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      Human consciousness is supported by dynamic complex patterns of brain signal coordination

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          Abstract

          Dynamic patterns of brain activity at rest distinguish conscious and unconscious states in humans.

          Abstract

          Adopting the framework of brain dynamics as a cornerstone of human consciousness, we determined whether dynamic signal coordination provides specific and generalizable patterns pertaining to conscious and unconscious states after brain damage. A dynamic pattern of coordinated and anticoordinated functional magnetic resonance imaging signals characterized healthy individuals and minimally conscious patients. The brains of unresponsive patients showed primarily a pattern of low interareal phase coherence mainly mediated by structural connectivity, and had smaller chances to transition between patterns. The complex pattern was further corroborated in patients with covert cognition, who could perform neuroimaging mental imagery tasks, validating this pattern’s implication in consciousness. Anesthesia increased the probability of the less complex pattern to equal levels, validating its implication in unconsciousness. Our results establish that consciousness rests on the brain’s ability to sustain rich brain dynamics and pave the way for determining specific and generalizable fingerprints of conscious and unconscious states.

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          Most cited references34

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          Individual variability in functional connectivity architecture of the human brain.

          The fact that people think or behave differently from one another is rooted in individual differences in brain anatomy and connectivity. Here, we used repeated-measurement resting-state functional MRI to explore intersubject variability in connectivity. Individual differences in functional connectivity were heterogeneous across the cortex, with significantly higher variability in heteromodal association cortex and lower variability in unimodal cortices. Intersubject variability in connectivity was significantly correlated with the degree of evolutionary cortical expansion, suggesting a potential evolutionary root of functional variability. The connectivity variability was also related to variability in sulcal depth but not cortical thickness, positively correlated with the degree of long-range connectivity but negatively correlated with local connectivity. A meta-analysis further revealed that regions predicting individual differences in cognitive domains are predominantly located in regions of high connectivity variability. Our findings have potential implications for understanding brain evolution and development, guiding intervention, and interpreting statistical maps in neuroimaging. Copyright © 2013 Elsevier Inc. All rights reserved.
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            The JFK Coma Recovery Scale-Revised: measurement characteristics and diagnostic utility.

            To determine the measurement properties and diagnostic utility of the JFK Coma Recovery Scale-Revised (CRS-R). Analysis of interrater and test-retest reliability, internal consistency, concurrent validity, and diagnostic accuracy. Acute inpatient brain injury rehabilitation hospital. Convenience sample of 80 patients with severe acquired brain injury admitted to an inpatient Coma Intervention Program with a diagnosis of either vegetative state (VS) or minimally conscious state (MCS). Not applicable. The CRS-R, the JFK Coma Recovery Scale (CRS), and the Disability Rating Scale (DRS). Interrater and test-retest reliability were high for CRS-R total scores. Subscale analysis showed moderate to high interrater and test-retest agreement although systematic differences in scoring were noted on the visual and oromotor/verbal subscales. CRS-R total scores correlated significantly with total scores on the CRS and DRS indicating acceptable concurrent validity. The CRS-R was able to distinguish 10 patients in an MCS who were otherwise misclassified as in a VS by the DRS. The CRS-R can be administered reliably by trained examiners and repeated measurements yield stable estimates of patient status. CRS-R subscale scores demonstrated good agreement across raters and ratings but should be used cautiously because some scores were underrepresented in the current study. The CRS-R appears capable of differentiating patients in an MCS from those in a VS.
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              Willful modulation of brain activity in disorders of consciousness.

              The differential diagnosis of disorders of consciousness is challenging. The rate of misdiagnosis is approximately 40%, and new methods are required to complement bedside testing, particularly if the patient's capacity to show behavioral signs of awareness is diminished. At two major referral centers in Cambridge, United Kingdom, and Liege, Belgium, we performed a study involving 54 patients with disorders of consciousness. We used functional magnetic resonance imaging (MRI) to assess each patient's ability to generate willful, neuroanatomically specific, blood-oxygenation-level-dependent responses during two established mental-imagery tasks. A technique was then developed to determine whether such tasks could be used to communicate yes-or-no answers to simple questions. Of the 54 patients enrolled in the study, 5 were able to willfully modulate their brain activity. In three of these patients, additional bedside testing revealed some sign of awareness, but in the other two patients, no voluntary behavior could be detected by means of clinical assessment. One patient was able to use our technique to answer yes or no to questions during functional MRI; however, it remained impossible to establish any form of communication at the bedside. These results show that a small proportion of patients in a vegetative or minimally conscious state have brain activation reflecting some awareness and cognition. Careful clinical examination will result in reclassification of the state of consciousness in some of these patients. This technique may be useful in establishing basic communication with patients who appear to be unresponsive. 2010 Massachusetts Medical Society
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                Author and article information

                Journal
                Sci Adv
                Sci Adv
                SciAdv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                February 2019
                06 February 2019
                : 5
                : 2
                : eaat7603
                Affiliations
                [1 ]GIGA-Consciousness, GIGA Institute B34, University of Liège, Avenue de l’Hôpital, 11, 4000 Sart Tilman, Belgium.
                [2 ]INSERM, U 1127, F-75013 Paris, France.
                [3 ]Institut du Cerveau et de la Moelle Epinière, Hôpital Pitié-Salpêtrière, 47 bd de l’Hôpital, 75013 Paris, France.
                [4 ]Instituto de Física de Buenos Aires and Physics Deparment (University of Buenos Aires), Buenos Aires, Argentina.
                [5 ]Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Sud, Université Paris-Saclay, F-91191 Gif/Yvette, France.
                [6 ]Collège de France, 11, Place Marcelin Berthelot, 75005 Paris, France.
                [7 ]Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Calle Ramon Trias Fargas 25-27, Barcelona 08005, Spain.
                [8 ]Institucio Catalana de la Recerca I Estudis Avancats (ICREA), University of Pompeu Fabra, Passeig Lluis Companys 23, Barcelona 08010, Spain.
                [9 ]Laboratory of Integrative Neuroscience, Physics Department, FCEyN UBA and IFIBA, CONICET, Pabellón 1, Ciudad Universitaria, 1428 Buenos Aires, Argentina.
                [10 ]Department of Computer Science, Faculty of Exact and Natural Sciences, Intendente Güiraldes 2160–Ciudad Universitaria–C1428EGA, University of Buenos Aires, Argentina.
                [11 ]Sorbonne Universités, UPMC Université Paris 06, Faculté de Médecine Pitié-Salpêtrière, 91-105 bd de l’Hôpital, 75013 Paris, France.
                [12 ]CONICET–Universidad de Buenos Aires, Instituto de Investigación en Ciencias de la Computación, Godoy Cruz 2290, C1425FQB Ciudad Autónoma de Buenos Aires, Argentina.
                [13 ]Centre for Human Brain Health, University of Birmingham, B15 2TT Birmingham, UK.
                [14 ]School of Psychology, University of Birmingham, B15 2TT, Birmingham, UK.
                [15 ]The Brain and Mind Institute, Western Interdisciplinary Research Building, N6A 5B7 University of Western Ontario, London, Ontario, Canada.
                [16 ]Department of Neurology, Columbia University, 710 West 168th Street, New York, NY 10032-3784, USA.
                [17 ]Radiology Department, Citigroup Biomedical Imaging Center, Weill Cornell Medical College, 516 E. 72nd Street, New York, NY 10021, USA.
                [18 ]Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA.
                Author notes
                [†]

                These authors contributed equally to this work.

                [‡]

                Present address: Instituto de Investigaciones Psicológicas (IIPSI) CONICET, Enfermera Gordillo s/n, Córdoba, Argentina.

                Author information
                http://orcid.org/0000-0001-8021-3759
                http://orcid.org/0000-0003-0421-9993
                http://orcid.org/0000-0002-7418-8275
                http://orcid.org/0000-0003-4087-8259
                http://orcid.org/0000-0001-6291-3460
                http://orcid.org/0000-0001-5941-7546
                http://orcid.org/0000-0001-6752-8756
                http://orcid.org/0000-0003-2811-2074
                http://orcid.org/0000-0003-0008-426X
                http://orcid.org/0000-0002-2874-1009
                Article
                aat7603
                10.1126/sciadv.aat7603
                6365115
                30775433
                9802cef0-970d-4858-aaa8-2146e40b7fb5
                Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

                History
                : 05 April 2018
                : 19 December 2018
                Funding
                Funded by: doi http://dx.doi.org/10.13039/100000913, James S. McDonnell Foundation;
                Award ID: Phase I & II; 2008-2017
                Funded by: doi http://dx.doi.org/10.13039/501100000780, European Commission;
                Award ID: EU-H2020-FETFLAGSHIP-HBP-SGA1-GA720270
                Funded by: doi http://dx.doi.org/10.13039/501100000780, European Commission;
                Award ID: EU-H2020-fetopen-ga686764
                Funded by: doi http://dx.doi.org/10.13039/501100000780, European Commission;
                Award ID: FP7-HEALTH- 602150
                Categories
                Research Article
                Research Articles
                SciAdv r-articles
                Cognitive Neuroscience
                Neuroscience
                Cognitive Neuroscience
                Custom metadata
                Nielsen Marquez

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