4.7 Article

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

期刊

BRAIN
卷 137, 期 -, 页码 2258-2270

出版社

OXFORD UNIV PRESS
DOI: 10.1093/brain/awu141

关键词

consciousness; vegetative state; unresponsive wakefulness syndrome; minimally conscious state; EEG

资金

  1. INSERM
  2. CEA
  3. ERC
  4. Spoelbech foundation
  5. James S. McDonnell Foundation
  6. Fondation pour la Recherche Medicale (FRM)
  7. Institut pour le Cerveau et la Moelle epiniere (ICM Institute, Paris, France)
  8. program Investissements d'avenir'' [ANR-10-IAIHU-06]
  9. A-HP
  10. Direction Generale de l'Armement (DGA)
  11. Stic-Amsud grant 'RTBRAIN'
  12. James McDonell Foundation 21st Century Science Initiative in Understanding Human Cognition-Scholar Award
  13. AXA Research Fund

向作者/读者索取更多资源

What are the neural signatures of consciousness? Sitt et al. assess the suitability of putative electrophysiological markers of consciousness for distinguishing patients in a vegetative state from those in a minimally conscious or conscious state. Low-frequency power, EEG complexity, and information exchange constitute reliable, partially independent, markers 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.

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