Heart rate variability showed a loss of high-frequency parasympathetic activity. Individual cortical slow waves were coupled to the heartbeat. Heartbeat incidence peaked about 450 ms before slow-wave onset, and mean slow-wave frequency correlated with mean heart rate. CONCLUSIONS The authors observed a robust increase in heart rate with increasing propofol concentrations in healthy volunteers and patients. This was likely due to decreased parasympathetic cardioinhibition. Similar to non-rapid eye movement sleep, cortical slow waves are coupled to the cardiac rhythm, perhaps due to a common brainstem generator. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Marco S. Fabus
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Nuffield Division of Anaesthetics, University of Oxford, Oxford, United Kingdom
| | - Jamie W. Sleigh
- Department of Anaesthesiology, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Catherine E. Warnaby
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Nuffield Division of Anaesthetics, University of Oxford, Oxford, United Kingdom
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Miletínová E, Piorecký M, Koudelka V, Jiříček S, Tomeček D, Brunovský M, Horáček J, Bušková J. Alterations of sleep initiation in NREM parasomnia after sleep deprivation - A multimodal pilot study. Sleep Med X 2023; 6:100086. [PMID: 37745863 PMCID: PMC10511487 DOI: 10.1016/j.sleepx.2023.100086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/24/2023] [Accepted: 09/11/2023] [Indexed: 09/26/2023] Open
Abstract
Objectives NREM parasomnias also known as disorders of arousal (DOA) are characterised by abnormal motor and autonomic activation during arousals primarily from slow wave sleep. Dissociative state between sleep and wake is likely responsible for clinical symptoms of DOA. We therefore investigated potential dissociation outside of parasomnic events by using simultaneous 256-channel EEG (hdEEG) and functional magnetic resonance imaging (fMRI). Methods Eight DOA patients (3 women, mean age = 27.8; SD = 4.2) and 8 gender and age matched healthy volunteers (3 women, mean age = 26,5; SD = 4.0) were included into the study. They underwent 30-32 h of sleep deprivation followed by hdEEG and fMRI recording. We determined 2 conditions: falling asleep (FA) and arousal (A), that occurred outside of deep sleep and/or parasomnic event. We used multimodal approach using data obtained from EEG, fMRI and EEG-fMRI integration approach. Results DOA patients showed increase in delta and beta activity over postcentral gyrus and cuneus during awakening period. This group expressed increased connectivity between motor cortex and cingulate during arousals unrelated to parasomnic events in the beta frequency band. They also showed lower connectivity between different portions of cingulum. In contrast, the greater connectivity was found between thalamus and some cortical areas, such as occipital cortex. Conclusion Our findings suggest a complex alteration in falling asleep and arousal mechanisms at both subcortical and cortical levels in response to sleep deprivation. As this alteration is present also outside of slow wave sleep and/or parasomnic episodes we believe this could be a trait factor of DOA.
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Affiliation(s)
- E. Miletínová
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University in Prague, Ruská 87, Prague, Czech Republic
| | - M. Piorecký
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Department of Biomedical Technology, Faculty of Biomedical Engineering, CTU in Prague, Czech Republic
| | - V. Koudelka
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Department of Biomedical Technology, Faculty of Biomedical Engineering, CTU in Prague, Czech Republic
| | - S. Jiříček
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - D. Tomeček
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - M. Brunovský
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University in Prague, Ruská 87, Prague, Czech Republic
| | - J. Horáček
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University in Prague, Ruská 87, Prague, Czech Republic
| | - J. Bušková
- National Institute of Mental Health, Topolova 748, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University in Prague, Ruská 87, Prague, Czech Republic
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Somervail R, Cataldi J, Stephan AM, Siclari F, Iannetti GD. Dusk2Dawn: an EEGLAB plugin for automatic cleaning of whole-night sleep electroencephalogram using Artifact Subspace Reconstruction. Sleep 2023; 46:zsad208. [PMID: 37542730 DOI: 10.1093/sleep/zsad208] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 07/20/2023] [Indexed: 08/07/2023] Open
Abstract
Whole-night sleep electroencephalogram (EEG) is plagued by several types of large-amplitude artifacts. Common approaches to remove them are fraught with issues: channel interpolation, rejection of noisy intervals, and independent component analysis are time-consuming, rely on subjective user decisions, and result in signal loss. Artifact Subspace Reconstruction (ASR) is an increasingly popular approach to rapidly and automatically clean wake EEG data. Indeed, ASR adaptively removes large-amplitude artifacts regardless of their scalp topography or consistency throughout the recording. This makes ASR, at least in theory, a highly-promising tool to clean whole-night EEG. However, ASR crucially relies on calibration against a subset of relatively clean "baseline" data. This is problematic when the baseline changes substantially over time, as in whole-night EEG data. Here we tackled this issue and, for the first time, validated ASR for cleaning sleep EEG. We demonstrate that ASR applied out-of-the-box, with the parameters recommended for wake EEG, results in the dramatic removal of slow waves. We also provide an appropriate procedure to use ASR for automatic and rapid cleaning of whole-night sleep EEG data or any long EEG recording. Our procedure is freely available in Dusk2Dawn, an open-source plugin for EEGLAB.
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Affiliation(s)
- Richard Somervail
- Neuroscience and Behaviour Laboratory, Italian Institute of Technology (IIT), Rome, Italy
- Department of Neuroscience Physiology and Pharmacology, University College London (UCL), London, UK
| | - Jacinthe Cataldi
- Centre d'Investigation et de Recherche sur le Sommeil, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- The Sense Innovation and Research Center, Lausanne and Sion, Switzerland
| | - Aurélie M Stephan
- Centre d'Investigation et de Recherche sur le Sommeil, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- The Sense Innovation and Research Center, Lausanne and Sion, Switzerland
- Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Francesca Siclari
- Centre d'Investigation et de Recherche sur le Sommeil, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- The Sense Innovation and Research Center, Lausanne and Sion, Switzerland
- Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Gian Domenico Iannetti
- Neuroscience and Behaviour Laboratory, Italian Institute of Technology (IIT), Rome, Italy
- Department of Neuroscience Physiology and Pharmacology, University College London (UCL), London, UK
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12
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Andrillon T, Oudiette D. What is sleep exactly? Global and local modulations of sleep oscillations all around the clock. Neurosci Biobehav Rev 2023; 155:105465. [PMID: 37972882 DOI: 10.1016/j.neubiorev.2023.105465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 09/29/2023] [Accepted: 11/10/2023] [Indexed: 11/19/2023]
Abstract
Wakefulness, non-rapid eye-movement (NREM) and rapid eye-movement (REM) sleep differ from each other along three dimensions: behavioral, phenomenological, physiological. Although these dimensions often fluctuate in step, they can also dissociate. The current paradigm that views sleep as made of global NREM and REM states fail to account for these dissociations. This conundrum can be dissolved by stressing the existence and significance of the local regulation of sleep. We will review the evidence in animals and humans, healthy and pathological brains, showing different forms of local sleep and the consequences on behavior, cognition, and subjective experience. Altogether, we argue that the notion of local sleep provides a unified account for a host of phenomena: dreaming in REM and NREM sleep, NREM and REM parasomnias, intrasleep responsiveness, inattention and mind wandering in wakefulness. Yet, the physiological origins of local sleep or its putative functions remain unclear. Exploring further local sleep could provide a unique and novel perspective on how and why we sleep.
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Affiliation(s)
- Thomas Andrillon
- Paris Brain Institute, Sorbonne Université, Inserm-CNRS, Paris 75013, France; Monash Centre for Consciousness & Contemplative Studies, Monash University, Melbourne, VIC 3800, Australia.
| | - Delphine Oudiette
- Paris Brain Institute, Sorbonne Université, Inserm-CNRS, Paris 75013, France
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13
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Fan JM, Kudo K, Verma P, Ranasinghe KG, Morise H, Findlay AM, Vossel K, Kirsch HE, Raj A, Krystal AD, Nagarajan SS. Cortical Synchrony and Information Flow during Transition from Wakefulness to Light Non-Rapid Eye Movement Sleep. J Neurosci 2023; 43:8157-8171. [PMID: 37788939 PMCID: PMC10697405 DOI: 10.1523/jneurosci.0197-23.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 07/07/2023] [Accepted: 08/06/2023] [Indexed: 10/05/2023] Open
Abstract
Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.
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Affiliation(s)
- Joline M Fan
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
| | - Kiwamu Kudo
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
- Medical Imaging Center, Ricoh Company, Ltd., Kanazawa, Japan 243-0460
| | - Parul Verma
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Kamalini G Ranasinghe
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
| | - Hirofumi Morise
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
- Medical Imaging Center, Ricoh Company, Ltd., Kanazawa, Japan 243-0460
| | - Anne M Findlay
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Keith Vossel
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
- Mary S. Easton Center for Alzheimer's Disease Research, Department of Neurology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California 90095
| | - Heidi E Kirsch
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Ashish Raj
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Andrew D Krystal
- Department of Psychiatry, University of California-San Francisco, San Francisco, California 94143
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
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14
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Klar P, Çatal Y, Fogel S, Jocham G, Langner R, Owen AM, Northoff G. Auditory inputs modulate intrinsic neuronal timescales during sleep. Commun Biol 2023; 6:1180. [PMID: 37985812 PMCID: PMC10661171 DOI: 10.1038/s42003-023-05566-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 11/09/2023] [Indexed: 11/22/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) studies have demonstrated that intrinsic neuronal timescales (INT) undergo modulation by external stimulation during consciousness. It remains unclear if INT keep the ability for significant stimulus-induced modulation during primary unconscious states, such as sleep. This fMRI analysis addresses this question via a dataset that comprises an awake resting-state plus rest and stimulus states during sleep. We analyzed INT measured via temporal autocorrelation supported by median frequency (MF) in the frequency-domain. Our results were replicated using a biophysical model. There were two main findings: (1) INT prolonged while MF decreased from the awake resting-state to the N2 resting-state, and (2) INT shortened while MF increased during the auditory stimulus in sleep. The biophysical model supported these results by demonstrating prolonged INT in slowed neuronal populations that simulate the sleep resting-state compared to an awake state. Conversely, under sine wave input simulating the stimulus state during sleep, the model's regions yielded shortened INT that returned to the awake resting-state level. Our results highlight that INT preserve reactivity to stimuli in states of unconsciousness like sleep, enhancing our understanding of unconscious brain dynamics and their reactivity to stimuli.
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Affiliation(s)
- Philipp Klar
- Faculty of Mathematics and Natural Sciences, Institute of Experimental Psychology, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany.
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
| | - Yasir Çatal
- The Royal's Institute of Mental Health Research & University of Ottawa, Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Room 6435, Ottawa, ON, K1Z 7K4, Canada
| | - Stuart Fogel
- Sleep Unit, University of Ottawa Institute of Mental Health Research at The Royal, K1Z 7K4, Ottawa, ON, Canada
| | - Gerhard Jocham
- Faculty of Mathematics and Natural Sciences, Institute of Experimental Psychology, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany
| | - Robert Langner
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Adrian M Owen
- Departments of Physiology and Pharmacology and Psychology, Western University, London, ON, N6A 5B7, Canada
| | - Georg Northoff
- The Royal's Institute of Mental Health Research & University of Ottawa, Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Room 6435, Ottawa, ON, K1Z 7K4, Canada
- Centre for Cognition and Brain Disorders, Hangzhou Normal University, Tianmu Road 305, Hangzhou, Zhejiang Province, 310013, China
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15
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Esfahani MJ, Farboud S, Ngo HVV, Schneider J, Weber FD, Talamini LM, Dresler M. Closed-loop auditory stimulation of sleep slow oscillations: Basic principles and best practices. Neurosci Biobehav Rev 2023; 153:105379. [PMID: 37660843 DOI: 10.1016/j.neubiorev.2023.105379] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 08/25/2023] [Accepted: 08/30/2023] [Indexed: 09/05/2023]
Abstract
Sleep is essential for our physical and mental well-being. During sleep, despite the paucity of overt behavior, our brain remains active and exhibits a wide range of coupled brain oscillations. In particular slow oscillations are characteristic for sleep, however whether they are directly involved in the functions of sleep, or are mere epiphenomena, is not yet fully understood. To disentangle the causality of these relationships, experiments utilizing techniques to detect and manipulate sleep oscillations in real-time are essential. In this review, we first overview the theoretical principles of closed-loop auditory stimulation (CLAS) as a method to study the role of slow oscillations in the functions of sleep. We then describe technical guidelines and best practices to perform CLAS and analyze results from such experiments. We further provide an overview of how CLAS has been used to investigate the causal role of slow oscillations in various sleep functions. We close by discussing important caveats, open questions, and potential topics for future research.
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Affiliation(s)
| | - Soha Farboud
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands
| | - Hong-Viet V Ngo
- Department of Psychology, University of Essex, United Kingdom; Department of Psychology, University of Lübeck, Germany; Center for Brain, Behaviour and Metabolism, University of Lübeck, Germany
| | - Jules Schneider
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Germany; Department of Neurology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Germany
| | - Frederik D Weber
- Donders Institute for Brain, Cognition and Behaviour, Radboudumc, the Netherlands; Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Lucia M Talamini
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
| | - Martin Dresler
- Donders Institute for Brain, Cognition and Behaviour, Radboudumc, the Netherlands.
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16
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Ghibellini R, Meier B. Hypnagogic states are quite common: Self-reported prevalence, modalities, and gender differences. Conscious Cogn 2023; 115:103582. [PMID: 37812995 DOI: 10.1016/j.concog.2023.103582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 09/20/2023] [Accepted: 09/27/2023] [Indexed: 10/11/2023]
Abstract
The hypnagogic state refers to the transitional phase between wakefulness and sleep during which vivid experiences occur. In this questionnaire study, we assessed the self-reported prevalence of hypnagogic states considering the frequency of experiences in different modalities. We also assessed the emotional quality and the vividness of the experiences. Moreover, we compared hypnagogic states to other phenomena, such as dreams, sleep paralysis, imagination, and extra-sensory perception in these measures. Hypnagogic states were reported by 80.2 % of 4456 participants and were more prevalent in women than men. Experiences were most often kinaesthetic and visual, and less often auditory, tactile, and olfactory or gustatory. Hypnagogic states were less prevalent than dreams and characterized by different modality profiles. However, they were similar to dreams in their emotional quality, the irritation they caused, and in their vividness. In conclusion, hypnagogic states are quite common.
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Affiliation(s)
| | - Beat Meier
- Institute of Psychology, University of Bern, Switzerland
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17
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Biabani N, Birdseye A, Higgins S, Delogu A, Rosenzweig J, Cvetkovic Z, Nesbitt A, Drakatos P, Steier J, Kumari V, O’Regan D, Rosenzweig I. The neurophysiologic landscape of the sleep onset: a systematic review. J Thorac Dis 2023; 15:4530-4543. [PMID: 37691675 PMCID: PMC10482638 DOI: 10.21037/jtd-23-325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 07/21/2023] [Indexed: 09/12/2023]
Abstract
Background The sleep onset process is an ill-defined complex process of transition from wakefulness to sleep, characterized by progressive modifications at the subjective, behavioural, cognitive, and physiological levels. To this date, there is no international consensus which could aid a principled characterisation of this process for clinical research purposes. The current review aims to systemise the current knowledge about the underlying mechanisms of the natural heterogeneity of this process. Methods In this systematic review, studies investigating the process of the sleep onset from 1970 to 2022 were identified using electronic database searches of PsychINFO, MEDLINE, and Embase. Results A total of 139 studies were included; 110 studies in healthy participants and 29 studies in participants with sleep disorders. Overall, there is a limited consensus across a body of research about what distinct biomarkers of the sleep onset constitute. Only sparse data exists on the physiology, neurophysiology and behavioural mechanisms of the sleep onset, with majority of studies concentrating on the non-rapid eye movement stage 2 (NREM 2) as a potentially better defined and a more reliable time point that separates sleep from the wake, on the sleep wake continuum. Conclusions The neurophysiologic landscape of sleep onset bears a complex pattern associated with a multitude of behavioural and physiological markers and remains poorly understood. The methodological variation and a heterogenous definition of the wake-sleep transition in various studies to date is understandable, given that sleep onset is a process that has fluctuating and ill-defined boundaries. Nonetheless, the principled characterisation of the sleep onset process is needed which will allow for a greater conceptualisation of the mechanisms underlying this process, further influencing the efficacy of current treatments for sleep disorders.
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Affiliation(s)
- Nazanin Biabani
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
| | - Adam Birdseye
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Sean Higgins
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Alessio Delogu
- James Black Centre, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
| | - Jan Rosenzweig
- Department of Engineering, King’s College London, London, UK
| | - Zoran Cvetkovic
- Department of Engineering, King’s College London, London, UK
| | - Alexander Nesbitt
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
- Department of Neurology, Guy’s Hospital, Guy’s and St. Thomas’ NHS Foundation Trust, London, UK
| | - Panagis Drakatos
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
- School of Basic and Medical Biosciences, Faculty of Life Science and Medicine, King’s College London, London, UK
| | - Joerg Steier
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
- School of Basic and Medical Biosciences, Faculty of Life Science and Medicine, King’s College London, London, UK
| | - Veena Kumari
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
- Centre for Cognitive Neuroscience (CCN), College of Health, Medicine and Life Sciences, Brunel University London, London, UK
| | - David O’Regan
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
- School of Basic and Medical Biosciences, Faculty of Life Science and Medicine, King’s College London, London, UK
| | - Ivana Rosenzweig
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
- Sleep Disorders Centre, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
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18
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Ngomba RT, Lüttjohann A, Dexter A, Ray S, van Luijtelaar G. The Metabotropic Glutamate 5 Receptor in Sleep and Wakefulness: Focus on the Cortico-Thalamo-Cortical Oscillations. Cells 2023; 12:1761. [PMID: 37443795 PMCID: PMC10341329 DOI: 10.3390/cells12131761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 06/17/2023] [Accepted: 06/27/2023] [Indexed: 07/15/2023] Open
Abstract
Sleep is an essential innate but complex behaviour which is ubiquitous in the animal kingdom. Our knowledge of the distinct neural circuit mechanisms that regulate sleep and wake states in the brain are, however, still limited. It is therefore important to understand how these circuits operate during health and disease. This review will highlight the function of mGlu5 receptors within the thalamocortical circuitry in physiological and pathological sleep states. We will also evaluate the potential of targeting mGlu5 receptors as a therapeutic strategy for sleep disorders that often co-occur with epileptic seizures.
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Affiliation(s)
| | - Annika Lüttjohann
- Institute of Physiology I, University of Münster, 48149 Münster, Germany
| | - Aaron Dexter
- School of Pharmacy, University of Lincoln, Lincoln LN6 7DL, UK
| | - Swagat Ray
- Department of Life Sciences, School of Life and Environmental Sciences, University of Lincoln, Lincoln LN6 7DL, UK
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19
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Castelnovo A, Lividini A, Riedner BA, Avvenuti G, Jones SG, Miano S, Tononi G, Manconi M, Bernardi G. Origin, synchronization, and propagation of sleep slow waves in children. Neuroimage 2023; 274:120133. [PMID: 37094626 DOI: 10.1016/j.neuroimage.2023.120133] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 03/30/2023] [Accepted: 04/21/2023] [Indexed: 04/26/2023] Open
Abstract
STUDY OBJECTIVES Sleep slow wave activity, as measured using EEG delta power (<4 Hz), undergoes significant changes throughout development, mirroring changes in brain function and anatomy. Yet, age-dependent variations in the characteristics of individual slow waves have not been thoroughly investigated. Here we aimed at characterizing individual slow wave properties such as origin, synchronization, and cortical propagation at the transition between childhood and adulthood. METHODS We analyzed overnight high-density (256 electrodes) EEG recordings of healthy typically developing children (N=21, 10.3±1.5 years old) and young healthy adults (N=18, 31.1±4.4 years old). All recordings were preprocessed to reduce artifacts, and NREM slow waves were detected and characterized using validated algorithms. The threshold for statistical significance was set at p=0.05. RESULTS The slow waves of children were larger and steeper, but less widespread than those of adults. Moreover, they tended to mainly originate from and spread over more posterior brain areas. Relative to those of adults, the slow waves of children also displayed a tendency to more strongly involve and originate from the right than the left hemisphere. The separate analysis of slow waves characterized by high and low synchronization efficiency showed that these waves undergo partially distinct maturation patterns, consistent with their possible dependence on different generation and synchronization mechanisms. CONCLUSIONS Changes in slow wave origin, synchronization, and propagation at the transition between childhood and adulthood are consistent with known modifications in cortico-cortical and subcortico-cortical brain connectivity. In this light, changes in slow-wave properties may provide a valuable yardstick to assess, track, and interpret physiological and pathological development.
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Affiliation(s)
- Anna Castelnovo
- Sleep Medicine Unit, Neurocenter of Southern Switzerland, Ospedale Civico, Lugano, Switzerland; Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland; University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
| | - Althea Lividini
- Epilepsy Center - Sleep Medicine Center, Childhood and Adolescence Neuropsychiatry Unit, ASST SS. Paolo e Carlo, San Paolo Hospital, Milan, Italy
| | - Brady A Riedner
- Center for Sleep and Consciousness, Department of Psychiatry, University of Wisconsin - Madison, Madison, WI, USA
| | - Giulia Avvenuti
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Stephanie G Jones
- Department of Psychiatry, Wisconsin Institute for Sleep and Consciousness, University of Wisconsin-Madison(,) Madison, WI, USA
| | - Silvia Miano
- Sleep Medicine Unit, Neurocenter of Southern Switzerland, Ospedale Civico, Lugano, Switzerland; Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - Giulio Tononi
- Department of Psychiatry, Wisconsin Institute for Sleep and Consciousness, University of Wisconsin-Madison(,) Madison, WI, USA
| | - Mauro Manconi
- Sleep Medicine Unit, Neurocenter of Southern Switzerland, Ospedale Civico, Lugano, Switzerland; Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland; Department of Neurology, University Hospital, Inselspital, Bern, Switzerland
| | - Giulio Bernardi
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy.
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20
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Brodt S, Inostroza M, Niethard N, Born J. Sleep-A brain-state serving systems memory consolidation. Neuron 2023; 111:1050-1075. [PMID: 37023710 DOI: 10.1016/j.neuron.2023.03.005] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/23/2023] [Accepted: 03/06/2023] [Indexed: 04/08/2023]
Abstract
Although long-term memory consolidation is supported by sleep, it is unclear how it differs from that during wakefulness. Our review, focusing on recent advances in the field, identifies the repeated replay of neuronal firing patterns as a basic mechanism triggering consolidation during sleep and wakefulness. During sleep, memory replay occurs during slow-wave sleep (SWS) in hippocampal assemblies together with ripples, thalamic spindles, neocortical slow oscillations, and noradrenergic activity. Here, hippocampal replay likely favors the transformation of hippocampus-dependent episodic memory into schema-like neocortical memory. REM sleep following SWS might balance local synaptic rescaling accompanying memory transformation with a sleep-dependent homeostatic process of global synaptic renormalization. Sleep-dependent memory transformation is intensified during early development despite the immaturity of the hippocampus. Overall, beyond its greater efficacy, sleep consolidation differs from wake consolidation mainly in that it is supported, rather than impaired, by spontaneous hippocampal replay activity possibly gating memory formation in neocortex.
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Affiliation(s)
- Svenja Brodt
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany; Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
| | - Marion Inostroza
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Niels Niethard
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Jan Born
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany; Werner Reichert Center for Integrative Neuroscience, University of Tübingen, Tübingen, Germany.
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21
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Milosavljevic S, Smith AK, Wright CJ, Valafar H, Pocivavsek A. Kynurenine aminotransferase II inhibition promotes sleep and rescues impairments induced by neurodevelopmental insult. Transl Psychiatry 2023; 13:106. [PMID: 37002202 PMCID: PMC10066394 DOI: 10.1038/s41398-023-02399-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 03/14/2023] [Accepted: 03/16/2023] [Indexed: 04/03/2023] Open
Abstract
Dysregulated sleep is commonly reported in individuals with neuropsychiatric disorders, including schizophrenia (SCZ) and bipolar disorder (BPD). Physiology and pathogenesis of these disorders points to aberrant metabolism, during neurodevelopment and adulthood, of tryptophan via the kynurenine pathway (KP). Kynurenic acid (KYNA), a neuroactive KP metabolite derived from its precursor kynurenine by kynurenine aminotransferase II (KAT II), is increased in the brains of individuals with SCZ and BPD. We hypothesize that elevated KYNA, an inhibitor of glutamatergic and cholinergic neurotransmission, contributes to sleep dysfunction. Employing the embryonic kynurenine (EKyn) paradigm to elevate fetal brain KYNA, we presently examined pharmacological inhibition of KAT II to reduce KYNA in adulthood to improve sleep quality. Pregnant Wistar rats were fed either kynurenine (100 mg/day)(EKyn) or control (ECon) diet from embryonic day (ED) 15 to ED 22. Adult male (N = 24) and female (N = 23) offspring were implanted with devices to record electroencephalogram (EEG) and electromyogram (EMG) telemetrically for sleep-wake data acquisition. Each subject was treated with either vehicle or PF-04859989 (30 mg/kg, s.c.), an irreversible KAT II inhibitor, at zeitgeber time (ZT) 0 or ZT 12. KAT II inhibitor improved sleep architecture maintaining entrainment of the light-dark cycle; ZT 0 treatment with PF-04859989 induced transient improvements in rapid eye movement (REM) and non-REM (NREM) sleep during the immediate light phase, while the impact of ZT 12 treatment was delayed until the subsequent light phase. PF-04859989 administration at ZT 0 enhanced NREM delta spectral power and reduced activity and body temperature. In conclusion, reducing de novo KYNA production alleviated sleep disturbances and increased sleep quality in EKyn, while also improving sleep outcomes in ECon offspring. Our findings place attention on KAT II inhibition as a novel mechanistic approach to treating disrupted sleep behavior with potential translational implications for patients with neurodevelopmental and neuropsychiatric disorders.
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Affiliation(s)
- Snezana Milosavljevic
- Department of Pharmacology, Physiology and Neuroscience, University of South Carolina School of Medicine, Columbia, SC, USA
| | - Andrew K Smith
- Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA
| | - Courtney J Wright
- Department of Pharmacology, Physiology and Neuroscience, University of South Carolina School of Medicine, Columbia, SC, USA
| | - Homayoun Valafar
- Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA
| | - Ana Pocivavsek
- Department of Pharmacology, Physiology and Neuroscience, University of South Carolina School of Medicine, Columbia, SC, USA.
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22
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Ghibellini R, Meier B. The hypnagogic state: A brief update. J Sleep Res 2023; 32:e13719. [PMID: 36017720 PMCID: PMC10078162 DOI: 10.1111/jsr.13719] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/07/2022] [Accepted: 08/07/2022] [Indexed: 02/03/2023]
Abstract
The hypnagogic state refers to a transitional stage between wakefulness and sleep, in which sensory perceptions can be experienced. In this review, we compile and discuss the recent scientific literature on hypnagogia research regarding the future directions proposed by Schacter (1976; Psychological Bulletin, 83, 452). After a short introduction discussing the terminology used in hypnagogia research and the differentiation of hypnagogic states with other related phenomena, we review the reported prevalence of hypnagogic states. Then, we evaluate the six future directions suggested by Schacter and we propose three further future directions. First, a better understanding of the emotional quality of hypnagogic states is needed. Second, a better understanding of why hypnagogic states occur so frequently in the visual and kinaesthetic modalities is needed. Lastly, a better understanding of the purpose of hypnagogic states is needed. In conclusion, research has made great progress in recent years, and we are one step closer to demystifying the hypnagogic state.
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Affiliation(s)
| | - Beat Meier
- Institute of Psychology, University of Bern, Bern, Switzerland
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23
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Abdellahi MEA, Koopman ACM, Treder MS, Lewis PA. Targeting targeted memory reactivation: Characteristics of cued reactivation in sleep. Neuroimage 2023; 266:119820. [PMID: 36535324 DOI: 10.1016/j.neuroimage.2022.119820] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 11/16/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022] Open
Abstract
Targeted memory reactivation (TMR) is a technique in which sensory cues associated with memories during wake are used to trigger memory reactivation during subsequent sleep. The characteristics of such cued reactivation, and the optimal placement of TMR cues, remain to be determined. We built an EEG classification pipeline that discriminated reactivation of right- and left-handed movements and found that cues which fall on the up-going transition of the slow oscillation (SO) are more likely to elicit a classifiable reactivation. We also used a novel machine learning pipeline to predict the likelihood of eliciting a classifiable reactivation after each TMR cue using the presence of spindles and features of SOs. Finally, we found that reactivations occurred either immediately after the cue or one second later. These findings greatly extend our understanding of memory reactivation and pave the way for development of wearable technologies to efficiently enhance memory through cueing in sleep.
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Affiliation(s)
- Mahmoud E A Abdellahi
- School of Psychology, Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff CF24 4HQ, United Kingdom.
| | - Anne C M Koopman
- School of Psychology, Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff CF24 4HQ, United Kingdom
| | - Matthias S Treder
- School of Computer Science and Informatics, Cardiff University, Cardiff CF24 3AA, United Kingdom
| | - Penelope A Lewis
- School of Psychology, Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff CF24 4HQ, United Kingdom
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24
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EEG cortical activity and connectivity correlates of early sympathetic response during cold pressor test. Sci Rep 2023; 13:1338. [PMID: 36693870 PMCID: PMC9873641 DOI: 10.1038/s41598-023-27480-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 01/03/2023] [Indexed: 01/25/2023] Open
Abstract
Previous studies have identified several brain regions involved in the sympathetic response and its integration with pain, cognition, emotions and memory processes. However, little is known about how such regions dynamically interact during a sympathetic activation task. In this study, we analyzed EEG activity and effective connectivity during a cold pressor test (CPT). A source localization analysis identified a network of common active sources including the right precuneus (r-PCu), right and left precentral gyri (r-PCG, l-PCG), left premotor cortex (l-PMC) and left anterior cingulate cortex (l-ACC). We comprehensively analyzed the network dynamics by estimating power variation and causal interactions among the network regions through the direct directed transfer function (dDTF). A connectivity pattern dominated by interactions in [Formula: see text] (8-12) Hz band was observed in the resting state, with r-PCu acting as the main hub of information flow. After the CPT onset, we observed an abrupt suppression of such [Formula: see text]-band interactions, followed by a partial recovery towards the end of the task. On the other hand, an increase of [Formula: see text]-band (1-4) Hz interactions characterized the first part of CPT task. These results provide novel information on the brain dynamics induced by sympathetic stimuli. Our findings suggest that the observed suppression of [Formula: see text] and rise of [Formula: see text] dynamical interactions could reflect non-pain-specific arousal and attention-related response linked to stimulus' salience.
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25
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Lafrenière A, Lina JM, Hernandez J, Bouchard M, Gosselin N, Carrier J. Sleep slow waves' negative-to-positive-phase transition: a marker of cognitive and apneic status in aging. Sleep 2023; 46:zsac246. [PMID: 36219687 PMCID: PMC9832517 DOI: 10.1093/sleep/zsac246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 08/12/2022] [Indexed: 11/07/2022] Open
Abstract
The sleep slow-wave (SW) transition between negative and positive phases is thought to mirror synaptic strength and likely depends on brain health. This transition shows significant age-related changes but has not been investigated in pathological aging. The present study aimed at comparing the transition speed and other characteristics of SW between older adults with amnestic mild cognitive impairment (aMCI) and cognitively normal (CN) controls with and without obstructive sleep apnea (OSA). We also examined the association of SW characteristics with the longitudinal changes of episodic memory and executive functions and the degree of subjective cognitive complaints. aMCI (no/mild OSA = 17; OSA = 15) and CN (no/mild OSA = 20; OSA = 17) participants underwent a night of polysomnography and a neuropsychological evaluation at baseline and 18 months later. Participants with aMCI had a significantly slower SW negative-to-positive-phase transition speed and a higher proportion of SW that are "slow-switchers" than CN participants. These SW measures in the frontal region were significantly correlated with memory decline and cognitive complaints in aMCI and cognitive improvements in CN participants. The transition speed of the SW that are "fast-switchers" was significantly slower in OSA compared to no or mild obstructive sleep apnea participants. The SW transition-related metrics showed opposite correlations with the longitudinal episodic memory changes depending on the participants' cognitive status. These relationships were particularly strong in participants with aMCI. As the changes of the SW transition-related metrics in pathological aging might reflect synaptic alterations, future studies should investigate whether these new metrics covary with biomarker levels of synaptic integrity in this population.
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Affiliation(s)
- Alexandre Lafrenière
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
- Department of Psychology, Université de Montréal, Montreal, Canada
| | - Jean-Marc Lina
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
- Department of Electrical Engineering, École de Technologie Supérieure, Montreal, Canada
- Centre de Recherches Mathématiques, Université de Montréal, Montreal, Canada
| | - Jimmy Hernandez
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
- Department of Neurosciences, Université de Montréal, Montreal, Canada
| | - Maude Bouchard
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
| | - Nadia Gosselin
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
- Department of Psychology, Université de Montréal, Montreal, Canada
| | - Julie Carrier
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Canada
- Department of Psychology, Université de Montréal, Montreal, Canada
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Yoshida K, Toyoizumi T. Information maximization explains state-dependent synaptic plasticity and memory reorganization during non-rapid eye movement sleep. PNAS NEXUS 2022; 2:pgac286. [PMID: 36712943 PMCID: PMC9833047 DOI: 10.1093/pnasnexus/pgac286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022]
Abstract
Slow waves during the non-rapid eye movement (NREM) sleep reflect the alternating up and down states of cortical neurons; global and local slow waves promote memory consolidation and forgetting, respectively. Furthermore, distinct spike-timing-dependent plasticity (STDP) operates in these up and down states. The contribution of different plasticity rules to neural information coding and memory reorganization remains unknown. Here, we show that optimal synaptic plasticity for information maximization in a cortical neuron model provides a unified explanation for these phenomena. The model indicates that the optimal synaptic plasticity is biased toward depression as the baseline firing rate increases. This property explains the distinct STDP observed in the up and down states. Furthermore, it explains how global and local slow waves predominantly potentiate and depress synapses, respectively, if the background firing rate of excitatory neurons declines with the spatial scale of waves as the model predicts. The model provides a unifying account of the role of NREM sleep, bridging neural information coding, synaptic plasticity, and memory reorganization.
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27
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Fasano A, Biancardi C, Masi G, Della Vecchia S, Frumento P, Mazzoni A, Falotico E, Faraguna U, Sicca F. Maximum downward slope of sleep slow waves as a potential marker of attention-deficit/hyperactivity disorder clinical phenotypes. J Psychiatr Res 2022; 156:679-689. [PMID: 36399860 DOI: 10.1016/j.jpsychires.2022.10.057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 08/25/2022] [Accepted: 10/28/2022] [Indexed: 11/11/2022]
Abstract
BACKGROUND Attention-Deficit/Hyperactivity Disorder (ADHD) is a highly heterogeneous diagnostic category, encompassing several endophenotypes and comorbidities, including sleep problems. However, no predictor of clinical long-term trajectories or comorbidity has yet been established. Sleep EEG has been proposed as a potential tool for evaluating the synaptic strength during development, as well as the cortical thickness, which is presumed to be altered in ADHD. We investigated whether the slope of the Slow Waves (SWs), a microstructural parameter of the sleep EEG, was a potential predictive parameter for psychiatric comorbidities and neuropsychological dimensions in ADHD. METHODS 70 children (58 m; 8.76 ± 2.77 y) with ADHD who underwent psychiatric and neurologic evaluations and a standard EEG recording during naps were investigated. After sleep EEG analysis, we grouped the extracted SWs in bins of equal amplitude and then measured the associations, through generalized linear regression, between their maximum downward slopes (MDS) and the individual scores obtained from clinical rating scales. RESULTS The presence of Multiple Anxiety Disorders was positively associated with MDS of medium amplitude SWs in temporo-posterior left areas. The Child Behavior Checklist scores showed negative associations in the same areas for small SWs. The presence of autistic traits was positively associated with MDS of high amplitude SWs in bilateral anterior and temporal left areas. The WISC-IV Processing Speed Index showed negative associations with MDS of small-to-medium SWs in anterior and temporal right areas, while positive associations in posterior and temporal left areas. CONCLUSIONS Consistency of association clusters' localization on the scalp suggests that variations in the local MDS, revealing alterations of local synaptic strength and/or in daytime use of certain cortical circuits, could underlie specific neurodevelopmental trajectories resulting in different ADHD clinical phenotypes.
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Affiliation(s)
- Alessio Fasano
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
| | - Carlo Biancardi
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy.
| | - Gabriele Masi
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | | | - Paolo Frumento
- Department of Political Sciences, University of Pisa, Pisa, Italy
| | - Alberto Mazzoni
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Egidio Falotico
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Ugo Faraguna
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy; Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Pisa, Italy
| | - Federico Sicca
- Child and Adolescent Epilepsy and Clinical Neurophysiology Departmental Unit, USL Centro Toscana, 59100, Prato, Italy
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28
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Ruch S, Schmidig FJ, Knüsel L, Henke K. Closed-loop modulation of local slow oscillations in human NREM sleep. Neuroimage 2022; 264:119682. [PMID: 36240988 DOI: 10.1016/j.neuroimage.2022.119682] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 10/10/2022] [Accepted: 10/11/2022] [Indexed: 11/07/2022] Open
Abstract
Slow-wave sleep is the deep non-rapid eye-movement (NREM) sleep stage that is most relevant for the recuperative function of sleep. Its defining property is the presence of slow oscillations (<2 Hz) in the scalp electroencephalogram (EEG). Slow oscillations are generated by a synchronous back and forth between highly active UP-states and silent DOWN-states in neocortical neurons. Growing evidence suggests that closed-loop sensory stimulation targeted at UP-states of EEG-defined slow oscillations can enhance the slow oscillatory activity, increase sleep depth, and boost sleep's recuperative functions. However, several studies failed to replicate such findings. Failed replications might be due to the use of conventional closed-loop stimulation algorithms that analyze the signal from one single electrode and thereby neglect the fact that slow oscillations vary with respect to their origins, distributions, and trajectories on the scalp. In particular, conventional algorithms nonspecifically target functionally heterogeneous UP-states of distinct origins. After all, slow oscillations at distinct sites of the scalp have been associated with distinct functions. Here we present a novel EEG-based closed-loop stimulation algorithm that allows targeting UP- and DOWN-states of distinct cerebral origins based on topographic analyses of the EEG: the topographic targeting of slow oscillations (TOPOSO) algorithm. We present evidence that the TOPOSO algorithm can detect and target local slow oscillations with specific, predefined voltage maps on the scalp in real-time. When compared to a more conventional, single-channel-based approach, TOPOSO leads to fewer but locally more specific stimulations in a simulation study. In a validation study with napping participants, TOPOSO targets auditory stimulation reliably at local UP-states over frontal, sensorimotor, and centro-parietal regions. Importantly, auditory stimulation temporarily enhanced the targeted local state. However, stimulation then elicited a standard frontal slow oscillation rather than local slow oscillations. The TOPOSO algorithm is suitable for the modulation and the study of the functions of local slow oscillations.
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Affiliation(s)
- Simon Ruch
- Institute for Neuromodulation and Neurotechnology, Department of Neurosurgery and Neurotechnology, University Hospital and University of Tuebingen, Otfried-Müller-Str. 45, Tübingen 72076, Germany; Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland.
| | - Flavio Jean Schmidig
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
| | - Leona Knüsel
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
| | - Katharina Henke
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Fabrikstrasse 8, 3012 Bern, Switzerland
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29
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Abstract
The conventional wisdom that sleep is a global state, affecting the whole brain uniformly and simultaneously, was overturned by the discovery of local sleep, where individual neuronal populations were found to be asleep and the rest of the brain awake. However, due to the difficulty of monitoring local neuronal states in humans, our understanding of local sleep remains limited. Using simultaneous functional MRI (fMRI) and electroencephalography, we find that the oscillations of brain hemodynamic activity provide signatures of sleep at a local neuronal population level. We show that the fMRI signatures of sleep can be employed to monitor local neuronal states and investigate which brain regions are the first to fall asleep or wake up at wake–sleep transitions. Sleep can be distinguished from wake by changes in brain electrical activity, typically assessed using electroencephalography (EEG). The hallmark of nonrapid-eye-movement (NREM) sleep is the shift from high-frequency, low-amplitude wake EEG to low-frequency, high-amplitude sleep EEG dominated by spindles and slow waves. Here we identified signatures of sleep in brain hemodynamic activity, using simultaneous functional MRI (fMRI) and EEG. We found that, at the transition from wake to sleep, fMRI blood oxygen level–dependent (BOLD) activity evolved from a mixed-frequency pattern to one dominated by two distinct oscillations: a low-frequency (<0.1 Hz) oscillation prominent in light sleep and correlated with the occurrence of spindles, and a high-frequency oscillation (>0.1 Hz) prominent in deep sleep and correlated with the occurrence of slow waves. The two oscillations were both detectable across the brain but exhibited distinct spatiotemporal patterns. During the falling-asleep process, the low-frequency oscillation first appeared in the thalamus, then the posterior cortex, and lastly the frontal cortex, while the high-frequency oscillation first appeared in the midbrain, then the frontal cortex, and lastly the posterior cortex. During the waking-up process, both oscillations disappeared first from the thalamus, then the frontal cortex, and lastly the posterior cortex. The BOLD oscillations provide local signatures of spindle and slow wave activity. They may be employed to monitor the regional occurrence of sleep or wakefulness, track which regions are the first to fall asleep or wake up at the wake–sleep transitions, and investigate local homeostatic sleep processes.
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30
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Katsuki F, Gerashchenko D, Brown RE. Alterations of sleep oscillations in Alzheimer's disease: A potential role for GABAergic neurons in the cortex, hippocampus, and thalamus. Brain Res Bull 2022; 187:181-198. [PMID: 35850189 DOI: 10.1016/j.brainresbull.2022.07.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 06/01/2022] [Accepted: 07/06/2022] [Indexed: 02/07/2023]
Abstract
Sleep abnormalities are widely reported in patients with Alzheimer's disease (AD) and are linked to cognitive impairments. Sleep abnormalities could be potential biomarkers to detect AD since they are often observed at the preclinical stage. Moreover, sleep could be a target for early intervention to prevent or slow AD progression. Thus, here we review changes in brain oscillations observed during sleep, their connection to AD pathophysiology and the role of specific brain circuits. Slow oscillations (0.1-1 Hz), sleep spindles (8-15 Hz) and their coupling during non-REM sleep are consistently reduced in studies of patients and in AD mouse models although the timing and magnitude of these alterations depends on the pathophysiological changes and the animal model studied. Changes in delta (1-4 Hz) activity are more variable. Animal studies suggest that hippocampal sharp-wave ripples (100-250 Hz) are also affected. Reductions in REM sleep amount and slower oscillations during REM are seen in patients but less consistently in animal models. Thus, changes in a variety of sleep oscillations could impact sleep-dependent memory consolidation or restorative functions of sleep. Recent mechanistic studies suggest that alterations in the activity of GABAergic neurons in the cortex, hippocampus and thalamic reticular nucleus mediate sleep oscillatory changes in AD and represent a potential target for intervention. Longitudinal studies of the timing of AD-related sleep abnormalities with respect to pathology and dysfunction of specific neural networks are needed to identify translationally relevant biomarkers and guide early intervention strategies to prevent or delay AD progression.
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Affiliation(s)
- Fumi Katsuki
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA.
| | - Dmitry Gerashchenko
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA
| | - Ritchie E Brown
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA
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31
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Cataldi J, Stephan AM, Marchi NA, Haba-Rubio J, Siclari F. Abnormal timing of slow wave synchronization processes in non-rapid eye movement sleep parasomnias. Sleep 2022; 45:6591470. [PMID: 35641120 DOI: 10.1093/sleep/zsac111] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 04/06/2022] [Indexed: 01/29/2023] Open
Abstract
STUDY OBJECTIVES Sleepwalking, confusional arousals, and sleep terrors are parasomnias occurring out of non-rapid eye movement (NREM) sleep. Several previous studies have described EEG changes associated with NREM parasomnia episodes, but it remains unclear whether these changes are specific to parasomnia episodes or whether they are part of the normal awakening process. Here we directly compared regional brain activity, measured with high-density (hd-) EEG, between parasomnia episodes and normal awakenings (without behavioral manifestations of parasomnia). METHODS Twenty adult patients with non-rapid eye movement parasomnias underwent a baseline hd-EEG recording (256 electrodes) followed by a recovery sleep recording after 25 h of total sleep deprivation, during which auditory stimuli were administered to provoke parasomnia episodes. RESULTS Both normal awakenings (n = 25) and parasomnia episodes (n = 96) were preceded by large, steep, and "K-complex-like" slow waves in frontal and central brain regions, and by a concomitant increase in high-frequency EEG (beta) activity. Compared to normal awakenings, parasomnia episodes occurred on a less activated EEG background and displayed higher slow wave activity (SWA) and lower beta activity in frontal and central brain regions after movement onset. CONCLUSIONS Our results suggest that non-rapid eye movement awakenings, irrespective of behavioral manifestations of parasomnia episodes, involve an arousal-related slow wave synchronization process that predominantly recruits frontal and central brain areas. In parasomnia episodes, this synchronization process comes into play abnormally during periods of high SWA and is associated with higher SWA after movement onset. Thus, an abnormal timing of arousal-related slow wave synchronization processes could underlie the occurrence of NREM parasomnias.
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Affiliation(s)
- Jacinthe Cataldi
- Center for Investigation and Research on Sleep, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland.,The Sense Innovation and Research Center, Lausanne and Sion, Switzerland
| | - Aurélie M Stephan
- Center for Investigation and Research on Sleep, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland.,The Sense Innovation and Research Center, Lausanne and Sion, Switzerland
| | - Nicola A Marchi
- Center for Investigation and Research on Sleep, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland
| | - José Haba-Rubio
- Center for Investigation and Research on Sleep, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland
| | - Francesca Siclari
- Center for Investigation and Research on Sleep, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland.,The Sense Innovation and Research Center, Lausanne and Sion, Switzerland.,Department of Clinical Neurosciences, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland
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32
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Iinuma Y, Nobukawa S, Nishimura H, Takahashi T. Dynamic Characteristics of State Transitions Composed of Neural Activity in the Brain by Circadian Rhythms. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:152-157. [PMID: 36085992 DOI: 10.1109/embc48229.2022.9871057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In recent years, as a treatment for mental disorders in addition to drug treatment, a non-drug treatment called chronotherapy has been attracting attention. However, the achievement of optimized chronotherapy for each subject's condition requires that the disturbance of the patient's circadian rhythm must be captured over a long duration. Therefore, it is necessary to develop biomarkers that are easy to measure, quantitative, and continuously measured. Complexity analysis of electroencephalograms revealed specific patterns related to circadian rhythms. However, such complexity analysis cannot capture variability in spatial patterns, although moment-to-moment temporal dynamic characteristics can be captured. Therefore, it is necessary to evaluate the dynamic characteristics of the interaction of neural activity throughout the brain. To evaluate the dynamic whole-brain interaction, we proposed a new microstate approach based on the instantaneous frequency distribution. In this context, we hypothesized that it would be possible to detect circadian rhythms using the microstate approach. In this study, to clarify the dynamic interactions of the entire neural network of the brain by circadian rhythms, we measured EEG data at day and night, and detected dynamic state transitions based on the instantaneous frequency distribution of the whole brain from EEG. The results showed the probability of transition among region-specific phase-leading states related to circadian rhythms. This finding might be widely utilized to detect circadian rhythms in healthy and pathological conditions.
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33
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Decat N, Walter J, Koh ZH, Sribanditmongkol P, Fulcher BD, Windt JM, Andrillon T, Tsuchiya N. Beyond traditional sleep scoring: Massive feature extraction and data-driven clustering of sleep time series. Sleep Med 2022; 98:39-52. [PMID: 35779380 DOI: 10.1016/j.sleep.2022.06.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 05/23/2022] [Accepted: 06/02/2022] [Indexed: 11/30/2022]
Abstract
The widely used guidelines for sleep staging were developed for the visual inspection of electrophysiological recordings by the human eye. As such, these rules reflect a limited range of features in these data and are therefore restricted in accurately capturing the physiological changes associated with sleep. Here we present a novel analysis framework that extensively characterizes sleep dynamics using over 7700 time-series features from the hctsa software. We used clustering to categorize sleep epochs based on the similarity of their time-series features, without relying on established scoring conventions. The resulting sleep structure overlapped substantially with that defined by visual scoring. However, we also observed discrepancies between our approach and traditional scoring. This divergence principally stemmed from the extensive characterization by hctsa features, which captured distinctive time-series properties within the traditionally defined sleep stages that are overlooked with visual scoring. Lastly, we report time-series features that are highly discriminative of stages. Our framework lays the groundwork for a data-driven exploration of sleep sub-stages and has significant potential to identify new signatures of sleep disorders and conscious sleep states.
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Affiliation(s)
- Nicolas Decat
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Jasmine Walter
- Philosophy Department, Monash Centre for Consciousness and Contemplative Studies, Monash University, Melbourne, Victoria, Australia; Monash Centre for Consciousness and Contemplative Studies, Monash University, Melbourne, Victoria, Australia
| | - Zhao H Koh
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Piengkwan Sribanditmongkol
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Ben D Fulcher
- School of Physics, University of Sydney, Sydney, NSW, Australia
| | - Jennifer M Windt
- Philosophy Department, Monash Centre for Consciousness and Contemplative Studies, Monash University, Melbourne, Victoria, Australia; Monash Centre for Consciousness and Contemplative Studies, Monash University, Melbourne, Victoria, Australia
| | - Thomas Andrillon
- Philosophy Department, Monash Centre for Consciousness and Contemplative Studies, Monash University, Melbourne, Victoria, Australia; Paris Brain Institute, Sorbonne Université, Inserm-CNRS, Paris, 75013, France
| | - Naotsugu Tsuchiya
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia; Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Suita, Osaka, 565-0871, Japan; Advanced Telecommunications Research Computational Neuroscience Laboratories, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto, 619-0288, Japan.
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34
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Navarrete M, Arthur S, Treder MS, Lewis PA. Ongoing neural oscillations predict the post-stimulus outcome of closed loop auditory stimulation during slow-wave sleep. Neuroimage 2022; 253:119055. [PMID: 35276365 DOI: 10.1016/j.neuroimage.2022.119055] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Revised: 02/26/2022] [Accepted: 03/01/2022] [Indexed: 10/18/2022] Open
Abstract
Large slow oscillations (SO, 0.5-2 Hz) characterise slow-wave sleep and are crucial to memory consolidation and other physiological functions. Manipulating slow oscillations may enhance sleep and memory, as well as benefitting the immune system. Closed-loop auditory stimulation (CLAS) has been demonstrated to increase the SO amplitude and to boost fast sleep spindle activity (11-16 Hz). Nevertheless, not all such stimuli are effective in evoking SOs, even when they are precisely phase locked. Here, we studied what factors of the ongoing activity patterns may help to determine what oscillations to stimulate to effectively enhance SOs or SO-locked spindle activity. Hence, we trained classifiers using the morphological characteristics of the ongoing SO, as measured by electroencephalography (EEG), to predict whether stimulation would lead to a benefit in terms of the resulting SO and spindle amplitude. Separate classifiers were trained using trials from spontaneous control and stimulated datasets, and we evaluated their performance by applying them to held-out data both within and across conditions. We were able to predict both when large SOs occurred spontaneously, and whether a phase-locked auditory click effectively enlarged them with good accuracy for predicting the SO trough (∼70%) and SO peak values (∼80%). Also, we were able to predict when stimulation would elicit spindle activity with an accuracy of ∼60%. Finally, we evaluate the importance of the various SO features used to make these predictions. Our results offer new insight into SO and spindle dynamics and may suggest techniques for developing future methods for online optimization of stimulation.
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Affiliation(s)
- Miguel Navarrete
- Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Maindy Rd, Cardiff CF24 4HQ, UK.
| | - Steven Arthur
- School of Computer Science and Informatics, Cardiff University, Queen's Buildings, 5 The Parade, Roath, Cardiff CF24 3AA, UK
| | - Matthias S Treder
- School of Computer Science and Informatics, Cardiff University, Queen's Buildings, 5 The Parade, Roath, Cardiff CF24 3AA, UK
| | - Penelope A Lewis
- Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Maindy Rd, Cardiff CF24 4HQ, UK.
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35
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Krugliakova E, Skorucak J, Sousouri G, Leach S, Snipes S, Ferster ML, Da Poian G, Karlen W, Huber R. Boosting Recovery During Sleep by Means of Auditory Stimulation. Front Neurosci 2022; 16:755958. [PMID: 35185455 PMCID: PMC8847378 DOI: 10.3389/fnins.2022.755958] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 01/10/2022] [Indexed: 11/13/2022] Open
Abstract
Sufficient recovery during sleep is the basis of physical and psychological well-being. Understanding the physiological mechanisms underlying this restorative function is essential for developing novel approaches to promote recovery during sleep. Phase-targeted auditory stimulation (PTAS) is an increasingly popular technique for boosting the key electrophysiological marker of recovery during sleep, slow-wave activity (SWA, 1-4 Hz EEG power). However, it is unknown whether PTAS induces physiological sleep. In this study, we demonstrate that, when applied during deep sleep, PTAS accelerates SWA decline across the night which is associated with an overnight improvement in attentional performance. Thus, we provide evidence that PTAS enhances physiological sleep and demonstrate under which conditions this occurs most efficiently. These findings will be important for future translation into clinical populations suffering from insufficient recovery during sleep.
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Affiliation(s)
- Elena Krugliakova
- Child Development Centre and Children’s Research Centre, University Children’s Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Jelena Skorucak
- Child Development Centre and Children’s Research Centre, University Children’s Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Georgia Sousouri
- Child Development Centre and Children’s Research Centre, University Children’s Hospital Zurich, University of Zurich, Zurich, Switzerland
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Sven Leach
- Child Development Centre and Children’s Research Centre, University Children’s Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Sophia Snipes
- Child Development Centre and Children’s Research Centre, University Children’s Hospital Zurich, University of Zurich, Zurich, Switzerland
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Maria Laura Ferster
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Giulia Da Poian
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Walter Karlen
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Reto Huber
- Child Development Centre and Children’s Research Centre, University Children’s Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
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36
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Avvenuti G, Bernardi G. Local sleep: A new concept in brain plasticity. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:35-52. [PMID: 35034748 DOI: 10.1016/b978-0-12-819410-2.00003-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Traditionally, sleep and wakefulness have been considered as two global, mutually exclusive states. However, this view has been challenged by the discovery that sleep and wakefulness are actually locally regulated and that islands of these two states may often coexist in the same individual. Importantly, such a local regulation seems to be the key for many essential functions of sleep, including the maintenance of cognitive efficiency and the consolidation of new skills and memories. Indeed, local changes in sleep-related oscillations occur in brain areas that are used and involved in learning during wakefulness. In turn, these changes directly modulate experience-dependent brain adaptations and the consolidation of newly acquired memories. In line with these observations, alterations in the regional balance between wake- and sleep-like activity have been shown to accompany many pathologic conditions, including psychiatric and neurologic disorders. In the last decade, experimental research has started to shed light on the mechanisms involved in the local regulation of sleep and wakefulness. The results of this research have opened new avenues of investigation regarding the function of sleep and have revealed novel potential targets for the treatment of several pathologic conditions.
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Affiliation(s)
- Giulia Avvenuti
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Giulio Bernardi
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy.
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37
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Picchioni D, Özbay PS, Mandelkow H, de Zwart JA, Wang Y, van Gelderen P, Duyn JH. Autonomic arousals contribute to brain fluid pulsations during sleep. Neuroimage 2022; 249:118888. [PMID: 35017126 DOI: 10.1016/j.neuroimage.2022.118888] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 11/15/2021] [Accepted: 01/05/2022] [Indexed: 12/28/2022] Open
Abstract
During sleep, slow waves of neuro-electrical activity engulf the human brain and aid in the consolidation of memories. Recent research suggests that these slow waves may also promote brain health by facilitating the removal of metabolic waste, possibly by orchestrating the pulsatile flow of cerebro-spinal fluid (CSF) through local neural control over vascular tone. To investigate the role of slow waves in the generation of CSF pulsations, we analyzed functional MRI data obtained across the full sleep-wake cycle and during a respiratory task during wakefulness. This revealed a novel generating mechanism that relies on the autonomic regulation of cerebral vascular tone without requiring slow electrocortical activity or even sleep. Therefore, the role of CSF pulsations in brain waste clearance may, in part, depend on proper autoregulatory control of cerebral blood flow.
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Affiliation(s)
- Dante Picchioni
- Advance MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Bethesda, Maryland
| | - Pinar S Özbay
- Advance MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Bethesda, Maryland
| | - Hendrik Mandelkow
- Advance MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Bethesda, Maryland
| | - Jacco A de Zwart
- Advance MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Bethesda, Maryland
| | - Yicun Wang
- Advance MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Bethesda, Maryland
| | - Peter van Gelderen
- Advance MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Bethesda, Maryland
| | - Jeff H Duyn
- Advance MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Bethesda, Maryland.
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38
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OUP accepted manuscript. Cereb Cortex 2022; 32:4782-4796. [DOI: 10.1093/cercor/bhab516] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 12/08/2021] [Accepted: 12/09/2021] [Indexed: 11/14/2022] Open
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39
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Stephan AM, Lecci S, Cataldi J, Siclari F. Conscious experiences and high-density EEG patterns predicting subjective sleep depth. Curr Biol 2021; 31:5487-5500.e3. [PMID: 34710350 DOI: 10.1016/j.cub.2021.10.012] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 07/06/2021] [Accepted: 10/06/2021] [Indexed: 10/20/2022]
Abstract
What accounts for feeling deeply asleep? Standard sleep recordings only incompletely reflect subjective aspects of sleep and some individuals with so-called sleep misperception frequently feel awake although sleep recordings indicate clear-cut sleep. To identify the determinants of sleep perception, we performed 787 awakenings in 20 good sleepers and 10 individuals with sleep misperception and interviewed them about their subjective sleep depth while they underwent high-density EEG sleep recordings. Surprisingly, in good sleepers, sleep was subjectively lightest in the first 2 h of non-rapid eye movement (NREM) sleep, generally considered the deepest sleep, and deepest in rapid eye movement (REM) sleep. Compared to good sleepers, sleep misperceptors felt more frequently awake during sleep and reported lighter REM sleep. At the EEG level, spatially widespread high-frequency power was inversely related to subjective sleep depth in NREM sleep in both groups and in REM sleep in misperceptors. Subjective sleep depth positively correlated with dream-like qualities of reports of mental activity. These findings challenge the widely held notion that slow wave sleep best accounts for feeling deeply asleep. Instead, they indicate that subjective sleep depth is inversely related to a neurophysiological process that predominates in early NREM sleep, becomes quiescent in REM sleep, and is reflected in high-frequency EEG activity. In sleep misperceptors, this process is more frequently active, more spatially widespread, and abnormally persists into REM sleep. These findings help identify the neuromodulatory systems involved in subjective sleep depth and are relevant for studies aiming to improve subjective sleep quality.
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Affiliation(s)
- Aurélie M Stephan
- Center for Investigation and Research on Sleep, Lausanne University Hospital (CHUV), Rue du Bugnon 46, 1010 Lausanne, Switzerland
| | - Sandro Lecci
- Center for Investigation and Research on Sleep, Lausanne University Hospital (CHUV), Rue du Bugnon 46, 1010 Lausanne, Switzerland
| | - Jacinthe Cataldi
- Center for Investigation and Research on Sleep, Lausanne University Hospital (CHUV), Rue du Bugnon 46, 1010 Lausanne, Switzerland
| | - Francesca Siclari
- Center for Investigation and Research on Sleep, Lausanne University Hospital (CHUV), Rue du Bugnon 46, 1010 Lausanne, Switzerland; Department of Clinical Neurosciences, Lausanne University Hospital (CHUV), Rue du Bugnon 46, 1010 Lausanne, Switzerland.
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40
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Gorgoni M, Scarpelli S, Annarumma L, D’Atri A, Alfonsi V, Ferrara M, De Gennaro L. The Regional EEG Pattern of the Sleep Onset Process in Older Adults. Brain Sci 2021; 11:brainsci11101261. [PMID: 34679326 PMCID: PMC8534130 DOI: 10.3390/brainsci11101261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 09/14/2021] [Accepted: 09/21/2021] [Indexed: 02/05/2023] Open
Abstract
Healthy aging is characterized by macrostructural sleep changes and alterations of regional electroencephalographic (EEG) sleep features. However, the spatiotemporal EEG pattern of the wake-sleep transition has never been described in the elderly. The present study aimed to assess the topographical and temporal features of the EEG during the sleep onset (SO) in a group of 36 older participants (59–81 years). The topography of the 1 Hz bins’ EEG power and the time course of the EEG frequency bands were assessed. Moreover, we compared the delta activity and delta/beta ratio between the older participants and a group of young adults. The results point to several peculiarities in the elderly: (a) the generalized post-SO power increase in the slowest frequencies did not include the 7 Hz bin; (b) the alpha power revealed a frequency-specific pattern of post-SO modifications; (c) the sigma activity exhibited only a slight post-SO increase, and its highest bins showed a frontotemporal power decrease. Older adults showed a generalized reduction of delta power and delta/beta ratio in both pre- and post-SO intervals compared to young adults. From a clinical standpoint, the regional EEG activity may represent a target for brain stimulation techniques to reduce SO latency and sleep fragmentation.
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Affiliation(s)
- Maurizio Gorgoni
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy; (S.S.); (V.A.); (L.D.G.)
- Correspondence: ; Tel.: +39-064-9917-508
| | - Serena Scarpelli
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy; (S.S.); (V.A.); (L.D.G.)
| | | | - Aurora D’Atri
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, Italy; (A.D.); (M.F.)
| | - Valentina Alfonsi
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy; (S.S.); (V.A.); (L.D.G.)
| | - Michele Ferrara
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, Italy; (A.D.); (M.F.)
| | - Luigi De Gennaro
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy; (S.S.); (V.A.); (L.D.G.)
- Body and Action Lab, IRCCS Fondazione Santa Lucia, 00179 Rome, Italy;
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41
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Jaramillo V, Jendoubi J, Maric A, Mensen A, Heyse NC, Eberhard-Moscicka AK, Wiest R, Bassetti CLA, Huber R. Thalamic Influence on Slow Wave Slope Renormalization During Sleep. Ann Neurol 2021; 90:821-833. [PMID: 34516002 PMCID: PMC9291607 DOI: 10.1002/ana.26217] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 09/08/2021] [Accepted: 09/11/2021] [Indexed: 02/01/2023]
Abstract
Objective Slow waves are thought to mediate an overall reduction in synaptic strength during sleep. The specific contribution of the thalamus to this so‐called synaptic renormalization is unknown. Thalamic stroke is associated with daytime sleepiness, along with changes to sleep electroencephalography and cognition, making it a unique “experiment of nature” to assess the relationship between sleep rhythms, synaptic renormalization, and daytime functions. Methods Sleep was studied by polysomnography and high‐density electroencephalography over 17 nights in patients with thalamic (n = 12) and 15 nights in patients with extrathalamic (n = 11) stroke. Sleep electroencephalographic overnight slow wave slope changes and their relationship with subjective daytime sleepiness, cognition, and other functional tests were assessed. Results Thalamic and extrathalamic patients did not differ in terms of age, sleep duration, or apnea–hypopnea index. Conversely, overnight slope changes were reduced in a large cluster of electrodes in thalamic compared to extrathalamic stroke patients. This reduction was related to increased daytime sleepiness. No significant differences were found in other functional tests between the 2 groups. Interpretation In patients with thalamic stroke, a reduction in overnight slow wave slope change and increased daytime sleepiness was found. Sleep‐ and wake‐centered mechanisms for this relationship are discussed. Overall, this study suggests a central role of the thalamus in synaptic renormalization. ANN NEUROL 2021;90:821–833
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Affiliation(s)
- Valeria Jaramillo
- Children's Research Center, University Children's Hospital Zurich, University of Zurich, Zurich.,Child Development Center, University Children's Hospital Zurich, University of Zurich, Zurich
| | - Jasmine Jendoubi
- Sleep-Wake-Epilepsy Center, Department of Neurology, University Hospital Bern, University of Bern, Bern, Switzerland.,Center for Experimental Neurology, Department of Neurology, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Angelina Maric
- Department of Neurology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Armand Mensen
- Sleep-Wake-Epilepsy Center, Department of Neurology, University Hospital Bern, University of Bern, Bern, Switzerland.,Center for Experimental Neurology, Department of Neurology, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Natalie C Heyse
- Children's Research Center, University Children's Hospital Zurich, University of Zurich, Zurich.,Child Development Center, University Children's Hospital Zurich, University of Zurich, Zurich
| | - Aleksandra K Eberhard-Moscicka
- Perception and Eye Movement Laboratory, Departments of Neurology and Biomedical Research, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Department of Neuroradiology, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Claudio L A Bassetti
- Sleep-Wake-Epilepsy Center, Department of Neurology, University Hospital Bern, University of Bern, Bern, Switzerland.,Center for Experimental Neurology, Department of Neurology, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Reto Huber
- Children's Research Center, University Children's Hospital Zurich, University of Zurich, Zurich.,Child Development Center, University Children's Hospital Zurich, University of Zurich, Zurich.,Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich
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42
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Bouchard M, Lina JM, Gaudreault PO, Lafrenière A, Dubé J, Gosselin N, Carrier J. Sleeping at the switch. eLife 2021; 10:64337. [PMID: 34448453 PMCID: PMC8452310 DOI: 10.7554/elife.64337] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 08/26/2021] [Indexed: 11/13/2022] Open
Abstract
Sleep slow waves are studied for their role in brain plasticity, homeostatic regulation, and their changes during aging. Here, we address the possibility that two types of slow waves co-exist in humans. Thirty young and 29 older adults underwent a night of polysomnographic recordings. Using the transition frequency, slow waves with a slow transition (slow switchers) and those with a fast transition (fast switchers) were discovered. Slow switchers had a high electroencephalography (EEG) connectivity along their depolarization transition while fast switchers had a lower connectivity dynamics and dissipated faster during the night. Aging was associated with lower temporal dissipation of sleep pressure in slow and fast switchers and lower EEG connectivity at the microscale of the oscillations, suggesting a decreased flexibility in the connectivity network of older individuals. Our findings show that two different types of slow waves with possible distinct underlying functions coexist in the slow wave spectrum.
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Affiliation(s)
- Maude Bouchard
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montreal, Canada.,Department of Psychology, Université de Montréal, Montreal, Canada
| | - Jean-Marc Lina
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montreal, Canada.,Department of Electrical Engineering, École de Technologie Supérieure, Montreal, Canada.,Centre de Recherches Mathématiques, Université de Montréal, Montreal, Canada
| | - Pierre-Olivier Gaudreault
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montreal, Canada
| | - Alexandre Lafrenière
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montreal, Canada
| | - Jonathan Dubé
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montreal, Canada.,Department of Psychology, Université de Montréal, Montreal, Canada
| | - Nadia Gosselin
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montreal, Canada.,Department of Psychology, Université de Montréal, Montreal, Canada
| | - Julie Carrier
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montreal, Canada.,Department of Psychology, Université de Montréal, Montreal, Canada
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43
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Sousouri G, Krugliakova E, Skorucak J, Leach S, Snipes S, Ferster ML, Da Poian G, Karlen W, Huber R. Neuromodulation by means of phase-locked auditory stimulation affects key marker of excitability and connectivity during sleep. Sleep 2021; 45:6347149. [PMID: 34373925 DOI: 10.1093/sleep/zsab204] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 07/15/2021] [Indexed: 11/12/2022] Open
Abstract
The propagating pattern of sleep slow waves (high-amplitude oscillations < 4.5 Hz) serves as a blueprint of cortical excitability and brain connectivity. Phase-locked auditory stimulation is a promising tool for the modulation of ongoing brain activity during sleep; however, its underlying mechanisms remain unknown. Here, eighteen healthy young adults were measured with high-density electroencephalography (hd-EEG) in three experimental conditions; one with no stimulation, one with up- and one with down-phase stimulation; ten participants were included in the analysis. We show that up-phase auditory stimulation on a right prefrontal area locally enhances cortical involvement and promotes traveling by increasing the propagating distance and duration of targeted small-amplitude waves. On the contrary, down-phase stimulation proves more efficient at perturbing large-amplitude waves and interferes with ongoing traveling by disengaging cortical regions and interrupting high synchronicity in the target area as indicated by increased traveling speed. These results point out to different underlying mechanisms mediating the effects of up- and down-phase stimulation and highlight the strength of traveling analysis as a sensitive and informative method for the study of connectivity and cortical excitability alterations.
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Affiliation(s)
- Georgia Sousouri
- Child Development Centre and Children's Research Centre, University Children's Hospital Zürich, University of Zurich, Zurich, Switzerland
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Elena Krugliakova
- Child Development Centre and Children's Research Centre, University Children's Hospital Zürich, University of Zurich, Zurich, Switzerland
| | - Jelena Skorucak
- Child Development Centre and Children's Research Centre, University Children's Hospital Zürich, University of Zurich, Zurich, Switzerland
| | - Sven Leach
- Child Development Centre and Children's Research Centre, University Children's Hospital Zürich, University of Zurich, Zurich, Switzerland
| | - Sophia Snipes
- Child Development Centre and Children's Research Centre, University Children's Hospital Zürich, University of Zurich, Zurich, Switzerland
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Maria Laura Ferster
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Giulia Da Poian
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Walter Karlen
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Reto Huber
- Child Development Centre and Children's Research Centre, University Children's Hospital Zürich, University of Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zürich, Zurich, Switzerland
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44
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Ladenbauer J, Ladenbauer J, Külzow N, Flöel A. Memory-relevant nap sleep physiology in healthy and pathological aging. Sleep 2021; 44:6066546. [PMID: 33406266 DOI: 10.1093/sleep/zsab002] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 11/30/2020] [Indexed: 11/13/2022] Open
Abstract
STUDY OBJECTIVES Aging is associated with detrimental changes in sleep physiology, a process accelerated in Alzheimer's disease. Fine-tuned temporal interactions of non-rapid eye movement slow oscillations and spindles were shown to be particularly important for memory consolidation, and to deteriorate in healthy older adults. Whether this oscillatory interaction further decline in early stages of Alzheimer's disease such as mild cognitive impairment has not been investigated to date, but may have important therapeutic implications. METHODS Here, we assessed differences in sleep architecture and memory-relevant slow oscillation, sleep spindles and their functional coupling during a 90-min nap between healthy young and older adults, and in older patients with mild cognitive impairment. Furthermore, associations of nap-sleep characteristics with sleep-dependent memory performance change were evaluated. RESULTS We found significant differences between young and older healthy adults, and between young adults and patients with mild cognitive impairment, but not between healthy older adults and patients for several sleep metrics, including slow oscillation-spindle coupling. Moreover, sleep-dependent retention of verbal memories was significantly higher in young healthy adults versus older adults with and without mild cognitive impairment, but no difference between the two older groups was observed. Associations with sleep metrics were only found for pre-nap memory performances. CONCLUSIONS In conclusion, our results indicate changes in nap sleep physiology and sleep-related memory consolidation in older adults with and without mild cognitive impairment. Thus, interventions targeted at improving sleep physiology may help to reduce memory decline in both groups, but our study does not indicate additional benefits for patients with mild cognitive impairment. CLINICAL TRAIL REGISTRATION Effects of Brain Stimulation During Daytime Nap on Memory Consolidation in Younger, Healthy Subjects: https://clinicaltrials.gov/ct2/show/NCT01840865; NCT01840865. Effects of Brain Stimulation During a Daytime Nap on Memory Consolidation in Older Adults; https://clinicaltrials.gov/ct2/show/study/NCT01840839?term=01840839&draw=2&rank=1; NCT01840839. Effects of Brain Stimulation During a Daytime Nap on Memory Consolidation in Patients With Mild Cognitive Impairment; https://clinicaltrials.gov/ct2/show/NCT01782365?term=01782365&draw=2&rank=1; NCT01782365.
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Affiliation(s)
- Julia Ladenbauer
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany.,Department of Neurology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Josef Ladenbauer
- Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, École Normale Supérieure, PSL Research University, Paris, France
| | - Nadine Külzow
- Kliniken Beelitz GmbH, Neurologische Rehabilitation, Beelitz-Heilstätten, Germany
| | - Agnes Flöel
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany.,Department of Neurology, Charité Universitätsmedizin Berlin, Berlin, Germany
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45
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Andrillon T, Burns A, Mackay T, Windt J, Tsuchiya N. Predicting lapses of attention with sleep-like slow waves. Nat Commun 2021; 12:3657. [PMID: 34188023 PMCID: PMC8241869 DOI: 10.1038/s41467-021-23890-7] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 04/21/2021] [Indexed: 11/10/2022] Open
Abstract
Attentional lapses occur commonly and are associated with mind wandering, where focus is turned to thoughts unrelated to ongoing tasks and environmental demands, or mind blanking, where the stream of consciousness itself comes to a halt. To understand the neural mechanisms underlying attentional lapses, we studied the behaviour, subjective experience and neural activity of healthy participants performing a task. Random interruptions prompted participants to indicate their mental states as task-focused, mind-wandering or mind-blanking. Using high-density electroencephalography, we report here that spatially and temporally localized slow waves, a pattern of neural activity characteristic of the transition toward sleep, accompany behavioural markers of lapses and preceded reports of mind wandering and mind blanking. The location of slow waves could distinguish between sluggish and impulsive behaviours, and between mind wandering and mind blanking. Our results suggest attentional lapses share a common physiological origin: the emergence of local sleep-like activity within the awake brain.
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Affiliation(s)
- Thomas Andrillon
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia.
- Institut du Cerveau-Paris Brain Institute-ICM, Sorbonne Université, Inserm, CNRS, Paris, France.
| | - Angus Burns
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Teigane Mackay
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Jennifer Windt
- Philosophy Department, Monash University, Melbourne, VIC, Australia
| | - Naotsugu Tsuchiya
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Suita, Osaka, Japan
- Advanced Telecommunications Research Computational Neuroscience Laboratories, Soraku-gun, Kyoto, Japan
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46
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Bernardi G, Avvenuti G, Cataldi J, Lattanzi S, Ricciardi E, Polonara G, Silvestrini M, Siclari F, Fabri M, Bellesi M. Role of corpus callosum in sleep spindle synchronization and coupling with slow waves. Brain Commun 2021; 3:fcab108. [PMID: 34164621 PMCID: PMC8215432 DOI: 10.1093/braincomms/fcab108] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 04/14/2021] [Accepted: 04/19/2021] [Indexed: 12/25/2022] Open
Abstract
Sleep spindles of non-REM sleep are transient, waxing-and-waning 10–16 Hz EEG oscillations, whose cortical synchronization depends on the engagement of thalamo-cortical loops. However, previous studies in animal models lacking the corpus callosum due to agenesis or total callosotomy and in humans with agenesis of the corpus callosum suggested that cortico-cortical connections may also have a relevant role in cortical (inter-hemispheric) spindle synchronization. Yet, most of these works did not provide direct quantitative analyses to support their observations. By studying a rare sample of callosotomized, split-brain patients, we recently demonstrated that the total resection of the corpus callosum is associated with a significant reduction in the inter-hemispheric propagation of non-REM slow waves. Interestingly, sleep spindles are often temporally and spatially grouped around slow waves (0.5–4 Hz), and this coordination is thought to have an important role in sleep-dependent learning and memory consolidation. Given these premises, here we set out to investigate whether total callosotomy may affect the generation and spreading of sleep spindles, as well as their coupling with sleep slow waves. To this aim, we analysed overnight high-density EEG recordings (256 electrodes) collected in five patients who underwent total callosotomy due to drug-resistant epilepsy (age 40–53, two females), three non-callosotomized neurological patients (age 44–66, two females), and in a sample of 24 healthy adult control subjects (age 20–47, 13 females). Individual sleep spindles were automatically detected using a validated algorithm and their properties and topographic distributions were computed. All analyses were performed with and without a regression-based adjustment accounting for inter-subject age differences. The comparison between callosotomized patients and healthy subjects did not reveal systematic variations in spindle density, amplitude or frequency. However, callosotomized patients were characterized by a reduced spindle duration, which could represent the result of a faster desynchronization of spindle activity across cortical areas of the two hemispheres. In contrast with our previous findings regarding sleep slow waves, we failed to detect in callosotomized patients any clear, systematic change in the inter-hemispheric synchronization of sleep spindles. In line with this, callosotomized patients were characterized by a reduced extension of the spatial association between temporally coupled spindles and slow waves. Our findings are consistent with a dependence of spindles on thalamo-cortical rather than cortico-cortical connections in humans, but also revealed that, despite their temporal association, slow waves and spindles are independently regulated in terms of topographic expression.
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Affiliation(s)
- Giulio Bernardi
- Molecular Mind Laboratory, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Giulia Avvenuti
- Molecular Mind Laboratory, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Jacinthe Cataldi
- Center for Investigation and Research on Sleep, Lausanne University Hospital, Lausanne 1011, Switzerland
| | - Simona Lattanzi
- Department of Experimental and Clinical Medicine, Marche Polytechnic University, Ancona 60126, Italy
| | - Emiliano Ricciardi
- Molecular Mind Laboratory, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Gabriele Polonara
- Department of Odontostomatologic and Specialized Clinical Sciences, Marche Polytechnic University, Ancona 60126, Italy
| | - Mauro Silvestrini
- Department of Experimental and Clinical Medicine, Marche Polytechnic University, Ancona 60126, Italy
| | - Francesca Siclari
- Center for Investigation and Research on Sleep, Lausanne University Hospital, Lausanne 1011, Switzerland
| | - Mara Fabri
- Department of Experimental and Clinical Medicine, Marche Polytechnic University, Ancona 60126, Italy
| | - Michele Bellesi
- School of Bioscience and Veterinary Medicine, University of Camerino, Camerino 62032, Italy
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47
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Imperatori LS, Cataldi J, Betta M, Ricciardi E, Ince RAA, Siclari F, Bernardi G. Cross-participant prediction of vigilance stages through the combined use of wPLI and wSMI EEG functional connectivity metrics. Sleep 2021; 44:5998102. [PMID: 33220055 DOI: 10.1093/sleep/zsaa247] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 11/01/2020] [Indexed: 11/12/2022] Open
Abstract
Functional connectivity (FC) metrics describe brain inter-regional interactions and may complement information provided by common power-based analyses. Here, we investigated whether the FC-metrics weighted Phase Lag Index (wPLI) and weighted Symbolic Mutual Information (wSMI) may unveil functional differences across four stages of vigilance-wakefulness (W), NREM-N2, NREM-N3, and REM sleep-with respect to each other and to power-based features. Moreover, we explored their possible contribution in identifying differences between stages characterized by distinct levels of consciousness (REM+W vs. N2+N3) or sensory disconnection (REM vs. W). Overnight sleep and resting-state wakefulness recordings from 24 healthy participants (27 ± 6 years, 13F) were analyzed to extract power and FC-based features in six classical frequency bands. Cross-validated linear discriminant analyses (LDA) were applied to investigate the ability of extracted features to discriminate (1) the four vigilance stages, (2) W+REM vs. N2+N3, and (3) W vs. REM. For the four-way vigilance stages classification, combining features based on power and both connectivity metrics significantly increased accuracy relative to considering only power, wPLI, or wSMI features. Delta-power and connectivity (0.5-4 Hz) represented the most relevant features for all the tested classifications, in line with a possible involvement of slow waves in consciousness and sensory disconnection. Sigma-FC, but not sigma-power (12-16 Hz), was found to strongly contribute to the differentiation between states characterized by higher (W+REM) and lower (N2+N3) probabilities of conscious experiences. Finally, alpha-FC resulted as the most relevant FC-feature for distinguishing among wakefulness and REM sleep and may thus reflect the level of disconnection from the external environment.
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Affiliation(s)
- Laura Sophie Imperatori
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy.,Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom
| | - Jacinthe Cataldi
- Center for Investigation and Research on Sleep, Lausanne University Hospital, Lausanne, Switzerland
| | - Monica Betta
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | | | - Robin A A Ince
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom
| | - Francesca Siclari
- Center for Investigation and Research on Sleep, Lausanne University Hospital, Lausanne, Switzerland
| | - Giulio Bernardi
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy.,Center for Investigation and Research on Sleep, Lausanne University Hospital, Lausanne, Switzerland
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48
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McConnell BV, Kronberg E, Teale PD, Sillau SH, Fishback GM, Kaplan RI, Fought AJ, Dhanasekaran AR, Berman BD, Ramos AR, McClure RL, Bettcher BM. The Aging Slow Wave: A Shifting Amalgam of Distinct Slow Wave and Spindle Coupling Subtypes Define Slow Wave Sleep Across the Human Lifespan. Sleep 2021; 44:6276901. [PMID: 33999194 PMCID: PMC8503831 DOI: 10.1093/sleep/zsab125] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 03/14/2021] [Indexed: 11/14/2022] Open
Abstract
STUDY OBJECTIVES Slow wave and spindle coupling supports memory consolidation, and loss of coupling is linked with cognitive decline and neurodegeneration. Coupling is proposed to be a possible biomarker of neurological disease, yet little is known about the different subtypes of coupling that normally occur throughout human development and aging. Here we identify distinct subtypes of spindles within slow wave upstates and describe their relationships with sleep stage across the human lifespan. METHODS Coupling within a cross-sectional cohort of 582 subjects was quantified from stages N2 and N3 sleep across ages 6-88 years old. Results were analyzed across the study population via mixed model regression. Within a subset of subjects, we further utilized coupling to identify discrete subtypes of slow waves by their coupled spindles. RESULTS Two different subtypes of spindles were identified during the upstates of (distinct) slow waves: an "early-fast" spindle, more common in stage N2 sleep, and a "late-fast" spindle, more common in stage N3. We further found stages N2 and N3 sleep contain a mixture of discrete subtypes of slow waves, each identified by their unique coupled-spindle timing and frequency. The relative contribution of coupling subtypes shifts across the human lifespan, and a deeper sleep phenotype prevails with increasing age. CONCLUSIONS Distinct subtypes of slow waves and coupled spindles form the composite of slow wave sleep. Our findings support a model of sleep-dependent synaptic regulation via discrete slow wave/spindle coupling subtypes and advance a conceptual framework for the development of coupling-based biomarkers in age-associated neurological disease.
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Affiliation(s)
- Brice V McConnell
- Neurology, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Eugene Kronberg
- Neurology, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Peter D Teale
- Neurology, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Stefan H Sillau
- Neurology, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Grace M Fishback
- Neurology, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Rini I Kaplan
- Psychological & Brain Sciences Boston University, Boston, MA, USA
| | - Angela J Fought
- Neurology, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | | | - Brian D Berman
- Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA.,Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | - Alberto R Ramos
- Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
| | | | - Brianne M Bettcher
- Neurology, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
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49
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Betta M, Handjaras G, Leo A, Federici A, Farinelli V, Ricciardi E, Siclari F, Meletti S, Ballotta D, Benuzzi F, Bernardi G. Cortical and subcortical hemodynamic changes during sleep slow waves in human light sleep. Neuroimage 2021; 236:118117. [PMID: 33940148 DOI: 10.1016/j.neuroimage.2021.118117] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 04/09/2021] [Accepted: 04/18/2021] [Indexed: 12/22/2022] Open
Abstract
EEG slow waves, the hallmarks of NREM sleep are thought to be crucial for the regulation of several important processes, including learning, sensory disconnection and the removal of brain metabolic wastes. Animal research indicates that slow waves may involve complex interactions within and between cortical and subcortical structures. Conventional EEG in humans, however, has a low spatial resolution and is unable to accurately describe changes in the activity of subcortical and deep cortical structures. To overcome these limitations, here we took advantage of simultaneous EEG-fMRI recordings to map cortical and subcortical hemodynamic (BOLD) fluctuations time-locked to slow waves of light sleep. Recordings were performed in twenty healthy adults during an afternoon nap. Slow waves were associated with BOLD-signal increases in the posterior brainstem and in portions of thalamus and cerebellum characterized by preferential functional connectivity with limbic and somatomotor areas, respectively. At the cortical level, significant BOLD-signal decreases were instead found in several areas, including insula and somatomotor cortex. Specifically, a slow signal increase preceded slow-wave onset and was followed by a delayed, stronger signal decrease. Similar hemodynamic changes were found to occur at different delays across most cortical brain areas, mirroring the propagation of electrophysiological slow waves, from centro-frontal to inferior temporo-occipital cortices. Finally, we found that the amplitude of electrophysiological slow waves was positively related to the magnitude and inversely related to the delay of cortical and subcortical BOLD-signal changes. These regional patterns of brain activity are consistent with theoretical accounts of the functions of sleep slow waves.
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Affiliation(s)
- Monica Betta
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Giacomo Handjaras
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Andrea Leo
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Alessandra Federici
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Valentina Farinelli
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Emiliano Ricciardi
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Francesca Siclari
- Center for Investigation and Research on Sleep, Lausanne University Hospital, Lausanne, Switzerland
| | - Stefano Meletti
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Dept., Azienda Ospedaliera Universitaria di Modena, Modena, Italy
| | - Daniela Ballotta
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Francesca Benuzzi
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Giulio Bernardi
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy.
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50
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Vaidyanathan TV, Collard M, Yokoyama S, Reitman ME, Poskanzer KE. Cortical astrocytes independently regulate sleep depth and duration via separate GPCR pathways. eLife 2021; 10:63329. [PMID: 33729913 PMCID: PMC7968927 DOI: 10.7554/elife.63329] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 02/17/2021] [Indexed: 12/11/2022] Open
Abstract
Non-rapid eye movement (NREM) sleep, characterized by slow-wave electrophysiological activity, underlies several critical functions, including learning and memory. However, NREM sleep is heterogeneous, varying in duration, depth, and spatially across the cortex. While these NREM sleep features are thought to be largely independently regulated, there is also evidence that they are mechanistically coupled. To investigate how cortical NREM sleep features are controlled, we examined the astrocytic network, comprising a cortex-wide syncytium that influences population-level neuronal activity. We quantified endogenous astrocyte activity in mice over natural sleep and wake, then manipulated specific astrocytic G-protein-coupled receptor (GPCR) signaling pathways in vivo. We find that astrocytic Gi- and Gq-coupled GPCR signaling separately control NREM sleep depth and duration, respectively, and that astrocytic signaling causes differential changes in local and remote cortex. These data support a model in which the cortical astrocyte network serves as a hub for regulating distinct NREM sleep features. Sleep has many roles, from strengthening new memories to regulating mood and appetite. While we might instinctively think of sleep as a uniform state of reduced brain activity, the reality is more complex. First, over the course of the night, we cycle between a number of different sleep stages, which reflect different levels of sleep depth. Second, the amount of sleep depth is not necessarily even across the brain but can vary between regions. These sleep stages consist of either rapid eye movement (REM) sleep or non-REM (NREM) sleep. REM sleep is when most dreaming occurs, whereas NREM sleep is particularly important for learning and memory and can vary in duration and depth. During NREM sleep, large groups of neurons synchronize their firing to create rhythmic waves of activity known as slow waves. The more synchronous the activity, the deeper the sleep. Vaidyanathan et al. now show that brain cells called astrocytes help regulate NREM sleep. Astrocytes are not neurons but belong to a group of specialized cells called glia. They are the largest glia cell type in the brain and display an array of proteins on their surfaces called G-protein-coupled receptors (GPCRs). These enable them to sense sleep-wake signals from other parts of the brain and to generate their own signals. In fact, each astrocyte can communicate with thousands of neurons at once. They are therefore well-poised to coordinate brain activity during NREM sleep. Using innovative tools, Vaidyanathan et al. visualized astrocyte activity in mice as the animals woke up or fell asleep. The results showed that astrocytes change their activity just before each sleep–wake transition. They also revealed that astrocytes control both the depth and duration of NREM sleep via two different types of GPCR signals. Increasing one of these signals (Gi-GPCR) made the mice sleep more deeply but did not change sleep duration. Decreasing the other (Gq-GPCR) made the mice sleep for longer but did not affect sleep depth. Sleep problems affect many people at some point in their lives, and often co-exist with other conditions such as mental health disorders. Understanding how the brain regulates different features of sleep could help us develop better – and perhaps more specific – treatments for sleep disorders. The current study suggests that manipulating GPCRs on astrocytes might increase sleep depth, for example. But before work to test this idea can begin, we must first determine whether findings from sleeping mice also apply to people.
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Affiliation(s)
- Trisha V Vaidyanathan
- Neuroscience Graduate Program, University of California, San Francisco, San Francisco, United States.,Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, United States
| | - Max Collard
- Neuroscience Graduate Program, University of California, San Francisco, San Francisco, United States
| | - Sae Yokoyama
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, United States
| | - Michael E Reitman
- Neuroscience Graduate Program, University of California, San Francisco, San Francisco, United States.,Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, United States
| | - Kira E Poskanzer
- Neuroscience Graduate Program, University of California, San Francisco, San Francisco, United States.,Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, United States.,Kavli Institute for Fundamental Neuroscience, San Francisco, United States
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