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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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Cardone P, Alnagger N, Annen J, Bicego A, Gosseries O, Martial C. Psychedelics and disorders of consciousness: the current landscape and the path forward. Neurosci Conscious 2024; 2024:niae025. [PMID: 38881630 PMCID: PMC11179162 DOI: 10.1093/nc/niae025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 02/16/2024] [Accepted: 05/20/2024] [Indexed: 06/18/2024] Open
Abstract
Modern medicine has been shaken by the surge of psychedelic science that proposes a new approach to mitigate mental disorders, such as depression and post-traumatic stress disorder. Clinical trials to investigate whether psychedelic substances can treat psychiatric conditions are now underway, yet less discussion gravitates around their use in neurological disorders due to brain injury. One suggested implementation of brain-complexity enhancing psychedelics is to treat people with post-comatose disorders of consciousness (DoC). In this article, we discuss the rationale of this endeavour, examining possible outcomes of such experiments by postulating the existence of an optimal level of complexity. We consider the possible counterintuitive effects of both psychedelics and DoC on the functional connectivity of the default mode network and its possible impact on selfhood. We also elaborate on the role of computational modelling in providing complementary information to experimental studies, both contributing to our understanding of the treatment mechanisms and providing a path towards personalized medicine. Finally, we update the discourse surrounding the ethical considerations, encompassing clinical and scientific values.
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Affiliation(s)
- Paolo Cardone
- Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Centre du Cerveau2, University Hospital of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
| | - Naji Alnagger
- Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Centre du Cerveau2, University Hospital of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
| | - Jitka Annen
- Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Centre du Cerveau2, University Hospital of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Department of Data Analysis, University of Ghent, Henri Dunantlaan 1, Ghent 9000, Belgium
| | - Aminata Bicego
- Sensation and Perception Research Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Centre du Cerveau2, University Hospital of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Sensation and Perception Research Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
| | - Charlotte Martial
- Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Centre du Cerveau2, University Hospital of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
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Guo K, Zhang Q, Quan Z, Wang Y, Ma T, Jiang J, Kang F, Wang J. Whole-brain glucose metabolic pattern differentiates minimally conscious state from unresponsive wakefulness syndrome. CNS Neurosci Ther 2024; 30:e14787. [PMID: 38894559 PMCID: PMC11187933 DOI: 10.1111/cns.14787] [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: 03/12/2024] [Revised: 05/05/2024] [Accepted: 05/14/2024] [Indexed: 06/21/2024] Open
Abstract
AIMS The patient being minimally conscious state (MCS) may benefit from wake-up interventions aimed at improving quality of life and have a higher probability of recovering higher level of consciousness compared to patients with the unresponsive wakefulness syndrome (UWS). However, differentiation of the MCS and UWS poses challenge in clinical practice. This study aimed to explore glucose metabolic pattern (GMP) obtained from 18F-labeled-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) in distinguishing between UWS and MCS. METHODS Fifty-seven patients with disorders of consciousness (21 cases of UWS and 36 cases of MCS) who had undergone repeated standardized Coma Recovery Scale-Revised (CRS-R) evaluations were enrolled in this prospective study. 18F-FDG-PET was carried out in all patients and healthy controls (HCs). Voxel-based scaled subprofile model/principal component analysis (SSM/PCA) was used to generate GMPs. The expression score of whole-brain GMP was obtained, and its diagnostic accuracy was compared with the standardized uptake value ratio (SUVR). The diagnostic efficiency was validated by one-year later clinical outcomes. RESULTS UWS-MCS GMP exhibited hypometabolism in the frontal-parietal cortex, along with hypermetabolism in the unilateral lentiform nucleus, putamen, and anterior cingulate gyrus. The UWS-MCS-GMP expression score was significantly higher in UWS compared to MCS patients (0.90 ± 0.85 vs. 0 ± 0.93, p < 0.001). UWS-MCS-GMP expression score achieved an area under the curve (AUC) of 0.77 to distinguish MCS from UWS, surpassing that of SUVR based on the frontoparietal cortex (AUC = 0.623). UWS-MCS-GMP expression score was significantly correlated with the CRS-R score (r = -0.45, p = 0.004) and accurately predicted the one-year outcome in 73.7% of patients. CONCLUSION UWS and MCS exhibit specific glucose metabolism patterns, the UWS-MCS-GMP expression score significantly distinguishes MCS from UWS, making SSM/PCA a potential diagnostic methods in clinical practice for individual patients.
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Affiliation(s)
- Kun Guo
- Department of Nuclear Medicine, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Qi Zhang
- School of Communication & Information EngineeringShanghai UniversityShanghaiChina
| | - Zhiyong Quan
- Department of Nuclear Medicine, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Yirong Wang
- Department of Nuclear Medicine, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Taoqi Ma
- Department of Nuclear Medicine, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Jiehui Jiang
- School of Life SciencesShanghai UniversityShanghaiChina
| | - Fei Kang
- Department of Nuclear Medicine, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Jing Wang
- Department of Nuclear Medicine, Xijing HospitalFourth Military Medical UniversityXi'anChina
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Lo CCH, Woo PYM, Cheung VCK. Task-based EEG and fMRI paradigms in a multimodal clinical diagnostic framework for disorders of consciousness. Rev Neurosci 2024; 0:revneuro-2023-0159. [PMID: 38804042 DOI: 10.1515/revneuro-2023-0159] [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: 12/20/2023] [Accepted: 05/09/2024] [Indexed: 05/29/2024]
Abstract
Disorders of consciousness (DoC) are generally diagnosed by clinical assessment, which is a predominantly motor-driven process and accounts for up to 40 % of non-communication being misdiagnosed as unresponsive wakefulness syndrome (UWS) (previously known as prolonged/persistent vegetative state). Given the consequences of misdiagnosis, a more reliable and objective multimodal protocol to diagnosing DoC is needed, but has not been produced due to concerns regarding their interpretation and reliability. Of the techniques commonly used to detect consciousness in DoC, task-based paradigms (active paradigms) produce the most unequivocal result when findings are positive. It is well-established that command following (CF) reliably reflects preserved consciousness. Task-based electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can detect motor-independent CF and reveal preserved covert consciousness in up to 14 % of UWS patients. Accordingly, to improve the diagnostic accuracy of DoC, we propose a practical multimodal clinical decision framework centered on task-based EEG and fMRI, and complemented by measures like transcranial magnetic stimulation (TMS-EEG).
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Affiliation(s)
- Chris Chun Hei Lo
- School of Biomedical Sciences, and Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Peter Yat Ming Woo
- Division of Neurosurgery, Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Vincent C K Cheung
- School of Biomedical Sciences, and Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
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Shen Y, Peng L, Chen H, Xu P, Lv K, Xu Z, Shen H, Ji G, Xiong J, Hu D, Li Y, Lou M, Zeng LL, Qu L. Effects of long-term closed and socially isolating spaceflight analog environment on default mode network connectivity as indicated by fMRI. iScience 2024; 27:109617. [PMID: 38660401 PMCID: PMC11039341 DOI: 10.1016/j.isci.2024.109617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 03/18/2024] [Accepted: 03/26/2024] [Indexed: 04/26/2024] Open
Abstract
Long-term manned spaceflight and extraterrestrial planet settlement become the focus of space powers. However, the potential influence of closed and socially isolating spaceflight on the brain function remains unclear. A 180-day controlled ecological life support system integrated experiment was conducted, establishing a spaceflight analog environment to explore the effect of long-term socially isolating living. Three crewmembers were enrolled and underwent resting-state fMRI scanning before and after the experiment. We performed both seed-based and network-based analyses to investigate the functional connectivity (FC) changes of the default mode network (DMN), considering its key role in multiple higher-order cognitive functions. Compared with normal controls, the leader of crewmembers exhibited significantly reduced within-DMN and between-DMN FC after the experiment, while two others exhibited opposite trends. Moreover, individual differences of FC changes were further supported by evidence from behavioral analyses. The findings may shed new light on the development of psychological protection for space exploration.
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Affiliation(s)
- Yunxia Shen
- Department of Medical Imaging, Longgang Central Hospital of Shenzhen, Shenzhen, Guangdong 518116, China
| | - Limin Peng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Hailong Chen
- State Key Laboratory of Space Medicine, China Astronaut Research and Training Center, Beijing, Beijing 100094, China
| | - Pengfei Xu
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, Guangdong 518060, China
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, Guangdong 518057, China
| | - Ke Lv
- State Key Laboratory of Space Medicine, China Astronaut Research and Training Center, Beijing, Beijing 100094, China
| | - Zi Xu
- Department of Health Technology Research and Development, Space Institute of Southern China, Shenzhen, Guangdong 518117, China
| | - Hui Shen
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Guohua Ji
- State Key Laboratory of Space Medicine, China Astronaut Research and Training Center, Beijing, Beijing 100094, China
| | - Jianghui Xiong
- State Key Laboratory of Space Medicine, China Astronaut Research and Training Center, Beijing, Beijing 100094, China
| | - Dewen Hu
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Yinghui Li
- State Key Laboratory of Space Medicine, China Astronaut Research and Training Center, Beijing, Beijing 100094, China
| | - Mingwu Lou
- Department of Medical Imaging, Longgang Central Hospital of Shenzhen, Shenzhen, Guangdong 518116, China
| | - Ling-Li Zeng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
| | - Lina Qu
- State Key Laboratory of Space Medicine, China Astronaut Research and Training Center, Beijing, Beijing 100094, China
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6
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Mashour GA. Anesthesia and the neurobiology of consciousness. Neuron 2024; 112:1553-1567. [PMID: 38579714 PMCID: PMC11098701 DOI: 10.1016/j.neuron.2024.03.002] [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: 02/02/2024] [Revised: 03/05/2024] [Accepted: 03/06/2024] [Indexed: 04/07/2024]
Abstract
In the 19th century, the discovery of general anesthesia revolutionized medical care. In the 21st century, anesthetics have become indispensable tools to study consciousness. Here, I review key aspects of the relationship between anesthesia and the neurobiology of consciousness, including interfaces of sleep and anesthetic mechanisms, anesthesia and primary sensory processing, the effects of anesthetics on large-scale functional brain networks, and mechanisms of arousal from anesthesia. I discuss the implications of the data derived from the anesthetized state for the science of consciousness and then conclude with outstanding questions, reflections, and future directions.
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Affiliation(s)
- George A Mashour
- Center for Consciousness Science, Department of Anesthesiology, Department of Pharmacology, Neuroscience Graduate Program, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
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Șerban CA, Barborică A, Roceanu AM, Mîndruță IR, Ciurea J, Stancu M, Pâslaru AC, Zăgrean AM, Zăgrean L, Moldovan M. Towards an electroencephalographic measure of awareness based on the reactivity of oscillatory macrostates to hearing a subject's own name. Eur J Neurosci 2024; 59:771-785. [PMID: 37675619 DOI: 10.1111/ejn.16138] [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: 10/12/2022] [Revised: 08/09/2023] [Accepted: 08/16/2023] [Indexed: 09/08/2023]
Abstract
We proposed that the brain's electrical activity is composed of a sequence of alternating states with repeating topographic spectral distributions on scalp electroencephalogram (EEG), referred to as oscillatory macrostates. The macrostate showing the largest decrease in the probability of occurrence, measured as a percentage (reactivity), during sensory stimulation was labelled as the default EEG macrostate (DEM). This study aimed to assess the influence of awareness on DEM reactivity (DER). We included 11 middle cerebral artery ischaemic stroke patients with impaired awareness having a median Glasgow Coma Scale (GCS) of 6/15 and a group of 11 matched healthy controls. EEG recordings were carried out during auditory 1 min stimulation epochs repeating either the subject's own name (SON) or the SON in reverse (rSON). The DEM was identified across three SON epochs alternating with three rSON epochs. Compared with the patients, the DEM of controls contained more posterior theta activity reflecting source dipoles that could be mapped in the posterior cingulate cortex. The DER was measured from the 1 min quiet baseline preceding each stimulation epoch. The difference in mean DER between the SON and rSON epochs was measured by the salient EEG reactivity (SER) theoretically ranging from -100% to 100%. The SER was 12.4 ± 2.7% (Mean ± standard error of the mean) in controls and only 1.3 ± 1.9% in the patient group (P < 0.01). The patient SER decreased with the Glasgow Coma Scale. Our data suggest that awareness increases DER to SON as measured by SER.
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Affiliation(s)
- Cosmin-Andrei Șerban
- Physics Department, University of Bucharest, Bucharest, Romania
- Termobit Prod SRL, Bucharest, Romania
- FHC Inc, Bowdoin, Maine, USA
| | - Andrei Barborică
- Physics Department, University of Bucharest, Bucharest, Romania
- Termobit Prod SRL, Bucharest, Romania
- FHC Inc, Bowdoin, Maine, USA
| | | | | | - Jan Ciurea
- Department of Neurosurgery, Bagdasar-Arseni Emergency Hospital, Bucharest, Romania
| | - Mihai Stancu
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- Division of Neurobiology, Faculty of Biology, Ludwig Maximilian University, Munich, Germany
| | - Alexandru C Pâslaru
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Ana-Maria Zăgrean
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Leon Zăgrean
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Mihai Moldovan
- Termobit Prod SRL, Bucharest, Romania
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark
- Clinical Neurophysiology and Neurology, Rigshospitalet, Copenhagen, Denmark
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8
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Gallucci A, Varoli E, Del Mauro L, Hassan G, Rovida M, Comanducci A, Casarotto S, Lo Re V, Romero Lauro LJ. Multimodal approaches supporting the diagnosis, prognosis and investigation of neural correlates of disorders of consciousness: A systematic review. Eur J Neurosci 2024; 59:874-933. [PMID: 38140883 DOI: 10.1111/ejn.16149] [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: 12/12/2022] [Revised: 08/30/2023] [Accepted: 09/11/2023] [Indexed: 12/24/2023]
Abstract
The limits of the standard, behaviour-based clinical assessment of patients with disorders of consciousness (DoC) prompted the employment of functional neuroimaging, neurometabolic, neurophysiological and neurostimulation techniques, to detect brain-based covert markers of awareness. However, uni-modal approaches, consisting in employing just one of those techniques, are usually not sufficient to provide an exhaustive exploration of the neural underpinnings of residual awareness. This systematic review aimed at collecting the evidence from studies employing a multimodal approach, that is, combining more instruments to complement DoC diagnosis, prognosis and better investigating their neural correlates. Following the PRISMA guidelines, records from PubMed, EMBASE and Scopus were screened to select peer-review original articles in which a multi-modal approach was used for the assessment of adult patients with a diagnosis of DoC. Ninety-two observational studies and 32 case reports or case series met the inclusion criteria. Results highlighted a diagnostic and prognostic advantage of multi-modal approaches that involve electroencephalography-based (EEG-based) measurements together with neuroimaging or neurometabolic data or with neurostimulation. Multimodal assessment deepened the knowledge on the neural networks underlying consciousness, by showing correlations between the integrity of the default mode network and the different clinical diagnosis of DoC. However, except for studies using transcranial magnetic stimulation combined with electroencephalography, the integration of more than one technique in most of the cases occurs without an a priori-designed multi-modal diagnostic approach. Our review supports the feasibility and underlines the advantages of a multimodal approach for the diagnosis, prognosis and for the investigation of neural correlates of DoCs.
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Affiliation(s)
- Alessia Gallucci
- Ph.D. Program in Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
- NeuroMi (Neuroscience Center), University of Milano-Bicocca, Milan, Italy
| | - Erica Varoli
- Neurology Service, Department of Diagnostic and Therapeutic Services, Istituto di Ricovero e Cura a Carattere Scientifico-Istituto Mediterraneo per i Trapianti e Terapie ad Alta Specializzazione (IRCCS ISMETT), Palermo, Italy
| | - Lilia Del Mauro
- Department of Psychology, University of Milano-Bicocca, Milan, Italy
| | - Gabriel Hassan
- Department of Biomedical and Clinical Sciences, University of Milan, Italy
| | - Margherita Rovida
- Department of Psychology, University of Milano-Bicocca, Milan, Italy
| | - Angela Comanducci
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
- Università Campus Bio-Medico di Roma, Rome, Italy
| | - Silvia Casarotto
- Department of Biomedical and Clinical Sciences, University of Milan, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Vincenzina Lo Re
- Neurology Service, Department of Diagnostic and Therapeutic Services, Istituto di Ricovero e Cura a Carattere Scientifico-Istituto Mediterraneo per i Trapianti e Terapie ad Alta Specializzazione (IRCCS ISMETT), Palermo, Italy
| | - Leonor J Romero Lauro
- NeuroMi (Neuroscience Center), University of Milano-Bicocca, Milan, Italy
- Department of Psychology, University of Milano-Bicocca, Milan, Italy
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9
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Arnts H, Tewarie P, van Erp W, Schuurman R, Boon LI, Pennartz CMA, Stam CJ, Hillebrand A, van den Munckhof P. Deep brain stimulation of the central thalamus restores arousal and motivation in a zolpidem-responsive patient with akinetic mutism after severe brain injury. Sci Rep 2024; 14:2950. [PMID: 38316863 PMCID: PMC10844373 DOI: 10.1038/s41598-024-52267-1] [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: 06/20/2023] [Accepted: 01/16/2024] [Indexed: 02/07/2024] Open
Abstract
After severe brain injury, zolpidem is known to cause spectacular, often short-lived, restorations of brain functions in a small subgroup of patients. Previously, we showed that these zolpidem-induced neurological recoveries can be paralleled by significant changes in functional connectivity throughout the brain. Deep brain stimulation (DBS) is a neurosurgical intervention known to modulate functional connectivity in a wide variety of neurological disorders. In this study, we used DBS to restore arousal and motivation in a zolpidem-responsive patient with severe brain injury and a concomitant disorder of diminished motivation, more than 10 years after surviving hypoxic ischemia. We found that DBS of the central thalamus, targeted at the centromedian-parafascicular complex, immediately restored arousal and was able to transition the patient from a state of deep sleep to full wakefulness. Moreover, DBS was associated with temporary restoration of communication and ability to walk and eat in an otherwise wheelchair-bound and mute patient. With the use of magnetoencephalography (MEG), we revealed that DBS was generally associated with a marked decrease in aberrantly high levels of functional connectivity throughout the brain, mimicking the effects of zolpidem. These results imply that 'pathological hyperconnectivity' after severe brain injury can be associated with reduced arousal and behavioral performance and that DBS is able to modulate connectivity towards a 'healthier baseline' with lower synchronization, and, can restore functional brain networks long after severe brain injury. The presence of hyperconnectivity after brain injury may be a possible future marker for a patient's responsiveness for restorative interventions, such as DBS, and suggests that lower degrees of overall brain synchronization may be conducive to cognition and behavioral responsiveness.
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Affiliation(s)
- Hisse Arnts
- Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Department of Neurosurgery, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Prejaas Tewarie
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Willemijn van Erp
- Department of Primary and Community Care, Centre for Family Medicine, Geriatric Care and Public Health, Radboud University Medical Centre, Nijmegen, The Netherlands
- Accolade Zorg, Bosch en Duin, The Netherlands
- Libra Rehabilitation & Audiology, Tilburg, The Netherlands
| | - Rick Schuurman
- Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Lennard I Boon
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Cognitive and Systems Neuroscience Group, Swammerdam Institute, Center for Neuroscience, University of Amsterdam, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Pepijn van den Munckhof
- Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
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Othman MH, Møller K, Kjaergaard J, Kondziella D. Detecting signatures of consciousness in acute brain injury after stimulation with apomorphine and methylphenidate: protocol for a placebo-controlled, randomized, cross-over study. BMJ Neurol Open 2024; 6:e000584. [PMID: 38268756 PMCID: PMC10806905 DOI: 10.1136/bmjno-2023-000584] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 12/04/2023] [Indexed: 01/26/2024] Open
Abstract
Introduction Acute brain injury can lead to states of decreased consciousness, that is, disorder of consciousness (DoC). Detecting signs of consciousness early is vital for DoC management in the intensive care unit (ICU), neurorehabilitation and long-term prognosis. Our primary objective is to investigate the potential of pharmacological stimulant therapies in eliciting signs of consciousness among unresponsive or low-responsive acute DoC patients. Methods In a placebo-controlled, randomised, cross-over setting, we evaluate the effect of methylphenidate and apomorphine in 50 DoC patients with acute traumatic or non-traumatic brain injury admitted to the ICU. Patients are examined before and after administration of the trial drugs using (1) neurobehavioural scales to determine the clinical level of consciousness, (2) automated pupillometry to record pupillary responses as a signature for awareness and (3) near-infrared spectroscopy combined with electroencephalography to record neurovascular coupling as a measure for cortical activity. Primary outcomes include pupillary dilations and increase in cortical activity during passive and active paradigms. Ethics The study has been approved by the ethics committee (Journal-nr: H-21022096) and follows the principles of the Declaration of Helsinki. It is deemed to pose minimal risks and to hold a significant potential to improve treatment options for DoC patients. If the stimulants are shown to enhance cortical modulation of pupillary function and neurovascular coupling, this would warrant a large multicentre trial to evaluate their clinical impact. Dissemination Results will be available on EudraCT, clinicaltrialsregister.eu and published in an international peer-reviewed journal. Trial registration number EudraCT Number: 2021-001453-31.
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Affiliation(s)
- Marwan H Othman
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Kirsten Møller
- Department of Neuroanesthesiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Jesper Kjaergaard
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Daniel Kondziella
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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11
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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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12
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Sarma AK, Popli G, Anzalone A, Contillo N, Cornell C, Nunn AM, Rowland JA, Godwin DW, Flashman LA, Couture D, Stapleton-Kotloski JR. Use of magnetic source imaging to assess recovery after severe traumatic brain injury-an MEG pilot study. Front Neurol 2023; 14:1257886. [PMID: 38020602 PMCID: PMC10656620 DOI: 10.3389/fneur.2023.1257886] [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: 07/14/2023] [Accepted: 10/13/2023] [Indexed: 12/01/2023] Open
Abstract
Rationale Severe TBI (sTBI) is a devastating neurological injury that comprises a significant global trauma burden. Early comprehensive neurocritical care and rehabilitation improve outcomes for such patients, although better diagnostic and prognostic tools are necessary to guide personalized treatment plans. Methods In this study, we explored the feasibility of conducting resting state magnetoencephalography (MEG) in a case series of sTBI patients acutely after injury (~7 days), and then about 1.5 and 8 months after injury. Synthetic aperture magnetometry (SAM) was utilized to localize source power in the canonical frequency bands of delta, theta, alpha, beta, and gamma, as well as DC-80 Hz. Results At the first scan, SAM source maps revealed zones of hypofunction, islands of preserved activity, and hemispheric asymmetry across bandwidths, with markedly reduced power on the side of injury for each patient. GCS scores improved at scan 2 and by scan 3 the patients were ambulatory. The SAM maps for scans 2 and 3 varied, with most patients showing increasing power over time, especially in gamma, but a continued reduction in power in damaged areas and hemispheric asymmetry and/or relative diminishment in power at the site of injury. At the group level for scan 1, there was a large excess of neural generators operating within the delta band relative to control participants, while the number of neural generators for beta and gamma were significantly reduced. At scan 2 there was increased beta power relative to controls. At scan 3 there was increased group-wise delta power in comparison to controls. Conclusion In summary, this pilot study shows that MEG can be safely used to monitor and track the recovery of brain function in patients with severe TBI as well as to identify patient-specific regions of decreased or altered brain function. Such MEG maps of brain function may be used in the future to tailor patient-specific rehabilitation plans to target regions of altered spectral power with neurostimulation and other treatments.
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Affiliation(s)
- Anand Karthik Sarma
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Neurocritical Care, Piedmont Atlanta Hospital, Atlanta, GA, United States
| | - Gautam Popli
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Anthony Anzalone
- Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Department of Neurosurgery, Henry Ford Health System, Detroit, MI, United States
| | - Nicholas Contillo
- Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Cassandra Cornell
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Andrew M. Nunn
- Department of Surgery, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Jared A. Rowland
- Department of Neurobiology and Anatomy, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Research and Education Department, W.G. (Bill) Hefner VA Healthcare System, Salisbury, NC, United States
| | - Dwayne W. Godwin
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Department of Neurobiology and Anatomy, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Research and Education Department, W.G. (Bill) Hefner VA Healthcare System, Salisbury, NC, United States
| | - Laura A. Flashman
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Daniel Couture
- Department of Neurosurgery, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Jennifer R. Stapleton-Kotloski
- Department of Neurology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
- Department of Neurobiology and Anatomy, Wake Forest University School of Medicine, Winston-Salem, NC, United States
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13
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Papadimitriou C, Lindemann L, Meehan AJ. Making the visible seen: The interactional competence of a person in a disordered state of consciousness. Soc Sci Med 2023; 336:116261. [PMID: 37806147 DOI: 10.1016/j.socscimed.2023.116261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/18/2023] [Accepted: 09/21/2023] [Indexed: 10/10/2023]
Abstract
We examine a 12-min video-recorded interaction among a patient (KN) in a disordered state of consciousness (DOC) and a speech language pathologist clinician (CL) that takes place in a medical rehabilitation setting. The video is a demonstration of how caregivers could use a clinical assessment to observe their loved one's behavior to communicate potential behavioral changes to healthcare professionals. The purpose of this paper is to make visible the communication practices used by participants that may not be obvious to researchers, medical rehabilitation practitioners, and clinical assessment developers. We use phenomenological, linguistic and conversation analytic approaches to analyze the interaction. We found that KN demonstrates multiple conversational competencies, some (but not all) of which are acknowledged by CL, and most of which are not directly addressed by the assessment scoring criteria. For example, KN demonstrates conversational competency by responding non-verbally to CL's prompts from the assessment protocol and following along with the unspoken rules of discourse. He does this primarily through gaze, which broadcasts the focus of his attention and actively signals his participation in the conversation. Though KN does not always respond correctly to CL's questions, he nevertheless demonstrates implicit conversational competencies during turns of talk such as returning to 'neutral' position which signals the completion of a turn of talk. KN's conversational competencies may be missed by CL and the assessment protocol but we argue that they are important in understanding KN's capacity. Our analyses show that competency is not simply a performance by one person who appropriately and correctly responds to a series of questions in a prescribed time frame. Competence is a collaborative achievement among participants, co-produced in situ, and influenced by linguistic and cultural habits of talk and epistemic norms that privilege clinical knowledge and expertise.
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Affiliation(s)
| | - Luke Lindemann
- George Washington University, 2121 I St NW, Washington, DC, 20052, USA.
| | - Albert J Meehan
- Oakland University, 318 Meadow Brook Rd, Rochester, MI, 48309, USA.
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14
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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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15
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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: 3] [Impact Index Per Article: 3.0] [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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16
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Kumar A, Ridha M, Claassen J. Prognosis of consciousness disorders in the intensive care unit. Presse Med 2023; 52:104180. [PMID: 37805070 PMCID: PMC10995112 DOI: 10.1016/j.lpm.2023.104180] [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: 09/19/2023] [Accepted: 10/03/2023] [Indexed: 10/09/2023] Open
Abstract
Assessments of consciousness are a critical part of prognostic algorithms for critically ill patients suffering from severe brain injuries. There have been significant advances in the field of coma science over the past two decades, providing clinicians with more advanced and precise tools for diagnosing and prognosticating disorders of consciousness (DoC). Advanced neuroimaging and electrophysiological techniques have vastly expanded our understanding of the biological mechanisms underlying consciousness, and have helped identify new states of consciousness. One of these, termed cognitive motor dissociation, can predict functional recovery at 1 year post brain injury, and is present in up to 15-20% of patients with DoC. In this chapter, we review several tools that are used to predict DoC, describing their strengths and limitations, from the neurological examination to advanced imaging and electrophysiologic techniques. We also describe multimodal assessment paradigms that can be used to identify covert consciousness and thus help recognize patients with the potential for future recovery and improve our prognostication practices.
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Affiliation(s)
- Aditya Kumar
- Department of Neurology, Columbia University Medical Center, New York-Presbyterian Hospital, New York, NY, USA
| | - Mohamed Ridha
- Department of Neurology, Columbia University Medical Center, New York-Presbyterian Hospital, New York, NY, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, New York-Presbyterian Hospital, New York, NY, USA.
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17
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Lawn T, Martins D, O'Daly O, Williams S, Howard M, Dipasquale O. The effects of propofol anaesthesia on molecular-enriched networks during resting-state and naturalistic listening. Neuroimage 2023; 271:120018. [PMID: 36935083 PMCID: PMC10410200 DOI: 10.1016/j.neuroimage.2023.120018] [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: 10/31/2022] [Accepted: 03/09/2023] [Indexed: 03/19/2023] Open
Abstract
Placing a patient in a state of anaesthesia is crucial for modern surgical practice. However, the mechanisms by which anaesthetic drugs, such as propofol, impart their effects on consciousness remain poorly understood. Propofol potentiates GABAergic transmission, which purportedly has direct actions on cortex as well as indirect actions via ascending neuromodulatory systems. Functional imaging studies to date have been limited in their ability to unravel how these effects on neurotransmission impact the system-level dynamics of the brain. Here, we leveraged advances in multi-modal imaging, Receptor-Enriched Analysis of functional Connectivity by Targets (REACT), to investigate how different levels of propofol-induced sedation alter neurotransmission-related functional connectivity (FC), both at rest and when individuals are exposed to naturalistic auditory stimulation. Propofol increased GABA-A- and noradrenaline transporter-enriched FC within occipital and somatosensory regions respectively. Additionally, during auditory stimulation, the network related to the dopamine transporter showed reduced FC within bilateral regions of temporal and mid/posterior cingulate cortices, with the right temporal cluster showing an interaction between auditory stimulation and level of consciousness. In bringing together these micro- and macro-scale systems, we provide support for both direct GABAergic and indirect noradrenergic and dopaminergic-related network changes under propofol sedation. Further, we delineate a cognition-related reconfiguration of the dopaminergic network, highlighting the utility of REACT to explore the molecular substrates of consciousness and cognition.
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Affiliation(s)
- Timothy Lawn
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK.
| | - Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK
| | - Steve Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK
| | - Matthew Howard
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's college London, London, UK
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18
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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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19
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Liyana Arachige M, Seneviratne U, John N, Ma H, Phan TG. Mapping topography and network of brain injury in patients with disorders of consciousness. Front Neurol 2023; 14:1027160. [PMID: 37064187 PMCID: PMC10090673 DOI: 10.3389/fneur.2023.1027160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 03/14/2023] [Indexed: 03/31/2023] Open
Abstract
BackgroundThere is a growing interest in the topography of brain regions associated with disorders of consciousness. This has caused increased research output, yielding many publications investigating the topic with varying methodologies. The objective of this study was to ascertain the topographical regions of the brain most frequently associated with disorders of consciousness.MethodsWe performed a cross-sectional text-mining analysis of disorders of consciousness studies. A text mining algorithm built in the Python programming language searched documents for anatomical brain terminology. We reviewed primary PubMed studies between January 1st 2000 to 8th February 2023 for the search query “Disorders of Consciousness.” The frequency of brain regions mentioned in these articles was recorded, ranked, then built into a graphical network. Subgroup analysis was performed by evaluating the impact on our results if analyses were based on abstracts, full-texts, or topic-modeled groups (non-negative matrix factorization was used to create subgroups of each collection based on their key topics). Brain terms were ranked by their frequency and concordance was measured between subgroups. Graphical analysis was performed to explore relationships between the anatomical regions mentioned. The PageRank algorithm (used by Google to list search results in order of relevance) was used to determine global importance of the regions.ResultsThe PubMed search yielded 24,944 abstracts and 3,780 full texts. The topic-modeled subgroups contained 2015 abstracts and 283 full texts. Text Mining across all document groups concordantly ranked the thalamus the highest (Savage score = 11.716), followed by the precuneus (Savage score = 4.983), hippocampus (Savage score = 4.483). Graphical analysis had 5 clusters with the thalamus once again having the highest PageRank score (PageRank = 0.0344).ConclusionThe thalamus, precuneus and cingulate cortex are strongly associated with disorders of consciousness, likely due to the roles they play in maintaining awareness and involvement in the default mode network, respectively. The findings also suggest that other areas of the brain like the cerebellum, cuneus, amygdala and hippocampus also share connections to consciousness should be further investigated.
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Affiliation(s)
- Manoj Liyana Arachige
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Monash Health, Clayton, VIC, Australia
| | - Udaya Seneviratne
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Monash Health, Clayton, VIC, Australia
| | - Nevin John
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Monash Health, Clayton, VIC, Australia
| | - Henry Ma
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Monash Health, Clayton, VIC, Australia
| | - Thanh G. Phan
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC, Australia
- Department of Neurology, Monash Health, Clayton, VIC, Australia
- *Correspondence: Thanh G. Phan,
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Xu C, Li H, Gao J, Li L, He F, Yu J, Ling Y, Gao J, Li J, Melloni L, Luo B, Ding N. Statistical learning in patients in the minimally conscious state. Cereb Cortex 2023; 33:2507-2516. [PMID: 35670595 DOI: 10.1093/cercor/bhac222] [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: 01/04/2022] [Revised: 05/08/2022] [Accepted: 05/10/2022] [Indexed: 12/22/2022] Open
Abstract
When listening to speech, cortical activity can track mentally constructed linguistic units such as words, phrases, and sentences. Recent studies have also shown that the neural responses to mentally constructed linguistic units can predict the outcome of patients with disorders of consciousness (DoC). In healthy individuals, cortical tracking of linguistic units can be driven by both long-term linguistic knowledge and online learning of the transitional probability between syllables. Here, we investigated whether statistical learning could occur in patients in the minimally conscious state (MCS) and patients emerged from the MCS (EMCS) using electroencephalography (EEG). In Experiment 1, we presented to participants an isochronous sequence of syllables, which were composed of either 4 real disyllabic words or 4 reversed disyllabic words. An inter-trial phase coherence analysis revealed that the patient groups showed similar word tracking responses to real and reversed words. In Experiment 2, we presented trisyllabic artificial words that were defined by the transitional probability between words, and a significant word-rate EEG response was observed for MCS patients. These results suggested that statistical learning can occur with a minimal conscious level. The residual statistical learning ability in MCS patients could potentially be harnessed to induce neural plasticity.
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Affiliation(s)
- Chuan Xu
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Hangcheng Li
- Department of Rehabilitation, Hangzhou Mingzhou Brain Rehabilitation Hospital, Hangzhou 311215, China
| | - Jiaxin Gao
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
- Research Center for Advanced Artificial Intelligence Theory, Zhejiang Lab, Hangzhou 311121, China
| | - Lingling Li
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Fangping He
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Jie Yu
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Yi Ling
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Jian Gao
- Department of Rehabilitation, Hangzhou Mingzhou Brain Rehabilitation Hospital, Hangzhou 311215, China
| | - Jingqi Li
- Department of Rehabilitation, Hangzhou Mingzhou Brain Rehabilitation Hospital, Hangzhou 311215, China
| | - Lucia Melloni
- New York University Comprehensive Epilepsy Center, 223 34th Street, New York, NY 10016, USA
| | - Benyan Luo
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Nai Ding
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
- Research Center for Advanced Artificial Intelligence Theory, Zhejiang Lab, Hangzhou 311121, China
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21
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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] [Key Words] [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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22
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Bonin EAC, Lejeune N, Szymkowicz E, Bonhomme V, Martial C, Gosseries O, Laureys S, Thibaut A. Assessment and management of pain/nociception in patients with disorders of consciousness or locked-in syndrome: A narrative review. Front Syst Neurosci 2023; 17:1112206. [PMID: 37021037 PMCID: PMC10067681 DOI: 10.3389/fnsys.2023.1112206] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/06/2023] [Indexed: 04/07/2023] Open
Abstract
The assessment and management of pain and nociception is very challenging in patients unable to communicate functionally such as patients with disorders of consciousness (DoC) or in locked-in syndrome (LIS). In a clinical setting, the detection of signs of pain and nociception by the medical staff is therefore essential for the wellbeing and management of these patients. However, there is still a lot unknown and a lack of clear guidelines regarding the assessment, management and treatment of pain and nociception in these populations. The purpose of this narrative review is to examine the current knowledge regarding this issue by covering different topics such as: the neurophysiology of pain and nociception (in healthy subjects and patients), the source and impact of nociception and pain in DoC and LIS and, finally, the assessment and treatment of pain and nociception in these populations. In this review we will also give possible research directions that could help to improve the management of this specific population of severely brain damaged patients.
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Affiliation(s)
- Estelle A. C. Bonin
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liège, Belgium
- Centre du Cerveau, Liège University Hospital, Liège, Belgium
| | - Nicolas Lejeune
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liège, Belgium
- Centre Hospitalier Neurologique (CHN) William Lennox, Saint-Luc Hospital Group, Ottignies-Louvain-la-Neuve, Belgium
- Institute of Neuroscience, Université catholique de Louvain, Brussels, Belgium
| | - Emilie Szymkowicz
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liège, Belgium
- Centre du Cerveau, Liège University Hospital, Liège, Belgium
| | - Vincent Bonhomme
- Department of Anesthesia and Intensive Care Medicine, Liège University Hospital, Liège, Belgium
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness Thematic Unit, GIGA-Research, Liège, Belgium
| | - Charlotte Martial
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liège, Belgium
- Centre du Cerveau, Liège University Hospital, Liège, Belgium
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liège, Belgium
- Centre du Cerveau, Liège University Hospital, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liège, Belgium
- Centre du Cerveau, Liège University Hospital, Liège, Belgium
- Joint International Research Unit on Consciousness, CERVO Brain Research Centre, Centre Intégré Universitaire de Santé et Services Sociaux (CIUSS), University Laval, Québec City, QC, Canada
| | - Aurore Thibaut
- Coma Science Group, GIGA-Consciousness Thematic Unit, GIGA-Research, Liège, Belgium
- Centre du Cerveau, Liège University Hospital, Liège, Belgium
- *Correspondence: Aurore Thibaut,
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23
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Li H, Zhang X, Sun X, Dong L, Lu H, Yue S, Zhang H. Functional networks in prolonged disorders of consciousness. Front Neurosci 2023; 17:1113695. [PMID: 36875660 PMCID: PMC9981972 DOI: 10.3389/fnins.2023.1113695] [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: 12/01/2022] [Accepted: 01/25/2023] [Indexed: 02/19/2023] Open
Abstract
Prolonged disorders of consciousness (DoC) are characterized by extended disruptions of brain activities that sustain wakefulness and awareness and are caused by various etiologies. During the past decades, neuroimaging has been a practical method of investigation in basic and clinical research to identify how brain properties interact in different levels of consciousness. Resting-state functional connectivity within and between canonical cortical networks correlates with consciousness by a calculation of the associated temporal blood oxygen level-dependent (BOLD) signal process during functional MRI (fMRI) and reveals the brain function of patients with prolonged DoC. There are certain brain networks including the default mode, dorsal attention, executive control, salience, auditory, visual, and sensorimotor networks that have been reported to be altered in low-level states of consciousness under either pathological or physiological states. Analysis of brain network connections based on functional imaging contributes to more accurate judgments of consciousness level and prognosis at the brain level. In this review, neurobehavioral evaluation of prolonged DoC and the functional connectivity within brain networks based on resting-state fMRI were reviewed to provide reference values for clinical diagnosis and prognostic evaluation.
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Affiliation(s)
- Hui Li
- Rehabilitation Center, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.,Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China.,University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Xiaonian Zhang
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China
| | - Xinting Sun
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China
| | - Linghui Dong
- Rehabilitation Center, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.,Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China.,University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Haitao Lu
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China
| | - Shouwei Yue
- Rehabilitation Center, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.,University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Hao Zhang
- Rehabilitation Center, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.,Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China.,University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
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24
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Zheng RZ, Qi ZX, Wang Z, Xu ZY, Wu XH, Mao Y. Clinical Decision on Disorders of Consciousness After Acquired Brain Injury: Stepping Forward. Neurosci Bull 2023; 39:138-162. [PMID: 35804219 PMCID: PMC9849546 DOI: 10.1007/s12264-022-00909-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 04/10/2022] [Indexed: 01/22/2023] Open
Abstract
Major advances have been made over the past few decades in identifying and managing disorders of consciousness (DOC) in patients with acquired brain injury (ABI), bringing the transformation from a conceptualized definition to a complex clinical scenario worthy of scientific exploration. Given the continuously-evolving framework of precision medicine that integrates valuable behavioral assessment tools, sophisticated neuroimaging, and electrophysiological techniques, a considerably higher diagnostic accuracy rate of DOC may now be reached. During the treatment of patients with DOC, a variety of intervention methods are available, including amantadine and transcranial direct current stimulation, which have both provided class II evidence, zolpidem, which is also of high quality, and non-invasive stimulation, which appears to be more encouraging than pharmacological therapy. However, heterogeneity is profoundly ingrained in study designs, and only rare schemes have been recommended by authoritative institutions. There is still a lack of an effective clinical protocol for managing patients with DOC following ABI. To advance future clinical studies on DOC, we present a comprehensive review of the progress in clinical identification and management as well as some challenges in the pathophysiology of DOC. We propose a preliminary clinical decision protocol, which could serve as an ideal reference tool for many medical institutions.
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Affiliation(s)
- Rui-Zhe Zheng
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- National Center for Neurological Disorders, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China
| | - Zeng-Xin Qi
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- National Center for Neurological Disorders, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China
| | - Zhe Wang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- National Center for Neurological Disorders, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China
| | - Ze-Yu Xu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- National Center for Neurological Disorders, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China
| | - Xue-Hai Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
- National Center for Neurological Disorders, Shanghai, 200040, China.
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China.
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China.
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China.
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China.
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
- National Center for Neurological Disorders, Shanghai, 200040, China.
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China.
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China.
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China.
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China.
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25
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Ten-Year Change in Disorders of Consciousness: A Bibliometric Analysis. MEDICINA (KAUNAS, LITHUANIA) 2022; 59:medicina59010078. [PMID: 36676702 PMCID: PMC9867218 DOI: 10.3390/medicina59010078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/21/2022] [Accepted: 12/26/2022] [Indexed: 12/31/2022]
Abstract
Objectives: Disorders of consciousness (DoC) is a dynamic and challenging discipline, presenting intriguing challenges to clinicians and neurorehabilitation specialists for the lack of reliable assessment methods and interventions. Understanding DoC keeps pace with scientific research is urgent to need. We quantitively analyzed publications on DoC over the recent 10 years via bibliometrics analysis, to summarize the intellectual structure, current research hotspots, and future research trends in the field of DoC. Methods: Literature was obtained from the Science Citation Index Expanded of Web of Science Core Collection (WoSCC). To illustrate the knowledge structure of DoC, CiteSpace 5.8.R3 was used to conduct a co-occurrence analysis of countries, institutions, and keywords, and a co-citation analysis of references and journals. Also, Gephi 0.9.2 contributed to the author and co-cited author analysis. We found the most influential journals, authors, and countries and the most talked about keywords in the last decade of research. Results: A total of 1919 publications were collected. Over the past 10 years, the total number of annual publications has continued to increase, with the largest circulation in 2018. We found most DoC research and close cooperation originated from developed countries, e.g., the USA, Canada, and Italy. Academics from Belgium appear to have a strong presence in the field of DoC. The most influential journals were also mainly distributed in the USA and some European countries. Conclusions: This bibliometric study sheds light on the knowledge architecture of DoC research over the past decade, reflecting current hotspots and emerging trends, and providing new insights for clinicians and academics interested in DoC. The hot issues in DoC were diagnosing and differentiating the level of consciousness, and detecting covert awareness in early severe brain-injured patients. New trends focus on exploring the recovery mechanism of DoC and neuromodulation techniques.
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26
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Ballanti S, Campagnini S, Liuzzi P, Hakiki B, Scarpino M, Macchi C, Oddo CM, Carrozza MC, Grippo A, Mannini A. EEG-based methods for recovery prognosis of patients with disorders of consciousness: A systematic review. Clin Neurophysiol 2022; 144:98-114. [PMID: 36335795 DOI: 10.1016/j.clinph.2022.09.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 09/15/2022] [Accepted: 09/19/2022] [Indexed: 11/19/2022]
Abstract
OBJECTIVE Disorders of consciousness (DoC) are acquired conditions of severely altered consciousness. Electroencephalography (EEG)-derived biomarkers have been studied as clinical predictors of consciousness recovery. Therefore, this study aimed to systematically review the methods, features, and models used to derive prognostic EEG markers in patients with DoC in a rehabilitation setting. METHODS We conducted a systematic literature search of EEG-based strategies for consciousness recovery prognosis in five electronic databases. RESULTS The search resulted in 2964 papers. After screening, 15 studies were included in the review. Our analyses revealed that simpler experimental settings and similar filtering cut-off frequencies are preferred. The results of studies were categorised by extracting qualitative and quantitative features. The quantitative features were further classified into evoked/event-related potentials, spectral measures, entropy measures, and graph-theory measures. Despite the variety of methods, features from all categories, including qualitative ones, exhibited significant correlations with DoC prognosis. Moreover, no agreement was found on the optimal set of EEG-based features for the multivariate prognosis of patients with DoC, which limits the computational methods applied for outcome prediction and correlation analysis to classical ones. Nevertheless, alpha power, reactivity, and higher complexity metrics were often found to be predictive of consciousness recovery. CONCLUSIONS This study's findings confirm the essential role of qualitative EEG and suggest an important role for quantitative EEG. Their joint use could compensate for their reciprocal limitations. SIGNIFICANCE This study emphasises the need for further efforts toward guidelines on standardised EEG analysis pipeline, given the already proven role of EEG markers in the recovery prognosis of patients with DoC.
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Affiliation(s)
- Sara Ballanti
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy; The Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera 56025, Pisa, Italy; Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa 56127, Italy.
| | - Silvia Campagnini
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy; The Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera 56025, Pisa, Italy; Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa 56127, Italy.
| | - Piergiuseppe Liuzzi
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy; The Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera 56025, Pisa, Italy; Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa 56127, Italy.
| | - Bahia Hakiki
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy.
| | | | - Claudio Macchi
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy; Department of Experimental and Clinical Medicine, University of Florence, Firenze 50143, Italy.
| | - Calogero Maria Oddo
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera 56025, Pisa, Italy; Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa 56127, Italy.
| | - Maria Chiara Carrozza
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera 56025, Pisa, Italy; Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa 56127, Italy.
| | | | - Andrea Mannini
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy.
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27
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Intrinsic brain dynamics in the Default Mode Network predict involuntary fluctuations of visual awareness. Nat Commun 2022; 13:6923. [PMID: 36376303 PMCID: PMC9663583 DOI: 10.1038/s41467-022-34410-6] [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: 06/22/2021] [Accepted: 10/25/2022] [Indexed: 11/16/2022] Open
Abstract
Brain activity is intrinsically organised into spatiotemporal patterns, but it is still not clear whether these intrinsic patterns are functional or epiphenomenal. Using a simultaneous fMRI-EEG implementation of a well-known bistable visual task, we showed that the latent transient states in the intrinsic EEG oscillations can predict upcoming involuntarily perceptual transitions. The critical state predicting a dominant perceptual transition was characterised by the phase coupling between the precuneus (PCU), a key node of the Default Mode Network (DMN), and the primary visual cortex (V1). The interaction between the lifetime of this state and the PCU- > V1 Granger-causal effect is correlated with the perceptual fluctuation rate. Our study suggests that the brain's endogenous dynamics are phenomenologically relevant, as they can elicit a diversion between potential visual processing pathways, while external stimuli remain the same. In this sense, the intrinsic DMN dynamics pre-empt the content of consciousness.
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Coppola P, Allanson J, Naci L, Adapa R, Finoia P, Williams GB, Pickard JD, Owen AM, Menon DK, Stamatakis EA. The complexity of the stream of consciousness. Commun Biol 2022; 5:1173. [PMID: 36329176 PMCID: PMC9633704 DOI: 10.1038/s42003-022-04109-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 10/10/2022] [Indexed: 11/06/2022] Open
Abstract
Typical consciousness can be defined as an individual-specific stream of experiences. Modern consciousness research on dynamic functional connectivity uses clustering techniques to create common bases on which to compare different individuals. We propose an alternative approach by combining modern theories of consciousness and insights arising from phenomenology and dynamical systems theory. This approach enables a representation of an individual's connectivity dynamics in an intrinsically-defined, individual-specific landscape. Given the wealth of evidence relating functional connectivity to experiential states, we assume this landscape is a proxy measure of an individual's stream of consciousness. By investigating the properties of this landscape in individuals in different states of consciousness, we show that consciousness is associated with short term transitions that are less predictable, quicker, but, on average, more constant. We also show that temporally-specific connectivity states are less easily describable by network patterns that are distant in time, suggesting a richer space of possible states. We show that the cortex, cerebellum and subcortex all display consciousness-relevant dynamics and discuss the implication of our results in forming a point of contact between dynamical systems interpretations and phenomenology.
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Affiliation(s)
- Peter Coppola
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Judith Allanson
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's Hospital, Cambridge, UK
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Lloyd Building, Trinity College Dublin, Dublin, Ireland
| | - Ram Adapa
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Paola Finoia
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - Guy B Williams
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - John D Pickard
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Adrian M Owen
- The Brain and Mind Institute, Western Interdisciplinary Research Building, N6A 5B7 University of Western Ontario, London, ON, Canada
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
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Liu Y, Kang XG, Chen BB, Song CG, Liu Y, Hao JM, Yuan F, Jiang W. Detecting residual brain networks in disorders of consciousness: a resting-state fNIRS study. Brain Res 2022; 1798:148162. [DOI: 10.1016/j.brainres.2022.148162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/22/2022] [Accepted: 11/08/2022] [Indexed: 11/12/2022]
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30
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Wang Y, Chen S, Xia X, Peng Y, Wu B. Altered functional connectivity and regional brain activity in a triple-network model in minimally conscious state and vegetative-state/unresponsive wakefulness syndrome patients: A resting-state functional magnetic resonance imaging study. Front Behav Neurosci 2022; 16:1001519. [PMID: 36299294 PMCID: PMC9588962 DOI: 10.3389/fnbeh.2022.1001519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 09/26/2022] [Indexed: 11/13/2022] Open
Abstract
The purpose of this study was to investigate changes in functional connectivity and regional brain activity between and within the default mode network (DMN), salience network (SN), and executive control network (ECN) among individuals with disorders of consciousness (DOC) in the conditions of minimally conscious state (MCS) and vegetative-state/unresponsive wakefulness syndrome (VS/UWS). Twenty-five VS/UWS patients, 14 MCS patients, and 30 healthy individuals as normal control, completed resting-state fMRI scans. ROI-wise functional connectivity and fractional amplitude of low-frequency fluctuation (fALFF) were implemented to examine group differences. All ROI-wise and fALFF analyses masks were identified from the triple-network model. ROI-wise analyses indicated significantly decreased functional connectivity between posterior cingulate cortex (DMN)-left anterior insula (SN), right anterior insula (SN)-left dorsolateral prefrontal cortex (ECN), and right anterior insula (SN)-right amygdala (SN) in VS/UWS patients compared to MCS patients. Moreover, fALFF were observed reduced in the triple-network across all DOC patients, and as the clinical manifestations of DOC deteriorated from MCS to VS/UWS, fALFF in dorsal DMN, anterior/posterior SN, and left ECN became significantly reduced. Moreover, a positive correlation between fALFF of the left ECN and Coma Recovery Scale-Revised (CRS-R) total scores was found across all DOC patients. These findings contribute to a better understanding of the underlying neural mechanism of functional connectivity and regional brain activity in DOC patients, and this triple-network model provides new connectivity pattern changes that may be integrated in future diagnostic tools based on the neural signatures of conscious states.
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Affiliation(s)
- Yituo Wang
- Department of Radiology, Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Shanshan Chen
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing, China
| | - Xiaoyu Xia
- Senior Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Department of Neurosurgery, Hainan Hospital of Chinese PLA General Hospital, Sanya, China
| | - Ying Peng
- Department of Radiology, Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Bing Wu
- Department of Radiology, Seventh Medical Center of Chinese PLA General Hospital, Beijing, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- *Correspondence: Bing Wu,
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31
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Maschke C, Duclos C, Blain-Moraes S. Paradoxical markers of conscious levels: Effects of propofol on patients in disorders of consciousness. Front Hum Neurosci 2022; 16:992649. [PMID: 36277055 PMCID: PMC9584648 DOI: 10.3389/fnhum.2022.992649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 09/12/2022] [Indexed: 11/13/2022] Open
Abstract
Human consciousness is widely understood to be underpinned by rich and diverse functional networks, whose breakdown results in unconsciousness. Candidate neural correlates of anesthetic-induced unconsciousness include: (1) disrupted frontoparietal functional connectivity; (2) disrupted brain network hubs; and (3) reduced spatiotemporal complexity. However, emerging counterexamples have revealed that these markers may appear outside of the state they are associated with, challenging both their inclusion as markers of conscious level, and the theories of consciousness that rely on their evidence. In this study, we present a case series of three individuals in disorders of consciousness (DOC) who exhibit paradoxical brain responses to exposure to anesthesia. High-density electroencephalographic data were recorded from three patients with unresponsive wakefulness syndrome (UWS) while they underwent a protocol of propofol anesthesia with a targeted effect site concentration of 2 μg/ml. Network hubs and directionality of functional connectivity in the alpha frequency band (8–13 Hz), were estimated using the weighted phase lag index (wPLI) and directed phase lag index (dPLI). The spatiotemporal signal complexity was estimated using three types of Lempel-Ziv complexity (LZC). Our results illustrate that exposure to propofol anesthesia can paradoxically result in: (1) increased frontoparietal feedback-dominant connectivity; (2) posterior network hubs; and (3) increased spatiotemporal complexity. The case examples presented in this paper challenge the role of functional connectivity and spatiotemporal complexity in theories of consciousness and for the clinical evaluation of levels of human consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Catherine Duclos
- Hôpital du Sacré-Cœur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord-de-l’île-de-Montréal, Montreal, QC, Canada
- Department of Anesthesiology and Pain Medicine, Université de Montréal, Montreal, QC, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, QC, Canada
- School of Physical and Occupational Therapy, McGill University, Montreal, QC, Canada
- *Correspondence: Stefanie Blain-Moraes,
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32
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Fomins A, Sych Y, Helmchen F. Conservative significance testing of tripartite statistical relations in multivariate neural data. Netw Neurosci 2022; 6:1243-1274. [PMID: 38800452 PMCID: PMC11117094 DOI: 10.1162/netn_a_00259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 06/14/2022] [Indexed: 05/29/2024] Open
Abstract
An important goal in systems neuroscience is to understand the structure of neuronal interactions, frequently approached by studying functional relations between recorded neuronal signals. Commonly used pairwise measures (e.g., correlation coefficient) offer limited insight, neither addressing the specificity of estimated neuronal interactions nor potential synergistic coupling between neuronal signals. Tripartite measures, such as partial correlation, variance partitioning, and partial information decomposition, address these questions by disentangling functional relations into interpretable information atoms (unique, redundant, and synergistic). Here, we apply these tripartite measures to simulated neuronal recordings to investigate their sensitivity to noise. We find that the considered measures are mostly accurate and specific for signals with noiseless sources but experience significant bias for noisy sources.We show that permutation testing of such measures results in high false positive rates even for small noise fractions and large data sizes. We present a conservative null hypothesis for significance testing of tripartite measures, which significantly decreases false positive rate at a tolerable expense of increasing false negative rate. We hope our study raises awareness about the potential pitfalls of significance testing and of interpretation of functional relations, offering both conceptual and practical advice.
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Affiliation(s)
- Aleksejs Fomins
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, Switzerland
| | - Yaroslav Sych
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Experimental Neurology Center, Department of Neurology, Inselspital University Hospital Bern, Bern, Switzerland
- Present address: Institute of Cellular and Integrative Neurosciences, University of Strasbourg and CNRS, Strasbourg, France
| | - Fritjof Helmchen
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, Switzerland
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33
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Demertzi A, Kucyi A, Ponce-Alvarez A, Keliris GA, Whitfield-Gabrieli S, Deco G. Functional network antagonism and consciousness. Netw Neurosci 2022; 6:998-1009. [PMID: 38800457 PMCID: PMC11117090 DOI: 10.1162/netn_a_00244] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 03/06/2022] [Indexed: 05/29/2024] Open
Abstract
Spontaneous brain activity changes across states of consciousness. A particular consciousness-mediated configuration is the anticorrelations between the default mode network and other brain regions. What this antagonistic organization implies about consciousness to date remains inconclusive. In this Perspective Article, we propose that anticorrelations are the physiological expression of the concept of segregation, namely the brain's capacity to show selectivity in the way areas will be functionally connected. We postulate that this effect is mediated by the process of neural inhibition, by regulating global and local inhibitory activity. While recognizing that this effect can also result from other mechanisms, neural inhibition helps the understanding of how network metastability is affected after disrupting local and global neural balance. In combination with relevant theories of consciousness, we suggest that anticorrelations are a physiological prior that can work as a marker of preserved consciousness. We predict that if the brain is not in a state to host anticorrelations, then most likely the individual does not entertain subjective experience. We believe that this link between anticorrelations and the underlying physiology will help not only to comprehend how consciousness happens, but also conceptualize effective interventions for treating consciousness disorders in which anticorrelations seem particularly affected.
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Affiliation(s)
- Athena Demertzi
- Physiology of Cognition, GIGA Consciousness Research Unit, GIGA Institute (B34), Sart Tilman, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition (PsyNCog), Faculty of Psychology, Logopedics and Educational Sciences, Sart Tilman, University of Liège, Liège, Belgium
- GIGA-CRC In Vivo Imaging, Sart Tilman, University of Liège, Liège, Belgium
- Fund for Scientific Research, FNRS, Bruxelles, Belgium
| | - Aaron Kucyi
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Adrián Ponce-Alvarez
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Georgios A. Keliris
- Bio-Imaging Lab, Department of Biomedical Sciences, University of Antwerp, Wilrijk, Belgium
| | - Susan Whitfield-Gabrieli
- Department of Psychology, Northeastern University, Boston, MA, USA
- Northeastern University Biomedical Imaging Center (NUBIC), Northeastern University Interdisciplinary Science and Engineering Complex (ISEC), Boston, MA, USA
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Melbourne, VIC, Australia
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34
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Wu W, Xu C, Huang X, Xiao Q, Zheng X, Zhong H, Liang Q, Xie Q. Is frontoparietal electroencephalogram activity related to the level of functional disability in patients emerging from a minimally conscious state? A preliminary study. Front Hum Neurosci 2022; 16:972538. [PMID: 36248686 PMCID: PMC9556633 DOI: 10.3389/fnhum.2022.972538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Accepted: 09/13/2022] [Indexed: 11/30/2022] Open
Abstract
Objective When regaining consciousness, patients who emerge from a minimally conscious state (EMCS) present with different levels of functional disability, which pose great challenges for treatment. This study investigated the frontoparietal activity in EMCS patients and its effects on functional disability. Materials and methods In this preliminary study, 12 EMCS patients and 12 healthy controls were recruited. We recorded a resting-state scalp electroencephalogram (EEG) for at least 5 min for each participant. Each patient was assessed using the disability rating scale (DRS) to determine the level of functional disability. We analyzed the EEG power spectral density and sensor-level functional connectivity in relation to the patient’s functional disability. Results In the frontoparietal region, EMCS patients demonstrated lower relative beta power (P < 0.01) and higher weighted phase lag index (wPLI) values in the theta (P < 0.01) and gamma (P < 0.01) bands than healthy controls. The frontoparietal theta wPLI values of EMCS patients were positively correlated with the DRS scores (rs = 0.629, P = 0.029). At the whole-brain level, EMCS patients only had higher wPLI values in the theta band (P < 0.01) than healthy controls. The whole-brain theta wPLI values of EMCS patients were also positively correlated with the DRS scores (rs = 0.650, P = 0.022). No significant difference in the power and connectivity between the frontoparietal region and the whole brain in EMCS patients was observed. Conclusion EMCS patients still experience neural dysfunction, especially in the frontoparietal region. However, the theta connectivity in the frontoparietal region did not increase specifically. At the level of the whole brain, the same shift could also be seen. Theta functional connectivity in the whole brain may underlie different levels of functional disability.
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35
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Amiri M, Fisher PM, Raimondo F, Sidaros A, Cacic Hribljan M, Othman MH, Zibrandtsen I, Albrechtsen SS, Bergdal O, Hansen AE, Hassager C, Højgaard JLS, Jakobsen EW, Jensen HR, Møller J, Nersesjan V, Nikolic M, Olsen MH, Sigurdsson ST, Sitt JD, Sølling C, Welling KL, Willumsen LM, Hauerberg J, Larsen VA, Fabricius M, Knudsen GM, Kjaergaard J, Møller K, Kondziella D. Multimodal prediction of residual consciousness in the intensive care unit: the CONNECT-ME study. Brain 2022; 146:50-64. [PMID: 36097353 PMCID: PMC9825454 DOI: 10.1093/brain/awac335] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 07/25/2022] [Accepted: 08/14/2022] [Indexed: 01/15/2023] Open
Abstract
Functional MRI (fMRI) and EEG may reveal residual consciousness in patients with disorders of consciousness (DoC), as reflected by a rapidly expanding literature on chronic DoC. However, acute DoC is rarely investigated, although identifying residual consciousness is key to clinical decision-making in the intensive care unit (ICU). Therefore, the objective of the prospective, observational, tertiary centre cohort, diagnostic phase IIb study 'Consciousness in neurocritical care cohort study using EEG and fMRI' (CONNECT-ME, NCT02644265) was to assess the accuracy of fMRI and EEG to identify residual consciousness in acute DoC in the ICU. Between April 2016 and November 2020, 87 acute DoC patients with traumatic or non-traumatic brain injury were examined with repeated clinical assessments, fMRI and EEG. Resting-state EEG and EEG with external stimulations were evaluated by visual analysis, spectral band analysis and a Support Vector Machine (SVM) consciousness classifier. In addition, within- and between-network resting-state connectivity for canonical resting-state fMRI networks was assessed. Next, we used EEG and fMRI data at study enrolment in two different machine-learning algorithms (Random Forest and SVM with a linear kernel) to distinguish patients in a minimally conscious state or better (≥MCS) from those in coma or unresponsive wakefulness state (≤UWS) at time of study enrolment and at ICU discharge (or before death). Prediction performances were assessed with area under the curve (AUC). Of 87 DoC patients (mean age, 50.0 ± 18 years, 43% female), 51 (59%) were ≤UWS and 36 (41%) were ≥ MCS at study enrolment. Thirty-one (36%) patients died in the ICU, including 28 who had life-sustaining therapy withdrawn. EEG and fMRI predicted consciousness levels at study enrolment and ICU discharge, with maximum AUCs of 0.79 (95% CI 0.77-0.80) and 0.71 (95% CI 0.77-0.80), respectively. Models based on combined EEG and fMRI features predicted consciousness levels at study enrolment and ICU discharge with maximum AUCs of 0.78 (95% CI 0.71-0.86) and 0.83 (95% CI 0.75-0.89), respectively, with improved positive predictive value and sensitivity. Overall, both machine-learning algorithms (SVM and Random Forest) performed equally well. In conclusion, we suggest that acute DoC prediction models in the ICU be based on a combination of fMRI and EEG features, regardless of the machine-learning algorithm used.
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Affiliation(s)
| | | | | | - Annette Sidaros
- Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark,Department of Neurophysiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Melita Cacic Hribljan
- Department of Neurophysiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Marwan H Othman
- Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Ivan Zibrandtsen
- Department of Neurophysiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Simon S Albrechtsen
- Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Ove Bergdal
- Department of Neurosurgery, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Adam Espe Hansen
- Department of Radiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christian Hassager
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark,Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Joan Lilja S Højgaard
- Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | | | - Helene Ravnholt Jensen
- Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Jacob Møller
- Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Vardan Nersesjan
- Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark,Biological and Precision Psychiatry, Copenhagen Research Center for Mental Health, Copenhagen University Hospital, Copenhagen, Denmark
| | - Miki Nikolic
- Department of Neurophysiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Markus Harboe Olsen
- Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Sigurdur Thor Sigurdsson
- Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Jacobo D Sitt
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | - Christine Sølling
- Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Karen Lise Welling
- Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Lisette M Willumsen
- Department of Neurosurgery, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - John Hauerberg
- Department of Neurosurgery, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Vibeke Andrée Larsen
- Department of Radiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Martin Fabricius
- Department of Neurophysiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Gitte Moos Knudsen
- Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Jesper Kjaergaard
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark,Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Kirsten Møller
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark,Department of Neuroanaesthesiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Daniel Kondziella
- Correspondence to: Daniel Kondziella, MD, MSc, PhD FEBN Department of Neurology Copenhagen University Hospital, Rigshospitalet Blegdamsvej 9, DK-2100 Copenhagen E-mail:
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What lies underneath: Precise classification of brain states using time-dependent topological structure of dynamics. PLoS Comput Biol 2022; 18:e1010412. [PMID: 36067227 PMCID: PMC9481177 DOI: 10.1371/journal.pcbi.1010412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 09/16/2022] [Accepted: 07/18/2022] [Indexed: 11/19/2022] Open
Abstract
The self-organising global dynamics underlying brain states emerge from complex recursive nonlinear interactions between interconnected brain regions. Until now, most efforts of capturing the causal mechanistic generating principles have supposed underlying stationarity, being unable to describe the non-stationarity of brain dynamics, i.e. time-dependent changes. Here, we present a novel framework able to characterise brain states with high specificity, precisely by modelling the time-dependent dynamics. Through describing a topological structure associated to the brain state at each moment in time (its attractor or ‘information structure’), we are able to classify different brain states by using the statistics across time of these structures hitherto hidden in the neuroimaging dynamics. Proving the strong potential of this framework, we were able to classify resting-state BOLD fMRI signals from two classes of post-comatose patients (minimally conscious state and unresponsive wakefulness syndrome) compared with healthy controls with very high precision. Brain states emerge through continuously evolving dynamics of brain networks. The usual way of modelling these dynamics is by using stationary systems: there is one structure (attractor) which is responsible of the brain dynamics. We adopt a different approach by characterising the brain activity through a landscape of informational structures (IS) changing in time. We use a model transformation procedure to produce these structures and look at several properties related to how the different brain networks interact not in the observed resting-state fMRI signal but in the information structure underlying it. These properties provide measures strongly related with relevant characteristics of conscious activity, such as metastability, information integration or synchronisation. The distribution of IS measures is studied for healthy controls (HC) and two groups of post-comatose patients with disorders of consciousness (DOC): minimally conscious state (MCS) and unresponsive wakefulness syndrome (UWS). Based on IS measures, machine learners classifiers identify the state of consciousness with an outstanding discrimination (precision of 95.6% por HC/DOC and 86.6% for MCS/UWS).
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37
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Jang SH, Choi EB. Differences in the thalamocortical tract of the ascending reticular activating system in disorders of consciousness after hypoxic-ischemic brain injury: A pilot study. Medicine (Baltimore) 2022; 101:e30199. [PMID: 36107607 PMCID: PMC9439801 DOI: 10.1097/md.0000000000030199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
This study purposed to investigate differences in the thalamocortical tract of the ascending reticular activating system between vegetative state (VS) and minimally conscious state (MCS) patients with hypoxic-ischemic brain injury (HI-BI). Fourteen patients with disorders of consciousness following HI-BI (VS group: 7 patients, MCS group: 7 patients) and 12 normal subjects were recruited. The 5 parts of reconstructed thalamocortical tract were prefrontal cortex (PFC), premotor cortex, primary motor cortex (M1), primary somatosensory cortex (S1), and posterior parietal cortex (PPC). The fractional anisotropy (FA) value and tract volume (TV) in each part of the thalamocortical tract were estimated. The FA values and TV of all parts of the thalamocortical tract in the VS group and the FA values of all parts and TV of PFC, premotor cortex, and PPC parts in the MCS group were lower than the control group (P < .05). In addition, the FA values of PFC and PPC parts were significantly lower in the VS group than the MCS group (P < .05). The results of our pilot study indicate that PFC and PPC parts of the thalamocortical tract are important areas to assess for differentiation of VS and MCS after HI-BI.
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Affiliation(s)
- Sung Ho Jang
- Department of Physical Medicine and Rehabilitation, College of Medicine, Yeungnam University, Namku, Taegu, Republic of Korea
| | - Eun Bi Choi
- Department of Physical Medicine and Rehabilitation, College of Medicine, Yeungnam University, Namku, Taegu, Republic of Korea
- *Correspondence: Eun Bi Choi, Department of Physical Medicine and Rehabilitation, College of Medicine, Yeungnam University, 317-1, Daemyungdong, Namku, Taegu 705-717, Republic of Korea (e-mail: )
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38
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Multimodal MRI-Based Whole-Brain Assessment in Patients In Anoxoischemic Coma by Using 3D Convolutional Neural Networks. Neurocrit Care 2022; 37:303-312. [PMID: 35876960 PMCID: PMC9343298 DOI: 10.1007/s12028-022-01525-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 04/20/2022] [Indexed: 11/17/2022]
Abstract
Background There is an unfulfilled need to find the best way to automatically capture, analyze, organize, and merge structural and functional brain magnetic resonance imaging (MRI) data to ultimately extract relevant signals that can assist the medical decision process at the bedside of patients in postanoxic coma. We aimed to develop and validate a deep learning model to leverage multimodal 3D MRI whole-brain times series for an early evaluation of brain damages related to anoxoischemic coma. Methods This proof-of-concept, prospective, cohort study was undertaken at the intensive care unit affiliated with the University Hospital (Toulouse, France), between March 2018 and May 2020. All patients were scanned in coma state at least 2 days (4 ± 2 days) after cardiac arrest. Over the same period, age-matched healthy volunteers were recruited and included. Brain MRI quantification encompassed both “functional data” from regions of interest (precuneus and posterior cingulate cortex) with whole-brain functional connectivity analysis and “structural data” (gray matter volume, T1-weighted, fractional anisotropy, and mean diffusivity). A specifically designed 3D convolutional neuronal network (CNN) was created to allow conscious state discrimination (coma vs. controls) by using raw MRI indices as the input. A voxel-wise visualization method based on the study of convolutional filters was applied to support CNN outcome. The Ethics Committee of the University Teaching Hospital of Toulouse, France (2018-A31) approved the study and informed consent was obtained from all participants. Results The final cohort consisted of 29 patients in postanoxic coma and 34 healthy volunteers. Coma patients were successfully discerned from controls by using 3D CNN in combination with different MR indices. The best accuracy was achieved by functional MRI data, in particular with resting-state functional MRI of the posterior cingulate cortex, with an accuracy of 0.96 (range 0.94–0.98) on the test set from 10-time repeated tenfold cross-validation. Even more satisfactory performances were achieved through the majority voting strategy, which was able to compensate for mistakes from single MR indices. Visualization maps allowed us to identify the most relevant regions for each MRI index, notably regions previously described as possibly being involved in consciousness emergence. Interestingly, a posteriori analysis of misclassified patients indicated that they may present some common functional MRI traits with controls, which suggests further favorable outcomes. Conclusions A fully automated identification of clinically relevant signals from complex multimodal neuroimaging data is a major research topic that may bring a radical paradigm shift in the neuroprognostication of patients with severe brain injury. We report for the first time a successful discrimination between patients in postanoxic coma patients from people serving as controls by using 3D CNN whole-brain structural and functional MRI data. Clinical Trial Numberhttp://ClinicalTrials.gov (No. NCT03482115). Supplementary Information The online version contains supplementary material available at 10.1007/s12028-022-01525-z.
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Guo Y, Li R, Zhang R, Liu C, Zhang L, Zhao D, Shan Q, Wang X, Hu Y. Dynamic Changes of Brain Activity in Patients With Disorders of Consciousness During Recovery of Consciousness. Front Neurosci 2022; 16:878203. [PMID: 35720697 PMCID: PMC9201077 DOI: 10.3389/fnins.2022.878203] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 05/10/2022] [Indexed: 11/13/2022] Open
Abstract
The disorder of brain activity dynamics is one of the main characteristics leading to disorders of consciousness (DOC). However, few studies have explored whether the dynamics of brain activity can be modulated, and whether the dynamics of brain activity can help to evaluate the state of consciousness and the recovery progress of consciousness. In current study, 20 patients with minimally conscious state (MCS) and 13 patients with vegetative state (VS) were enrolled, and resting state electroencephalogram (EEG) data and the coma recovery scale-revised (CRS-R) scores were collected three times before and after high-definition transcranial direct current stimulation (HD-tDCS) treatment. The patients were divided into the improved group and the unimproved group according to whether the CRS-R scores were improved after the treatment, and the dynamic changes of resting state EEG microstate parameters during treatment were analyzed. The results showed the occurrence per second (OPS) of microstate D was significantly different between the MCS group and VS group, and it was positively correlated with the CRS-R before the treatment. After 2 weeks of the treatment, the OPS of microstate D improved significantly in the improved group. Meanwhile, the mean microstate duration (MMD), ratio of time coverage (Cov) of microstate C and the Cov of microstate D were significantly changed after the treatment. Compared with the microstates parameters before the treatment, the dynamic changes of parameters with significant difference in the improved group showed a consistent trend after the treatment. In contrast, the microstates parameters did not change significantly after the treatment in the unimproved group. The results suggest that the dynamics of EEG brain activity can be modulated by HD-tDCS, and the improvement in brain activity dynamics is closely related to the recovery of DOC, which is helpful to evaluate the level of DOC and the progress of recovery of consciousness.
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Affiliation(s)
- Yongkun Guo
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Engineering Research Center for Prevention and Treatment of Brain Injury, Zhengzhou, China
| | - Ruiqi Li
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, China
| | - Rui Zhang
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, China
| | - Chunying Liu
- Henan Engineering Research Center for Prevention and Treatment of Brain Injury, Zhengzhou, China
| | - Lipeng Zhang
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, China
| | - Dexiao Zhao
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qiao Shan
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Engineering Research Center for Prevention and Treatment of Brain Injury, Zhengzhou, China
| | - Xinjun Wang
- The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Engineering Research Center for Prevention and Treatment of Brain Injury, Zhengzhou, China
- *Correspondence: Xinjun Wang,
| | - Yuxia Hu
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, China
- Yuxia Hu,
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Fischer D, Newcombe V, Fernandez-Espejo D, Snider SB. Applications of Advanced MRI to Disorders of Consciousness. Semin Neurol 2022; 42:325-334. [PMID: 35790201 DOI: 10.1055/a-1892-1894] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
Disorder of consciousness (DoC) after severe brain injury presents numerous challenges to clinicians, as the diagnosis, prognosis, and management are often uncertain. Magnetic resonance imaging (MRI) has long been used to evaluate brain structure in patients with DoC. More recently, advances in MRI technology have permitted more detailed investigations of the brain's structural integrity (via diffusion MRI) and function (via functional MRI). A growing literature has begun to show that these advanced forms of MRI may improve our understanding of DoC pathophysiology, facilitate the identification of patient consciousness, and improve the accuracy of clinical prognostication. Here we review the emerging evidence for the application of advanced MRI for patients with DoC.
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Affiliation(s)
- David Fischer
- Division of Neurocritical Care, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Virginia Newcombe
- Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Davinia Fernandez-Espejo
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
| | - Samuel B Snider
- Division of Neurocritical Care, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
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Papadimitriou C, Weaver JA, Guernon A, Walsh E, Mallinson T, Pape TLB. "Fluctuation is the norm": Rehabilitation practitioner perspectives on ambiguity and uncertainty in their work with persons in disordered states of consciousness after traumatic brain injury. PLoS One 2022; 17:e0267194. [PMID: 35446897 PMCID: PMC9022828 DOI: 10.1371/journal.pone.0267194] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 04/04/2022] [Indexed: 11/19/2022] Open
Abstract
The purpose of this study is to describe the clinical lifeworld of rehabilitation practitioners who work with patients in disordered states of consciousness (DoC) after severe traumatic brain injury (TBI). We interviewed 21 practitioners using narrative interviewing methods from two specialty health systems that admit patients in DoC to inpatient rehabilitation. The overarching theme arising from the interview data is "Experiencing ambiguity and uncertainty in clinical reasoning about consciousness" when treating persons in DoC. We describe practitioners' practices of looking for consistency, making sense of ambiguous and hard to explain patient responses, and using trial and error or "tinkering" to care for patients. Due to scientific uncertainty about diagnosis and prognosis in DoC and ambiguity about interpretation of patient responses, working in the field of DoC disrupts the canonical meaning-making processes that practitioners have been trained in. Studying the lifeworld of rehabilitation practitioners through their story-making and story-telling uncovers taken-for-granted assumptions and normative structures that may exist in rehabilitation medical and scientific culture, including practitioner training. We are interested in understanding these canonical breaches in order to make visible how practitioners make meaning while treating patients.
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Affiliation(s)
- Christina Papadimitriou
- Departments of Interdisciplinary Health Sciences, and Sociology, Oakland University, Rochester, MI, United States of America
| | - Jennifer A. Weaver
- Department of Occupational Therapy, Colorado State University, Fort Collins, CO, United States of America
| | - Ann Guernon
- Speech-Language Pathology Department, Lewis University, Romeoville, IL, United States of America
| | - Elyse Walsh
- Research Service and Center for Innovation in Complex Chronic Healthcare, Edward Hines Jr. VA, Hines, IL, United States of America
| | - Trudy Mallinson
- Department of Clinical Research & Leadership, George Washington University, Washington, DC, United States of America
| | - Theresa L. Bender Pape
- Research Service and Center for Innovation in Complex Chronic Healthcare, Edward Hines Jr. VA, Hines, IL, United States of America
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, United States of America
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Farisco M, Pennartz C, Annen J, Cecconi B, Evers K. Indicators and criteria of consciousness: ethical implications for the care of behaviourally unresponsive patients. BMC Med Ethics 2022; 23:30. [PMID: 35313885 PMCID: PMC8935680 DOI: 10.1186/s12910-022-00770-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 03/13/2022] [Indexed: 11/24/2022] Open
Abstract
Background Assessing consciousness in other subjects, particularly in non-verbal and behaviourally disabled subjects (e.g., patients with disorders of consciousness), is notoriously challenging but increasingly urgent. The high rate of misdiagnosis among disorders of consciousness raises the need for new perspectives in order to inspire new technical and clinical approaches.
Main body We take as a starting point a recently introduced list of operational indicators of consciousness that facilitates its recognition in challenging cases like non-human animals and Artificial Intelligence to explore their relevance to disorders of consciousness and their potential ethical impact on the diagnosis and healthcare of relevant patients. Indicators of consciousness mean particular capacities that can be deduced from observing the behaviour or cognitive performance of the subject in question (or from neural correlates of such performance) and that do not define a hard threshold in deciding about the presence of consciousness, but can be used to infer a graded measure based on the consistency amongst the different indicators. The indicators of consciousness under consideration offer a potential useful strategy for identifying and assessing residual consciousness in patients with disorders of consciousness, setting the theoretical stage for an operationalization and quantification of relevant brain activity. Conclusions Our heuristic analysis supports the conclusion that the application of the identified indicators of consciousness to its disorders will likely inspire new strategies for assessing three very urgent issues: the misdiagnosis of disorders of consciousness; the need for a gold standard in detecting consciousness and diagnosing its disorders; and the need for a refined taxonomy of disorders of consciousness.
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Affiliation(s)
- Michele Farisco
- Centre for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden. .,Science and Society Unit, Biogem, Biology and Molecular Genetics Research Institute, Ariano Irpino, AV, Italy.
| | - Cyriel Pennartz
- Department of Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Research Priority Area, Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Jitka Annen
- Coma Science Group, GIGA-Consciousness, University of Liege, Liege, Belgium.,Centre du Cerveau, University Hospital of Liege, Liege, Belgium
| | - Benedetta Cecconi
- Coma Science Group, GIGA-Consciousness, University of Liege, Liege, Belgium.,Centre du Cerveau, University Hospital of Liege, Liege, Belgium
| | - Kathinka Evers
- Centre for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden
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Coppola P, Spindler LRB, Luppi AI, Adapa R, Naci L, Allanson J, Finoia P, Williams GB, Pickard JD, Owen AM, Menon DK, Stamatakis EA. Network dynamics scale with levels of awareness. Neuroimage 2022; 254:119128. [PMID: 35331869 DOI: 10.1016/j.neuroimage.2022.119128] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 02/10/2022] [Accepted: 03/20/2022] [Indexed: 02/04/2023] Open
Abstract
Small world topologies are thought to provide a valuable insight into human brain organisation and consciousness. However, functional magnetic resonance imaging studies in consciousness have not yielded consistent results. Given the importance of dynamics for both consciousness and cognition, here we investigate how the diversity of small world dynamics (quantified by sample entropy; dSW-E1) scales with decreasing levels of awareness (i.e., sedation and disorders of consciousness). Paying particular attention to result reproducibility, we show that dSW-E is a consistent predictor of levels of awareness even when controlling for the underlying functional connectivity dynamics. We find that dSW-E of subcortical and cortical areas are predictive, with the former showing higher and more robust effect sizes across analyses. We find that the network dynamics of intermodular communication in the cerebellum also have unique predictive power for levels of awareness. Consequently, we propose that the dynamic reorganisation of the functional information architecture, in particular of the subcortex, is a characteristic that emerges with awareness and has explanatory power beyond that of the complexity of dynamic functional connectivity.
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Affiliation(s)
- Peter Coppola
- Division of Anaesthesia, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Department of Clinical Neurosciences, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK
| | - Lennart R B Spindler
- Division of Anaesthesia, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Department of Clinical Neurosciences, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK
| | - Andrea I Luppi
- Division of Anaesthesia, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Department of Clinical Neurosciences, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK
| | - Ram Adapa
- Division of Anaesthesia, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Division of Neurosurgery, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Lloyd Building, Dublin 2, Ireland
| | - Judith Allanson
- Department of Clinical Neurosciences, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Department of Neurosciences, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation, Hills Rd., Cambridge, CB2 0QQ, UK
| | - Paola Finoia
- Division of Anaesthesia, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Division of Neurosurgery, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK
| | - Guy B Williams
- Department of Clinical Neurosciences, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus (Box 65), Cambridge CB2 0QQ, UK
| | - John D Pickard
- Department of Clinical Neurosciences, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Division of Neurosurgery, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus (Box 65), Cambridge CB2 0QQ, UK
| | - Adrian M Owen
- The Brain and Mind Institute, Western Interdisciplinary Research Building, University of Western Ontario, London, ON N6A 5B7, Canada
| | - David K Menon
- Division of Anaesthesia, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus (Box 65), Cambridge CB2 0QQ, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK; Department of Clinical Neurosciences, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Hills Rd., Cambridge CB2 0QQ, UK.
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Medina JP, Nigri A, Stanziano M, D’Incerti L, Sattin D, Ferraro S, Rossi Sebastiano D, Pinardi C, Marotta G, Leonardi M, Bruzzone MG, Rosazza C. Resting-State fMRI in Chronic Patients with Disorders of Consciousness: The Role of Lower-Order Networks for Clinical Assessment. Brain Sci 2022; 12:brainsci12030355. [PMID: 35326311 PMCID: PMC8946756 DOI: 10.3390/brainsci12030355] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/24/2022] [Accepted: 02/28/2022] [Indexed: 01/27/2023] Open
Abstract
Resting-state fMRI (rs-fMRI) is a widely used technique to investigate the residual brain functions of patients with Disorders of Consciousness (DoC). Nonetheless, it is unclear how the networks that are more associated with primary functions, such as the sensory–motor, medial/lateral visual and auditory networks, contribute to clinical assessment. In this study, we examined the rs-fMRI lower-order networks alongside their structural MRI data to clarify the corresponding association with clinical assessment. We studied 109 chronic patients with DoC and emerged from DoC with structural MRI and rs-fMRI: 65 in vegetative state/unresponsive wakefulness state (VS/UWS), 34 in minimally conscious state (MCS) and 10 with severe disability. rs-fMRI data were analyzed with independent component analyses and seed-based analyses, in relation to structural MRI and clinical data. The results showed that VS/UWS had fewer networks than MCS patients and the rs-fMRI activity in each network was decreased. Visual networks were correlated to the clinical status, and in cases where no clinical response occurred, rs-fMRI indicated distinctive networks conveying information in a similar way to other techniques. The information provided by single networks was limited, whereas the four networks together yielded better classification results, particularly when the model included rs-fMRI and structural MRI data (AUC = 0.80). Both quantitative and qualitative rs-fMRI analyses yielded converging results; vascular etiology might confound the results, and disease duration generally reduced the number of networks observed. The lower-order rs-fMRI networks could be used clinically to support and corroborate visual function assessments in DoC.
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Affiliation(s)
- Jean Paul Medina
- Neuroradiology Unit, Diagnostic and Technology Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (J.P.M.); (M.S.); (L.D.); (S.F.); (C.P.); (M.G.B.)
| | - Anna Nigri
- Neuroradiology Unit, Diagnostic and Technology Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (J.P.M.); (M.S.); (L.D.); (S.F.); (C.P.); (M.G.B.)
- Correspondence: (A.N.); (C.R.)
| | - Mario Stanziano
- Neuroradiology Unit, Diagnostic and Technology Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (J.P.M.); (M.S.); (L.D.); (S.F.); (C.P.); (M.G.B.)
- Neurosciences Department “Rita Levi Montalcini”, University of Turin, 10126 Turin, Italy
| | - Ludovico D’Incerti
- Neuroradiology Unit, Diagnostic and Technology Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (J.P.M.); (M.S.); (L.D.); (S.F.); (C.P.); (M.G.B.)
- Neuroradiology Unit, Children’s Hospital A. Meyer—University of Florence, 50139 Florence, Italy
| | - Davide Sattin
- IRCCS Istituti Clinici Scientifici Maugeri di Milano, 20138 Milan, Italy;
| | - Stefania Ferraro
- Neuroradiology Unit, Diagnostic and Technology Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (J.P.M.); (M.S.); (L.D.); (S.F.); (C.P.); (M.G.B.)
- MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Davide Rossi Sebastiano
- Epileptology Unit, Department of Neurophysiology and Diagnostic, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy;
| | - Chiara Pinardi
- Neuroradiology Unit, Diagnostic and Technology Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (J.P.M.); (M.S.); (L.D.); (S.F.); (C.P.); (M.G.B.)
- Medical Physics Unit, Asst Nord Milano, Sesto San Giovanni, 20099 Milan, Italy
| | - Giorgio Marotta
- Department of Nuclear Medicine, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy;
| | - Matilde Leonardi
- Neurology, Public Health, Disability Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy;
| | - Maria Grazia Bruzzone
- Neuroradiology Unit, Diagnostic and Technology Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (J.P.M.); (M.S.); (L.D.); (S.F.); (C.P.); (M.G.B.)
| | - Cristina Rosazza
- Neuroradiology Unit, Diagnostic and Technology Department, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (J.P.M.); (M.S.); (L.D.); (S.F.); (C.P.); (M.G.B.)
- Department of Humanistic Studies, University of Urbino Carlo Bo, 61029 Urbino, Italy
- Correspondence: (A.N.); (C.R.)
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Wu H, Qi Z, Wu X, Zhang J, Wu C, Huang Z, Zang D, Fogel S, Tanabe S, Hudetz AG, Northoff G, Mao Y, Qin P. Anterior precuneus related to the recovery of consciousness. Neuroimage Clin 2022; 33:102951. [PMID: 35134706 PMCID: PMC8856921 DOI: 10.1016/j.nicl.2022.102951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 01/22/2022] [Accepted: 01/25/2022] [Indexed: 11/28/2022]
Abstract
Degree centrality of anterior precuneus correlated with Glasgow Outcome Scale scores. Anterior precuneus was shown as a hub in multiple recoverable unconscious states. Anterior precuneus had similar connectivity pattern in recoverable unconscious states.
The neural mechanism that enables the recovery of consciousness in patients with unresponsive wakefulness syndrome (UWS) remains unclear. The aim of the current study is to characterize the cortical hub regions related to the recovery of consciousness. In the current fMRI study, voxel-wise degree centrality analysis was adopted to identify the cortical hubs related to the recovery of consciousness, for which a total of 27 UWS patients were recruited, including 13 patients who emerged from UWS (UWS-E), and 14 patients who remained in UWS (UWS-R) at least three months after the experiment performance. Furthermore, other recoverable unconscious states were adopted as validation groups, including three independent N3 sleep datasets (n = 12, 9, 9 respectively) and three independent anesthesia datasets (n = 27, 14, 6 respectively). Spatial similarity of the hub characteristic with the validation groups between the UWS-E and UWS-R was compared using the dice coefficient. Finally, with the cortical regions persistently shown as hubs across UWS-E and validation states, functional connectivity analysis was further performed to explore the connectivity patterns underlying the recovery of consciousness. The results identified four cortical hubs in the UWS-E, which showed significantly higher degree centrality for UWS-E than UWS-R, including the anterior precuneus, left inferior parietal lobule, left inferior frontal gyrus, and left middle frontal gyrus, of which the degree centrality value also positively correlated with the patients’ Glasgow Outcome Scale (GOS) score that assessed global brain functioning outcome after a brain injury. Furthermore, the anterior precuneus was found with significantly higher similarity of hub characteristics as well as functional connectivity patterns between UWS-E and the validation groups. The results suggest that the recovery of consciousness may be relevant to the integrity of cortical hubs in the recoverable unconscious states, especially the anterior precuneus. The identified cortical hub regions could serve as potential treatment targets for patients with UWS.
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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
| | - Zengxin Qi
- 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
| | - Xuehai Wu
- 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; Pazhou Lab, Guangzhou 510335, China
| | - Jun Zhang
- Department of Anesthesiology, Fudan University Shanghai Cancer Center Shanghai, 200433, China
| | - Changwei Wu
- Research Center for Brain and Consciousness, Taipei Medical University, Taipei 11031, Taiwan; Graduate Institute of Humanities in Medicine, Taipei Medical University, Taipei 11031, Taiwan; Shuang-Ho Hospital, Taipei Medical University, New Taipei 23561, Taiwan
| | - Zirui Huang
- Department of Anesthesiology and Center for Consciousness Science, University of Michigan, Ann Arbor, MI 48105, USA
| | - Di Zang
- 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
| | - Stuart Fogel
- School of Psychology, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Sean Tanabe
- Department of Anesthesiology and Center for Consciousness Science, University of Michigan, Ann Arbor, MI 48105, USA
| | - Anthony G Hudetz
- Department of Anesthesiology and Center for Consciousness Science, University of Michigan, Ann Arbor, MI 48105, USA
| | - Georg Northoff
- Institute of Mental Health Research, University of Ottawa, Ottawa, Ontario, ON K1Z 7K4, Canada; Mental Health Centre, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Ying Mao
- 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.
| | - 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 510335, China.
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Bagnato S. The role of plasticity in the recovery of consciousness. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:375-395. [PMID: 35034750 DOI: 10.1016/b978-0-12-819410-2.00020-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Disorders of consciousness (DOCs), i.e., coma, vegetative state, and minimally conscious state are the consequences of a severe brain injury that disrupts the brain ability to generate consciousness. Recovery from DOCs requires functional and structural changes in the brain. The sites where these plastic changes take place vary according to the pathophysiology of the DOC. The ascending reticular activating system of the brainstem and its complex connections with the thalamus and cortex are involved in the pathophysiology of coma. Subcortical structures, such as the striatum and globus pallidus, together with thalamocortical and corticothalamic projections, the basal forebrain, and several networks among different cortical areas are probably involved in vegetative and minimally conscious states. Some mechanisms of plasticity that allegedly operate in each of these sites to promote recovery of consciousness will be discussed in this chapter. While some mechanisms of plasticity work at a local level, others produce functional changes in complex neuronal networks, for example by entraining neuronal oscillations. The specific mechanisms of brain plasticity represent potential targets for future treatments aiming to restore consciousness in patients with severe DOCs.
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Affiliation(s)
- Sergio Bagnato
- Unit of Neurophysiology and Unit for Severe Acquired Brain Injuries, Rehabilitation Department, Giuseppe Giglio Foundation, Cefalù (PA), Italy.
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Porcaro C, Nemirovsky IE, Riganello F, Mansour Z, Cerasa A, Tonin P, Stojanoski B, Soddu A. Diagnostic Developments in Differentiating Unresponsive Wakefulness Syndrome and the Minimally Conscious State. Front Neurol 2022; 12:778951. [PMID: 35095725 PMCID: PMC8793804 DOI: 10.3389/fneur.2021.778951] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/08/2021] [Indexed: 12/12/2022] Open
Abstract
When treating patients with a disorder of consciousness (DOC), it is essential to obtain an accurate diagnosis as soon as possible to generate individualized treatment programs. However, accurately diagnosing patients with DOCs is challenging and prone to errors when differentiating patients in a Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) from those in a Minimally Conscious State (MCS). Upwards of ~40% of patients with a DOC can be misdiagnosed when specifically designed behavioral scales are not employed or improperly administered. To improve diagnostic accuracy for these patients, several important neuroimaging and electrophysiological technologies have been proposed. These include Positron Emission Tomography (PET), functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), and Transcranial Magnetic Stimulation (TMS). Here, we review the different ways in which these techniques can improve diagnostic differentiation between VS/UWS and MCS patients. We do so by referring to studies that were conducted within the last 10 years, which were extracted from the PubMed database. In total, 55 studies met our criteria (clinical diagnoses of VS/UWS from MCS as made by PET, fMRI, EEG and TMS- EEG tools) and were included in this review. By summarizing the promising results achieved in understanding and diagnosing these conditions, we aim to emphasize the need for more such tools to be incorporated in standard clinical practice, as well as the importance of data sharing to incentivize the community to meet these goals.
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Affiliation(s)
- Camillo Porcaro
- Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy
- Institute of Cognitive Sciences and Technologies (ISTC)–National Research Council (CNR), Rome, Italy
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom
- *Correspondence: Camillo Porcaro ; orcid.org/0000-0003-4847-163X
| | - Idan Efim Nemirovsky
- Department of Physics and Astronomy, Brain and Mind Institute, University of Western Ontario, London, ON, Canada
| | - Francesco Riganello
- Sant'Anna Institute and Research in Advanced Neurorehabilitation (RAN), Crotone, Italy
| | - Zahra Mansour
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
| | - Antonio Cerasa
- Sant'Anna Institute and Research in Advanced Neurorehabilitation (RAN), Crotone, Italy
- Institute for Biomedical Research and Innovation (IRIB), National Research Council, Messina, Italy
- Pharmacotechnology Documentation and Transfer Unit, Preclinical and Translational Pharmacology, Department of Pharmacy, Health Science and Nutrition, University of Calabria, Rende, Italy
| | - Paolo Tonin
- Sant'Anna Institute and Research in Advanced Neurorehabilitation (RAN), Crotone, Italy
| | - Bobby Stojanoski
- Faculty of Social Science and Humanities, University of Ontario Institute of Technology, Oshawa, ON, Canada
- Department of Psychology, Brain and Mind Institute, University of Western Ontario, London, ON, Canada
| | - Andrea Soddu
- Department of Physics and Astronomy, Brain and Mind Institute, University of Western Ontario, London, ON, Canada
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Wang H, Han X, Li M, Yang ZH, Liu WH, Wang ZC. Long-term hemodialysis may affect enlarged perivascular spaces in maintenance hemodialysis patients: evidence from a pilot MRI study. Quant Imaging Med Surg 2022; 12:341-353. [PMID: 34993083 DOI: 10.21037/qims-20-1246] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Accepted: 06/23/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND Hemodialysis (HD) causes various nervous system abnormalities. Alterations in white matter (WM) microstructure after long-term HD have been reported in a few previous studies; however, no studies have been performed to investigate enlarged perivascular spaces (PVS) in WM regions. We measured cerebral blood flow (CBF) and white matter volume (WMV) in HD patients to assess enlarged PVS severity in the WM across the whole brain and suggest possible explanations for this. METHODS Fifty-one HD patients and 51 age-, sex-, and education-matched healthy controls (HCs) were recruited. The number of enlarged PVS in the centrum semiovale (CS), cerebral watershed (CW), and basal ganglia (BG) regions were assessed by T2-weighted MRI. CBF was estimated by arterial spin labeling (ASL), which is a non-invasive perfusion imaging technique. WMV was assessed by the computational anatomy toolbox (CAT12), which is a statistical analysis package. Differences in descriptive variables (two-tailed t-tests, χ2 tests, Mann-Whitney U tests, and Friedman M tests), an intra-class correlation between radiologists, the relationship between enlarged PVS number and HD duration, normalized CBF and WMV (multiple regression), and group differences in CBF and WMV {voxel-wise t-tests with age and sex as covariates [cluster size >50 voxels, false discovery rate (FDR) corrected, P<0.05]} were assessed. RESULTS HD patients displayed a more significant number of CS-PVS and CW-PVS in WM regions compared with the HCs, but there was no significant difference in the number of BG-PVS. The number of CS-PVS and CW-PVS were positively associated with HD duration. The number of CW-PVS was positively associated with CBF changes and WMV alteration in HD patients. Meanwhile, significant differences in the blood pressure (BP) readings pre-HD, intra-HD, and post-HD were observed in HD patients. Compared with the HCs, the HD patients showed higher CBF in the CS, CW, and BG regions (P<0.05). Hence, decreased WMV in the CS, CW, and BG regions were shown in the HD patients compared with the HCs (P<0.05). CONCLUSIONS Enlarged CS-PVS and CW-PVS on MRI might be a feature of long-term HD patients. Enlarged CW-PVS number is associated with higher CBF in the CW region and lower WMV in the CW region in HD patients.
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Affiliation(s)
- Hao Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xue Han
- Department of Nephrology, Faculty of Kidney Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Mingan Li
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zheng-Han Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Wen-Hu Liu
- Department of Nephrology, Faculty of Kidney Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhen-Chang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
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Qureshi AY, Stevens RD. Mapping the Unconscious Brain: Insights From Advanced Neuroimaging. J Clin Neurophysiol 2022; 39:12-21. [PMID: 34474430 DOI: 10.1097/wnp.0000000000000846] [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: 01/18/2023] Open
Abstract
SUMMARY Recent advances in neuroimaging have been a preeminent factor in the scientific effort to unravel mechanisms of conscious awareness and the pathophysiology of disorders of consciousness. In the first part of this review, we selectively discuss operational models of consciousness, the biophysical signal that is measured using different imaging modalities, and knowledge on disorders of consciousness that has been gleaned with each neuroimaging modality. Techniques considered include diffusion-weighted imaging, diffusion tensor imaging, different types of nuclear medicine imaging, functional MRI, magnetoencephalography, and the combined transcranial magnetic stimulation-electroencephalography approach. In the second part of this article, we provide an overview of how advanced neuroimaging can be leveraged to support neurological prognostication, the use of machine learning to process high-dimensional imaging data, potential applications in clinical practice, and future directions.
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Affiliation(s)
- Abid Y Qureshi
- Department of Neurology, University of Kansas Medical Center, Kansas City, Missouri, U.S.A.; and
| | - Robert D Stevens
- Departments of Anesthesiology and Critical Care, Neurology, Radiology, and Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, U.S.A
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Serban CA, Barborica A, Roceanu AM, Mindruta I, Ciurea J, Pâslaru AC, Zăgrean AM, Zăgrean L, Moldovan M. A method to assess the default EEG macrostate and its reactivity to stimulation. Clin Neurophysiol 2021; 134:50-64. [PMID: 34973517 DOI: 10.1016/j.clinph.2021.12.002] [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: 02/07/2021] [Revised: 08/23/2021] [Accepted: 12/04/2021] [Indexed: 11/16/2022]
Abstract
OBJECTIVE The default mode network (DMN) is deactivated by stimulation. We aimed to assess the DMN reactivity impairment by routine EEG recordings in stroke patients with impaired consciousness. METHODS Binocular light flashes were delivered at 1 Hz in 1-minute epochs, following a 1-minute baseline (PRE). The EEG was decomposed in a series of binary oscillatory macrostates by topographic spectral clustering. The most deactivated macrostate was labeled the default EEG macrostate (DEM). Its reactivity (DER) was quantified as the decrease in DEM occurrence probability during stimulation. A normalized DER index (DERI) was calculated as DER/PRE. The measures were compared between 14 healthy controls and 32 comatose patients under EEG monitoring following an acute stroke. RESULTS The DEM was mapped to the posterior DMN hubs. In the patients, these DEM source dipoles were 3-4 times less frequent and were associated with an increased theta activity. Even in a reduced 6-channel montage, a DER below 6.26% corresponding to a DERI below 0.25 could discriminate the patients with sensitivity and specificity well above 80%. CONCLUSION The method detected the DMN impairment in post-stroke coma patients. SIGNIFICANCE The DEM and its reactivity to stimulation could be useful to monitor the DMN function at bedside.
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Affiliation(s)
- Cosmin-Andrei Serban
- Physics Department, University of Bucharest, Romania; Termobit Prod SRL, Bucharest, Romania; FHC Inc, Bowdoin, ME, USA.
| | - Andrei Barborica
- Physics Department, University of Bucharest, Romania; Termobit Prod SRL, Bucharest, Romania; FHC Inc, Bowdoin, ME, USA.
| | | | - Ioana Mindruta
- Neurology Department, University Emergency Hospital, Bucharest, Romania.
| | - Jan Ciurea
- Department of Neurosurgery, Bagdasar-Arseni Emergency Hospital, Bucharest, Romania.
| | - Alexandru C Pâslaru
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Ana-Maria Zăgrean
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Leon Zăgrean
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Mihai Moldovan
- Termobit Prod SRL, Bucharest, Romania; Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania; Neuroscience, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Neurophysiology, Rigshospitalet, Copenhagen, Denmark.
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