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Zhu H, Michalak AJ, Merricks EM, Agopyan-Miu AHCW, Jacobs J, Hamberger MJ, Sheth SA, McKhann GM, Feldstein N, Schevon CA, Hillman EMC. Spectral-switching analysis reveals real-time neuronal network representations of concurrent spontaneous naturalistic behaviors in human brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.08.600416. [PMID: 39026706 PMCID: PMC11257469 DOI: 10.1101/2024.07.08.600416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Despite abundant evidence of functional networks in the human brain, their neuronal underpinnings, and relationships to real-time behavior have been challenging to resolve. Analyzing brain-wide intracranial-EEG recordings with video monitoring, acquired in awake subjects during clinical epilepsy evaluation, we discovered the tendency of each brain region to switch back and forth between 2 distinct power spectral densities (PSDs 2-55Hz). We further recognized that this 'spectral switching' occurs synchronously between distant sites, even between regions with differing baseline PSDs, revealing long-range functional networks that would be obscured in analysis of individual frequency bands. Moreover, the real-time PSD-switching dynamics of specific networks exhibited striking alignment with activities such as conversation and hand movements, revealing a multi-threaded functional network representation of concurrent naturalistic behaviors. Network structures and their relationships to behaviors were stable across days, but were altered during N3 sleep. Our results provide a new framework for understanding real-time, brain-wide neural-network dynamics.
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Affiliation(s)
- Hongkun Zhu
- Department of Biomedical Engineering, Columbia University
- Department of Neurology, Columbia University Irving Medical Center, New York, NY 10032, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027
| | - Andrew J Michalak
- Department of Neurology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Edward M Merricks
- Department of Neurology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | | | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University
- Department of Neurological Surgery, Columbia University Medical Center, New York, 10032, New York, USA
| | - Marla J Hamberger
- Department of Neurology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Sameer A Sheth
- Department of Neurological Surgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Guy M McKhann
- Department of Neurological Surgery, Columbia University Medical Center, New York, 10032, New York, USA
| | - Neil Feldstein
- Department of Neurological Surgery, Columbia University Medical Center, New York, 10032, New York, USA
| | - Catherine A Schevon
- Department of Neurology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Elizabeth M C Hillman
- Department of Biomedical Engineering, Columbia University
- Department of Radiology, Columbia University Medical Center, New York, 10032, New York, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027
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2
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Ran B, Su E, He D, Guo Z, Jiang B. Functional MRI-based biomarkers of insomnia with objective short sleep duration phenotype. Sleep Med 2024; 121:191-195. [PMID: 39002327 DOI: 10.1016/j.sleep.2024.07.012] [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: 04/03/2024] [Revised: 05/31/2024] [Accepted: 07/09/2024] [Indexed: 07/15/2024]
Abstract
BACKGROUND Insomnia disorder with objective short sleep duration (ISS) phenotype is a more serious biological subtype than insomnia with objective normal sleep duration (INS) phenotype, and the neuroimaging data is helpful to understand the pathophysiology of the ISS phenotype. This study was to compare the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) between the ISS phenotype and the INS phenotype. METHODS In this cross-sectional study, 55 patients with insomnia disorder were recruited, and 22 of them were defined as the ISS phenotype by the objective cardiopulmonary coupling (CPC) technique. The blood oxygen level-dependent (BOLD) sequences of all participants were obtained using the 3.0 T magnetic resonance imaging system. We analyzed and compared the ALFF, ReHo, and FC between the ISS phenotype and the INS phenotype. We also conducted Pearson's correlation analysis between significant neuroimaging biomarkers and the CPC parameters. RESULTS The differences were not significant in ALFF (PFWE-corr>0.05) or ReHo (PFWE-corr>0.05) between the ISS phenotype and the INS phenotype. For the FC analysis, the ISS phenotype had a Hub-node of the left inferior occipital gyrus (IOG.L), with significantly decreased connections (p<0.001) in the bilateral occipital, parietal, and temporal regions. The significant FCs were closely related to sleep parameters. CONCLUSION The left inferior occipital gyrus (IOG.L), as a Hub-node with decreased functional connections, may be a potential fMRI-based biomarker of the ISS phenotype.
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Affiliation(s)
- Bingqing Ran
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, 637000, Sichuan, China
| | - E Su
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, 637000, Sichuan, China
| | - Dongmei He
- Department of Neurology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, 637000, Sichuan, China
| | - Zhiwei Guo
- Institute of Brain Function, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, 637000, Sichuan, China
| | - Binghu Jiang
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, 637000, Sichuan, China; Institute of Brain Function, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, 637000, Sichuan, China.
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3
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Lee K, Wang Y, Cross NE, Jegou A, Razavipour F, Pomares FB, Perrault AA, Nguyen A, Aydin Ü, Uji M, Abdallah C, Anticevic A, Frauscher B, Benali H, Dang-vu TT, Grova C. NREM sleep brain networks modulate cognitive recovery from sleep deprivation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.28.601285. [PMID: 39005401 PMCID: PMC11244911 DOI: 10.1101/2024.06.28.601285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Decrease in cognitive performance after sleep deprivation followed by recovery after sleep suggests its key role, and especially non-rapid eye movement (NREM) sleep, in the maintenance of cognition. It remains unknown whether brain network reorganization in NREM sleep stages N2 and N3 can uniquely be mapped onto individual differences in cognitive performance after a recovery nap following sleep deprivation. Using resting state functional magnetic resonance imaging (fMRI), we quantified the integration and segregation of brain networks during NREM sleep stages N2 and N3 while participants took a 1-hour nap following 24-hour sleep deprivation, compared to well-rested wakefulness. Here, we advance a new analytic framework called the hierarchical segregation index (HSI) to quantify network segregation across spatial scales, from whole-brain to the voxel level, by identifying spatio-temporally overlapping large-scale networks and the corresponding voxel-to-region hierarchy. Our results show that network segregation increased in the default mode, dorsal attention and somatomotor networks during NREM sleep compared to wakefulness. Segregation within the visual, limbic, and executive control networks exhibited N2 versus N3 sleep-specific voxel-level patterns. More segregation during N3 was associated with worse recovery of working memory, executive attention, and psychomotor vigilance after the nap. The level of spatial resolution of network segregation varied among brain regions and was associated with the recovery of performance in distinct cognitive tasks. We demonstrated the sensitivity and reliability of voxel-level HSI to provide key insights into within-region variation, suggesting a mechanistic understanding of how NREM sleep replenishes cognition after sleep deprivation.
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Affiliation(s)
- Kangjoo Lee
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA, 06510
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, QC, Canada H3A 2B4
| | - Yimeng Wang
- Multimodal Functional Imaging Lab, Department of Physics, Concordia University, Montréal, QC, Canada H4B 2A7
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China 200025
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China 200025
| | - Nathan E. Cross
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- Sleep, Cognition and Neuroimaging Lab, Department of Health, Kinesiology and Applied Physiology & Center for Studies in Behavioral Neurobiology, Concordia University, Montréal, QC, Canada H4B 1R6
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, CIUSSS Centre-Sud-de-l’Ile-de-Montréal, Montréal, QC, Canada H3W 1W5
| | - Aude Jegou
- Multimodal Functional Imaging Lab, Department of Physics, Concordia University, Montréal, QC, Canada H4B 2A7
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- Sleep, Cognition and Neuroimaging Lab, Department of Health, Kinesiology and Applied Physiology & Center for Studies in Behavioral Neurobiology, Concordia University, Montréal, QC, Canada H4B 1R6
| | - Fatemeh Razavipour
- Multimodal Functional Imaging Lab, Department of Physics, Concordia University, Montréal, QC, Canada H4B 2A7
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
| | - Florence B. Pomares
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- Sleep, Cognition and Neuroimaging Lab, Department of Health, Kinesiology and Applied Physiology & Center for Studies in Behavioral Neurobiology, Concordia University, Montréal, QC, Canada H4B 1R6
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, CIUSSS Centre-Sud-de-l’Ile-de-Montréal, Montréal, QC, Canada H3W 1W5
| | - Aurore A. Perrault
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- Sleep, Cognition and Neuroimaging Lab, Department of Health, Kinesiology and Applied Physiology & Center for Studies in Behavioral Neurobiology, Concordia University, Montréal, QC, Canada H4B 1R6
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, CIUSSS Centre-Sud-de-l’Ile-de-Montréal, Montréal, QC, Canada H3W 1W5
| | - Alex Nguyen
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- Sleep, Cognition and Neuroimaging Lab, Department of Health, Kinesiology and Applied Physiology & Center for Studies in Behavioral Neurobiology, Concordia University, Montréal, QC, Canada H4B 1R6
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, CIUSSS Centre-Sud-de-l’Ile-de-Montréal, Montréal, QC, Canada H3W 1W5
| | - Ümit Aydin
- Multimodal Functional Imaging Lab, Department of Physics, Concordia University, Montréal, QC, Canada H4B 2A7
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, United Kingdom, RG6 6ET
| | - Makoto Uji
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- Sleep, Cognition and Neuroimaging Lab, Department of Health, Kinesiology and Applied Physiology & Center for Studies in Behavioral Neurobiology, Concordia University, Montréal, QC, Canada H4B 1R6
| | - Chifaou Abdallah
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, QC, Canada H3A 2B4
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montréal, QC, Canada H3A 1A1
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montréal, QC, Canada H3A 2B4
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA, 06510
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, Connecticut, USA, 06510
- Department of Psychology, Yale University School of Medicine, New Haven, Connecticut, USA, 06510
| | - Birgit Frauscher
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montréal, QC, Canada H3A 1A1
- Analytical Neurophysiology Lab, Department of Neurology, Duke University Medical Center, Durham, NC, USA
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montréal, QC, Canada H3A 2B4
| | - Habib Benali
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- Biomedical Imaging and Healthy Aging Laboratory, Department of Electrical and Computer Engineering, Concordia University, Montréal, Québec, Canada H3G 1S6
| | - Thien Thanh Dang-vu
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- Sleep, Cognition and Neuroimaging Lab, Department of Health, Kinesiology and Applied Physiology & Center for Studies in Behavioral Neurobiology, Concordia University, Montréal, QC, Canada H4B 1R6
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, CIUSSS Centre-Sud-de-l’Ile-de-Montréal, Montréal, QC, Canada H3W 1W5
| | - Christophe Grova
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, QC, Canada H3A 2B4
- Multimodal Functional Imaging Lab, Department of Physics, Concordia University, Montréal, QC, Canada H4B 2A7
- Concordia School of Health / PERFORM Centre, Concordia University, Montréal, QC, Canada H4B 1R6
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montréal, QC, Canada H3A 1A1
- Centre De Recherches En Mathématiques, Montréal, Québec, Canada H3C 3J7
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Li G, Cao Y, Yang C, Li X, Yang Y, Yang L, Hao D, Li CSR. Sex differences in dorsolateral prefrontal cortical and superior colliculus activities support the impact of alcohol use severity and sleep deficiency on two-back memory. Quant Imaging Med Surg 2024; 14:4972-4986. [PMID: 39022273 PMCID: PMC11250293 DOI: 10.21037/qims-24-156] [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: 01/25/2024] [Accepted: 05/20/2024] [Indexed: 07/20/2024]
Abstract
Background Working memory refers to a process of temporary storage and manipulation of information to support planning, decision-making, and action. Frequently comorbid alcohol misuse and sleep deficiency have both been associated with working memory deficits. However, how alcohol misuse and sleep deficiency interact to impact working memory remains unclear. In this study, we aim to investigate the neural processes inter-relating alcohol misuse, sleep deficiency and working memory. Methods We curated the Human Connectome Project (HCP) dataset and investigated the neural correlation of working memory in link with alcohol use severity and sleep deficiency in 991 young adults (521 women). The two were indexed by the first principal component (PC1) of principal component analysis of all drinking metrics and Pittsburgh Sleep Quality Index (PSQI) score, respectively. We processed the imaging data with published routines and evaluated the results with a corrected threshold. We used path model to characterize the inter-relationship between the clinical, behavioral, and neural measures, and explored sex differences in the findings. Results In whole-brain regression, we identified β estimates of dorsolateral prefrontal cortex response (DLPFC β) to 2- vs. 0-back in correlation with PC1. The DLPFC showed higher activation in positive correlation with PC1 across men and women (r=0.16, P<0.001). Path analyses showed the model PC1 → DLPFC β → differences in reaction time (2- minus 0-back; RT2-0) of correct trials → differences in critical success index (2- minus 0-back; CSI2-0) with the best fit. In women alone, in addition to the DLPFC, a cluster in the superior colliculus (SC) showed a significant negative correlation with the PSQI score (r=-0.23, P<0.001), and the path model showed the inter-relationship of PC1, PSQI score, DLPFC and SC β's, and CSI2-0 in women. Conclusions Alcohol misuse may involve higher DLPFC activation in functional compensation, whereas, in women only, sleep deficiency affects 2-back memory by depressing SC activity. In women only, path model suggests inter-related impact of drinking severity and sleep deficiency on 2-back memory. These findings suggest potential sex differences in the impact of drinking and sleep problems on working memory that need to be further investigated.
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Affiliation(s)
- Guangfei Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Yingjie Cao
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Chunlan Yang
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Xuwen Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Yimin Yang
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
| | - Lin Yang
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Dongmei Hao
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, China
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Chiang-Shan R. Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
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5
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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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6
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Kung YC, Li CW, Hsu AL, Liu CY, Wu CW, Chang WC, Lin CP. Neurovascular coupling in eye-open-eye-close task and resting state: Spectral correspondence between concurrent EEG and fMRI. Neuroimage 2024; 289:120535. [PMID: 38342188 DOI: 10.1016/j.neuroimage.2024.120535] [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: 09/09/2023] [Revised: 01/23/2024] [Accepted: 02/08/2024] [Indexed: 02/13/2024] Open
Abstract
Neurovascular coupling serves as an essential neurophysiological mechanism in functional neuroimaging, which is generally presumed to be robust and invariant across different physiological states, encompassing both task engagement and resting state. Nevertheless, emerging evidence suggests that neurovascular coupling may exhibit state dependency, even in normal human participants. To investigate this premise, we analyzed the cross-frequency spectral correspondence between concurrently recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, utilizing them as proxies for neurovascular coupling during the two conditions: an eye-open-eye-close (EOEC) task and a resting state. We hypothesized that given the state dependency of neurovascular coupling, EEG-fMRI spectral correspondences would change between the two conditions in the visual system. During the EOEC task, we observed a negative phase-amplitude-coupling (PAC) between EEG alpha-band and fMRI visual activity. Conversely, in the resting state, a pronounced amplitude-amplitude-coupling (AAC) emerged between EEG and fMRI signals, as evidenced by the spectral correspondence between the EEG gamma-band of the midline occipital channel (Oz) and the high-frequency fMRI signals (0.15-0.25 Hz) in the visual network. This study reveals distinct scenarios of EEG-fMRI spectral correspondence in healthy participants, corroborating the state-dependent nature of neurovascular coupling.
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Affiliation(s)
- Yi-Chia Kung
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chia-Wei Li
- Department of Radiology, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| | - Ai-Ling Hsu
- Bachelor Program in Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Chi-Yun Liu
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
| | - Changwei W Wu
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan; Research Center of Sleep Medicine, Taipei Medical University Hospital, Taipei, Taiwan.
| | - Wei-Chou Chang
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Hsinchu, Taiwan; Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
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7
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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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8
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Ruby P, Evangelista E, Bastuji H, Peter-Derex L. From physiological awakening to pathological sleep inertia: Neurophysiological and behavioural characteristics of the sleep-to-wake transition. Neurophysiol Clin 2024; 54:102934. [PMID: 38394921 DOI: 10.1016/j.neucli.2023.102934] [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: 09/30/2023] [Revised: 12/07/2023] [Accepted: 12/08/2023] [Indexed: 02/25/2024] Open
Abstract
Sleep inertia refers to the transient physiological state of hypoarousal upon awakening, associated with various degrees of impaired neurobehavioral performance, confusion, a desire to return to sleep and often a negative emotional state. Scalp and intracranial electro-encephalography as well as functional imaging studies have provided evidence that the sleep inertia phenomenon is underpinned by an heterogenous cerebral state mixing local sleep and local wake patterns of activity, at the neuronal and network levels. Sleep inertia is modulated by homeostasis and circadian processes, sleep stage upon awakening, and individual factors; this translates into a huge variability in its intensity even under physiological conditions. In sleep disorders, especially in hypersomnolence disorders such as idiopathic hypersomnia, sleep inertia may be a daily, serious and long-lasting symptom leading to severe impairment. To date, few tools have been developed to assess sleep inertia in clinical practice. They include mainly questionnaires and behavioral tests such as the psychomotor vigilance task. Only one neurophysiological protocol has been evaluated in hypersomnia, the forced awakening test which is based on an event-related potentials paradigm upon awakening. This contrasts with the major functional consequences of sleep inertia and its potentially dangerous consequences in subjects required to perform safety-critical tasks soon after awakening. There is a great need to identify reproducible biomarkers correlated with sleep inertia-associated cognitive and behavioral impairment. These biomarkers will aim at better understanding and measuring sleep inertia in physiological and pathological conditions, as well as objectively evaluating wake-promoting treatments or non-pharmacological countermeasures to reduce this phenomenon.
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Affiliation(s)
- Perrine Ruby
- Lyon Neuroscience Research Centre, INSERM U1028, CNRS UMR 5292, Lyon, France
| | - Elisa Evangelista
- Sleep disorder Unit, Carémeau Hospital, Centre Hospitalo-universitaire de Nîmes, France; Institute for Neurosciences of Montpellier INM, Univ Montpellier, INSERM, Montpellier, France
| | - Hélène Bastuji
- Lyon Neuroscience Research Centre, INSERM U1028, CNRS UMR 5292, Lyon, France; Centre for Sleep Medicine and Respiratory Diseases, Croix-Rousse Hospital, Hospices Civils de Lyon, Lyon 1 University, Lyon, France
| | - Laure Peter-Derex
- Lyon Neuroscience Research Centre, INSERM U1028, CNRS UMR 5292, Lyon, France; Centre for Sleep Medicine and Respiratory Diseases, Croix-Rousse Hospital, Hospices Civils de Lyon, Lyon 1 University, Lyon, France.
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9
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Cecconi B, Montupil J, Mortaheb S, Panda R, Sanders RD, Phillips C, Alnagger N, Remacle E, Defresne A, Boly M, Bahri MA, Lamalle L, Laureys S, Gosseries O, Bonhomme V, Annen J. Study protocol: Cerebral characterization of sensory gating in disconnected dreaming states during propofol anesthesia using fMRI. Front Neurosci 2024; 18:1306344. [PMID: 38419667 PMCID: PMC10900985 DOI: 10.3389/fnins.2024.1306344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 01/29/2024] [Indexed: 03/02/2024] Open
Abstract
Background Disconnected consciousness describes a state in which subjective experience (i.e., consciousness) becomes isolated from the external world. It appears frequently during sleep or sedation, when subjective experiences remain vivid but are unaffected by external stimuli. Traditional methods of differentiating connected and disconnected consciousness, such as relying on behavioral responsiveness or on post-anesthesia reports, have demonstrated limited accuracy: unresponsiveness has been shown to not necessarily equate to unconsciousness and amnesic effects of anesthesia and sleep can impair explicit recollection of events occurred during sleep/sedation. Due to these methodological challenges, our understanding of the neural mechanisms underlying sensory disconnection remains limited. Methods To overcome these methodological challenges, we employ a distinctive strategy by combining a serial awakening paradigm with auditory stimulation during mild propofol sedation. While under sedation, participants are systematically exposed to auditory stimuli and questioned about their subjective experience (to assess consciousness) and their awareness of the sounds (to evaluate connectedness/disconnectedness from the environment). The data collected through interviews are used to categorize participants into connected and disconnected consciousness states. This method circumvents the requirement for responsiveness in assessing consciousness and mitigates amnesic effects of anesthesia as participants are questioned while still under sedation. Functional MRI data are concurrently collected to investigate cerebral activity patterns during connected and disconnected states, to elucidate sensory disconnection neural gating mechanisms. We examine whether this gating mechanism resides at the thalamic level or results from disruptions in information propagation to higher cortices. Furthermore, we explore the potential role of slow-wave activity (SWA) in inducing disconnected consciousness by quantifying high-frequency BOLD oscillations, a known correlate of slow-wave activity. Discussion This study represents a notable advancement in the investigation of sensory disconnection. The serial awakening paradigm effectively mitigates amnesic effects by collecting reports immediately after regaining responsiveness, while still under sedation. Ultimately, this research holds the potential to understand how sensory gating is achieved at the neural level. These biomarkers might be relevant for the development of sensitive anesthesia monitoring to avoid intraoperative connected consciousness and for the assessment of patients suffering from pathologically reduced consciousness. Clinical trial registration European Union Drug Regulating Authorities Clinical Trials Database (EudraCT), identifier 2020-003524-17.
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Affiliation(s)
- Benedetta Cecconi
- Coma Science Group, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Javier Montupil
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium
- University Department of Anesthesia and Intensive Care Medicine, Centre Hospitalier Régional de la Citadelle (CHR Citadelle), Liège, Belgium
| | - Sepehr Mortaheb
- Physiology of Cognition Research Lab, GIGA-Consciousness, GIGA Institute, University of Liège, Liege, Belgium
| | - Rajanikant Panda
- Coma Science Group, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Robert D. Sanders
- Central Clinical School, Sydney Medical School & NHMRC Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia
- Department of Anaesthetics & Institute of Academic Surgery, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - Christophe Phillips
- GIGA-CRC—In vivo Imaging—Neuroimaging, Data Acquisition and Processing, GIGA Institute, University of Liège, Liège, Belgium
| | - Naji Alnagger
- Coma Science Group, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Emma Remacle
- Coma Science Group, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium
| | - Aline Defresne
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium
- University Department of Anesthesia and Intensive Care Medicine, Centre Hospitalier Régional de la Citadelle (CHR Citadelle), Liège, Belgium
- Department of Anesthesia and Intensive Care Medicine, Liège University Hospital, Liège, Belgium
| | - Melanie Boly
- Department of Psychiatry, Wisconsin Institute for Sleep and Consciousness, University of Wisconsin, Madison, WI, United States
| | - Mohamed Ali Bahri
- GIGA-CRC—In vivo Imaging—Aging & Memory, GIGA Institute, University of Liège, Liège, Belgium
| | - Laurent Lamalle
- GIGA-CRC—In vivo Imaging—Aging & Memory, GIGA Institute, University of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
- Cervo Brain Research Centre, University Institute in Mental Health of Quebec, Québec, QC, Canada
- Consciousness Science Institute, Hangzhou Normal University, Hangzhou, China
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Vincent Bonhomme
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium
- Department of Anesthesia and Intensive Care Medicine, Liège University Hospital, Liège, Belgium
| | - Jitka Annen
- Coma Science Group, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
- Department of Data Analysis, University of Ghent, Ghent, Belgium
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10
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Helakari H, Järvelä M, Väyrynen T, Tuunanen J, Piispala J, Kallio M, Ebrahimi SM, Poltojainen V, Kananen J, Elabasy A, Huotari N, Raitamaa L, Tuovinen T, Korhonen V, Nedergaard M, Kiviniemi V. Effect of sleep deprivation and NREM sleep stage on physiological brain pulsations. Front Neurosci 2023; 17:1275184. [PMID: 38105924 PMCID: PMC10722275 DOI: 10.3389/fnins.2023.1275184] [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: 08/09/2023] [Accepted: 11/02/2023] [Indexed: 12/19/2023] Open
Abstract
Introduction Sleep increases brain fluid transport and the power of pulsations driving the fluids. We investigated how sleep deprivation or electrophysiologically different stages of non-rapid-eye-movement (NREM) sleep affect the human brain pulsations. Methods Fast functional magnetic resonance imaging (fMRI) was performed in healthy subjects (n = 23) with synchronous electroencephalography (EEG), that was used to verify arousal states (awake, N1 and N2 sleep). Cardiorespiratory rates were verified with physiological monitoring. Spectral power analysis assessed the strength, and spectral entropy assessed the stability of the pulsations. Results In N1 sleep, the power of vasomotor (VLF < 0.1 Hz), but not cardiorespiratory pulsations, intensified after sleep deprived vs. non-sleep deprived subjects. The power of all three pulsations increased as a function of arousal state (N2 > N1 > awake) encompassing brain tissue in both sleep stages, but extra-axial CSF spaces only in N2 sleep. Spectral entropy of full band and respiratory pulsations decreased most in N2 sleep stage, while cardiac spectral entropy increased in ventricles. Discussion In summary, the sleep deprivation and sleep depth, both increase the power and harmonize the spectral content of human brain pulsations.
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Affiliation(s)
- Heta Helakari
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Matti Järvelä
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Tommi Väyrynen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Johanna Tuunanen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Johanna Piispala
- Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Mika Kallio
- Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Seyed Mohsen Ebrahimi
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Valter Poltojainen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Janne Kananen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
- Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Ahmed Elabasy
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Niko Huotari
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Lauri Raitamaa
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Maiken Nedergaard
- Center of Translational Neuromedicine, University of Copenhagen, Copenhagen, Denmark
- Center of Translational Neuromedicine, University of Rochester, Rochester, NY, United States
| | - Vesa Kiviniemi
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
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11
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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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12
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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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13
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Kwak HY, Leem J, Seung HB, Kwon CY, Jeong HS, Kim SH. Acupuncture Therapy for Military Veterans Suffering from Posttraumatic Stress Disorder and Related Symptoms: A Scoping Review of Clinical Studies. Healthcare (Basel) 2023; 11:2957. [PMID: 37998449 PMCID: PMC10671227 DOI: 10.3390/healthcare11222957] [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: 10/13/2023] [Revised: 11/10/2023] [Accepted: 11/12/2023] [Indexed: 11/25/2023] Open
Abstract
Military personnel in combat face a high risk of developing posttraumatic stress disorder (PTSD). In this study, a protocol-based scoping review was conducted to identify the current status of research on the efficacy of acupuncture for treating combat-related PTSD in military personnel. A literature search was conducted across 14 databases in November 2022, and data from the included studies were collected and descriptively analyzed. A total of eight studies were included. Participants were assessed for core PTSD symptoms using the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-5 and the Clinician-Administered PTSD Scale, as well as related symptoms, such as sleep issues. Although the efficacy of acupuncture has been substantiated in numerous studies, certain metrics did not exhibit improvement. Auricular acupuncture was the most commonly used treatment (50%) followed by manual acupuncture (25%) and a combination of both (25%). Shenmen and Kidney points were frequently targeted at auricular acupoints. The treatment period varied between 5 days and 2 months. While adverse events were reported in two of the fifty-five patients in the intervention group and in four of the sixty-four patients in the control group in the randomized controlled trial studies, no fatal adverse events were reported.
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Affiliation(s)
- Hui-Yong Kwak
- Republic of Korea Army, Capital Defense Command, Gwacheon-daero, Gwanak-gu, Seoul 08801, Republic of Korea;
| | - Jungtae Leem
- Research Center of Traditional Korean Medicine, College of Korean Medicine, Wonkwang University, 460 Iksan-daero, Iksan 54538, Republic of Korea;
| | - Hye-bin Seung
- College of Korean Medicine, Daegu Haany University, 1, Hanuidae-ro, Gyeongsan 38578, Republic of Korea;
| | - Chan-Young Kwon
- Department of Oriental Neuropsychiatry, College of Korean Medicine, Dong-Eui University, Busan 47227, Republic of Korea;
| | - Hye-Seon Jeong
- Department of Clinical Korean Medicine, Graduate School, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemoon-gu, Seoul 02447, Republic of Korea;
| | - Sang-Ho Kim
- Department of Neuropsychiatry of Korean Medicine, Pohang Korean Medicine Hospital Affiliated to Daegu Haany University, Pohang 37685, Republic of Korea
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14
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Zelmann R, Paulk AC, Tian F, Balanza Villegas GA, Dezha Peralta J, Crocker B, Cosgrove GR, Richardson RM, Williams ZM, Dougherty DD, Purdon PL, Cash SS. Differential cortical network engagement during states of un/consciousness in humans. Neuron 2023; 111:3479-3495.e6. [PMID: 37659409 PMCID: PMC10843836 DOI: 10.1016/j.neuron.2023.08.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 06/13/2023] [Accepted: 08/08/2023] [Indexed: 09/04/2023]
Abstract
What happens in the human brain when we are unconscious? Despite substantial work, we are still unsure which brain regions are involved and how they are impacted when consciousness is disrupted. Using intracranial recordings and direct electrical stimulation, we mapped global, network, and regional involvement during wake vs. arousable unconsciousness (sleep) vs. non-arousable unconsciousness (propofol-induced general anesthesia). Information integration and complex processing we`re reduced, while variability increased in any type of unconscious state. These changes were more pronounced during anesthesia than sleep and involved different cortical engagement. During sleep, changes were mostly uniformly distributed across the brain, whereas during anesthesia, the prefrontal cortex was the most disrupted, suggesting that the lack of arousability during anesthesia results not from just altered overall physiology but from a disconnection between the prefrontal and other brain areas. These findings provide direct evidence for different neural dynamics during loss of consciousness compared with loss of arousability.
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Affiliation(s)
- Rina Zelmann
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA.
| | - Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
| | - Fangyun Tian
- Department of Anesthesia, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Britni Crocker
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Harvard-MIT Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick L Purdon
- Department of Anesthesia, Massachusetts General Hospital, Boston, MA, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
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15
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Örzsik B, Palombo M, Asllani I, Dijk DJ, Harrison NA, Cercignani M. Higher order diffusion imaging as a putative index of human sleep-related microstructural changes and glymphatic clearance. Neuroimage 2023; 274:120124. [PMID: 37084927 DOI: 10.1016/j.neuroimage.2023.120124] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/16/2023] [Accepted: 04/18/2023] [Indexed: 04/23/2023] Open
Abstract
The brain has a unique macroscopic waste clearance system, termed the glymphatic system which utilises perivascular tunnels surrounded by astroglia to promote cerebrospinal-interstitial fluid exchange. Rodent studies have demonstrated a marked increase in glymphatic clearance during sleep which has been linked to a sleep-induced expansion of the extracellular space and concomitant reduction in intracellular volume. However, despite being implicated in the pathophysiology of multiple human neurodegenerative disorders, non-invasive techniques for imaging glymphatic clearance in humans are currently limited. Here we acquired multi-shell diffusion weighted MRI (dwMRI) in twenty-one healthy young participants (6 female, 22.3 ± 3.2 years) each scanned twice, once during wakefulness and once during sleep induced by a combination of one night of sleep deprivation and 10 mg of the hypnotic zolpidem 30 min before scanning. To capture hypothesised sleep-associated changes in intra/extracellular space, dwMRI were analysed using higher order diffusion modelling with the prediction that sleep-associated increases in interstitial (extracellular) fluid volume would result in a decrease in diffusion kurtosis, particularly in areas associated with slow wave generation at the onset of sleep. In line with our hypothesis, we observed a global reduction in diffusion kurtosis (t15=2.82, p = 0.006) during sleep as well as regional reductions in brain areas associated with slow wave generation during early sleep and default mode network areas that are highly metabolically active during wakefulness. Analysis with a higher-order representation of diffusion (MAP-MRI) further indicated that changes within the intra/extracellular domain rather than membrane permeability likely underpin the observed sleep-associated decrease in kurtosis. These findings identify higher-order modelling of dwMRI as a potential new non-invasive method for imaging glymphatic clearance and extend rodent findings to suggest that sleep is also associated with an increase in interstitial fluid volume in humans.
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Affiliation(s)
- Balázs Örzsik
- Radiology, Leiden University Medical Center, Leiden, the Netherlands; CISC, Brighton and Sussex Medical School, Brighton, United Kingdom.
| | - Marco Palombo
- CUBRIC, Cardiff University, United Kingdom; School of Computer Science and Informatics, Cardiff University, Cardiff, UK
| | - Iris Asllani
- CISC, Brighton and Sussex Medical School, Brighton, United Kingdom; Rochester Institute of Technology, New York, United States
| | - Derk-Jan Dijk
- Surrey Sleep Research Centre, Faculty of Health and Medical Sciences, University of Surrey, Guildford UK; UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, Guildford UK
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16
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Yu Y, Qiu Y, Li G, Zhang K, Bo B, Pei M, Ye J, Thompson GJ, Cang J, Fang F, Feng Y, Duan X, Tong C, Liang Z. Sleep fMRI with simultaneous electrophysiology at 9.4 T in male mice. Nat Commun 2023; 14:1651. [PMID: 36964161 PMCID: PMC10039056 DOI: 10.1038/s41467-023-37352-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 03/14/2023] [Indexed: 03/26/2023] Open
Abstract
Sleep is ubiquitous and essential, but its mechanisms remain unclear. Studies in animals and humans have provided insights of sleep at vastly different spatiotemporal scales. However, challenges remain to integrate local and global information of sleep. Therefore, we developed sleep fMRI based on simultaneous electrophysiology at 9.4 T in male mice. Optimized un-anesthetized mouse fMRI setup allowed manifestation of NREM and REM sleep, and a large sleep fMRI dataset was collected and openly accessible. State dependent global patterns were revealed, and state transitions were found to be global, asymmetrical and sequential, which can be predicted up to 17.8 s using LSTM models. Importantly, sleep fMRI with hippocampal recording revealed potentiated sharp-wave ripple triggered global patterns during NREM than awake state, potentially attributable to co-occurrence of spindle events. To conclude, we established mouse sleep fMRI with simultaneous electrophysiology, and demonstrated its capability by revealing global dynamics of state transitions and neural events.
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Affiliation(s)
- Yalin Yu
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yue Qiu
- Department of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Gen Li
- Department of Biomedical Engineering, College of Future Technology, Academy for Advanced Interdisciplinary Studies, National Biomedical Imaging Centre, Peking University, Beijing, China
| | - Kaiwei Zhang
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Binshi Bo
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Mengchao Pei
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Jingjing Ye
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | | | - Jing Cang
- Department of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Fang Fang
- Department of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China
- The Central Hospital of Xuhui District, Shanghai, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Xiaojie Duan
- Department of Biomedical Engineering, College of Future Technology, Academy for Advanced Interdisciplinary Studies, National Biomedical Imaging Centre, Peking University, Beijing, China.
| | - Chuanjun Tong
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
| | - Zhifeng Liang
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China.
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17
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Benarroch E. What Is the Involvement of the Cerebellum During Sleep? Neurology 2023; 100:572-577. [PMID: 36941065 PMCID: PMC10033165 DOI: 10.1212/wnl.0000000000207161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 01/19/2023] [Indexed: 03/17/2023] Open
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Astrocyte strategies in the energy-efficient brain. Essays Biochem 2023; 67:3-16. [PMID: 36350053 DOI: 10.1042/ebc20220077] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/11/2022] [Accepted: 10/13/2022] [Indexed: 11/10/2022]
Abstract
Astrocytes generate ATP through glycolysis and mitochondrion respiration, using glucose, lactate, fatty acids, amino acids, and ketone bodies as metabolic fuels. Astrocytic mitochondria also participate in neuronal redox homeostasis and neurotransmitter recycling. In this essay, we aim to integrate the multifaceted evidence about astrocyte bioenergetics at the cellular and systems levels, with a focus on mitochondrial oxidation. At the cellular level, the use of fatty acid β-oxidation and the existence of molecular switches for the selection of metabolic mode and fuels are examined. At the systems level, we discuss energy audits of astrocytes and how astrocytic Ca2+ signaling might contribute to the higher performance and lower energy consumption of the brain as compared to engineered circuits. We finish by examining the neural-circuit dysregulation and behavior impairment associated with alterations of astrocytic mitochondria. We conclude that astrocytes may contribute to brain energy efficiency by coupling energy, redox, and computational homeostasis in neural circuits.
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