Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state

In recent years, numerous electrophysiological signatures of consciousness have been proposed. Here, we perform a systematic analysis of these electroencephalography markers by quantifying their efficiency in differentiating patients in a vegetative state from those in a minimally conscious or consc...

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Vydané v:Brain (London, England : 1878) Ročník 137; číslo Pt 8; s. 2258
Hlavní autori: Sitt, Jacobo Diego, King, Jean-Remi, El Karoui, Imen, Rohaut, Benjamin, Faugeras, Frederic, Gramfort, Alexandre, Cohen, Laurent, Sigman, Mariano, Dehaene, Stanislas, Naccache, Lionel
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England 01.08.2014
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ISSN:1460-2156, 1460-2156
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Abstract In recent years, numerous electrophysiological signatures of consciousness have been proposed. Here, we perform a systematic analysis of these electroencephalography markers by quantifying their efficiency in differentiating patients in a vegetative state from those in a minimally conscious or conscious state. Capitalizing on a review of previous experiments and current theories, we identify a series of measures that can be organized into four dimensions: (i) event-related potentials versus ongoing electroencephalography activity; (ii) local dynamics versus inter-electrode information exchange; (iii) spectral patterns versus information complexity; and (iv) average versus fluctuations over the recording session. We analysed a large set of 181 high-density electroencephalography recordings acquired in a 30 minutes protocol. We show that low-frequency power, electroencephalography complexity, and information exchange constitute the most reliable signatures of the conscious state. When combined, these measures synergize to allow an automatic classification of patients' state of consciousness.
AbstractList In recent years, numerous electrophysiological signatures of consciousness have been proposed. Here, we perform a systematic analysis of these electroencephalography markers by quantifying their efficiency in differentiating patients in a vegetative state from those in a minimally conscious or conscious state. Capitalizing on a review of previous experiments and current theories, we identify a series of measures that can be organized into four dimensions: (i) event-related potentials versus ongoing electroencephalography activity; (ii) local dynamics versus inter-electrode information exchange; (iii) spectral patterns versus information complexity; and (iv) average versus fluctuations over the recording session. We analysed a large set of 181 high-density electroencephalography recordings acquired in a 30 minutes protocol. We show that low-frequency power, electroencephalography complexity, and information exchange constitute the most reliable signatures of the conscious state. When combined, these measures synergize to allow an automatic classification of patients' state of consciousness.In recent years, numerous electrophysiological signatures of consciousness have been proposed. Here, we perform a systematic analysis of these electroencephalography markers by quantifying their efficiency in differentiating patients in a vegetative state from those in a minimally conscious or conscious state. Capitalizing on a review of previous experiments and current theories, we identify a series of measures that can be organized into four dimensions: (i) event-related potentials versus ongoing electroencephalography activity; (ii) local dynamics versus inter-electrode information exchange; (iii) spectral patterns versus information complexity; and (iv) average versus fluctuations over the recording session. We analysed a large set of 181 high-density electroencephalography recordings acquired in a 30 minutes protocol. We show that low-frequency power, electroencephalography complexity, and information exchange constitute the most reliable signatures of the conscious state. When combined, these measures synergize to allow an automatic classification of patients' state of consciousness.
In recent years, numerous electrophysiological signatures of consciousness have been proposed. Here, we perform a systematic analysis of these electroencephalography markers by quantifying their efficiency in differentiating patients in a vegetative state from those in a minimally conscious or conscious state. Capitalizing on a review of previous experiments and current theories, we identify a series of measures that can be organized into four dimensions: (i) event-related potentials versus ongoing electroencephalography activity; (ii) local dynamics versus inter-electrode information exchange; (iii) spectral patterns versus information complexity; and (iv) average versus fluctuations over the recording session. We analysed a large set of 181 high-density electroencephalography recordings acquired in a 30 minutes protocol. We show that low-frequency power, electroencephalography complexity, and information exchange constitute the most reliable signatures of the conscious state. When combined, these measures synergize to allow an automatic classification of patients' state of consciousness.
Author Sitt, Jacobo Diego
Dehaene, Stanislas
Gramfort, Alexandre
Sigman, Mariano
Faugeras, Frederic
Naccache, Lionel
Rohaut, Benjamin
King, Jean-Remi
El Karoui, Imen
Cohen, Laurent
Author_xml – sequence: 1
  givenname: Jacobo Diego
  surname: Sitt
  fullname: Sitt, Jacobo Diego
  email: jdsitt@gmail.com, jeanremi.king@gmail.com
  organization: 1 Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale, U992, F-91191 Gif/Yvette, France2 NeuroSpin Centre, Institute of BioImaging Commissariat à l'Energie Atomique, F-91191 Gif/Yvette, France3 Inserm U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013, Paris, France jdsitt@gmail.com jeanremi.king@gmail.com
– sequence: 2
  givenname: Jean-Remi
  surname: King
  fullname: King, Jean-Remi
  email: jdsitt@gmail.com, jeanremi.king@gmail.com
  organization: 1 Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale, U992, F-91191 Gif/Yvette, France2 NeuroSpin Centre, Institute of BioImaging Commissariat à l'Energie Atomique, F-91191 Gif/Yvette, France3 Inserm U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013, Paris, France jdsitt@gmail.com jeanremi.king@gmail.com
– sequence: 3
  givenname: Imen
  surname: El Karoui
  fullname: El Karoui, Imen
  organization: 3 Inserm U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013, Paris, France
– sequence: 4
  givenname: Benjamin
  surname: Rohaut
  fullname: Rohaut, Benjamin
  organization: 3 Inserm U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013, Paris, France4 AP-HP, Groupe hospitalier Pitié-Salpêtrière, Department of Neurology, Intensive Care Unit, Paris, France
– sequence: 5
  givenname: Frederic
  surname: Faugeras
  fullname: Faugeras, Frederic
  organization: 3 Inserm U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013, Paris, France5 AP-HP, Groupe hospitalier Pitié-Salpêtrière, Department of Neurophysiology, Paris, France
– sequence: 6
  givenname: Alexandre
  surname: Gramfort
  fullname: Gramfort, Alexandre
  organization: 2 NeuroSpin Centre, Institute of BioImaging Commissariat à l'Energie Atomique, F-91191 Gif/Yvette, France6 Institut Mines-Télécom, Télécom ParisTech, CNRS LTCI, France
– sequence: 7
  givenname: Laurent
  surname: Cohen
  fullname: Cohen, Laurent
  organization: 3 Inserm U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013, Paris, France4 AP-HP, Groupe hospitalier Pitié-Salpêtrière, Department of Neurology, Intensive Care Unit, Paris, France
– sequence: 8
  givenname: Mariano
  surname: Sigman
  fullname: Sigman, Mariano
  organization: 7 Integrative Neuroscience Laboratory, Physics Department, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina8 Universidad Torcuato Di Tella, Almirante Juan Saenz Valiente 1010, C1428BIJ Buenos Aires, Argentina
– sequence: 9
  givenname: Stanislas
  surname: Dehaene
  fullname: Dehaene, Stanislas
  organization: 1 Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale, U992, F-91191 Gif/Yvette, France2 NeuroSpin Centre, Institute of BioImaging Commissariat à l'Energie Atomique, F-91191 Gif/Yvette, France9 Université Paris 11, Orsay, France10 Collège de France, F-75005 Paris, France
– sequence: 10
  givenname: Lionel
  surname: Naccache
  fullname: Naccache, Lionel
  organization: 3 Inserm U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013, Paris, France5 AP-HP, Groupe hospitalier Pitié-Salpêtrière, Department of Neurophysiology, Paris, France
BackLink https://www.ncbi.nlm.nih.gov/pubmed/24919971$$D View this record in MEDLINE/PubMed
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Keywords unresponsive wakefulness syndrome
consciousness
EEG
minimally conscious state
vegetative state
Language English
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PublicationTitle Brain (London, England : 1878)
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Snippet In recent years, numerous electrophysiological signatures of consciousness have been proposed. Here, we perform a systematic analysis of these...
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StartPage 2258
SubjectTerms Adolescent
Adult
Aged
Aged, 80 and over
Biomarkers
Brain - physiopathology
Brain Mapping - classification
Brain Mapping - methods
Brain Mapping - standards
Clinical Protocols
Consciousness Disorders - classification
Consciousness Disorders - etiology
Consciousness Disorders - physiopathology
Electroencephalography - classification
Electroencephalography - methods
Electroencephalography - standards
Evoked Potentials - physiology
Female
Humans
Male
Middle Aged
Persistent Vegetative State - classification
Persistent Vegetative State - etiology
Persistent Vegetative State - physiopathology
Trauma Severity Indices
Young Adult
Title Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state
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