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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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2
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Yin Z, Yu H, Yuan T, Smyth C, Anjum MF, Zhu G, Ma R, Xu Y, An Q, Gan Y, Merk T, Qin G, Xie H, Zhang N, Wang C, Jiang Y, Meng F, Yang A, Neumann WJ, Starr P, Little S, Li L, Zhang J. Generalized sleep decoding with basal ganglia signals in multiple movement disorders. NPJ Digit Med 2024; 7:122. [PMID: 38729977 PMCID: PMC11087561 DOI: 10.1038/s41746-024-01115-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 04/23/2024] [Indexed: 05/12/2024] Open
Abstract
Sleep disturbances profoundly affect the quality of life in individuals with neurological disorders. Closed-loop deep brain stimulation (DBS) holds promise for alleviating sleep symptoms, however, this technique necessitates automated sleep stage decoding from intracranial signals. We leveraged overnight data from 121 patients with movement disorders (Parkinson's disease, Essential Tremor, Dystonia, Essential Tremor, Huntington's disease, and Tourette's syndrome) in whom synchronized polysomnograms and basal ganglia local field potentials were recorded, to develop a generalized, multi-class, sleep specific decoder - BGOOSE. This generalized model achieved 85% average accuracy across patients and across disease conditions, even in the presence of recordings from different basal ganglia targets. Furthermore, we also investigated the role of electrocorticography on decoding performances and proposed an optimal decoding map, which was shown to facilitate channel selection for optimal model performances. BGOOSE emerges as a powerful tool for generalized sleep decoding, offering exciting potentials for the precision stimulation delivery of DBS and better management of sleep disturbances in movement disorders.
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Affiliation(s)
- Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Campus Mitte, Charite-Universitatsmedizin Berlin, Chariteplatz 1, 10117, Berlin, Germany.
| | - Huiling Yu
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, 100084, Beijing, China
| | - Tianshuo Yuan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Clay Smyth
- Department of Bioengineering, University of California, San Francisco, UCSF Byers Hall Box 2520, 1700 Fourth St Ste 203, San Francisco, CA, 94143, USA
| | - Md Fahim Anjum
- Department of Neurology, University of California, San Francisco, 1651 4th Street, San Francisco, CA, 94158, USA
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Campus Mitte, Charite-Universitatsmedizin Berlin, Chariteplatz 1, 10117, Berlin, Germany
| | - Ruoyu Ma
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yichen Xu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Qi An
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yifei Gan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Timon Merk
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Campus Mitte, Charite-Universitatsmedizin Berlin, Chariteplatz 1, 10117, Berlin, Germany
| | - Guofan Qin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Hutao Xie
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ning Zhang
- Department of Neuropsychiatry, Behavioral Neurology and Sleep Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunxue Wang
- Department of Neuropsychiatry, Behavioral Neurology and Sleep Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yin Jiang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Campus Mitte, Charite-Universitatsmedizin Berlin, Chariteplatz 1, 10117, Berlin, Germany
| | - Philip Starr
- Department of Neurosurgery, University of California, San Francisco, Eighth Floor, 400 Parnassus Ave, San Francisco, CA, 94143, USA
| | - Simon Little
- Department of Neurology, University of California, San Francisco, 1651 4th Street, San Francisco, CA, 94158, USA.
| | - Luming Li
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, 100084, Beijing, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, 100084, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
- Beijing Key Laboratory of Neurostimulation, Beijing, China.
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Wang YL, Avigdor T, Hannan S, Abdallah C, Dubeau F, Peter-Derex L, Frauscher B. Intracerebral Dynamics of Sleep Arousals: A Combined Scalp-Intracranial EEG Study. J Neurosci 2024; 44:e0617232024. [PMID: 38471781 PMCID: PMC11026366 DOI: 10.1523/jneurosci.0617-23.2024] [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: 04/10/2023] [Revised: 02/05/2024] [Accepted: 02/12/2024] [Indexed: 03/14/2024] Open
Abstract
As an intrinsic component of sleep architecture, sleep arousals represent an intermediate state between sleep and wakefulness and are important for sleep-wake regulation. They are defined in an all-or-none manner, whereas they actually present a wide range of scalp-electroencephalography (EEG) activity patterns. It is poorly understood how these arousals differ in their mechanisms. Stereo-EEG (SEEG) provides the unique opportunity to record intracranial activities in superficial and deep structures in humans. Using combined polysomnography and SEEG, we quantitatively categorized arousals during nonrapid eye movement sleep into slow wave (SW) and non-SW arousals based on whether they co-occurred with a scalp-EEG SW event. We then investigated their intracranial correlates in up to 26 brain regions from 26 patients (12 females). Across both arousal types, intracranial theta, alpha, sigma, and beta activities increased in up to 25 regions (p < 0.05; d = 0.06-0.63), while gamma and high-frequency (HF) activities decreased in up to 18 regions across the five brain lobes (p < 0.05; d = 0.06-0.44). Intracranial delta power widely increased across five lobes during SW arousals (p < 0.05 in 22 regions; d = 0.10-0.39), while it widely decreased during non-SW arousals (p < 0.05 in 19 regions; d = 0.10-0.30). Despite these main patterns, unique activities were observed locally in some regions such as the hippocampus and middle cingulate cortex, indicating spatial heterogeneity of arousal responses. Our results suggest that non-SW arousals correspond to a higher level of brain activation than SW arousals. The decrease in HF activities could potentially explain the absence of awareness and recollection during arousals.
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Affiliation(s)
- Yingqi Laetitia Wang
- Analytical Neurophysiology Lab, Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 2B4, Canada
| | - Tamir Avigdor
- Analytical Neurophysiology Lab, Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 2B4, Canada
| | - Sana Hannan
- Department of Biomedical and Life Sciences, Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Chifaou Abdallah
- Analytical Neurophysiology Lab, Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 2B4, Canada
| | - François Dubeau
- Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 2B4, Canada
| | - Laure Peter-Derex
- Centre de Médecine du Sommeil et des Maladies respiratoires, University Hospital of Lyon, Lyon 1 University, Lyon 69004, France
| | - Birgit Frauscher
- Analytical Neurophysiology Lab, Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 2B4, Canada
- Analytical Neurophysiology Lab, Departments of Neurology & Biomedical Engineering, Duke University, Durham, North Carolina 27705
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4
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Thieux M, Zhang M, Guignard‐Perret A, Mazza S, Plancoulaine S, Guyon A, Franco P. Does the brain sleep differently depending on intellectual abilities? CNS Neurosci Ther 2024; 30:e14378. [PMID: 37485816 PMCID: PMC10848103 DOI: 10.1111/cns.14378] [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: 04/08/2023] [Revised: 06/05/2023] [Accepted: 07/12/2023] [Indexed: 07/25/2023] Open
Abstract
AIMS To compare the children's sleep electroencephalogram according to their intellectual profile. METHODS Children were grouped according to their Wechsler Intelligence Scale for Children (WISC) scores (17 with normal intelligence quotient [IQ, NIQ] and 24 with high IQ [HIQ]). Comparisons of spectral power between groups and its relationship with WISC scores were assessed using analyses of variance and linear regression models, adjusted for age and sex. RESULTS Children with HIQ had more rapid eye movement (REM) sleep, especially late at night, and more power in slow-frequency bands during REM sleep than those with NIQ. There were also positive associations between the processing speed index and the spectral power in β bands in NREM sleep, and with the spectral power in α, σ, β, and γ bands in REM sleep, with different associations between groups. CONCLUSION The enhanced power in slow bands during REM sleep in children with HIQ overlaps with that of typical REM sleep oscillations thought to be involved in emotional memory consolidation. The dissimilar relationships between spectral power and WISC scores in NIQ and HIQ groups may underlie functional differences in brain activity related to cognitive efficiency, questioning the direction of the relationship between sleep and cognitive functioning.
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Affiliation(s)
- Marine Thieux
- INSERM U1028, CNRS UMR5292Lyon Neuroscience Research CenterLyonFrance
| | - Min Zhang
- INSERM U1028, CNRS UMR5292Lyon Neuroscience Research CenterLyonFrance
| | - Anne Guignard‐Perret
- Pediatric Sleep Unit, Department of Pediatric Clinical Epileptology, Sleep Disorders and Functional Neurology, Hôpital Femme Mère EnfantHospices Civils de LyonLyonFrance
| | - Stéphanie Mazza
- Research on Healthcare Performance RESHAPE, INSERM U1290Université Claude Bernard Lyon 1LyonFrance
| | - Sabine Plancoulaine
- INSERM U1028, CNRS UMR5292Lyon Neuroscience Research CenterLyonFrance
- Inserm, INRAE, Center for Research in Epidemiology and Statistics (CRESS)Université Paris Cité and Université Sorbonne Paris NordParisFrance
| | - Aurore Guyon
- Pediatric Sleep Unit, Department of Pediatric Clinical Epileptology, Sleep Disorders and Functional Neurology, Hôpital Femme Mère EnfantHospices Civils de LyonLyonFrance
| | - Patricia Franco
- INSERM U1028, CNRS UMR5292Lyon Neuroscience Research CenterLyonFrance
- Pediatric Sleep Unit, Department of Pediatric Clinical Epileptology, Sleep Disorders and Functional Neurology, Hôpital Femme Mère EnfantHospices Civils de LyonLyonFrance
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Greenblatt AS, Beniczky S, Nascimento FA. Pitfalls in scalp EEG: Current obstacles and future directions. Epilepsy Behav 2023; 149:109500. [PMID: 37931388 DOI: 10.1016/j.yebeh.2023.109500] [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: 09/02/2023] [Revised: 10/15/2023] [Accepted: 10/17/2023] [Indexed: 11/08/2023]
Abstract
Although electroencephalography (EEG) serves a critical role in the evaluation and management of seizure disorders, it is commonly misinterpreted, resulting in avoidable medical, social, and financial burdens to patients and health care systems. Overinterpretation of sharply contoured transient waveforms as being representative of interictal epileptiform abnormalities lies at the core of this problem. However, the magnitude of these errors is amplified by the high prevalence of paroxysmal events exhibited in clinical practice that compel investigation with EEG. Neurology training programs, which vary considerably both in the degree of exposure to EEG and the composition of EEG didactics, have not effectively addressed this widespread issue. Implementation of competency-based curricula in lieu of traditional educational approaches may enhance proficiency in EEG interpretation amongst general neurologists in the absence of formal subspecialty training. Efforts in this regard have led to the development of a systematic, high-fidelity approach to the interpretation of epileptiform discharges that is readily employable across medical centers. Additionally, machine learning techniques hold promise for accelerating accurate and reliable EEG interpretation, particularly in settings where subspecialty interpretive EEG services are not readily available. This review highlights common diagnostic errors in EEG interpretation, limitations in current educational paradigms, and initiatives aimed at resolving these challenges.
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Affiliation(s)
- Adam S Greenblatt
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Sándor Beniczky
- Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund and Aarhus University Hospital, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Fábio A Nascimento
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
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Ferrara M, D’Atri A, Salfi F. Novel insights into the role of eye movements during REM sleep in memory consolidation. Sleep 2023; 46:zsad178. [PMID: 37432046 PMCID: PMC10566246 DOI: 10.1093/sleep/zsad178] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Indexed: 07/12/2023] Open
Affiliation(s)
- Michele Ferrara
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, L’Aquila, Italy
| | - Aurora D’Atri
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, L’Aquila, Italy
| | - Federico Salfi
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, L’Aquila, Italy
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7
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van den Berg NH, Gibbings A, Baena D, Pozzobon A, Al-Kuwatli J, Ray LB, Fogel SM. Eye movements during phasic versus tonic rapid eye movement sleep are biomarkers of dissociable electroencephalogram processes for the consolidation of novel problem-solving skills. Sleep 2023; 46:zsad151. [PMID: 37246548 DOI: 10.1093/sleep/zsad151] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/22/2023] [Indexed: 05/30/2023] Open
Abstract
The hallmark eye movement (EM) bursts that occur during rapid eye movement (REM) sleep are markers of consolidation for procedural memory involving novel cognitive strategies and problem-solving skills. Examination of the brain activity associated with EMs during REM sleep might elucidate the processes involved in memory consolidation, and may uncover the functional significance of REM sleep and EMs themselves. Participants performed a REM-dependent, novel procedural problem-solving task (i.e. the Tower of Hanoi; ToH) before and after intervals of either overnight sleep (n = 20) or a daytime 8-hour wake period (n = 20). In addition, event-related spectral perturbation of the electroencephalogram (EEG) time-locked to EMs occurring either in bursts (i.e. phasic REM), or in isolation (i.e. tonic REM), were compared to sleep on a non-learning control night. ToH improvement was greater following sleep compared to wakefulness. During sleep, prefrontal theta (~2-8 Hz) and central-parietal-occipital sensorimotor rhythm (SMR) activity (~8-16 Hz) time-locked to EMs, were greater on the ToH night versus control night, and during phasic REM sleep, were both positively correlated with overnight memory improvements. Furthermore, SMR power during tonic REM increased significantly from the control night to ToH night, but was relatively stable from night to night during phasic REM. These results suggest that EMs are markers of learning-related increases in theta and SMR during phasic and tonic REM sleep. Phasic and tonic REM sleep may be functionally distinct in terms of their contribution to procedural memory consolidation.
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Affiliation(s)
| | - Aaron Gibbings
- School of Psychology, University of Ottawa, Ottawa, Canada
| | - Daniel Baena
- School of Psychology, University of Ottawa, Ottawa, Canada
| | | | | | - Laura B Ray
- School of Psychology, University of Ottawa, Ottawa, Canada
- The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
- University of Ottawa Brain and Mind Research Institute, University of Ottawa, Ottawa, Canada
| | - Stuart M Fogel
- School of Psychology, University of Ottawa, Ottawa, Canada
- The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
- University of Ottawa Brain and Mind Research Institute, University of Ottawa, Ottawa, Canada
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8
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Lambert I, Peter-Derex L. Spotlight on Sleep Stage Classification Based on EEG. Nat Sci Sleep 2023; 15:479-490. [PMID: 37405208 PMCID: PMC10317531 DOI: 10.2147/nss.s401270] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 06/21/2023] [Indexed: 07/06/2023] Open
Abstract
The recommendations for identifying sleep stages based on the interpretation of electrophysiological signals (electroencephalography [EEG], electro-oculography [EOG], and electromyography [EMG]), derived from the Rechtschaffen and Kales manual, were published in 2007 at the initiative of the American Academy of Sleep Medicine, and regularly updated over years. They offer an important tool to assess objective markers in different types of sleep/wake subjective complaints. With the aims and advantages of simplicity, reproducibility and standardization of practices in research and, most of all, in sleep medicine, they have overall changed little in the way they describe sleep. However, our knowledge on sleep/wake physiology and sleep disorders has evolved since then. High-density electroencephalography and intracranial electroencephalography studies have highlighted local regulation of sleep mechanisms, with spatio-temporal heterogeneity in vigilance states. Progress in the understanding of sleep disorders has allowed the identification of electrophysiological biomarkers better correlated with clinical symptoms and outcomes than standard sleep parameters. Finally, the huge development of sleep medicine, with a demand for explorations far exceeding the supply, has led to the development of alternative studies, which can be carried out at home, based on a smaller number of electrophysiological signals and on their automatic analysis. In this perspective article, we aim to examine how our description of sleep has been constructed, has evolved, and may still be reshaped in the light of advances in knowledge of sleep physiology and the development of technical recording and analysis tools. After presenting the strengths and limitations of the classification of sleep stages, we propose to challenge the "EEG-EOG-EMG" paradigm by discussing the physiological signals required for sleep stages identification, provide an overview of new tools and automatic analysis methods and propose avenues for the development of new approaches to describe and understand sleep/wake states.
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Affiliation(s)
- Isabelle Lambert
- APHM, Timone Hospital, Sleep Unit, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille University, INSERM, Institut de Neuroscience des Systemes, Marseille, France
| | - Laure Peter-Derex
- Center for Sleep Medicine and Respiratory Diseases, Croix-Rousse Hospital, Hospices Civils de Lyon, Lyon 1 University, Lyon, France
- Lyon Neuroscience Research Center, PAM Team, INSERM U1028, CNRS UMR 5292, Lyon, France
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9
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Peter-Derex L, von Ellenrieder N, van Rosmalen F, Hall J, Dubeau F, Gotman J, Frauscher B. Regional variability in intracerebral properties of NREM to REM sleep transitions in humans. Proc Natl Acad Sci U S A 2023; 120:e2300387120. [PMID: 37339200 PMCID: PMC10293806 DOI: 10.1073/pnas.2300387120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 05/12/2023] [Indexed: 06/22/2023] Open
Abstract
Transitions between wake and sleep states show a progressive pattern underpinned by local sleep regulation. In contrast, little evidence is available on non-rapid eye movement (NREM) to rapid eye movement (REM) sleep boundaries, considered as mainly reflecting subcortical regulation. Using polysomnography (PSG) combined with stereoelectroencephalography (SEEG) in humans undergoing epilepsy presurgical evaluation, we explored the dynamics of NREM-to-REM transitions. PSG was used to visually score transitions and identify REM sleep features. SEEG-based local transitions were determined automatically with a machine learning algorithm using features validated for automatic intra-cranial sleep scoring (10.5281/zenodo.7410501). We analyzed 2988 channel-transitions from 29 patients. The average transition time from all intracerebral channels to the first visually marked REM sleep epoch was 8 s ± 1 min 58 s, with a great heterogeneity between brain areas. Transitions were observed first in the lateral occipital cortex, preceding scalp transition by 1 min 57 s ± 2 min 14 s (d = -0.83), and close to the first sawtooth wave marker. Regions with late transitions were the inferior frontal and orbital gyri (1 min 1 s ± 2 min 1 s, d = 0.43, and 1 min 1 s ± 2 min 5 s, d = 0.43, after scalp transition). Intracranial transitions were earlier than scalp transitions as the night advanced (last sleep cycle, d = -0.81). We show a reproducible gradual pattern of REM sleep initiation, suggesting the involvement of cortical mechanisms of regulation. This provides clues for understanding oneiric experiences occurring at the NREM/REM boundary.
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Affiliation(s)
- Laure Peter-Derex
- Center for Sleep Medicine and Respiratory Diseases, Croix-Rousse Hospital, University Hospital of Lyon, Lyon 1 University, 69004Lyon, France
- Lyon Neuroscience Research Center, CNRS UMR5292/INSERM U1028, Lyon69000, France
| | - Nicolás von Ellenrieder
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QCH3A 2B4, Canada
| | - Frank van Rosmalen
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QCH3A 2B4, Canada
| | - Jeffery Hall
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QCH3A 2B4, Canada
| | - François Dubeau
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QCH3A 2B4, Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QCH3A 2B4, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QCH3A 2B4, Canada
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, QCH3A 2B4, Canada
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10
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Picard-Deland C, Bernardi G, Genzel L, Dresler M, Schoch SF. Memory reactivations during sleep: a neural basis of dream experiences? Trends Cogn Sci 2023; 27:568-582. [PMID: 36959079 DOI: 10.1016/j.tics.2023.02.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/18/2023] [Accepted: 02/28/2023] [Indexed: 03/25/2023]
Abstract
Newly encoded memory traces are spontaneously reactivated during sleep. Since their discovery in the 1990s, these memory reactivations have been discussed as a potential neural basis for dream experiences. New results from animal and human research, as well as from the rapidly growing field of sleep and dream engineering, provide essential insights into this question, and reveal both strong parallels and disparities between the two phenomena. We suggest that, although memory reactivations may contribute to subjective experiences across different states of consciousness, they are not likely to be the primary neural basis of dreaming. We identify important limitations in current research paradigms and suggest novel strategies to address this question empirically.
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Affiliation(s)
- Claudia Picard-Deland
- Dream and Nightmare Laboratory, Center for Advanced Research in Sleep Medicine, University of Montreal, Montreal, QC, Canada
| | - Giulio Bernardi
- Institutions, Markets, Technologies (IMT) School for Advanced Studies Lucca, Lucca, Italy
| | - Lisa Genzel
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Martin Dresler
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Sarah F Schoch
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands; Center of Competence Sleep and Health Zurich, University of Zurich, Zurich, Switzerland.
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11
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Schiller K, von Ellenrieder N, Avigdor T, El Kosseifi C, Abdallah C, Minato E, Gotman J, Frauscher B. Focal epilepsy impacts rapid eye movement sleep microstructure. Sleep 2023; 46:zsac250. [PMID: 36242588 PMCID: PMC9905780 DOI: 10.1093/sleep/zsac250] [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: 06/30/2022] [Revised: 08/16/2022] [Indexed: 12/12/2022] Open
Abstract
STUDY OBJECTIVES Whereas there is plenty of evidence on the influence of epileptic activity on non-rapid eye movement (NREM) sleep macro- and micro-structure, data on the impact of epilepsy on rapid eye movement (REM) sleep remains sparse. Using high-density electroencephalography (HD-EEG), we assessed global and focal disturbances of sawtooth waves (STW) as cortically generated sleep oscillations of REM sleep in patients with focal epilepsy. METHODS Twenty-two patients with drug-resistant focal epilepsy (13 females; mean age, 32.6 ± 10.7 years; 12 temporal lobe epilepsy) and 12 healthy controls (3 females; 24.0 ± 3.2 years) underwent combined overnight HD-EEG and polysomnography. STW rate, duration, frequency, power, spatial extent, IED rates and sleep homeostatic properties were analyzed. RESULTS STW rate and duration were reduced in patients with focal epilepsy compared to healthy controls (rate: 0.64/min ± 0.46 vs. 1.12/min ± 0.41, p = .005, d = -0.98; duration: 3.60 s ± 0.76 vs. 4.57 ± 1.00, p = .003, d = -1.01). Not surprisingly given the fronto-central maximum of STW, the reductions were driven by extratemporal lobe epilepsy patients (rate: 0.45/min ± 0.31 vs. 1.12/min ± 0.41, p = .0004, d = -1.35; duration: 3.49 s ± 0.92 vs. 4.57 ± 1.00, p = .017, d = -0.99) and were more pronounced in the first vs. the last sleep cycle (rate first cycle patients vs. controls: 0.60/min ± 0.49 vs. 1.10/min ± 0.55, p = .016, d = -0.90, rate last cycle patients vs. controls: 0.67/min ± 0.51 vs. 0.99/min ± 0.49, p = .11, d = -0.62; duration first cycle patients vs. controls: 3.60s ± 0.76 vs. 4.57 ± 1.00, p = .003, d = -1.01, duration last cycle patients vs. controls: 3.66s ± 0.84 vs. 4.51 ± 1.26, p = .039, d = -0.80). There was no regional decrease of STWs in the region with the epileptic focus vs. the contralateral side (all p > .05). CONCLUSION Patients with focal epilepsy and in particular extratemporal lobe epilepsy show a global reduction of STW activity in REM sleep. This may suggest that epilepsy impacts cortically generated sleep oscillations even in REM sleep when epileptic activity is low.
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Affiliation(s)
- Katharina Schiller
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
- Hospital Group Ostallgaeu-Kaufbeuren, Department of Pediatrics, Kaufbeuren, Germany
- Medical University Innsbruck, Department of Pediatrics, Innsbruck, Austria
| | | | - Tamir Avigdor
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Charbel El Kosseifi
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Chifaou Abdallah
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Erica Minato
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
- Department of Medicine and Center for Neuroscience Studies, Queen’s University; Kingston, Ontario, Canada
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12
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Interictal sleep recordings during presurgical evaluation: Bidirectional perspectives on sleep related network functioning. Rev Neurol (Paris) 2022; 178:703-713. [DOI: 10.1016/j.neurol.2022.03.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 03/08/2022] [Accepted: 03/08/2022] [Indexed: 11/23/2022]
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13
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von Ellenrieder N, Peter-Derex L, Gotman J, Frauscher B. SleepSEEG: Automatic sleep scoring using intracranial EEG recordings only. J Neural Eng 2022; 19. [PMID: 35439736 DOI: 10.1088/1741-2552/ac6829] [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: 12/22/2021] [Accepted: 04/18/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE To perform automatic sleep scoring based only on intracranial EEG, without the need for scalp electroencephalography (EEG), electrooculography (EOG) and electromyography (EMG), in order to study sleep, epilepsy, and their interaction. APPROACH Data from 33 adult patients was used for development and training of the automatic scoring algorithm using both oscillatory and non-oscillatory spectral features. The first step consisted in unsupervised clustering of channels based on feature variability. For each cluster the classification was done in two steps, a multiclass tree followed by binary classification trees to distinguish the more challenging stage N1. The test data consisted in 11 patients, in whom the classification was done independently for each channel and then combined to get a single stage per epoch. MAIN RESULTS An overall agreement of 78% was observed in the test set between the sleep scoring of the algorithm and two human experts scoring based on scalp EEG, EOG and EMG. Balanced sensitivity and specificity were obtained for the different sleep stages. The performance was excellent for stages W, N2, and N3, and good for stage R, but with high variability across patients. The performance for the challenging stage N1 was poor, but at a similar level as for published algorithms based on scalp EEG. High confidence epochs in different stages (other than N1) can be identified with median per patient specificity >80%. SIGNIFICANCE The automatic algorithm can perform sleep scoring of long term recordings of patients with intracranial electrodes undergoing presurgical evaluation in the absence of scalp EEG, EOG and EMG, which are normally required to define sleep stages but are difficult to use in the context of intracerebral studies. It also constitutes a valuable tool to generate hypotheses regarding local aspects of sleep, and will be significant for sleep evaluation in clinical epileptology and neuroscience research.
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Affiliation(s)
- Nicolás von Ellenrieder
- Montreal Neurological Institute and Hospital, McGill University, 3801 University streeet, Montreal, Quebec, H3A 2B4, CANADA
| | - Laure Peter-Derex
- PAM Team, Centre de Recherche en Neurosciences de Lyon, 95 Boulevard Pinel, Lyon, Rhône-Alpes , 69675 BRON, FRANCE
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, 3801 University St, Montreal, Quebec, H3A 2B4, CANADA
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, CANADA
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Ioannides AA, Orphanides GA, Liu L. Rhythmicity in heart rate and its surges usher a special period of sleep, a likely home for PGO waves. Curr Res Physiol 2022; 5:118-141. [PMID: 35243361 PMCID: PMC8867048 DOI: 10.1016/j.crphys.2022.02.003] [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: 11/14/2021] [Revised: 02/01/2022] [Accepted: 02/06/2022] [Indexed: 11/30/2022] Open
Abstract
High amplitude electroencephalogram (EEG) events, like unitary K-complex (KC), are used to partition sleep into stages and hence define the hypnogram, a key instrument of sleep medicine. Throughout sleep the heart rate (HR) changes, often as a steady HR increase leading to a peak, what is known as a heart rate surge (HRS). The hypnogram is often unavailable when most needed, when sleep is disturbed and the graphoelements lose their identity. The hypnogram is also difficult to define during normal sleep, particularly at the start of sleep and the periods that precede and follow rapid eye movement (REM) sleep. Here, we use objective quantitative criteria that group together periods that cannot be assigned to a conventional sleep stage into what we call REM0 periods, with the presence of a HRS one of their defining properties. Extended REM0 periods are characterized by highly regular sequences of HRS that generate an infra-low oscillation around 0.05 Hz. During these regular sequence of HRS, and just before each HRS event, we find avalanches of high amplitude events for each one of the mass electrophysiological signals, i.e. related to eye movement, the motor system and the general neural activity. The most prominent features of long REM0 periods are sequences of three to five KCs which we label multiple K-complexes (KCm). Regarding HRS, a clear dissociation is demonstrated between the presence or absence of high gamma band spectral power (55-95 Hz) of the two types of KCm events: KCm events with strong high frequencies (KCmWSHF) cluster just before the peak of HRS, while KCm between HRS show no increase in high gamma band (KCmNOHF). Tomographic estimates of activity from magnetoencephalography (MEG) in pre-KC periods (single and multiple) showed common increases in the cholinergic Nucleus Basalis of Meynert in the alpha band. The direct contrast of KCmWSHF with KCmNOHF showed increases in all subjects in the high sigma band in the base of the pons and in three subjects in both the delta and high gamma bands in the medial Pontine Reticular Formation (mPRF), the putative Long Lead Initial pulse (LLIP) for Ponto-Geniculo-Occipital (PGO) waves.
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Affiliation(s)
- Andreas A. Ioannides
- Lab. for Human Brain Dynamics, AAI Scientific Cultural Services Ltd., Nicosia, 1065, Cyprus
| | - Gregoris A. Orphanides
- Lab. for Human Brain Dynamics, AAI Scientific Cultural Services Ltd., Nicosia, 1065, Cyprus
- The English School, Nicosia, 1684, Cyprus
| | - Lichan Liu
- Lab. for Human Brain Dynamics, AAI Scientific Cultural Services Ltd., Nicosia, 1065, Cyprus
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15
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Zhou L, Zhu Q, Wu B, Qin B, Hu H, Qian Z. A comparison of directed functional connectivity among fist-related brain activities during movement imagery, movement execution, and movement observation. Brain Res 2021; 1777:147769. [PMID: 34971597 DOI: 10.1016/j.brainres.2021.147769] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 12/03/2021] [Accepted: 12/24/2021] [Indexed: 12/22/2022]
Abstract
Brain-computer interface (BCI) has been widely used in sports training and rehabilitation training. It is primarily based on action simulation, including movement imagery (MI) and movement observation (MO). However, the development of BCI technology is limited due to the challenge of getting an in-depth understanding of brain networks involved in MI, MO, and movement execution (ME). To better understand the brain activity changes and the communications across various brain regions under MO, ME, and MI, this study conducted the fist experiment under MO, ME, and MI. We recorded 64-channel electroencephalography (EEG) from 39 healthy subjects (25 males, 14 females, all right-handed) during fist tasks, obtained intensities and locations of sources using EEG source imaging (ESI), computed source activation modes, and finally investigated the brain networks using spectral Granger causality (GC). The brain regions involved in the three motor conditions are similar, but the degree of participation of each brain region and the network connections among the brain regions are different. MO, ME, and MI did not recruit shared brain connectivity networks. In addition, both source activation modes and brain network connectivity had lateralization advantages.
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Affiliation(s)
- Lu Zhou
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Qiaoqiao Zhu
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Biao Wu
- Electronic Information Department, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Bing Qin
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Haixu Hu
- Sports Training Academy, Nanjing Sport Institute, Nanjing, China
| | - Zhiyu Qian
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
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16
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de la Chapelle A, Frauscher B, Valomon A, Ruby PM, Peter-Derex L. Relationship Between Epilepsy and Dreaming: Current Knowledge, Hypotheses, and Perspectives. Front Neurosci 2021; 15:717078. [PMID: 34552464 PMCID: PMC8451887 DOI: 10.3389/fnins.2021.717078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 08/16/2021] [Indexed: 11/13/2022] Open
Abstract
The interactions between epilepsy and sleep are numerous and the impact of epilepsy on cognition is well documented. Epilepsy is therefore likely to influence dreaming as one sleep-related cognitive activity. The frequency of dream recall is indeed decreased in patients with epilepsy, especially in those with primary generalized seizures. The content of dreams is also disturbed in epilepsy patients, being more negative and with more familiar settings. While several confounding factors (anti-seizure medications, depression and anxiety disorders, cognitive impairment) may partly account for these changes, some observations suggest an effect of seizures themselves on dreams. Indeed, the incorporation of seizure symptoms in dream content has been described, concomitant or not with a focal epileptic discharge during sleep, suggesting that epilepsy might directly or indirectly interfere with dreaming. These observations, together with current knowledge on dream neurophysiology and the links between epilepsy and sleep, suggest that epilepsy may impact not only wake- but also sleep-related cognition.
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Affiliation(s)
| | - Birgit Frauscher
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Amandine Valomon
- Lyon Neuroscience Research Center, CNRS UMR 5292, INSERM U1028-PAM Team, Lyon, France
| | - Perrine Marie Ruby
- Lyon Neuroscience Research Center, CNRS UMR 5292, INSERM U1028-PAM Team, Lyon, France
| | - Laure Peter-Derex
- Lyon Neuroscience Research Center, CNRS UMR 5292, INSERM U1028-PAM Team, Lyon, France.,Center for Sleep Medicine and Respiratory Diseases, Lyon University Hospital, Lyon 1 University, Lyon, France
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17
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Picard-Deland C, Nielsen T. Targeted memory reactivation has a sleep stage-specific delayed effect on dream content. J Sleep Res 2021; 31:e13391. [PMID: 34018262 DOI: 10.1111/jsr.13391] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 04/13/2021] [Accepted: 04/29/2021] [Indexed: 12/29/2022]
Abstract
Although new learning is known to reappear in later dream scenarios, the timing of such reappearances remains unclear. Sometimes, references to new learning occur relatively quickly, 1 day post-learning (day-residue effect); at other times there may be a substantive delay, 5-7 days, before such references appear (dream-lag effect). We studied temporal delays in dream reactivation following the learning of a virtual reality (VR) flying task using 10-day home sleep/dream logs, and how these might be influenced by targeted memory reactivation (TMR). Participants were exposed twice to a VR task in the sleep laboratory; once before and once after a 2-hr opportunity to nap (n = 65) or to read (n = 32). Auditory cues associated with the VR task were replayed in either wake, rapid eye movement (REM) sleep, slow-wave sleep (SWS) or were not replayed. Although we previously showed that TMR cueing did not have an immediate effect on dream content, in the present study we extend these results by showing that TMR in sleep has instead a delayed effect on task-dream reactivations: participants dreamed more about the task 1-2 days later when TMR was applied in REM sleep and 5-6 days later when it was applied in SWS sleep, compared to participants with no cueing. Findings may help explain the temporal relationships between dream and memory reactivations and clarify the occurrence of day-residue and dream-lag phenomena.
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Affiliation(s)
- Claudia Picard-Deland
- Dream and Nightmare Laboratory, Center for Advanced Research in Sleep Medicine, CIUSSS-NÎM - Hôpital du Sacré-Coeur de Montréal, Montréal, QC, Canada.,Department of Neuroscience, Université de Montréal, Montréal, QC, Canada
| | - Tore Nielsen
- Dream and Nightmare Laboratory, Center for Advanced Research in Sleep Medicine, CIUSSS-NÎM - Hôpital du Sacré-Coeur de Montréal, Montréal, QC, Canada.,Department of Psychiatry and Addictology, Université de Montréal, Montréal, QC, Canada
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