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Wang J, Lai Q, Han J, Qin P, Wu H. Neuroimaging biomarkers for the diagnosis and prognosis of patients with disorders of consciousness. Brain Res 2024; 1843:149133. [PMID: 39084451 DOI: 10.1016/j.brainres.2024.149133] [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: 10/23/2023] [Revised: 05/29/2024] [Accepted: 07/25/2024] [Indexed: 08/02/2024]
Abstract
The progress in neuroimaging and electrophysiological techniques has shown substantial promise in improving the clinical assessment of disorders of consciousness (DOC). Through the examination of both stimulus-induced and spontaneous brain activity, numerous comprehensive investigations have explored variations in brain activity patterns among patients with DOC, yielding valuable insights for clinical diagnosis and prognostic purposes. Nonetheless, reaching a consensus on precise neuroimaging biomarkers for patients with DOC remains a challenge. Therefore, in this review, we begin by summarizing the empirical evidence related to neuroimaging biomarkers for DOC using various paradigms, including active, passive, and resting-state approaches, by employing task-based fMRI, resting-state fMRI (rs-fMRI), electroencephalography (EEG), and positron emission tomography (PET) techniques. Subsequently, we conducted a review of studies examining the neural correlates of consciousness in patients with DOC, with the findings holding potential value for the clinical application of DOC. Notably, previous research indicates that neuroimaging techniques have the potential to unveil covert awareness that conventional behavioral assessments might overlook. Furthermore, when integrated with various task paradigms or analytical approaches, this combination has the potential to significantly enhance the accuracy of both diagnosis and prognosis in DOC patients. Nonetheless, the stability of these neural biomarkers still needs additional validation, and future directions may entail integrating diagnostic and prognostic methods with big data and deep learning approaches.
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Affiliation(s)
- Jiaying Wang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China
| | - Qiantu Lai
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China
| | - Junrong Han
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Institute for Brain Research and Rehabilitation, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Pengmin Qin
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China; Pazhou Lab, Guangzhou 510330, China.
| | - Hang Wu
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Institute for Brain Research and Rehabilitation, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China.
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2
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Kazazian K, Abdalmalak A, Novi SL, Norton L, Moulavi-Ardakani R, Kolisnyk M, Gofton TE, Mesquita RC, Owen AM, Debicki DB. Functional near-infrared spectroscopy: A novel tool for detecting consciousness after acute severe brain injury. Proc Natl Acad Sci U S A 2024; 121:e2402723121. [PMID: 39186658 PMCID: PMC11388405 DOI: 10.1073/pnas.2402723121] [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: 03/11/2024] [Accepted: 07/05/2024] [Indexed: 08/28/2024] Open
Abstract
Recent advancements in functional neuroimaging have demonstrated that some unresponsive patients in the intensive care unit retain a level of consciousness that is inconsistent with their behavioral diagnosis of awareness. Functional near-infrared spectroscopy (fNIRS) is a portable optical neuroimaging method that can be used to measure neural activity with good temporal and spatial resolution. However, the reliability of fNIRS for detecting the neural correlates of consciousness remains to be established. In a series of studies, we evaluated whether fNIRS can record sensory, perceptual, and command-driven neural processing in healthy participants and in behaviorally nonresponsive patients. At the individual healthy subject level, we demonstrate that fNIRS can detect commonly studied resting state networks, sensorimotor processing, speech-specific auditory processing, and volitional command-driven brain activity to a motor imagery task. We then tested fNIRS with three acutely brain injured patients and found that one could willfully modulate their brain activity when instructed to imagine playing a game of tennis-providing evidence of preserved consciousness despite no observable behavioral signs of awareness. The successful application of fNIRS for detecting preserved awareness among behaviorally nonresponsive patients highlights its potential as a valuable tool for uncovering hidden cognitive states in critical care settings.
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Affiliation(s)
- Karnig Kazazian
- Western Institute of Neuroscience, Western University, London N6A 3K7, Canada
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Western University, London N6A 3K7, Canada
| | - Androu Abdalmalak
- Western Institute of Neuroscience, Western University, London N6A 3K7, Canada
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Western University, London N6A 3K7, Canada
| | - Sergio L Novi
- Western Institute of Neuroscience, Western University, London N6A 3K7, Canada
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Western University, London N6A 3K7, Canada
| | - Loretta Norton
- Western Institute of Neuroscience, Western University, London N6A 3K7, Canada
- Department of Psychology, King's University College at Western University, London N6A 2M3, Canada
| | | | - Matthew Kolisnyk
- Western Institute of Neuroscience, Western University, London N6A 3K7, Canada
| | - Teneille E Gofton
- Western Institute of Neuroscience, Western University, London N6A 3K7, Canada
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London N6A 3K7, Canada
| | - Rickson C Mesquita
- School of Computer Science, University of Birmingham, Birmingham B15 2SQ, United Kingdom
- Gleb Wataghin Institute of Physics, University of Campinas, Campinas 13083-970, Brazil
| | - Adrian M Owen
- Western Institute of Neuroscience, Western University, London N6A 3K7, Canada
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Western University, London N6A 3K7, Canada
- Department of Psychology, Faculty of Social Science, Western University, London N6A 3K7, Canada
| | - Derek B Debicki
- Western Institute of Neuroscience, Western University, London N6A 3K7, Canada
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London N6A 3K7, Canada
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3
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Hoyer RS, Tewarie PKB, Laureys S. Spatiotemporal dynamics of brain activity in cognition and consciousness: Comment on "Beyond task responsePre-stimulus activity modulates contents of consciousness" by Northoff, Zilio, and Zhang. Phys Life Rev 2024; 50:63-65. [PMID: 38964240 DOI: 10.1016/j.plrev.2024.06.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2024] [Accepted: 06/18/2024] [Indexed: 07/06/2024]
Affiliation(s)
- Roxane S Hoyer
- Joint International Research Unit on Consciousness, CERVO Brain Research Centre, Laval University, Canada
| | - Prejaas K B Tewarie
- Joint International Research Unit on Consciousness, CERVO Brain Research Centre, Laval University, Canada; Sir Peter Mansfield Imaging Center, School of Physics, University of Nottingham, United Kingdom; Clinical Neurophysiology Group, University of Twente, Netherlands
| | - Steven Laureys
- Joint International Research Unit on Consciousness, CERVO Brain Research Centre, Laval University, Canada; GIGA Consciousness Research Unit and Coma Science Group, Liège University, Belgium; International Consciousness Science Institute, Hangzhou Normal University, Hangzhou, China
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He Z, Lu R, Ge J, Guan Y, Chen Y, Liu G, Xie H, Bai Y, Wu Y, Wu J, Jia J. Disorder of consciousness related pattern could distinguish minimally conscious state from unresponsive wakefulness syndrome: A F-18-FDG-PET study. Brain Res Bull 2024; 215:111023. [PMID: 38964662 DOI: 10.1016/j.brainresbull.2024.111023] [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: 04/17/2024] [Revised: 06/26/2024] [Accepted: 06/28/2024] [Indexed: 07/06/2024]
Abstract
BACKGROUND Accurate evaluation of level of disorder of consciousness (DOC) is clinically challenging. OBJECTIVE This study aimed to establish a distinctive DOC-related pattern (DOCRP) for assessing disease severity and distinguishing unresponsive wakefulness syndrome (UWS) from minimally conscious state (MCS). METHODS Fifteen patients with DOC and eighteen health subjects with F-18-fluorodeoxyglucose (F-18-FDG) positron emission tomography (PET) were enrolled in this study. All patients were assessed by Coma Recovery Scale-Revised (CRS-R) and all individuals were randomly divided into two cohorts (Cohort A and B). DOCRP was identified in Cohort A and subsequently validated in Cohort B and A+B. We also assessed the discriminatory power of DOCRP between MCS and UWS. RESULTS The DOCRP was characterized bilaterally by relatively decreased metabolism in the medial and lateral frontal lobes, parieto-temporal lobes, cingulate gyrus and caudate, associated with relatively increased metabolism in the cerebellum and brainstem. DOCRP expression exhibited high accuracy in differentiating DOC patients from controls (P<0.0001, AUC=1.000), and furthermore could effectively distinguish MCS from UWS (P=0.037, AUC=0.821, sensitivity: 85.7 %, specificity: 75.0 %). Particularly in the subgroup of DOC patients survived global hypoxic-ischemic brain injury, DOCRP expression exhibited even better discriminatory power between MCS and UWS (P=0.046, AUC=1.000). CONCLUSIONS DOCRP might serve as an objective biomarker in distinguishing between UWS and MCS, especially in patients survived global hypoxic-ischemic brain injury. TRIAL REGISTRATION NUMBER ChiCTR2300073717 (Chinese clinical trial registry site, http://www.chictr.org).
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Affiliation(s)
- Zhijie He
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Rongrong Lu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingjie Ge
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Yihui Guan
- Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Ying Chen
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Gang Liu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Hongyu Xie
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yulong Bai
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yi Wu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Junfa Wu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.
| | - Jie Jia
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; National Center for Neurological Disorders, Shanghai, China.
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5
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Kim YT, Kim H, So M, Kong J, Kim KT, Hong JH, Son Y, Sa JK, Do S, Han JH, Kim JB. Differentiating loss of consciousness causes through artificial intelligence-enabled decoding of functional connectivity. Neuroimage 2024; 297:120749. [PMID: 39033787 DOI: 10.1016/j.neuroimage.2024.120749] [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: 04/08/2024] [Revised: 07/12/2024] [Accepted: 07/18/2024] [Indexed: 07/23/2024] Open
Abstract
Differential diagnosis of acute loss of consciousness (LOC) is crucial due to the need for different therapeutic strategies despite similar clinical presentations among etiologies such as nonconvulsive status epilepticus, metabolic encephalopathy, and benzodiazepine intoxication. While altered functional connectivity (FC) plays a pivotal role in the pathophysiology of LOC, there has been a lack of efforts to develop differential diagnosis artificial intelligence (AI) models that feature the distinctive FC change patterns specific to each LOC cause. Three approaches were applied for extracting features for the AI models: three-dimensional FC adjacency matrices, vectorized FC values, and graph theoretical measurements. Deep learning using convolutional neural networks (CNN) and various machine learning algorithms were implemented to compare classification accuracy using electroencephalography (EEG) data with different epoch sizes. The CNN model using FC adjacency matrices achieved the highest accuracy with an AUC of 0.905, with 20-s epoch data being optimal for classifying the different LOC causes. The high accuracy of the CNN model was maintained in a prospective cohort. Key distinguishing features among the LOC causes were found in the delta and theta brain wave bands. This research advances the understanding of LOC's underlying mechanisms and shows promise for enhancing diagnosis and treatment selection. Moreover, the AI models can provide accurate LOC differentiation with a relatively small amount of EEG data in 20-s epochs, which may be clinically useful.
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Affiliation(s)
- Young-Tak Kim
- Department of Biomedical Sciences, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Hayom Kim
- Department of Neurology, Korea University Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Mingyeong So
- Department of Neurology, Korea University Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Jooheon Kong
- Department of Neurology, Korea University Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Keun-Tae Kim
- Department of Neurology, Korea University Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Je Hyeong Hong
- Department of Electronic Engineering, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea
| | - Yunsik Son
- Department of Computer Science and Engineering, Dongguk University, 30, Pildong-ro 1-gil, Jung-gu, Seoul, 04620, Republic of Korea
| | - Jason K Sa
- Department of Biomedical Sciences, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea; Department of Biomedical Informatics, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Synho Do
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 125 Nashua Street, Suite 2210, Boston, MA, 02114, United States; KU-KIST Graduate School of Converging Science and Technology, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea; Kempner Institute, Harvard University, 150 Western Avenue, Boston, MA, 02134, United States
| | - Jae-Ho Han
- Department of Brain and Cognitive Engineering, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Jung Bin Kim
- Department of Neurology, Korea University Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea.
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6
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Mograbi DC, Rodrigues R, Bienemann B, Huntley J. Brain Networks, Neurotransmitters and Psychedelics: Towards a Neurochemistry of Self-Awareness. Curr Neurol Neurosci Rep 2024; 24:323-340. [PMID: 38980658 PMCID: PMC11258181 DOI: 10.1007/s11910-024-01353-y] [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] [Accepted: 06/17/2024] [Indexed: 07/10/2024]
Abstract
PURPOSE OF REVIEW Self-awareness can be defined as the capacity of becoming the object of one's own awareness and, increasingly, it has been the target of scientific inquiry. Self-awareness has important clinical implications, and a better understanding of the neurochemical basis of self-awareness may help clarifying causes and developing interventions for different psychopathological conditions. The current article explores the relationship between neurochemistry and self-awareness, with special attention to the effects of psychedelics. RECENT FINDINGS The functioning of self-related networks, such as the default-mode network and the salience network, and how these are influenced by different neurotransmitters is discussed. The impact of psychedelics on self-awareness is reviewed in relation to specific processes, such as interoception, body ownership, agency, metacognition, emotional regulation and autobiographical memory, within a framework based on predictive coding. Improved outcomes in emotional regulation and autobiographical memory have been observed in association with the use of psychedelics, suggesting higher-order self-awareness changes, which can be modulated by relaxation of priors and improved coping mechanisms linked to cognitive flexibility. Alterations in bodily self-awareness are less consistent, being potentially impacted by doses employed, differences in acute/long-term effects and the presence of clinical conditions. Future studies investigating the effects of different molecules in rebalancing connectivity between resting-state networks may lead to novel therapeutic approaches and the refinement of existing treatments.
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Affiliation(s)
- Daniel C Mograbi
- Department of Psychology, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil.
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
| | - Rafael Rodrigues
- Department of Psychology, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Bheatrix Bienemann
- Department of Psychology, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Jonathan Huntley
- Division of Psychiatry, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
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7
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Vaz A, Wathen C, Miranda S, Thomas R, Darlington T, Jabarkheel R, Tomlinson S, Arena J, Bond K, Salwi S, Ajmera S, Bachschmid-Romano L, Gugger J, Sandsmark D, Diaz-Arrastia R, Schuster J, Ramayya AG, Cajigas I, Pesaran B, Chen HI, Petrov D. Return of intracranial beta oscillations and traveling waves with recovery from traumatic brain injury. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.19.604293. [PMID: 39091808 PMCID: PMC11291083 DOI: 10.1101/2024.07.19.604293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Traumatic brain injury (TBI) remains a pervasive clinical problem associated with significant morbidity and mortality. However, TBI remains clinically and biophysically ill-defined, and prognosis remains difficult even with the standardization of clinical guidelines and advent of multimodality monitoring. Here we leverage a unique data set from TBI patients implanted with either intracranial strip electrodes during craniotomy or quad-lumen intracranial bolts with depth electrodes as part of routine clinical practice. By extracting spectral profiles of this data, we found that the presence of narrow-band oscillatory activity in the beta band (12-30 Hz) closely corresponds with the neurological exam as quantified with the standard Glasgow Coma Scale (GCS). Further, beta oscillations were distributed over the cortical surface as traveling waves, and the evolution of these waves corresponded to recovery from coma, consistent with the putative role of waves in perception and cognitive activity. We consequently propose that beta oscillations and traveling waves are potential biomarkers of recovery from TBI. In a broader sense, our findings suggest that emergence from coma results from recovery of thalamo-cortical interactions that coordinate cortical beta rhythms.
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Affiliation(s)
- Alex Vaz
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Connor Wathen
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Stephen Miranda
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Rachel Thomas
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Timothy Darlington
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Rashad Jabarkheel
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Samuel Tomlinson
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - John Arena
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Kamila Bond
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sanjana Salwi
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sonia Ajmera
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | | | - James Gugger
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Danielle Sandsmark
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ramon Diaz-Arrastia
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - James Schuster
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ashwin G Ramayya
- Department of Neurosurgery, Stanford University, Palo Alto, CA, 94305, USA
| | - Iahn Cajigas
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Bijan Pesaran
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - H Isaac Chen
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104, USA
| | - Dmitriy Petrov
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
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Luppi AI, Mediano PAM, Rosas FE, Allanson J, Pickard J, Carhart-Harris RL, Williams GB, Craig MM, Finoia P, Owen AM, Naci L, Menon DK, Bor D, Stamatakis EA. A synergistic workspace for human consciousness revealed by Integrated Information Decomposition. eLife 2024; 12:RP88173. [PMID: 39022924 PMCID: PMC11257694 DOI: 10.7554/elife.88173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024] Open
Abstract
How is the information-processing architecture of the human brain organised, and how does its organisation support consciousness? Here, we combine network science and a rigorous information-theoretic notion of synergy to delineate a 'synergistic global workspace', comprising gateway regions that gather synergistic information from specialised modules across the human brain. This information is then integrated within the workspace and widely distributed via broadcaster regions. Through functional MRI analysis, we show that gateway regions of the synergistic workspace correspond to the human brain's default mode network, whereas broadcasters coincide with the executive control network. We find that loss of consciousness due to general anaesthesia or disorders of consciousness corresponds to diminished ability of the synergistic workspace to integrate information, which is restored upon recovery. Thus, loss of consciousness coincides with a breakdown of information integration within the synergistic workspace of the human brain. This work contributes to conceptual and empirical reconciliation between two prominent scientific theories of consciousness, the Global Neuronal Workspace and Integrated Information Theory, while also advancing our understanding of how the human brain supports consciousness through the synergistic integration of information.
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Affiliation(s)
- Andrea I Luppi
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
- University Division of Anaesthesia, School of Clinical Medicine, University of CambridgeCambridgeUnited Kingdom
| | - Pedro AM Mediano
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Fernando E Rosas
- Center for Psychedelic Research, Department of Brain Science, Imperial College LondonLondonUnited Kingdom
- Center for Complexity Science, Imperial College LondonLondonUnited Kingdom
- Data Science Institute, Imperial College LondonLondonUnited Kingdom
| | - Judith Allanson
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
- Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's HospitalCambridgeUnited Kingdom
| | - John Pickard
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
- Wolfson Brain Imaging Centre, University of CambridgeCambridgeUnited Kingdom
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's HospitalCambridgeUnited Kingdom
| | - Robin L Carhart-Harris
- Center for Psychedelic Research, Department of Brain Science, Imperial College LondonLondonUnited Kingdom
- Psychedelics Division - Neuroscape, Department of Neurology, University of CaliforniaSan FranciscoUnited States
| | - Guy B Williams
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
- Wolfson Brain Imaging Centre, University of CambridgeCambridgeUnited Kingdom
| | - Michael M Craig
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
- University Division of Anaesthesia, School of Clinical Medicine, University of CambridgeCambridgeUnited Kingdom
| | - Paola Finoia
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
| | - Adrian M Owen
- Department of Psychology and Department of Physiology and Pharmacology, The Brain and Mind Institute, University of Western OntarioLondonCanada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Lloyd Building, Trinity CollegeDublinIreland
| | - David K Menon
- University Division of Anaesthesia, School of Clinical Medicine, University of CambridgeCambridgeUnited Kingdom
- Wolfson Brain Imaging Centre, University of CambridgeCambridgeUnited Kingdom
| | - Daniel Bor
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Emmanuel A Stamatakis
- University Division of Anaesthesia, School of Clinical Medicine, University of CambridgeCambridgeUnited Kingdom
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9
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Barra ME, Solt K, Yu X, Edlow BL. Restoring consciousness with pharmacologic therapy: Mechanisms, targets, and future directions. Neurotherapeutics 2024:e00374. [PMID: 39019729 DOI: 10.1016/j.neurot.2024.e00374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 04/16/2024] [Accepted: 05/03/2024] [Indexed: 07/19/2024] Open
Abstract
Severe brain injury impairs consciousness by disrupting a broad spectrum of neurotransmitter systems. Emerging evidence suggests that pharmacologic modulation of specific neurotransmitter systems, such as dopamine, promotes recovery of consciousness. Clinical guidelines now endorse the use of amantadine in individuals with traumatic disorders of consciousness (DoC) based on level 1 evidence, and multiple neurostimulants are used off-label in clinical practice, including methylphenidate, modafinil, bromocriptine, levodopa, and zolpidem. However, the relative contributions of monoaminergic, glutamatergic, cholinergic, GABAergic, and orexinergic neurotransmitter systems to recovery of consciousness after severe brain injury are unknown, and personalized approaches to targeted therapy have yet to be developed. This review summarizes the state-of-the-science in the neurochemistry and neurobiology of neurotransmitter systems involved in conscious behaviors, followed by a discussion of how pharmacologic therapies may be used to modulate these neurotransmitter systems and promote recovery of consciousness. We consider pharmacologic modulation of consciousness at the synapse, circuit, and network levels, with a focus on the mesocircuit model that has been proposed to explain the consciousness-promoting effects of various monoaminergic, glutamatergic, and paradoxically, GABAergic therapies. Though fundamental questions remain about neurotransmitter mechanisms, target engagement and optimal therapy selection for individual patients, we propose that pharmacologic therapies hold great promise to promote recovery and improve quality of life for patients with severe brain injuries.
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Affiliation(s)
- Megan E Barra
- Department of Pharmacy, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
| | - Ken Solt
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Xin Yu
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
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10
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De Koninck BP, Brazeau D, Deshaies AA, Briand MM, Maschke C, Williams V, Arbour C, Williamson D, Duclos C, Bernard F, Blain-Moraes S, De Beaumont L. Modulation of brain activity in brain-injured patients with a disorder of consciousness in intensive care with repeated 10-Hz transcranial alternating current stimulation (tACS): a randomised controlled trial protocol. BMJ Open 2024; 14:e078281. [PMID: 38991682 PMCID: PMC11243138 DOI: 10.1136/bmjopen-2023-078281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/13/2024] Open
Abstract
INTRODUCTION Therapeutic interventions for disorders of consciousness lack consistency; evidence supports non-invasive brain stimulation, but few studies assess neuromodulation in acute-to-subacute brain-injured patients. This study aims to validate the feasibility and assess the effect of a multi-session transcranial alternating current stimulation (tACS) intervention in subacute brain-injured patients on recovery of consciousness, related brain oscillations and brain network dynamics. METHODS AND ANALYSES The study is comprised of two phases: a validation phase (n=12) and a randomised controlled trial (n=138). Both phases will be conducted in medically stable brain-injured adult patients (traumatic brain injury and hypoxic-ischaemic encephalopathy), with a Glasgow Coma Scale score ≤12 after continuous sedation withdrawal. Recruitment will occur at the intensive care unit of a Level 1 Trauma Centre in Montreal, Quebec, Canada. The intervention includes a 20 min 10 Hz tACS at 1 mA intensity or a sham session over parieto-occipital cortical sites, repeated over five consecutive days. The current's frequency targets alpha brain oscillations (8-13 Hz), known to be associated with consciousness. Resting-state electroencephalogram (EEG) will be recorded four times daily for five consecutive days: pre and post-intervention, at 60 and 120 min post-tACS. Two additional recordings will be included: 24 hours and 1-week post-protocol. Multimodal measures (blood samples, pupillometry, behavioural consciousness assessments (Coma Recovery Scale-revised), actigraphy measures) will be acquired from baseline up to 1 week after the stimulation. EEG signal analysis will focus on the alpha bandwidth (8-13 Hz) using spectral and functional network analyses. Phone assessments at 3, 6 and 12 months post-tACS, will measure long-term functional recovery, quality of life and caregivers' burden. ETHICS AND DISSEMINATION Ethical approval for this study has been granted by the Research Ethics Board of the CIUSSS du Nord-de-l'Île-de-Montréal (Project ID 2021-2279). The findings of this two-phase study will be submitted for publication in a peer-reviewed academic journal and submitted for presentation at conferences. The trial's results will be published on a public trial registry database (ClinicalTrials.gov). TRIAL REGISTRATION NUMBER NCT05833568.
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Affiliation(s)
- Béatrice P De Koninck
- Psychology, University of Montreal, Montreal, Quebec, Canada
- Research Center, Hopital du Sacre-Coeur de Montreal, Montreal, Quebec, Canada
| | - Daphnee Brazeau
- Psychology, University of Montreal, Montreal, Quebec, Canada
- Research Center, Hopital du Sacre-Coeur de Montreal, Montreal, Quebec, Canada
| | | | - Marie-Michele Briand
- CIUSSS du Nord-de-l'Ile-de-Montreal, Montreal, Quebec, Canada
- IRDPQ, Montreal, Quebec, Canada
| | - Charlotte Maschke
- McGill University, Montreal, Quebec, Canada
- Montreal General Hospital, Montreal, Quebec, Canada
| | - Virginie Williams
- Research Center, Hopital du Sacre-Coeur de Montreal, Montreal, Quebec, Canada
| | - Caroline Arbour
- Research Center, Hopital du Sacre-Coeur de Montreal, Montreal, Quebec, Canada
- University of Montreal, Montreal, Quebec, Canada
| | | | - Catherine Duclos
- Research Center, Hopital du Sacre-Coeur de Montreal, Montreal, Quebec, Canada
- Anesthesiology and Pain Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Francis Bernard
- Research Center, Hopital du Sacre-Coeur de Montreal, Montreal, Quebec, Canada
- Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, Montreal, Quebec, Canada
- Physical and Occupational Therapy, McGill University, Montreal, Quebec, Canada
| | - Louis De Beaumont
- Research Center, Hopital du Sacre-Coeur de Montreal, Montreal, Quebec, Canada
- Surgery, University of Montreal, Montreal, Quebec, Canada
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11
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Ihalainen R, Annen J, Gosseries O, Cardone P, Panda R, Martial C, Thibaut A, Laureys S, Chennu S. Lateral frontoparietal effective connectivity differentiates and predicts state of consciousness in a cohort of patients with traumatic disorders of consciousness. PLoS One 2024; 19:e0298110. [PMID: 38968195 PMCID: PMC11226086 DOI: 10.1371/journal.pone.0298110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 01/13/2024] [Indexed: 07/07/2024] Open
Abstract
Neuroimaging studies have suggested an important role for the default mode network (DMN) in disorders of consciousness (DoC). However, the extent to which DMN connectivity can discriminate DoC states-unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS)-is less evident. Particularly, it is unclear whether effective DMN connectivity, as measured indirectly with dynamic causal modelling (DCM) of resting EEG can disentangle UWS from healthy controls and from patients considered conscious (MCS+). Crucially, this extends to UWS patients with potentially "covert" awareness (minimally conscious star, MCS*) indexed by voluntary brain activity in conjunction with partially preserved frontoparietal metabolism as measured with positron emission tomography (PET+ diagnosis; in contrast to PET- diagnosis with complete frontoparietal hypometabolism). Here, we address this gap by using DCM of EEG data acquired from patients with traumatic brain injury in 11 UWS (6 PET- and 5 PET+) and in 12 MCS+ (11 PET+ and 1 PET-), alongside with 11 healthy controls. We provide evidence for a key difference in left frontoparietal connectivity when contrasting UWS PET- with MCS+ patients and healthy controls. Next, in a leave-one-subject-out cross-validation, we tested the classification performance of the DCM models demonstrating that connectivity between medial prefrontal and left parietal sources reliably discriminates UWS PET- from MCS+ patients and controls. Finally, we illustrate that these models generalize to an unseen dataset: models trained to discriminate UWS PET- from MCS+ and controls, classify MCS* patients as conscious subjects with high posterior probability (pp > .92). These results identify specific alterations in the DMN after severe brain injury and highlight the clinical utility of EEG-based effective connectivity for identifying patients with potential covert awareness.
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Affiliation(s)
- Riku Ihalainen
- Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States of America
- School of Computing, University of Kent, Canterbury, United Kingdom
| | - Jitka Annen
- Coma Science Group, GIGA Consciousness Research Unit, University and University Hospital of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
- Department of Data Analysis, University of Ghent, Ghent, Belgium
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness Research Unit, University and University Hospital of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Paolo Cardone
- Coma Science Group, GIGA Consciousness Research Unit, University and University Hospital of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Rajanikant Panda
- Coma Science Group, GIGA Consciousness Research Unit, University and University Hospital of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Charlotte Martial
- Coma Science Group, GIGA Consciousness Research Unit, University and University Hospital of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Aurore Thibaut
- Coma Science Group, GIGA Consciousness Research Unit, University and University Hospital of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness Research Unit, University and University Hospital of Liège, Liège, Belgium
- CERVO Brain Research Centre, de la Canardière, Québec, Canada
- Consciousness Science Institute, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Srivas Chennu
- School of Computing, University of Kent, Canterbury, United Kingdom
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12
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Secci S, Liuzzi P, Hakiki B, Burali R, Draghi F, Romoli AM, di Palma A, Scarpino M, Grippo A, Cecchi F, Frosini A, Mannini A. Low-density EEG-based Functional Connectivity Discriminates Minimally Conscious State plus from minus. Clin Neurophysiol 2024; 163:197-208. [PMID: 38761713 DOI: 10.1016/j.clinph.2024.04.021] [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: 05/04/2023] [Revised: 04/03/2024] [Accepted: 04/18/2024] [Indexed: 05/20/2024]
Abstract
OBJECTIVE Within the continuum of consciousness, patients in a Minimally Conscious State (MCS) may exhibit high-level behavioral responses (MCS+) or may not (MCS-). The evaluation of residual consciousness and related classification is crucial to propose tailored rehabilitation and pharmacological treatments, considering the inherent differences among groups in diagnosis and prognosis. Currently, differential diagnosis relies on behavioral assessments posing a relevant risk of misdiagnosis. In this context, EEG offers a non-invasive approach to model the brain as a complex network. The search for discriminating features could reveal whether behavioral responses in post-comatose patients have a defined physiological background. Additionally, it is essential to determine whether the standard behavioral assessment for quantifying responsiveness holds physiological significance. METHODS In this prospective observational study, we investigated whether low-density EEG-based graph metrics could discriminate MCS+/- patients by enrolling 57 MCS patients (MCS-: 30; males: 28). At admission to intensive rehabilitation, 30 min resting-state closed-eyes EEG recordings were performed together with consciousness diagnosis following international guidelines. After EEG preprocessing, graphs' metrics were estimated using different connectivity measures, at multiple connection densities and frequency bands (α,θ,δ). Metrics were also provided to cross-validated Machine Learning (ML) models with outcome MCS+/-. RESULTS A lower level of brain activity integration was found in the MCS- group in the α band. Instead, in the δ band MCS- group presented an higher level of clustering (weighted clustering coefficient) respect to MCS+. The best-performing solution in discriminating MCS+/- through the use of ML was an Elastic-Net regularized logistic regression with a cross-validation accuracy of 79% (sensitivity and specificity of 74% and 85% respectively). CONCLUSION Despite tackling the MCS+/- differential diagnosis is highly challenging, a daily-routine low-density EEG might allow to differentiate across these differently responsive brain networks. SIGNIFICANCE Graph-theoretical features are shown to discriminate between these two neurophysiologically similar conditions, and may thus support the clinical diagnosis.
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Affiliation(s)
- Sara Secci
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci 269, Firenze, FI, Italy
| | - Piergiuseppe Liuzzi
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci 269, Firenze, FI, Italy; Scuola Superiore Sant'Anna, BioRobotics Institute, Viale Rinaldo Piaggio 34, Pontedera, PI, Italy
| | - Bahia Hakiki
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci 269, Firenze, FI, Italy; Dipartimento di Medicina Sperimentale e Clinica, Largo Brambilla 3, FI, Italy.
| | - Rachele Burali
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci 269, Firenze, FI, Italy
| | - Francesca Draghi
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci 269, Firenze, FI, Italy
| | - Anna Maria Romoli
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci 269, Firenze, FI, Italy
| | - Azzurra di Palma
- Dipartimento di Matematica e Informatica, Università di Firenze, Viale Morgagni 65, FI, Italy
| | - Maenia Scarpino
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci 269, Firenze, FI, Italy
| | - Antonello Grippo
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci 269, Firenze, FI, Italy
| | - Francesca Cecchi
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci 269, Firenze, FI, Italy; Dipartimento di Medicina Sperimentale e Clinica, Largo Brambilla 3, FI, Italy
| | - Andrea Frosini
- Dipartimento di Matematica e Informatica, Università di Firenze, Viale Morgagni 65, FI, Italy
| | - Andrea Mannini
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci 269, Firenze, FI, Italy
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13
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Haipt A, Rosenbaum D, Fuhr K, Batra A, Ehlis AC. Differential effects of hypnotherapy and cognitive behavioral therapy on the default mode network of depressed patients. Front Psychol 2024; 15:1401946. [PMID: 38993341 PMCID: PMC11238146 DOI: 10.3389/fpsyg.2024.1401946] [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: 03/16/2024] [Accepted: 06/13/2024] [Indexed: 07/13/2024] Open
Abstract
Hypnosis has been applied in healing procedures since the earliest of recorded history and today it is implemented in a wholesome concept Hypnotherapy (HT1). On a neurophysiological level, hypnosis has been associated with parts of the Default Mode Network (DMN2), but its effects on this network when induced in a treatment setting of a widespread disorder, namely depression, have never been investigated. Depression is associated with abnormal functional connectivity (FC3) of the DMN. Cognitive Behavioral Therapy (CBT4) has proven itself to be an effective treatment for depression; effects of CBT on DMN-related regions are heterogeneous. In the past years, HT was found to be a promising alternative or helpful adjunction. Yet, its underlying mechanisms remain to be unclear. In this original study 75 depressed patients receiving either CBT or HT were included and measured during resting-state before and after therapy with functional near-infrared-spectroscopy (fNIRS5). On symptom level, results show a significant reduction in both groups. On a neurophysiological level, first exploratory analyses hint toward treatment effects in two components of the DMN. However, these effects do not withstand correction for multiple testing. Still, our study is a first stepstone in the investigation of neural mechanisms of HT and offers first ideas about possible implications.
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Affiliation(s)
- Alina Haipt
- Department of Psychophysiology and Optical Imaging, University Hospital of Tuebingen, Tuebingen, Germany
| | - David Rosenbaum
- Department of Psychophysiology and Optical Imaging, University Hospital of Tuebingen, Tuebingen, Germany
| | - Kristina Fuhr
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Tuebingen, Germany
| | - Anil Batra
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Tuebingen, Germany
| | - Ann-Christine Ehlis
- Department of Psychophysiology and Optical Imaging, University Hospital of Tuebingen, Tuebingen, Germany
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14
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Toplutaş E, Aydın F, Hanoğlu L. EEG Microstate Analysis in Patients with Disorders of Consciousness and Its Clinical Significance. Brain Topogr 2024; 37:377-387. [PMID: 36735192 DOI: 10.1007/s10548-023-00939-y] [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: 09/30/2022] [Accepted: 01/19/2023] [Indexed: 02/04/2023]
Abstract
Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness.
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Affiliation(s)
- Eren Toplutaş
- Department of Neurology, Istanbul Eyupsultan Public Hospital, Istanbul, Turkey.
- Program of Neuroscience Ph.D., Graduate School of Health Sciences,, Istanbul Medipol University, Istanbul, Turkey.
| | - Fatma Aydın
- Program of Neuroscience Ph.D., Graduate School of Health Sciences,, Istanbul Medipol University, Istanbul, Turkey
| | - Lütfü Hanoğlu
- Department of Neurology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
- Neuroimaging and Neuromodulation Lab, Clinical Electrophysiology, REMER, Istanbul Medipol University, Istanbul, Turkey
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15
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Wu M, Concolato M, Sorger B, Yu Y, Li X, Luo B, Riecke L. Acoustic-electric trigeminal-nerve stimulation enhances functional connectivity in patients with disorders of consciousness. CNS Neurosci Ther 2024; 30:e14385. [PMID: 37525451 PMCID: PMC10928333 DOI: 10.1111/cns.14385] [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: 12/19/2022] [Revised: 06/29/2023] [Accepted: 07/16/2023] [Indexed: 08/02/2023] Open
Abstract
AIM Disruption of functional brain connectivity is thought to underlie disorders of consciousness (DOC) and recovery of impaired connectivity is suggested as an indicator of consciousness restoration. We recently found that rhythmic acoustic-electric trigeminal-nerve stimulation (i.e., musical stimulation synchronized to electrical stimulation of the trigeminal nerve) in the gamma band can improve consciousness in patients with DOC. Here, we investigated whether these beneficial stimulation effects are mediated by alterations in functional connectivity. METHODS Sixty-three patients with DOC underwent 5 days of gamma, beta, or sham acoustic-electric trigeminal-nerve stimulation. Resting-state electroencephalography was measured before and after the stimulation and functional connectivity was assessed using phase-lag index (PLI). RESULTS We found that gamma stimulation induces an increase in gamma-band PLI. Further characterization revealed that the enhancing effect is (i) specific to the gamma band (as we observed no comparable change in beta-band PLI and no effect of beta-band acoustic-electric stimulation or sham stimulation), (ii) widely spread across the cortex, and (iii) accompanied by improvements in patients' auditory abilities. CONCLUSION These findings show that gamma acoustic-electric trigeminal-nerve stimulation can improve resting-state functional connectivity in the gamma band, which in turn may be linked to auditory abilities and/or consciousness restoration in DOC patients.
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Affiliation(s)
- Min Wu
- Department of Cognitive Neuroscience, Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Marta Concolato
- Department of Cognitive Neuroscience, Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
- Department of Developmental Psychology and SocializationUniversity of PadovaPadovaItaly
| | - Bettina Sorger
- Department of Cognitive Neuroscience, Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Yamei Yu
- Department of Neurology and Brain Medical Centre, First Affiliated Hospital, School of MedicineZhejiang UniversityHangzhouChina
| | - Xiaoxia Li
- Department of Neurology and Brain Medical Centre, First Affiliated Hospital, School of MedicineZhejiang UniversityHangzhouChina
| | - Benyan Luo
- Department of Neurology and Brain Medical Centre, First Affiliated Hospital, School of MedicineZhejiang UniversityHangzhouChina
| | - Lars Riecke
- Department of Cognitive Neuroscience, Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
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16
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Farg H, Elnakib A, Gebreil A, Alksas A, van Bogaert E, Mahmoud A, Khalil A, Ghazal M, Abou El-Ghar M, El-Baz A, Contractor S. Diagnostic value of PET imaging in clinically unresponsive patients. Br J Radiol 2024; 97:283-291. [PMID: 38308033 DOI: 10.1093/bjr/tqad040] [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: 01/18/2023] [Revised: 07/27/2023] [Accepted: 11/21/2023] [Indexed: 02/04/2024] Open
Abstract
Rapid advancements in the critical care management of acute brain injuries have facilitated the survival of numerous patients who may have otherwise succumbed to their injuries. The probability of conscious recovery hinges on the extent of structural brain damage and the level of metabolic and functional cerebral impairment, which remain challenging to assess via laboratory, clinical, or functional tests. Current research settings and guidelines highlight the potential value of fluorodeoxyglucose-PET (FDG-PET) for diagnostic and prognostic purposes, emphasizing its capacity to consistently illustrate a metabolic reduction in cerebral glucose uptake across various disorders of consciousness. Crucially, FDG-PET might be a pivotal tool for differentiating between patients in the minimally conscious state and those in the unresponsive wakefulness syndrome, a persistent clinical challenge. In patients with disorders of consciousness, PET offers utility in evaluating the degree and spread of functional disruption, as well as identifying irreversible neural damage. Further, studies that capture responses to external stimuli can shed light on residual or revived brain functioning. Nevertheless, the validity of these findings in predicting clinical outcomes calls for additional long-term studies with larger patient cohorts suffering from consciousness impairment. Misdiagnosis of conscious illnesses during bedside clinical assessments remains a significant concern. Based on the clinical research settings, current clinical guidelines recommend PET for diagnostic and/or prognostic purposes. This review article discusses the clinical categories of conscious disorders and the diagnostic and prognostic value of PET imaging in clinically unresponsive patients, considering the known limitations of PET imaging in such contexts.
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Affiliation(s)
- Hashim Farg
- Radiology Department, Urology and Nephrology Center, Mansoura University, 35516 Mansoura, Egypt
| | - Ahmed Elnakib
- BioImaging Lab, Bioengineering Department, University of Louisville, Louisville, KY 40292, United States
| | - Ahmad Gebreil
- BioImaging Lab, Bioengineering Department, University of Louisville, Louisville, KY 40292, United States
| | - Ahmed Alksas
- BioImaging Lab, Bioengineering Department, University of Louisville, Louisville, KY 40292, United States
| | - Eric van Bogaert
- Department of Radiology, University of Louisville, Louisville, KY 40202, United States
| | - Ali Mahmoud
- BioImaging Lab, Bioengineering Department, University of Louisville, Louisville, KY 40292, United States
| | - Ashraf Khalil
- College of Technological Innovation, Zayed University, Abu Dhabi 4783, United Arab Emirates
| | - Mohammed Ghazal
- Electrical, Computer, and Biomedical Engineering Department, Abu Dhabi University, Abu Dhabi 59911, United Arab Emirates
| | - Mohamed Abou El-Ghar
- Radiology Department, Urology and Nephrology Center, Mansoura University, 35516 Mansoura, Egypt
| | - Ayman El-Baz
- BioImaging Lab, Bioengineering Department, University of Louisville, Louisville, KY 40292, United States
| | - Sohail Contractor
- Department of Radiology, University of Louisville, Louisville, KY 40202, United States
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17
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Claassen J, Kondziella D, Alkhachroum A, Diringer M, Edlow BL, Fins JJ, Gosseries O, Hannawi Y, Rohaut B, Schnakers C, Stevens RD, Thibaut A, Monti M. Cognitive Motor Dissociation: Gap Analysis and Future Directions. Neurocrit Care 2024; 40:81-98. [PMID: 37349602 DOI: 10.1007/s12028-023-01769-3] [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: 05/10/2023] [Accepted: 05/26/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND Patients with disorders of consciousness who are behaviorally unresponsive may demonstrate volitional brain responses to motor imagery or motor commands detectable on functional magnetic resonance imaging or electroencephalography. This state of cognitive motor dissociation (CMD) may have prognostic significance. METHODS The Neurocritical Care Society's Curing Coma Campaign identified an international group of experts who convened in a series of monthly online meetings between September 2021 and April 2023 to examine the science of CMD and identify key knowledge gaps and unmet needs. RESULTS The group identified major knowledge gaps in CMD research: (1) lack of information about patient experiences and caregiver accounts of CMD, (2) limited epidemiological data on CMD, (3) uncertainty about underlying mechanisms of CMD, (4) methodological variability that limits testing of CMD as a biomarker for prognostication and treatment trials, (5) educational gaps for health care personnel about the incidence and potential prognostic relevance of CMD, and (6) challenges related to identification of patients with CMD who may be able to communicate using brain-computer interfaces. CONCLUSIONS To improve the management of patients with disorders of consciousness, research efforts should address these mechanistic, epidemiological, bioengineering, and educational gaps to enable large-scale implementation of CMD assessment in clinical practice.
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Affiliation(s)
- Jan Claassen
- Department of Neurology, Neurological Institute, Columbia University Irving Medical Center, NewYork Presbyterian Hospital, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA.
| | - Daniel Kondziella
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | | | - Michael Diringer
- Department of Neurology, Washington University, St. Louis, MO, USA
| | - Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Joseph J Fins
- Division of Medical Ethics, Department of Medicine, Weill Cornell Medical College, NewYork Presbyterian Hospital, New York, NY, 10032, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liege, Liege, Belgium
- Centre du Cerveau, University Hospital of Liege, Liege, Belgium
| | - Yousef Hannawi
- Division of Cerebrovascular Diseases and Neurocritical Care, Department of Neurology, The Ohio State University, Columbus, OH, USA
| | - Benjamin Rohaut
- Sorbonne Université, Assistance Publique-Hôpitaux de Paris (AP-HP) - Pitié Salpêtrière, Paris, France
| | | | - Robert D Stevens
- Department of Anesthesiology and Critical Care Medicine, Neurology, and Radiology, School of Medicine, Secondary Appointment in Biomedical Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Aurore Thibaut
- Coma Science Group, GIGA Consciousness, University of Liege, Liege, Belgium
- Centre du Cerveau, University Hospital of Liege, Liege, Belgium
| | - Martin Monti
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
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18
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Xu LB, Hampton S, Fischer D. Neuroimaging in Disorders of Consciousness and Recovery. Phys Med Rehabil Clin N Am 2024; 35:51-64. [PMID: 37993193 DOI: 10.1016/j.pmr.2023.06.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
There is a clinical need for more accurate diagnosis and prognostication in patients with disorders of consciousness (DoC). There are several neuroimaging modalities that enable detailed, quantitative assessment of structural and functional brain injury, with demonstrated diagnostic and prognostic value. Additionally, longitudinal neuroimaging studies have hinted at quantifiable structural and functional neuroimaging biomarkers of recovery, with potential implications for the management of DoC.
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Affiliation(s)
- Linda B Xu
- Department of Neurology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA.
| | - Stephen Hampton
- Department of Physical Medicine and Rehabilitation, University of Pennsylvania, 1800 Lombard Street, Philadelphia, PA 19146, USA
| | - David Fischer
- Department of Neurology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA.
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19
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Li Y, Gao J, Yang Y, Zhuang Y, Kang Q, Li X, Tian M, Lv H, He J. Temporal and spatial variability of dynamic microstate brain network in disorders of consciousness. CNS Neurosci Ther 2024; 30:e14641. [PMID: 38385681 PMCID: PMC10883110 DOI: 10.1111/cns.14641] [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: 10/10/2023] [Revised: 01/17/2024] [Accepted: 02/01/2024] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Accurately diagnosing patients with the vegetative state (VS) and the minimally conscious state (MCS) reached a misdiagnosis of approximately 40%. METHODS A method combined microstate and dynamic functional connectivity (dFC) to study the spatiotemporal variability of the brain in disorders of consciousness (DOC) patients was proposed. Resting-state EEG data were obtained from 16 patients with MCS and 16 patients with VS. Mutual information (MI) was used to assess the EEG connectivity in each microstate. MI-based features with statistical differences were selected as the total feature subset (TFS), then the TFS was utilized to feature selection and fed into the classifier, obtaining the optimal feature subsets (OFS) in each microstate. Subsequently, an OFS-based MI functional connectivity network (MIFCN) was constructed in the cortex. RESULTS The group-average MI connectivity matrix focused on all channels revealed that all five microstates exhibited stronger information interaction in the MCS when comparing with the VS. While OFS-based MIFCN, which only focused on a few channels, revealed greater MI flow in VS patients than in MCS patients under microstates A, B, C, and E, except for microstate D. Additionally, the average classification accuracy of OFS in the five microstates was 96.2%. CONCLUSION Constructing features based on microstates to distinguish between two categories of DOC patients had effectiveness.
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Affiliation(s)
- Yaqian Li
- Key Laboratory of Cognitive Science of State Ethnic Affairs Commission, College of Biomedical EngineeringSouth‐Central Minzu UniversityWuhanChina
| | - Junfeng Gao
- Key Laboratory of Cognitive Science of State Ethnic Affairs Commission, College of Biomedical EngineeringSouth‐Central Minzu UniversityWuhanChina
| | - Ying Yang
- College of Foreign LanguagesWuhan University of TechnologyWuhanChina
| | - Yvtong Zhuang
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Qianruo Kang
- Key Laboratory of Cognitive Science of State Ethnic Affairs Commission, College of Biomedical EngineeringSouth‐Central Minzu UniversityWuhanChina
| | - Xiang Li
- Key Laboratory of Cognitive Science of State Ethnic Affairs Commission, College of Biomedical EngineeringSouth‐Central Minzu UniversityWuhanChina
| | - Min Tian
- Key Laboratory of Cognitive Science of State Ethnic Affairs Commission, College of Biomedical EngineeringSouth‐Central Minzu UniversityWuhanChina
| | - Haoan Lv
- Key Laboratory of Cognitive Science of State Ethnic Affairs Commission, College of Biomedical EngineeringSouth‐Central Minzu UniversityWuhanChina
| | - Jianghong He
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
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20
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Sergeenko EV, Belousova OB, Pilipenko YV. [Diagnostic criteria for prolonged and chronic disturbances of consciousness after aneurysmal subarachnoid hemorrhages]. ZHURNAL VOPROSY NEIROKHIRURGII IMENI N. N. BURDENKO 2024; 88:117-121. [PMID: 39169590 DOI: 10.17116/neiro202488041117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/23/2024]
Abstract
BACKGROUND In recent years, prolonged states of impaired consciousness became widespread among patients with aneurysmal subarachnoid hemorrhage. Treatment and maintenance of vital functions in such patients represent a complex medical, economic and social problem. In this regard, searching for the causes of prolonged states of impaired consciousness and predicting the outcomes are important. OBJECTIVE To analyze available literature data on prevention and treatment of prolonged states of impaired consciousness after aneurysmal subarachnoid hemorrhage. RESULTS We reviewed the PubMed database using the keywords «unresponsive wakefulness syndrome», «persistent vegetative state2, «minimal consciousness state» and «outcome of subarachnoid hemorrhage». Only 4 reports devoted to the causes and treatment outcomes in patients with prolonged impairment of consciousness after aneurysmal subarachnoid hemorrhage were found. At the same time, patients with aneurysmal subarachnoid hemorrhage comprise up to 11% among all cases of prolonged states of impaired consciousness. Examination, management and treatment of patients with prolonged impairment of consciousness after aneurysmal subarachnoid hemorrhage are carried out according to general principles without taking into account specific etiological and pathogenetic factors. CONCLUSION Increased number of patients with prolonged impairment of consciousness after aneurysmal subarachnoid hemorrhage necessitates analysis of etiopathogenesis and outcomes of these disorders based on modern clinical, instrumental and laboratory assessment of the brain.
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21
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Russell ME, Hammond FM, Murtaugh B. Prognosis and enhancement of recovery in disorders of consciousness. NeuroRehabilitation 2024; 54:43-59. [PMID: 38277313 DOI: 10.3233/nre-230148] [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] [Indexed: 01/28/2024]
Abstract
Disorders of consciousness after severe brain injury encompass conditions of coma, vegetative state/unresponsive wakefulness syndrome, and minimally conscious state. DoC clinical presentation pose perplexing challenges to medical professionals, researchers, and families alike. The outcome is uncertain in the first weeks to months after a brain injury, with families and medical providers often making important decisions that require certainty. Prognostication for individuals with these conditions has been the subject of intense scientific investigation that continues to strive for valid prognostic indicators and algorithms for predicting recovery of consciousness. This manuscript aims to provide an overview of the current clinical landscape surrounding prognosis and optimizing recovery in DoC and the current and future research that could improve prognostic accuracy after severe brain injury. Improved understanding of these factors will aid healthcare professionals in providing optimal care, fostering hope, and advocating for ethical practices in the management of individuals with DoC.
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Affiliation(s)
- Mary E Russell
- Department of Physical Medicine and Rehabilitation, University of Texas McGovern Medical School, Houston, TX, USA
- TIRR Memorial Hermann - The Woodlands, Shenandoah, TX, USA
| | - Flora M Hammond
- Department of Physical Medicine and Rehabilitation, Indiana University School of Medicine, Indianapolis, IN, USA
- Rehabilitation Hospital of Indiana, Indianapolis, IN, USA
| | - Brooke Murtaugh
- Department of Rehabilitation Programs, Madonna Rehabilitation Hospitals, Lincoln, NE, USA
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22
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Edlow BL, Boerwinkle VL, Annen J, Boly M, Gosseries O, Laureys S, Mukherjee P, Puybasset L, Stevens RD, Threlkeld ZD, Newcombe VFJ, Fernandez-Espejo D. Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Neuroimaging. Neurocrit Care 2023; 39:611-617. [PMID: 37552410 DOI: 10.1007/s12028-023-01794-2] [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: 06/19/2023] [Accepted: 06/22/2023] [Indexed: 08/09/2023]
Abstract
BACKGROUND Over the past 5 decades, advances in neuroimaging have yielded insights into the pathophysiologic mechanisms that cause disorders of consciousness (DoC) in patients with severe brain injuries. Structural, functional, metabolic, and perfusion imaging studies have revealed specific neuroanatomic regions, such as the brainstem tegmentum, thalamus, posterior cingulate cortex, medial prefrontal cortex, and occipital cortex, where lesions correlate with the current or future state of consciousness. Advanced imaging modalities, such as diffusion tensor imaging, resting-state functional magnetic resonance imaging (fMRI), and task-based fMRI, have been used to improve the accuracy of diagnosis and long-term prognosis, culminating in the endorsement of fMRI for the clinical evaluation of patients with DoC in the 2018 US (task-based fMRI) and 2020 European (task-based and resting-state fMRI) guidelines. As diverse neuroimaging techniques are increasingly used for patients with DoC in research and clinical settings, the need for a standardized approach to reporting results is clear. The success of future multicenter collaborations and international trials fundamentally depends on the implementation of a shared nomenclature and infrastructure. METHODS To address this need, the Neurocritical Care Society's Curing Coma Campaign convened an international panel of DoC neuroimaging experts to propose common data elements (CDEs) for data collection and reporting in this field. RESULTS We report the recommendations of this CDE development panel and disseminate CDEs to be used in neuroimaging studies of patients with DoC. CONCLUSIONS These CDEs will support progress in the field of DoC neuroimaging and facilitate international collaboration.
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Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
| | - Varina L Boerwinkle
- Clinical Resting-State Functional Magnetic Resonance Imaging Laboratory and Service, Department of Neurology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Jitka Annen
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre de Cerveau2, University Hospital of Liège, Liège, Belgium
| | - Melanie Boly
- Department of Neurology, University of Wisconsin, Madison, WI, USA
- Department of Psychiatry, Wisconsin Institute for Sleep and Consciousness, University of Wisconsin, Madison, WI, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre de Cerveau2, University Hospital of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre de Cerveau2, University Hospital of Liège, Liège, Belgium
- CERVO Research Institute, Laval University, Quebec, Canada
| | - Pratik Mukherjee
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Louis Puybasset
- Department of Anesthesiology and Intensive Care, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Robert D Stevens
- Departments of Anesthesiology and Critical Care Medicine, Neurology, Radiology, and Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zachary D Threlkeld
- Department of Neurology, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Davinia Fernandez-Espejo
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
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23
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Oujamaa L, Delon-Martin C, Jaroszynski C, Termenon M, Silva S, Payen JF, Achard S. Functional hub disruption emphasizes consciousness recovery in severe traumatic brain injury. Brain Commun 2023; 5:fcad319. [PMID: 38757093 PMCID: PMC11098044 DOI: 10.1093/braincomms/fcad319] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 08/20/2023] [Accepted: 11/21/2023] [Indexed: 05/18/2024] Open
Abstract
Severe traumatic brain injury can lead to transient or even chronic disorder of consciousness. To increase diagnosis and prognosis accuracy of disorder of consciousness, functional neuroimaging is recommended 1 month post-injury. Here, we investigated brain networks remodelling on longitudinal data between 1 and 3 months post severe traumatic brain injury related to change of consciousness. Thirty-four severe traumatic brain-injured patients were included in a cross-sectional and longitudinal clinical study, and their MRI data were compared to those of 20 healthy subjects. Long duration resting-state functional MRI were acquired in minimally conscious and conscious patients at two time points after their brain injury. The first time corresponds to the exit from intensive care unit and the second one to the discharge from post-intensive care rehabilitation ward. Brain networks data were extracted using graph analysis and metrics at each node quantifying local (clustering) and global (degree) connectivity characteristics. Comparison with brain networks of healthy subjects revealed patterns of hyper- and hypo-connectivity that characterize brain networks reorganization through the hub disruption index, a value quantifying the functional disruption in each individual severe traumatic brain injury graph. At discharge from intensive care unit, 24 patients' graphs (9 minimally conscious and 15 conscious) were fully analysed and demonstrated significant network disruption. Clustering and degree nodal metrics, respectively, related to segregation and integration properties of the network, were relevant to distinguish minimally conscious and conscious groups. At discharge from post-intensive care rehabilitation unit, 15 patients' graphs (2 minimally conscious, 13 conscious) were fully analysed. The conscious group still presented a significant difference with healthy subjects. Using mixed effects models, we showed that consciousness state, rather than time, explained the hub disruption index differences between minimally conscious and conscious groups. While severe traumatic brain-injured patients recovered full consciousness, regional functional connectivity evolved towards a healthy pattern. More specifically, the restoration of a healthy brain functional segregation could be necessary for consciousness recovery after severe traumatic brain injury. For the first time, extracting the hub disruption index directly from each patient's graph, we were able to track the clinical alteration and subsequent recovery of consciousness during the first 3 months following a severe traumatic brain injury.
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Affiliation(s)
- Lydia Oujamaa
- University Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Chantal Delon-Martin
- University Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Chloé Jaroszynski
- University Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Maite Termenon
- Faculty of Engineering, Biomedical Engineering Department, Mondragon Unibertsitatea (MU-ENG), 20500 Mondragon, Spain
| | - Stein Silva
- Toulouse NeuroImaging Center, Toulouse III Paul Sabatier University, Inserm, 31062 Toulouse, France
- Critical Care Unit, University Teaching Hospital of Purpan, 31059 Toulouse, France
| | - Jean-François Payen
- University Grenoble Alpes, Inserm U1216, Grenoble Institut Neurosciences, CHU Grenoble Alpes, 38000 Grenoble, France
| | - Sophie Achard
- University Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, 38000 Grenoble, France
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24
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Franzova E, Shen Q, Doyle K, Chen JM, Egbebike J, Vrosgou A, Carmona JC, Grobois L, Heinonen GA, Velazquez A, Gonzales IJ, Egawa S, Agarwal S, Roh D, Park S, Connolly ES, Claassen J. Injury patterns associated with cognitive motor dissociation. Brain 2023; 146:4645-4658. [PMID: 37574216 PMCID: PMC10629765 DOI: 10.1093/brain/awad197] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/14/2023] [Accepted: 05/28/2023] [Indexed: 08/15/2023] Open
Abstract
In unconscious appearing patients with acute brain injury, wilful brain activation to motor commands without behavioural signs of command following, known as cognitive motor dissociation (CMD), is associated with functional recovery. CMD can be detected by applying machine learning to EEG recorded during motor command presentation in behaviourally unresponsive patients. Identifying patients with CMD carries clinical implications for patient interactions, communication with families, and guidance of therapeutic decisions but underlying mechanisms of CMD remain unknown. By analysing structural lesion patterns and network level dysfunction we tested the hypothesis that, in cases with preserved arousal and command comprehension, a failure to integrate comprehended motor commands with motor outputs underlies CMD. Manual segmentation of T2-fluid attenuated inversion recovery and diffusion weighted imaging sequences quantifying structural injury was performed in consecutive unresponsive patients with acute brain injury (n = 107) who underwent EEG-based CMD assessments and MRI. Lesion pattern analysis was applied to identify lesion patterns common among patients with (n = 21) and without CMD (n = 86). Thalamocortical and cortico-cortical network connectivity were assessed applying ABCD classification of power spectral density plots and weighted pairwise phase consistency (WPPC) to resting EEG, respectively. Two distinct structural lesion patterns were identified on MRI for CMD and three for non-CMD patients. In non-CMD patients, injury to brainstem arousal pathways including the midbrain were seen, while no CMD patients had midbrain lesions. A group of non-CMD patients was identified with injury to the left thalamus, implicating possible language comprehension difficulties. Shared lesion patterns of globus pallidus and putamen were seen for a group of CMD patients, which have been implicated as part of the anterior forebrain mesocircuit in patients with reversible disorders of consciousness. Thalamocortical network dysfunction was less common in CMD patients [ABCD-index 2.3 (interquartile range, IQR 2.1-3.0) versus 1.4 (IQR 1.0-2.0), P < 0.0001; presence of D 36% versus 3%, P = 0.0006], but WPPC was not different. Bilateral cortical lesions were seen in patients with and without CMD. Thalamocortical disruption did not differ for those with CMD, but long-range WPPC was decreased in 1-4 Hz [odds ratio (OR) 0.8; 95% confidence interval (CI) 0.7-0.9] and increased in 14-30 Hz frequency ranges (OR 1.2; 95% CI 1.0-1.5). These structural and functional data implicate a failure of motor command integration at the anterior forebrain mesocircuit level with preserved thalamocortical network function for CMD patients with subcortical lesions. Amongst patients with bilateral cortical lesions preserved cortico-cortical network function is associated with CMD detection. These data may allow screening for CMD based on widely available structural MRI and resting EEG.
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Affiliation(s)
- Eva Franzova
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Qi Shen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Kevin Doyle
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Justine M Chen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jennifer Egbebike
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Athina Vrosgou
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jerina C Carmona
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Lauren Grobois
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Gregory A Heinonen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Angela Velazquez
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | | | - Satoshi Egawa
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Sachin Agarwal
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - David Roh
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Soojin Park
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - E Sander Connolly
- Department of Neurological Surgery, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
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25
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Northoff G, Daub J, Hirjak D. Overcoming the translational crisis of contemporary psychiatry - converging phenomenological and spatiotemporal psychopathology. Mol Psychiatry 2023; 28:4492-4499. [PMID: 37704861 PMCID: PMC10914603 DOI: 10.1038/s41380-023-02245-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 08/17/2023] [Accepted: 08/25/2023] [Indexed: 09/15/2023]
Abstract
Despite all neurobiological/neurocomputational progress in psychiatric research, recent authors speak about a 'crisis of contemporary psychiatry'. Some argue that we do not yet know the computational mechanisms underlying the psychopathological symptoms ('crisis of mechanism') while others diagnose a neglect of subjectivity, namely first-person experience ('crisis of subjectivity'). In this perspective, we propose that Phenomenological Psychopathology, due to its focus on first-person experience of space and time, is in an ideal position to address the crisis of subjectivity and, if extended to the brain's spatiotemporal topographic-dynamic structure as key focus of Spatiotemporal Psychopathology, the crisis of mechanism. We demonstrate how the first-person experiences of space and time differ between schizophrenia, mood disorders and anxiety disorders allowing for their differential-diagnosis - this addresses the crisis of subjectivity. Presupposing space and time as shared features of brain, experience, and symptoms as their "common currency", the structure of abnormal space and time experience may also serve as template for the structure of the brain's spatiotemporal neuro-computational mechanisms - this may address the crisis of mechanism. Preliminary scientific evidence in our examples of schizophrenia, bipolar disorder, anxiety disorder, and depression support such clinically relevant spatiotemporal determination of both first-person experience (crisis of subjectivity) and the brain's neuro-computational structure (crisis of mechanism). In conclusion, converging Phenomenological Psychopathology with Spatiotemporal Psychopathology might help to overcome the translational crisis in psychiatry by delineating more fine-grained neuro computational and -phenomenal mechanisms; this offers novel candidate biomarkers for diagnosis and therapy including both pharmacological and non-pharmacological treatment.
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Affiliation(s)
- Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada.
| | - Jonas Daub
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
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26
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Yu F, Gao Y, Li F, Zhang X, Hu F, Jia W, Li X. Resting-state EEG microstates as electrophysiological biomarkers in post-stroke disorder of consciousness. Front Neurosci 2023; 17:1257511. [PMID: 37849891 PMCID: PMC10577186 DOI: 10.3389/fnins.2023.1257511] [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: 07/12/2023] [Accepted: 09/18/2023] [Indexed: 10/19/2023] Open
Abstract
Introduction Ischemic stroke patients commonly experience disorder of consciousness (DOC), leading to poorer discharge outcomes and higher mortality risks. Therefore, the identification of applicable electrophysiological biomarkers is crucial for the rapid diagnosis and evaluation of post-stroke disorder of consciousness (PS-DOC), while providing supportive evidence for cerebral neurology. Methods In our study, we conduct microstate analysis on resting-state electroencephalography (EEG) of 28 post-stroke patients with awake consciousness and 28 patients with PS-DOC, calculating the temporal features of microstates. Furthermore, we extract the Lempel-Ziv complexity of microstate sequences and the delta/alpha power ratio of EEG on spectral. Statistical analysis is performed to examine the distinctions in features between the two groups, followed by inputting the distinctive features into a support vector machine for the classification of PS-DOC. Results Both groups obtain four optimal topographies of EEG microstates, but notable distinctions are observed in microstate C. Within the PS-DOC group, there is a significant increase in the mean duration and coverage of microstates B and C, whereas microstate D displays a contrasting trend. Additionally, noteworthy variations are found in the delta/alpha ratio and Lempel-Ziv complexity between the two groups. The integration of the delta/alpha ratio with microstates' temporal and Lempel-Ziv complexity features demonstrates the highest performance in the classifier (Accuracy = 91.07%). Discussion Our results suggest that EEG microstates can provide insights into the abnormal brain network dynamics in DOC patients post-stroke. Integrating the temporal and Lempel-Ziv complexity microstate features with spectral features offers a deeper understanding of the neuro mechanisms underlying brain damage in patients with DOC, holding promise as effective electrophysiological biomarkers for diagnosing PS-DOC.
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Affiliation(s)
- Fang Yu
- College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan, China
| | - Yanzhe Gao
- College of Life Sciences, Nankai University, Tianjin, China
| | - Fenglian Li
- College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan, China
| | - Xueying Zhang
- College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan, China
| | - Fengyun Hu
- The Fifth Clinical Medical College of Shanxi Medical University, Department of Neurology, Shanxi Provincial People’s Hospital, Taiyuan, China
| | - Wenhui Jia
- The Fifth Clinical Medical College of Shanxi Medical University, Department of Neurology, Shanxi Provincial People’s Hospital, Taiyuan, China
| | - Xiaohui Li
- College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan, China
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27
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Carlson JM, Lin DJ. Prognostication in Prolonged and Chronic Disorders of Consciousness. Semin Neurol 2023; 43:744-757. [PMID: 37758177 DOI: 10.1055/s-0043-1775792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
Patients with prolonged disorders of consciousness (DOCs) longer than 28 days may continue to make significant gains and achieve functional recovery. Occasionally, this recovery trajectory may extend past 3 (for nontraumatic etiologies) and 12 months (for traumatic etiologies) into the chronic period. Prognosis is influenced by several factors including state of DOC, etiology, and demographics. There are several testing modalities that may aid prognostication under active investigation including electroencephalography, functional and anatomic magnetic resonance imaging, and event-related potentials. At this time, only one treatment (amantadine) has been routinely recommended to improve functional recovery in prolonged DOC. Given that some patients with prolonged or chronic DOC have the potential to recover both consciousness and functional status, it is important for neurologists experienced in prognostication to remain involved in their care.
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Affiliation(s)
- Julia M Carlson
- Division of Neurocritical Care, Department of Neurology, University of North Carolina Hospital, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - David J Lin
- Center for Neurotechnology and Neurorecovery, Division of Neurocritical Care and Stroke Service, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
- Center for Neurorestoration and Neurotechnology, Rehabilitation Research and Development Service, Department of Veterans Affairs, Providence, Rhode Island
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28
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Sun F, Wang Y, Li Y, Li Y, Wang S, Xu F, Wang X. Variation in functional networks between clinical and subclinical discharges in childhood absence epilepsy: A multi-frequency MEG study. Seizure 2023; 111:109-121. [PMID: 37598560 DOI: 10.1016/j.seizure.2023.08.005] [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: 04/24/2023] [Revised: 08/06/2023] [Accepted: 08/09/2023] [Indexed: 08/22/2023] Open
Abstract
OBJECTIVE Two types of spike-and-wave discharges (SWDs) exist in childhood absence epilepsy (CAE): clinical discharges are prolonged and manifest primarily as impaired consciousness, whereas subclinical discharges are brief with few objectively visible symptoms. This study aimed to compare neural functional network and default mode network (DMN) activity between clinical and subclinical discharges to better understand the underlying mechanism of CAE. METHODS Using magnetoencephalography (MEG) data from 21 patients, we obtained 25 segments each of clinical discharges and subclinical discharges. Amplitude envelope correlation analysis was used to construct functional networks and graph theory was used to calculate network topological data. We then compared differences in functional connectivity within the DMN between clinical and subclinical discharges. All statistical comparisons were performed using paired-sample tests. RESULTS Compared to subclinical discharges, the functional network of clinical discharges exhibited higher synchronization - particularly in the parahippocampal gyrus - as early as 10 s before the seizure. Additionally, the functional network of clinical SWDs presented an anterior shift of key nodes in the alpha frequency band. Regarding clinical discharge progression, there were gradual increases in the parameter node strengths (S), clustering coefficients (C), and global efficiency (E) of the functional networks, while the path lengths (L) decreased. These changes were most prominent at the onset of discharges and followed by some recovery in the high-frequency bands, but no significant change in the low-frequency bands. Furthermore, connections within the DMN during the discharge period were significantly stronger for clinical discharge compared to subclinical discharges. CONCLUSIONS These findings suggest that a more regular network before abnormal discharges in clinical discharges contributes to SWD explosion and that the parahippocampal gyrus plays an important role in maintaining oscillations. An absence seizure is a gradual process and the emergence of SWDs may be accompanied by initiation of inhibitory mechanisms. Enhanced functional connectivity among DMN brain regions may indicate that patients have entered a state of introspection, and functional abnormalities in the parahippocampal gyrus may be associated with patients' transient memory loss.
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Affiliation(s)
- Fangling Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yingfan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yihan Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yanzhang Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Siyi Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Fengyuan Xu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
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Wang J, Gao X, Xiang Z, Sun F, Yang Y. Evaluation of consciousness rehabilitation via neuroimaging methods. Front Hum Neurosci 2023; 17:1233499. [PMID: 37780959 PMCID: PMC10537959 DOI: 10.3389/fnhum.2023.1233499] [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: 06/02/2023] [Accepted: 08/30/2023] [Indexed: 10/03/2023] Open
Abstract
Accurate evaluation of patients with disorders of consciousness (DoC) is crucial for personalized treatment. However, misdiagnosis remains a serious issue. Neuroimaging methods could observe the conscious activity in patients who have no evidence of consciousness in behavior, and provide objective and quantitative indexes to assist doctors in their diagnosis. In the review, we discussed the current research based on the evaluation of consciousness rehabilitation after DoC using EEG, fMRI, PET, and fNIRS, as well as the advantages and limitations of each method. Nowadays single-modal neuroimaging can no longer meet the researchers` demand. Considering both spatial and temporal resolution, recent studies have attempted to focus on the multi-modal method which can enhance the capability of neuroimaging methods in the evaluation of DoC. As neuroimaging devices become wireless, integrated, and portable, multi-modal neuroimaging methods will drive new advancements in brain science research.
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Affiliation(s)
| | | | | | - Fangfang Sun
- College of Automation, Hangzhou Dianzi University, Hangzhou, China
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Vitello MM, Rosenfelder MJ, Cardone P, Niimi M, Willacker L, Thibaut A, Lejeune N, Laureys S, Bender A, Gosseries O. A protocol for a multicenter randomized and personalized controlled trial using rTMS in patients with disorders of consciousness. Front Neurol 2023; 14:1216468. [PMID: 37545735 PMCID: PMC10401598 DOI: 10.3389/fneur.2023.1216468] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 07/06/2023] [Indexed: 08/08/2023] Open
Abstract
Background Improving the functional recovery of patients with DoC remains one of the greatest challenges of the field. Different theories exist about the role of the anterior (prefrontal areas) versus posterior (parietal areas) parts of the brain as hotspots for the recovery of consciousness. Repetitive transcranial magnetic stimulation (rTMS) is a powerful non-invasive brain stimulation technique for the treatment of DoC. However, a direct comparison of the effect of TMS treatment on the front versus the back of the brain has yet to be performed. In this study, we aim to assess the short- and long-term effects of frontal and parietal rTMS on DoC recovery and characterize responders phenotypically. Methods/design Ninety patients with subacute and prolonged DoC will be included in a two-part multicenter prospective study. In the first phase (randomized controlled trial, RCT), patients will undergo four rTMS sessions in a crossover design over 10 days, targeting (i) the left dorsolateral prefrontal cortex (DLPFC) and (ii) the left angular gyrus (AG), as well as (iii & iv) their sham alternatives. In the second phase (longitudinal personalized trial), patients will receive personalized stimulations for 20 working days targeting the brain area that showed the best results in the RCT and will be randomly assigned to either active or sham intervention. The effects of rTMS on neurobehavioral and neurophysiological functioning in patients with DoC will be evaluated using clinical biomarkers of responsiveness (i.e., the Coma Recovery Scale-Revised; CRS-R), and electrophysiological biomarkers (e.g., power spectra, functional and effective connectivity, perturbational complexity index before and after intervention). Functional long-term outcomes will be assessed at 3 and 6 months post-intervention. Adverse events will be recorded during the treatment phase. Discussion This study seeks to identify which brain region (front or back) is best to stimulate for the treatment of patients with DoC using rTMS, and to characterize the neural correlates of its action regarding recovery of consciousness and functional outcome. In addition, we will define the responders' profile based on patients' characteristics and functional impairments; and develop biomarkers of responsiveness using EEG analysis according to the clinical responsiveness to the treatment. Clinical Trial Registration https://clinicaltrials.gov/ct2/show/NCT04401319, Clinicaltrials.gov, n° NCT04401319.
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Affiliation(s)
- Marie M. Vitello
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Martin J. Rosenfelder
- Department of Neurology, Therapiezentrum Burgau, Burgau, Germany
- Clinical and Biological Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
| | - Paolo Cardone
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Masachika Niimi
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
- Department of Rehabilitation Medicine, Nihon University School of Medicine, Tokyo, Japan
| | - Lina Willacker
- Department of Neurology, Ludwig-Maximilians University Hospital of Munich, University of Munich, Munich, Germany
| | - Aurore Thibaut
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Nicolas Lejeune
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
- William Lennox Neurological Hospital, Ottignies-Louvain-la-Neuve, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
- CERVO Research Center, Laval University, Québec, QC, Canada
| | - Andreas Bender
- Department of Neurology, Therapiezentrum Burgau, Burgau, Germany
- Department of Neurology, Ludwig-Maximilians University Hospital of Munich, University of Munich, Munich, Germany
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
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Yang Y, Dai Y, He Q, Wang S, Chen X, Geng X, He J, Duan F. Altered brain functional connectivity in vegetative state and minimally conscious state. Front Aging Neurosci 2023; 15:1213904. [PMID: 37469954 PMCID: PMC10352323 DOI: 10.3389/fnagi.2023.1213904] [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: 04/28/2023] [Accepted: 06/06/2023] [Indexed: 07/21/2023] Open
Abstract
Objectives The pathological mechanism for a disorder of consciousness (DoC) is still not fully understood. Based on traditional behavioral scales, there is a high rate of misdiagnosis for subtypes of DoC. We aimed to explore whether topological characterization may explain the pathological mechanisms of DoC and be effective in diagnosing the subtypes of DoC. Methods Using resting-state functional magnetic resonance imaging data, the weighted brain functional networks for normal control subjects and patients with vegetative state (VS) and minimally conscious state (MCS) were constructed. Global and local network characteristics of each group were analyzed. A support vector machine was employed to identify MCS and VS patients. Results The average connection strength was reduced in DoC patients and roughly equivalent in MCS and VS groups. Global efficiency, local efficiency, and clustering coefficients were reduced, and characteristic path length was increased in DoC patients (p < 0.05). For patients of both groups, global network measures were not significantly different (p > 0.05). Nodal efficiency, nodal local efficiency, and nodal clustering coefficient were reduced in frontoparietal brain areas, limbic structures, and occipital and temporal brain areas (p < 0.05). The comparison of nodal centrality suggested that DoC causes reorganization of the network structure on a large scale, especially the thalamus. Lobal network measures emphasized that the differences between the two groups of patients mainly involved frontoparietal brain areas. The accuracy, sensitivity, and specificity of the classifier for identifying MCS and VS patients were 89.83, 78.95, and 95%, respectively. Conclusion There is an association between altered network structures and clinical symptoms of DoC. With the help of network metrics, it is feasible to differentiate MCS and VS patients.
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Affiliation(s)
- Yi Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
- Beijing Institute of Brain Disorders, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yangyang Dai
- Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation, College of Artificial Intelligence, Nankai University, Tianjin, China
| | - Qiheng He
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shan Wang
- Department of Information and Communications Engineering, School of Engineering, Tokyo Institute of Technology, Yokohama, Kanagawa, Japan
| | - Xueling Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiaoli Geng
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianghong He
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Feng Duan
- Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation, College of Artificial Intelligence, Nankai University, Tianjin, China
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Li A, Liu H, Lei X, He Y, Wu Q, Yan Y, Zhou X, Tian X, Peng Y, Huang S, Li K, Wang M, Sun Y, Yan H, Zhang C, He S, Han R, Wang X, Liu B. Hierarchical fluctuation shapes a dynamic flow linked to states of consciousness. Nat Commun 2023; 14:3238. [PMID: 37277338 DOI: 10.1038/s41467-023-38972-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 05/23/2023] [Indexed: 06/07/2023] Open
Abstract
Consciousness arises from the spatiotemporal neural dynamics, however, its relationship with neural flexibility and regional specialization remains elusive. We identified a consciousness-related signature marked by shifting spontaneous fluctuations along a unimodal-transmodal cortical axis. This simple signature is sensitive to altered states of consciousness in single individuals, exhibiting abnormal elevation under psychedelics and in psychosis. The hierarchical dynamic reflects brain state changes in global integration and connectome diversity under task-free conditions. Quasi-periodic pattern detection revealed that hierarchical heterogeneity as spatiotemporally propagating waves linking to arousal. A similar pattern can be observed in macaque electrocorticography. Furthermore, the spatial distribution of principal cortical gradient preferentially recapitulated the genetic transcription levels of the histaminergic system and that of the functional connectome mapping of the tuberomammillary nucleus, which promotes wakefulness. Combining behavioral, neuroimaging, electrophysiological, and transcriptomic evidence, we propose that global consciousness is supported by efficient hierarchical processing constrained along a low-dimensional macroscale gradient.
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Affiliation(s)
- Ang Li
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Haiyang Liu
- Department of Anesthesiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100101, China
- Department of Anesthesiology, Qinghai Provincial Traffic Hospital, Xining, 810001, China
| | - Xu Lei
- Sleep and Neuroimaging Center, Faculty of Psychology, Southwest University, Chongqing, 400715, China
- Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing, 400715, China
| | - Yini He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Qian Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Yan Yan
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
| | - Xin Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Xiaohan Tian
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Yingjie Peng
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Shangzheng Huang
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Kaixin Li
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Meng Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Yuqing Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Hao Yan
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Cheng Zhang
- The Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, 100034, China
| | - Sheng He
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Ruquan Han
- Department of Anesthesiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100101, China.
| | - Xiaoqun Wang
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
- New Cornerstone Science Laboratory, Beijing Normal University, Beijing, 100875, China.
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
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Alnagger N, Cardone P, Martial C, Laureys S, Annen J, Gosseries O. The current and future contribution of neuroimaging to the understanding of disorders of consciousness. Presse Med 2023; 52:104163. [PMID: 36796250 DOI: 10.1016/j.lpm.2022.104163] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 11/21/2022] [Accepted: 12/13/2022] [Indexed: 02/16/2023] Open
Abstract
Patients with disorders of consciousness (DoC) represent a group of severely brain-injured patients with varying capacities for consciousness in terms of both wakefulness and awareness. The current state-of-the-art for assessing these patients is through standardised behavioural examinations, but inaccuracies are commonplace. Neuroimaging and electrophysiological techniques have revealed vast insights into the relationships between neural alterations, andcognitive and behavioural features of consciousness in patients with DoC. This has led to the establishment of neuroimaging paradigms for the clinical assessment of DoC patients. Here, we review selected neuroimaging findings on the DoC population, outlining key findings of the dysfunction underlying DoC and presenting the current clinical utility of neuroimaging tools. We discuss that whilst individual brain areas play instrumental roles in generating and supporting consciousness, activation of these areas alone is not sufficient for conscious experience. Instead, for consciousness to arise, we need preserved thalamo-cortical circuits, in addition to sufficient connectivity between distinctly differentiated brain networks, underlined by connectivity both within, and between such brain networks. Finally, we present recent advances and future perspectives in computational methodologies applied to DoC, supporting the notion that progress in the science of DoC will be driven by a symbiosis of these data-driven analyses, and theory-driven research. Both perspectives will work in tandem to provide mechanistic insights contextualised within theoretical frameworks which ultimately inform the practice of clinical neurology.
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Affiliation(s)
- Naji Alnagger
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | - Paolo Cardone
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | - Charlotte Martial
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium; CERVO Research Center, Laval University, Quebec, Canada
| | - Jitka Annen
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), University Hospital of Liège, Liège, Belgium.
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Fingelkurts AA, Fingelkurts AA. Patients with Disorders of Consciousness: Are They Nonconscious, Unconscious, or Subconscious? Expanding the Discussion. Brain Sci 2023; 13:brainsci13050814. [PMID: 37239286 DOI: 10.3390/brainsci13050814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 05/14/2023] [Accepted: 05/16/2023] [Indexed: 05/28/2023] Open
Abstract
Unprecedented advancements in the diagnosis and treatment of patients with disorders of consciousness (DoC) have given rise to ethical questions about how to recognize and respect autonomy and a sense of agency of the personhood when those capacities are themselves disordered, as they typically are in patients with DoC. At the intersection of these questions rests the distinction between consciousness and unconsciousness. Indeed, evaluations of consciousness levels and capacity for recovery have a significant impact on decisions regarding whether to discontinue or prolong life-sustaining therapy for DoC patients. However, in the unconsciousness domain, there is the confusing array of terms that are regularly used interchangeably, making it quite challenging to comprehend what unconsciousness is and how it might be empirically grounded. In this opinion paper, we will provide a brief overview of the state of the field of unconsciousness and show how a rapidly evolving electroencephalogram (EEG) neuroimaging technique may offer empirical, theoretical, and practical tools to approach unconsciousness and to improve our ability to distinguish consciousness from unconsciousness and also nonconsciousness with greater precision, particularly in cases that are borderline (as is typical in patients with DoC). Furthermore, we will provide a clear description of three distant notions of (un)consciousness (unconsciousness, nonconsciousness, and subconsciousness) and discuss how they relate to the experiential selfhood which is essential for comprehending the moral significance of what makes life worth living.
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Onoda K, Akama H. Complex of global functional network as the core of consciousness. Neurosci Res 2023; 190:67-77. [PMID: 36535365 DOI: 10.1016/j.neures.2022.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 11/20/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022]
Abstract
Finding the neural basis of consciousness is challenging, and the distribution location of the core of consciousness remains inconclusive. Integrated information theory (IIT) argues that the posterior part of the brain is the hot zone of consciousness, especially phenological consciousness. The IIT has proposed a "main complex", a set of elements determined such that the information loss in a hierarchical partition approach is the largest among those of any other supersets and subsets, as the core of consciousness in a dynamic system. This approach may be applicable not only to phenomenal but also to access-consciousness. This study estimated the main complex of brain dynamics using functional magnetic resonance imaging in Human Connectome Project (HCP) and sleep datasets. The complex analyses revealed the common networks across various tasks and rest-state in HCP, composed of executive control, salience, and dorsal/ventral attention networks. The set of networks of the main complex was maintained during sleep. However, compared with the wakefulness stage, the amount of information of these networks and the default mode network, was reduced for the hypnagogic stage. The global interconnected structure composed of major functional networks can comprise the core of consciousness.
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Affiliation(s)
- Keiichi Onoda
- Department of Psychology, Otemon Gakuin University, Ibaraki, Osaka 567-8502, Japan.
| | - Hiroyuki Akama
- Department of Life Science and Technology, Tokyo Institute of Technology, Meguro, Tokyo 152-8550, Japan
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Jang S, Choi E. Relationship between Coma Recovery Scale-Revised and the Thalamocortical Tract of Ascending Reticular Activating System in Hypoxic-Ischemic Brain Injury: A Pilot Study. Healthcare (Basel) 2023; 11:healthcare11081148. [PMID: 37107982 PMCID: PMC10137777 DOI: 10.3390/healthcare11081148] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/13/2023] [Accepted: 04/13/2023] [Indexed: 04/29/2023] Open
Abstract
BACKGROUND This pilot study examined the relationship between the Coma Recovery Scale-Revised (CRS-R) and the five subparts of the thalamocortical tract in chronic patients with hypoxic-ischemic brain injury by diffusion tensor tractography (DTT). METHODS Seventeen consecutive chronic patients with hypoxic-ischemic brain injury were recruited. The consciousness state was evaluated using CRS-R. The five subparts of the thalamocortical tract (the prefrontal cortex, the premotor cortex, the primary motor cortex, the primary somatosensory cortex, and the posterior parietal cortex) were reconstructed using DTT. Fractional anisotropy and the tract volume of each subpart of the thalamocortical tract were estimated. RESULTS The CRS-R score showed a moderate positive correlation with the tract volume of the prefrontal cortex part of the thalamocortical tract (p < 0.05). In addition, the tract volume of the prefrontal cortex component of the thalamocortical tract could explain the variability in the CRS-R score (p < 0.05). CONCLUSION The prefrontal cortex part was closely related to the CRS-R score in chronic patients with hypoxic-ischemic brain injury. In addition, the change in the remaining number of neural fibers of the prefrontal cortex part appeared to be related to the change in conscious state.
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Affiliation(s)
- Sungho Jang
- Department of Physical Medicine and Rehabilitation, College of Medicine, Yeungnam University, Daegu 42415, Republic of Korea
| | - Eunbi Choi
- Department of Physical Medicine and Rehabilitation, College of Medicine, Yeungnam University, Daegu 42415, Republic of Korea
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Sahrizan NSA, Manan HA, Abdul Hamid H, Abdullah JM, Yahya N. Functional Alteration in the Brain Due to Tumour Invasion in Paediatric Patients: A Systematic Review. Cancers (Basel) 2023; 15:cancers15072168. [PMID: 37046828 PMCID: PMC10093754 DOI: 10.3390/cancers15072168] [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: 02/16/2023] [Revised: 03/29/2023] [Accepted: 03/29/2023] [Indexed: 04/14/2023] Open
Abstract
Working memory, language and speech abilities, motor skills, and visual abilities are often impaired in children with brain tumours. This is because tumours can invade the brain's functional areas and cause alterations to the neuronal networks. However, it is unclear what the mechanism of tumour invasion is and how various treatments can cause cognitive impairment. Therefore, this study aims to systematically evaluate the effects of tumour invasion on the cognitive, language, motor, and visual abilities of paediatric patients, as well as discuss the alterations and modifications in neuronal networks and anatomy. The electronic database, PubMed, was used to find relevant studies. The studies were systematically reviewed based on the type and location of brain tumours, cognitive assessment, and pre- and post-operative deficits experienced by patients. Sixteen studies were selected based on the inclusion and exclusion criteria following the guidelines from PRISMA. Most studies agree that tumour invasion in the brain causes cognitive dysfunction and alteration in patients. The effects of a tumour on cognition, language, motor, and visual abilities depend on the type of tumour and its location in the brain. The alteration to the neuronal networks is also dependent on the type and location of the tumour. However, the default mode network (DMN) is the most affected network, regardless of the tumour type and location.Furthermore, our findings suggest that different treatment types can also contribute to patients' cognitive function to improve or deteriorate. Deficits that persisted or were acquired after surgery could result from surgical manipulation or the progression of the tumour's growth. Meanwhile, recovery from the deficits indicated that the brain has the ability to recover and reorganise itself.
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Affiliation(s)
- Nur Shaheera Aidilla Sahrizan
- Department of Radiology, Makmal Pemprosesan Imej Kefungsian (Functional Image Processing Laboratory), University Kebangsaan Malaysia Medical Centre, Kuala Lumpur 56000, Malaysia
- Department of Radiology and Intervency, Hospital Pakar Kanak-Kanak (Children Specialist Hospital), Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia
| | - Hanani Abdul Manan
- Department of Radiology, Makmal Pemprosesan Imej Kefungsian (Functional Image Processing Laboratory), University Kebangsaan Malaysia Medical Centre, Kuala Lumpur 56000, Malaysia
- Department of Radiology and Intervency, Hospital Pakar Kanak-Kanak (Children Specialist Hospital), Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia
| | - Hamzaini Abdul Hamid
- Department of Radiology, Makmal Pemprosesan Imej Kefungsian (Functional Image Processing Laboratory), University Kebangsaan Malaysia Medical Centre, Kuala Lumpur 56000, Malaysia
- Department of Radiology and Intervency, Hospital Pakar Kanak-Kanak (Children Specialist Hospital), Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia
| | - Jafri Malin Abdullah
- Jabatan Neurosains, Pusat Pengajian Sains Perubatan, Jalan Hospital USM, Kampus Kesihatan, Universiti Sains Malaysia, Kota Bharu 16150, Malaysia
- Brain and Behaviour Cluster, Pusat Pengajian Sains Perubatan, Kampus Kesihatan, Universiti Sains Malaysia, Kota Bharu 16150, Malaysia
- Department of Neurosciences & Brain Behaviour Cluster, Hospital Universiti Sains Malaysia, Kampus Kesihatan, Universiti Sains Malaysia, Kota Bharu 16150, Malaysia
| | - Noorazrul Yahya
- Diagnostic Imaging & Radiotherapy Program, School of Diagnostic & Applied Health Sciences, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur 50300, Malaysia
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Taran S, Gros P, Gofton T, Boyd G, Briard JN, Chassé M, Singh JM. The reticular activating system: a narrative review of discovery, evolving understanding, and relevance to current formulations of brain death. Can J Anaesth 2023; 70:788-795. [PMID: 37155119 PMCID: PMC10203024 DOI: 10.1007/s12630-023-02421-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 05/10/2023] Open
Abstract
A series of landmark experiments conducted throughout the 20th century progressively localized the regions involved in consciousness to the reticular activating system (RAS) and its ascending projections. The first description of the RAS emerged in 1949 through seminal experiments performed by Moruzzi and Magoun in feline brainstems; additional experiments in the 1950s revealed connections between the RAS and the thalamus and neocortical structures. This knowledge has allowed for the explanation of disorders of consciousness with exquisite anatomic precision. The clinical relevance of the RAS is further apparent in modern definitions of brain death/death by neurologic criteria (BD/DNC), which require demonstration of the complete and permanent loss of capacity for consciousness as one of their core criteria. BD/DNC is currently understood across jurisdictions in terms of "whole brain" and "brainstem" formulations. Although their clinical examination between formulations is indistinguishable, policies for BD/DNC declaration may differ in the rare scenario of patients with isolated infratentorial brain injuries, in which ancillary testing is advised in the whole brain formulation but not the brainstem formulation. Canadian guidelines acknowledge that the distinction between whole brain and brainstem formulations is unclear with respect to clinical implications for patients with isolated infratentorial injuries. This has led to variability in Canadian clinicians' use of ancillary testing when the mechanism of BD/DNC is suspected to be an isolated infratentorial injury. The present narrative review highlights these concepts and explores implications for determination of BD/DNC in Canada, with specific emphasis on the RAS and its relevance to both formulations.
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Affiliation(s)
- Shaurya Taran
- Department of Medicine, University Health Network, Toronto, ON, Canada
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
- Toronto Western Hospital, Office 411-L, 2nd Floor McLaughlin, 399 Bathurst St., Toronto, ON, M5T 2S8, Canada
| | - Priti Gros
- Department of Medicine, University Health Network, Toronto, ON, Canada
- Division of Neurology, University Health Network, Toronto, ON, Canada
| | - Teneille Gofton
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Gordon Boyd
- Department of Medicine (Neurology) and Critical Care Medicine, Queen's University, Kingston, ON, Canada
| | - Joel Neves Briard
- Department of Neuroscience, Université de Montréal, Montreal, QC, Canada
| | - Michaël Chassé
- Department of Medicine, Université de Montréal, Montreal, QC, Canada
- Université de Montréal Hospital Research Centre, Montreal, QC, Canada
| | - Jeffrey M Singh
- Department of Medicine, University Health Network, Toronto, ON, Canada
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
- Ontario Health - Trillium Gift of Life Network, Toronto, ON, Canada
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Xu C, Zhu Z, Wu W, Zheng X, Zhong H, Huang X, Xie Q, Qian X. Effects of 10 Hz individualized repetitive transcranial magnetic stimulation on patients with disorders of consciousness: a study protocol for an exploratory double-blind crossover randomized sham-controlled trial. Trials 2023; 24:249. [PMID: 37005647 PMCID: PMC10067296 DOI: 10.1186/s13063-023-07122-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 01/28/2023] [Indexed: 04/04/2023] Open
Abstract
BACKGROUND Repetitive transcranial magnetic stimulation (rTMS), as a non-invasive brain stimulation technique, has shown potentials for consciousness recovery of patients with disorders of consciousness (DoC), as, to a certain extent, it is effective in regulating the excitability of central nervous system. However, it is difficult to achieve satisfactory effect with "one size fits all" rTMS treatment due to different clinical conditions of patients. There is an urgent need to develop individualized strategy to improve the effectiveness of rTMS on patients with DoC. METHODS Our protocol is a randomized double-blind sham-controlled crossover trial that includes 30 DoC patients. Each patient will received 20 sessions, in which 10 sessions will be rTMS-active stimulus, and the other 10 sessions will be sham stimulus, separated by no less than 10 days' washout period. The rTMS-active will include 10 Hz rTMS over the individualized-targeted selection area for each patient according to the different insult regions of the brain. Coma Recovery Scale-Revised (CRS-R) will be used as primary outcome at baseline, after the first stage of stimulation, at the end of the washout period, and after the second stage of stimulation. Secondary outcomes will be measured at the same time, including efficiency, relative spectral power, and functional connectivity of high-density electroencephalograph (EEG). Adverse events will be recorded during the study. DISCUSSION rTMS has obtained grade A evidence in treating patients with several central nervous system diseases, and there has been some evidence showing partial improvement on level of consciousness in DoC patients. However, the effectiveness of rTMS in DoC is only 30~36%, mostly due to the non-specific target selection. In this protocol, we present a double-blind crossover randomized sham-controlled trial based on the individualized-targeted selection strategy that aims to study the effectiveness of rTMS therapy for DoC, and the result may provide new insights to non-invasive brain stimulation. TRIAL REGISTRATION ClinicalTrials.gov : NCT05187000. Registered on January 10, 2022.
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Affiliation(s)
- Chengwei Xu
- Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong Province, 510280, People's Republic of China
| | - Zhaohua Zhu
- Clinical Research Center, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong Province, 510280, People's Republic of China
| | - Wanchun Wu
- Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong Province, 510280, People's Republic of China
| | - Xiaochun Zheng
- Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong Province, 510280, People's Republic of China
| | - Haili Zhong
- Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong Province, 510280, People's Republic of China
| | - Xiyan Huang
- Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong Province, 510280, People's Republic of China.
| | - Qiuyou Xie
- Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong Province, 510280, People's Republic of China.
| | - Xinyi Qian
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi province, 341000, People's Republic of China
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Yan Z, Tang J, Ge H, Liu D, Liu Y, Liu H, Zou Y, Hu X, Yang K, Chen J. Synergistic structural and functional alterations in the medial prefrontal cortex of patients with high-grade gliomas infiltrating the thalamus and the basal ganglia. Front Neurosci 2023; 17:1136534. [PMID: 37051149 PMCID: PMC10083262 DOI: 10.3389/fnins.2023.1136534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 02/28/2023] [Indexed: 03/28/2023] Open
Abstract
BackgroundHigh-grade gliomas (HGGs) are characterized by a high degree of tissue invasion and uncontrolled cell proliferation, inevitably damaging the thalamus and the basal ganglia. The thalamus exhibits a high level of structural and functional connectivity with the default mode network (DMN). The present study investigated the structural and functional compensation within the DMN in HGGs invading the thalamus along with the basal ganglia (HITBG).MethodsA total of 32 and 22 healthy controls were enrolled, and their demographics and neurocognition (digit span test, DST) were assessed. Of the 32 patients, 18 patients were involved only on the left side, while 15 of them were involved on the right side. This study assessed the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), gray matter (GM) volume, and functional connectivity (FC) within the DMN and compared these measures between patients with left and right HITBG and healthy controls (HCs).ResultThe medial prefrontal cortex (mPFC) region existed in synchrony with the significant increase in ALFF and GM volume in patients with left and right HITBG compared with HCs. In addition, patients with left HITBG exhibited elevated ReHo and GM precuneus volumes, which did not overlap with the findings in patients with right HITBG. The patients with left and right HITBG showed decreased GM volume in the contralateral hippocampus without any functional variation. However, no significant difference in FC values was observed in the regions within the DMN. Additionally, the DST scores were significantly lower in patients with HITBG, but there was no significant correlation with functional or GM volume measurements.ConclusionThe observed pattern of synchrony between structure and function was present in the neuroplasticity of the mPFC and the precuneus. However, patients with HITBG may have a limited capacity to affect the connectivity within the regions of the DMN. Furthermore, the contralateral hippocampus in patients with HITBG exhibited atrophy. Thus, preventing damage to these regions may potentially delay the progression of neurological function impairment in patients with HGG.
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Affiliation(s)
- Zheng Yan
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jun Tang
- Department of Neurosurgery, Yixing Hospital of Traditional Chinese Medicine, Yixing, China
| | - Honglin Ge
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Dongming Liu
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yong Liu
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Brain Functional Imaging, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongyi Liu
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Brain Functional Imaging, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yuanjie Zou
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Brain Functional Imaging, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xinhua Hu
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Brain Functional Imaging, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Kun Yang
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Brain Functional Imaging, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- *Correspondence: Kun Yang
| | - Jiu Chen
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- Institute of Brain Functional Imaging, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- Jiu Chen
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Wu H, Xie Q, Pan J, Liang Q, Lan Y, Guo Y, Han J, Xie M, Liu Y, Jiang L, Wu X, Li Y, Qin P. Identifying Patients with Cognitive Motor Dissociation Using Resting-state Temporal Stability. Neuroimage 2023; 272:120050. [PMID: 36963740 DOI: 10.1016/j.neuroimage.2023.120050] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 02/04/2023] [Accepted: 03/21/2023] [Indexed: 03/26/2023] Open
Abstract
Using task-dependent neuroimaging techniques, recent studies discovered a fraction of patients with disorders of consciousness (DOC) who had no command-following behaviors but showed a clear sign of awareness as healthy controls, which was defined as cognitive motor dissociation (CMD). However, existing task-dependent approaches might fail when CMD patients have cognitive function (e.g., attention, memory) impairments, in which patients with covert awareness cannot perform a specific task accurately and are thus wrongly considered unconscious, which leads to false-negative findings. Recent studies have suggested that sustaining a stable functional organization over time, i.e., high temporal stability, is crucial for supporting consciousness. Thus, temporal stability could be a powerful tool to detect the patient's cognitive functions (e.g., consciousness), while its alteration in the DOC and its capacity for identifying CMD were unclear. The resting-state fMRI (rs-fMRI) study included 119 participants from three independent research sites. A sliding-window approach was used to investigate global and regional temporal stability, which measured how stable the brain's functional architecture was across time. The temporal stability was compared in the first dataset (36/16 DOC/controls), and then a Support Vector Machine (SVM) classifier was built to discriminate DOC from controls. Furthermore, the generalizability of the SVM classifier was tested in the second independent dataset (35/21 DOC/controls). Finally, the SVM classifier was applied to the third independent dataset, where patients underwent rs-fMRI and brain-computer interface assessment (4/7 CMD/potential non-CMD), to test its performance in identifying CMD. Our results showed that global and regional temporal stability was impaired in DOC patients, especially in regions of the cingulo-opercular task control network, default-mode network, fronto-parietal task control network, and salience network. Using temporal stability as the feature, the SVM model not only showed good performance in the first dataset (accuracy = 90%), but also good generalizability in the second dataset (accuracy = 84%). Most importantly, the SVM model generalized well in identifying CMD in the third dataset (accuracy = 91%). Our preliminary findings suggested that temporal stability could be a potential tool to assist in diagnosing CMD. Furthermore, the temporal stability investigated in this study also contributed to a deeper understanding of the neural mechanism of consciousness.
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Affiliation(s)
- Hang Wu
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China
| | - Qiuyou Xie
- Joint Center for disorders of consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, 510220, China; Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, 510010, China
| | - Jiahui Pan
- School of Software, South China Normal University, Foshan, 528225, China; Pazhou Lab, Guangzhou, 510330, China
| | - Qimei Liang
- Joint Center for disorders of consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, 510220, China
| | - Yue Lan
- Joint Center for disorders of consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, 510220, China
| | - Yequn Guo
- Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, 510010, China
| | - Junrong Han
- Key Laboratory of Brain, Cognition and Education Science, Ministry of Education, China; Institute for Brain Research and Rehabilitation, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Musi Xie
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China
| | - Yueyao Liu
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China
| | - Liubei Jiang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China
| | - Xuehai Wu
- Pazhou Lab, Guangzhou, 510330, China; Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200433, China; Neurosurgical Institute of Fudan University, Shanghai Clinical Medical Center of Neurosurgery, Shanghai Key laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200433, China; State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200433, China.
| | - Yuanqing Li
- Pazhou Lab, Guangzhou, 510330, China; School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, China.
| | - Pengmin Qin
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China; Pazhou Lab, Guangzhou, 510330, China.
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Wang Y, Li Y, Sun F, Xu Y, Xu F, Wang S, Wang X. Altered neuromagnetic activity in default mode network in childhood absence epilepsy. Front Neurosci 2023; 17:1133064. [PMID: 37008207 PMCID: PMC10060817 DOI: 10.3389/fnins.2023.1133064] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
PurposeThe electrophysiological characterization of resting state oscillatory functional connectivity within the default mode network (DMN) during interictal periods in childhood absence epilepsy (CAE) remains unclear. Using magnetoencephalographic (MEG) recordings, this study investigated how the connectivity within the DMN was altered in CAE.MethodsUsing a cross-sectional design, we analyzed MEG data from 33 children newly diagnosed with CAE and 26 controls matched for age and sex. The spectral power and functional connectivity of the DMN were estimated using minimum norm estimation combined with the Welch technique and corrected amplitude envelope correlation.ResultsDefault mode network showed stronger activation in the delta band during the ictal period, however, the relative spectral power in other bands was significantly lower than that in the interictal period (pcorrected < 0.05 for DMN regions, except bilateral medial frontal cortex, left medial temporal lobe, left posterior cingulate cortex in the theta band, and the bilateral precuneus in the alpha band). It should be noted that the significant power peak in the alpha band was lost compared with the interictal data. Compared with controls, the interictal relative spectral power of DMN regions (except bilateral precuneus) in CAE patients was significantly increased in the delta band (pcorrected < 0.01), whereas the values of all DMN regions in the beta-gamma 2 band were significantly decreased (pcorrected < 0.01). In the higher frequency band (alpha-gamma1), especially in the beta and gamma1 band, the ictal node strength of DMN regions except the left precuneus was significantly higher than that in the interictal periods (pcorrected < 0.01), and the node strength of the right inferior parietal lobe increased most significantly in the beta band (Ictal: 3.8712 vs. Interictal: 0.7503, pcorrected < 0.01). Compared with the controls, the interictal node strength of DMN increased in all frequency bands, especially the right medial frontal cortex in the beta band (Controls: 0.1510 vs. Interictal: 3.527, pcorrected < 0.01). Comparing relative node strength between groups, the right precuneus in CAE children decreased significantly (β: Controls: 0.1009 vs. Interictal: 0.0475; γ 1: Controls:0.1149 vs. Interictal:0.0587, pcorrected < 0.01) such that it was no longer the central hub.ConclusionThese findings indicated DMN abnormalities in CAE patients, even in interictal periods without interictal epileptic discharges. Abnormal functional connectivity in CAE may reflect abnormal anatomo-functional architectural integration in DMN, as a result of cognitive mental impairment and unconsciousness during absence seizure. Future studies are needed to examine if the altered functional connectivity can be used as a biomarker for treatment responses, cognitive dysfunction, and prognosis in CAE patients.
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Marino MH, Koffer J, Nalla S. Update on Disorders of Consciousness. CURRENT PHYSICAL MEDICINE AND REHABILITATION REPORTS 2023. [DOI: 10.1007/s40141-023-00384-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
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Calabrese E, Gandhi S, Shih J, Otero M, Randazzo D, Hemphill C, Huie R, Talbott JF, Amorim E. Parieto-Occipital Injury on Diffusion MRI Correlates with Poor Neurologic Outcome following Cardiac Arrest. AJNR Am J Neuroradiol 2023; 44:254-260. [PMID: 36797027 PMCID: PMC10187825 DOI: 10.3174/ajnr.a7779] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 01/03/2023] [Indexed: 02/18/2023]
Abstract
BACKGROUND AND PURPOSE MR imaging of the brain provides unbiased neuroanatomic evaluation of brain injury and is useful for neurologic prognostication following cardiac arrest. Regional analysis of diffusion imaging may provide additional prognostic value and help reveal the neuroanatomic underpinnings of coma recovery. The purpose of this study was to evaluate global, regional, and voxelwise differences in diffusion-weighted MR imaging signal in patients in a coma after cardiac arrest. MATERIALS AND METHODS We retrospectively analyzed diffusion MR imaging data from 81 subjects who were comatose for >48 hours following cardiac arrest. Poor outcome was defined as the inability to follow simple commands at any point during hospitalization. ADC differences between groups were evaluated across the whole brain, locally by using voxelwise analysis and regionally by using ROI-based principal component analysis. RESULTS Subjects with poor outcome had more severe brain injury as measured by lower average whole-brain ADC (740 [SD, 102] × 10-6 mm2/s versus 833 [SD, 23] × 10-6 mm2/s, P < .001) and larger average volumes of tissue with ADC below 650 × 10-6 mms/s (464 [SD, 469] mL versus 62 [SD, 51] mL, P < .001). Voxelwise analysis showed lower ADC in the bilateral parieto-occipital areas and perirolandic cortices for the poor outcome group. ROI-based principal component analysis showed an association between lower ADC in parieto-occipital regions and poor outcome. CONCLUSIONS Brain injury affecting the parieto-occipital region measured with quantitative ADC analysis was associated with poor outcomes after cardiac arrest. These results suggest that injury to specific brain regions may influence coma recovery.
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Affiliation(s)
- E Calabrese
- From the Department of Radiology and Biomedical Imaging (E.C., S.G., J.F.T.)
| | - S Gandhi
- From the Department of Radiology and Biomedical Imaging (E.C., S.G., J.F.T.)
- Department of Radiology and Biomedical Imaging (S.G., J.F.T., E.A.), Zuckerberg San Francisco General Hospital, San Francisco, California
| | - J Shih
- Department of Neurology (J.S., M.O., D.R., C.H., E.A.), Weill Institute for Neurosciences
| | - M Otero
- Department of Neurology (J.S., M.O., D.R., C.H., E.A.), Weill Institute for Neurosciences
| | - D Randazzo
- Department of Neurology (J.S., M.O., D.R., C.H., E.A.), Weill Institute for Neurosciences
| | - C Hemphill
- Department of Neurology (J.S., M.O., D.R., C.H., E.A.), Weill Institute for Neurosciences
| | - R Huie
- Department of Neurological Surgery (R.H.), University of California, San Francisco, San Francisco, California
| | - J F Talbott
- From the Department of Radiology and Biomedical Imaging (E.C., S.G., J.F.T.)
- Department of Radiology and Biomedical Imaging (S.G., J.F.T., E.A.), Zuckerberg San Francisco General Hospital, San Francisco, California
| | - E Amorim
- Department of Neurology (J.S., M.O., D.R., C.H., E.A.), Weill Institute for Neurosciences
- Department of Radiology and Biomedical Imaging (S.G., J.F.T., E.A.), Zuckerberg San Francisco General Hospital, San Francisco, California
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Shu Z, Wu J, Li H, Liu J, Lu J, Lin J, Liang S, Wu J, Han J, Yu N. fNIRS-based functional connectivity signifies recovery in patients with disorders of consciousness after DBS treatment. Clin Neurophysiol 2023; 147:60-68. [PMID: 36702043 DOI: 10.1016/j.clinph.2022.12.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 11/20/2022] [Accepted: 12/12/2022] [Indexed: 01/17/2023]
Abstract
OBJECTIVE While deep brain stimulation (DBS) has proved effective for certain patients with disorders of consciousness (DOC), the working neural mechanism is not clear, the response varies for patients, and the assessment is inadequate. This paper aims to quantify the DBS-induced changes of consciousness in DOC patients at the neural functional level. METHODS Ten DOC patients were included for DBS surgery. The DBS target was the right centromedian-parafascicular (CM-pf) nuclei for four patients and the bilateral CM-pf nuclei for six patients. Functional near-infrared spectroscopy (fNIRS) was taken to measure the neural activation of patients, in parallel with Coma Recovery Scale-Revised (CRS-R), before the DBS surgery and one month after. The fNIRS signals were recorded from the frontal, parietal, and occipital lobes. Functional connectivity analysis quantified the communication between brain regions, area communication strength, and global communication efficiency. Linear regression analysis was conducted between the changes of indices based on functional connectivity analysis and the changes of the CRS-R index. RESULTS Patients with trauma (n = 4) exhibited a greater increase of CRS-R scores after DBS treatment compared with patients with hemorrhage (n = 4) and brainstem infarction (n = 2). Global communication efficiency changed consistently with the CRS-R index (slope = 57.384, p < 0.05, R2=0.483). No significant relationship was found between the changes of area communication strength of six brain lobes and the changes of the CRS-R index. CONCLUSIONS The cause of DOC is essential for the outcome of DBS treatment, and brain communication efficiency is a promising functional marker for DOC recovery. SIGNIFICANCE fNIRS-based functional connectivity analysis on brain network signifies changes of consciousness in DOC patients after DBS treatment.
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Affiliation(s)
- Zhilin Shu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China
| | - Jingchao Wu
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300350, China
| | - Haitao Li
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300350, China
| | - Jinrui Liu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China
| | - Jiewei Lu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China
| | - Jianeng Lin
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China
| | - Siquan Liang
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300350, China.
| | - Jialing Wu
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin 300350, China; Laboratory of Cerebral Vascular and Neurodegenerative Diseases, Tianjin Neurosurgical Institute, Tianjin Huanhu Hospital, Tianjin 300350, China.
| | - Jianda Han
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China.
| | - Ningbo Yu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China.
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Sawamura S, Ikegame Y, Kawasaki T, Nakayama N, Yano H, Shinoda J. Brainstem volume, diffusion, and metabolism are associated with chronic consciousness disorders after traumatic brain injury. J Neuroimaging 2023; 33:310-317. [PMID: 36424181 DOI: 10.1111/jon.13071] [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: 09/12/2022] [Revised: 10/18/2022] [Accepted: 11/09/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND AND PURPOSE We aimed to identify reliable neuroradiological features of the brainstem reflecting the neurological symptoms of patients with chronic disorders of consciousness (DOCs) due to severe traumatic brain injury (TBI). METHODS We retrospectively examined 86 patients with chronic DOCs due to severe TBI caused by automobile accidents. We studied the relationships among (1) neurological symptoms, including consciousness level, (2) integrated cognitive/physical condition, and (3) neuroradiological features of the brainstem (brainstem volume on MRI, fractional anisotropy [FA] value in the brainstem, and standardized uptake value [SUV] of 18F-fluorodeoxyglucose [FDG] on positron emission tomography in the brainstem). RESULTS Brainstem volume was significantly larger and FA values were significantly higher in patients with a better level of consciousness. However, brainstem volumes were significantly decreased and the maximum SUV (SUVmax ) of FDG significantly increased at 2 years following admission regardless of the level of consciousness at admission. The brainstem volume was significantly larger and the FA value and SUVmax of FDG were significantly higher in patients with better National Agency for Automotive Safety and Victims' Aid (NASVA) scores at admission. The decrease in the brainstem volume was significantly minimized and the SUVmax of FDG significantly increased in patients with more improvement in the NASVA score 2 years after admission. CONCLUSIONS The volume, FA value, and SUVmax of FDG of the brainstem are important neuroradiological features associated with the neurological conditions of patients with chronic DOCs due to severe TBI.
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Affiliation(s)
- Shogo Sawamura
- Department of Clinical Brain Sciences, Gifu University Graduate School of Medicine, Minokamo, Japan.,Department of Rehabilitation, Heisei College of Health Sciences, Gifu, Japan
| | - Yuka Ikegame
- Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Kizawa Memorial Hospital, Minokamo, Japan
| | - Tomohiro Kawasaki
- Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Kizawa Memorial Hospital, Minokamo, Japan
| | - Noriyuki Nakayama
- Department of Neurosurgery, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Hirohito Yano
- Department of Clinical Brain Sciences, Gifu University Graduate School of Medicine, Minokamo, Japan.,Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Kizawa Memorial Hospital, Minokamo, Japan
| | - Jun Shinoda
- Department of Clinical Brain Sciences, Gifu University Graduate School of Medicine, Minokamo, Japan.,Chubu Medical Center for Prolonged Traumatic Brain Dysfunction, Kizawa Memorial Hospital, Minokamo, Japan
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Riegner G, Posey G, Oliva V, Jung Y, Mobley W, Zeidan F. Disentangling self from pain: mindfulness meditation-induced pain relief is driven by thalamic-default mode network decoupling. Pain 2023; 164:280-291. [PMID: 36095039 PMCID: PMC9823141 DOI: 10.1097/j.pain.0000000000002731] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 06/14/2022] [Indexed: 02/06/2023]
Abstract
ABSTRACT For millenniums, mindfulness was believed to diminish pain by reducing the influence of self-appraisals of noxious sensations. Today, mindfulness meditation is a highly popular and effective pain therapy that is believed to engage multiple, nonplacebo-related mechanisms to attenuate pain. Recent evidence suggests that mindfulness meditation-induced pain relief is associated with the engagement of unique cortico-thalamo-cortical nociceptive filtering mechanisms. However, the functional neural connections supporting mindfulness meditation-based analgesia remain unknown. This mechanistically focused clinical trial combined functional magnetic resonance imaging with psychophysical pain testing (49°C stimulation and pain visual analogue scales) to identify the neural connectivity supporting the direct modulation of pain-related behavioral and neural responses by mindfulness meditation. We hypothesized that mindfulness meditation-based pain relief would be reflected by greater decoupling between brain mechanisms supporting appraisal (prefrontal) and nociceptive processing (thalamus). After baseline pain testing, 40 participants were randomized to a well-validated, 4-session mindfulness meditation or book-listening regimen. Functional magnetic resonance imaging and noxious heat (49°C; right calf) were combined during meditation to test study hypotheses. Mindfulness meditation significantly reduced behavioral and neural pain responses when compared to the controls. Preregistered (NCT03414138) whole-brain analyses revealed that mindfulness meditation-induced analgesia was moderated by greater thalamus-precuneus decoupling and ventromedial prefrontal deactivation, respectively, signifying a pain modulatory role across functionally distinct neural mechanisms supporting self-referential processing. Two separate preregistered seed-to-seed analyses found that mindfulness meditation-based pain relief was also associated with weaker contralateral thalamic connectivity with the prefrontal and primary somatosensory cortex, respectively. Thus, we propose that mindfulness meditation is associated with a novel self-referential nociceptive gating mechanism to reduce pain.
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Affiliation(s)
- Gabriel Riegner
- Department of Anesthesiology; University of California San Diego; La Jolla, CA, 92037; United States
| | - Grace Posey
- Department of Medicine; Tulane University School of Medicine; New Orleans, LA, 70112; United States
| | - Valeria Oliva
- Department of Anesthesiology; University of California San Diego; La Jolla, CA, 92037; United States
| | - Youngkyoo Jung
- Department of Radiology; University of California Davis; Sacramento, CA, 95817; United States
| | - William Mobley
- Department of Neurosciences; University of California San Diego; La Jolla, CA, 92093; United States
| | - Fadel Zeidan
- Department of Anesthesiology; University of California San Diego; La Jolla, CA, 92037; United States
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48
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Luppi AI, Vohryzek J, Kringelbach ML, Mediano PAM, Craig MM, Adapa R, Carhart-Harris RL, Roseman L, Pappas I, Peattie ARD, Manktelow AE, Sahakian BJ, Finoia P, Williams GB, Allanson J, Pickard JD, Menon DK, Atasoy S, Stamatakis EA. Distributed harmonic patterns of structure-function dependence orchestrate human consciousness. Commun Biol 2023; 6:117. [PMID: 36709401 PMCID: PMC9884288 DOI: 10.1038/s42003-023-04474-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 01/11/2023] [Indexed: 01/29/2023] Open
Abstract
A central question in neuroscience is how consciousness arises from the dynamic interplay of brain structure and function. Here we decompose functional MRI signals from pathological and pharmacologically-induced perturbations of consciousness into distributed patterns of structure-function dependence across scales: the harmonic modes of the human structural connectome. We show that structure-function coupling is a generalisable indicator of consciousness that is under bi-directional neuromodulatory control. We find increased structure-function coupling across scales during loss of consciousness, whether due to anaesthesia or brain injury, capable of discriminating between behaviourally indistinguishable sub-categories of brain-injured patients, tracking the presence of covert consciousness. The opposite harmonic signature characterises the altered state induced by LSD or ketamine, reflecting psychedelic-induced decoupling of brain function from structure and correlating with physiological and subjective scores. Overall, connectome harmonic decomposition reveals how neuromodulation and the network architecture of the human connectome jointly shape consciousness and distributed functional activation across scales.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK.
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK.
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, CB2 1SB, UK.
| | - Jakub Vohryzek
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
- Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, 08005, Spain
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Pedro A M Mediano
- Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, UK
- Department of Computing, Imperial College London, London, W12 0NN, UK
| | - Michael M Craig
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Ram Adapa
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Robin L Carhart-Harris
- Center for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, W12 0NN, UK
- Psychedelics Division - Neuroscape, Department of Neurology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Leor Roseman
- Center for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, W12 0NN, UK
| | - Ioannis Pappas
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Alexander R D Peattie
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Anne E Manktelow
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Barbara J Sahakian
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Psychiatry, MRC/Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB, UK
| | - Paola Finoia
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Guy B Williams
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Judith Allanson
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
| | - John D Pickard
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, CB2 0QQ, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Selen Atasoy
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK
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49
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Lu Z, Huo T, Deng J, Guo F, Liu K, Liu P, Wang Q, Xiong L. Transcutaneous electrical acupoint stimulation induced sedative effects in healthy volunteers: A resting-state fMRI study. Front Hum Neurosci 2023; 16:843186. [PMID: 36741778 PMCID: PMC9893780 DOI: 10.3389/fnhum.2022.843186] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Accepted: 12/06/2022] [Indexed: 01/21/2023] Open
Abstract
Background Previous studies indicated the sedative effect of acupoint stimulation. However, its mechanism remains unclear. This study aimed to investigate the sedative effect of transcutaneous electrical acupoint stimulation (TEAS) and to explore the brain regions involved in this effect in healthy volunteers using functional magnetic resonance imaging (fMRI) techniques. Methods In this randomized trial, 26 healthy volunteers were randomly assigned to the TEAS group (receiving 30 min of acupoint stimulation at HT7/PC4) and the control group. fMRI was conducted before and after the intervention. The primary outcome was the BIS value during the intervention. Secondary outcomes included the amplitude of low-frequency fluctuation (ALFF) and region of interest (ROI)-based functional connectivity (FC) showed by fMRI. Results In healthy volunteers, compared with the control group, ALFF values in the TEAS-treated volunteers decreased in the left thalamus, right putamen, and midbrain, while they increased in the left orbitofrontal cortex. More FC existed between the thalamus and the insula, middle cingulate cortex, somatosensory cortex, amygdala, and putamen in subjects after TEAS treatment compared with subjects that received non-stimulation. In addition, ALFF values of the thalamus positively correlated with BIS in both groups. Conclusion Transcutaneous electrical acupoint stimulation could induce a sedative effect in healthy volunteers, and inhibition of the thalamus was among its possible mechanisms. Clinical trial registration www.ClinicalTrials.gov; identifier: NCT01896063.
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Affiliation(s)
- Zhihong Lu
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, China,*Correspondence: Lize Xiong ✉
| | - Tingting Huo
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Jiao Deng
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Kang Liu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Peng Liu
- Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Qiang Wang
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Lize Xiong
- Department of Anesthesiology and Perioperative Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, China,Translational Research Institute of Brain and Brain-Like Intelligence, Department of Anesthesiology, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China,Zhihong Lu ✉
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50
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Pozeg P, Alemán-Goméz Y, Jöhr J, Muresanu D, Pincherle A, Ryvlin P, Hagmann P, Diserens K, Dunet V. Structural connectivity in recovery after coma: Connectome atlas approach. Neuroimage Clin 2023; 37:103358. [PMID: 36868043 PMCID: PMC9996111 DOI: 10.1016/j.nicl.2023.103358] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 02/06/2023] [Accepted: 02/20/2023] [Indexed: 03/05/2023]
Abstract
AIM Pathological states of recovery after coma as a result of a severe brain injury are marked with changes in structural connectivity of the brain. This study aimed to identify a topological correlation between white matter integrity and the level of functional and cognitive impairment in patients recovering after coma. METHODS Structural connectomes were computed based on fractional anisotropy maps from 40 patients using a probabilistic human connectome atlas. We used a network based statistics approach to identify potential brain networks associated with a more favorable outcome, assessed with clinical neurobehavioral scores at the patient's discharge from the acute neurorehabilitation unit. RESULTS We identified a subnetwork whose strength of connectivity correlated with a more favorable outcome as measured with the Disability Rating Scale (network based statistics: t >3.5, P =.010). The subnetwork predominated in the left hemisphere and included the thalamic nuclei, putamen, precentral and postcentral gyri, and medial parietal regions. Spearman correlation between the mean fractional anisotropy value of the subnetwork and the score was ρ = -0.60 (P <.0001). A less extensive overlapping subnetwork correlated with the Coma Recovery Scale Revised score, consisting mostly of the left hemisphere connectivity between the thalamic nuclei and pre- and post-central gyri (network based statistics: t >3.5, P =.033; Spearman's ρ = 0.58, P <.0001). CONCLUSION The present findings suggest an important role of structural connectivity between the thalamus, putamen and somatomotor cortex in the recovery from coma as evaluated with neurobehavioral scores. These structures are part of the motor circuit involved in the generation and modulation of voluntary movement, as well as the forebrain mesocircuit supposedly underlying the maintenance of consciousness. As behavioural assessment of consciousness depends heavily on the signs of voluntary motor behaviour, further work will elucidate whether the identified subnetwork reflects the structural architecture underlying the recovery of consciousness or rather the ability to communicate its content.
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Affiliation(s)
- Polona Pozeg
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne 1011, Switzerland; Connectomics Lab, Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne 1011, Switzerland
| | - Yasser Alemán-Goméz
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne 1011, Switzerland; Connectomics Lab, Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne 1011, Switzerland
| | - Jane Jöhr
- Neurology and Acute Neurorehabilitation Unit, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne 1011, Switzerland
| | - Dafin Muresanu
- Department of Neuroscience, Luliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca 400347, Romania
| | - Alessandro Pincherle
- Neurology Unit, Department of Medicine, Hôpitaux Robert Schuman, Luxembourg 2540, Luxembourg
| | - Philippe Ryvlin
- Laboratory of Cortical Excitability and Arousal Disorders, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne 1011, Switzerland
| | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne 1011, Switzerland; Connectomics Lab, Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne 1011, Switzerland
| | - Karin Diserens
- Neurology and Acute Neurorehabilitation Unit, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne 1011, Switzerland
| | - Vincent Dunet
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne 1011, Switzerland.
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