Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state
Jacobo Diego Sitta b c d, Jean-Rémi Kinga b c d, Imen El Karouic e, Benjamin Rohautc f g, Frédéric Faugerasc h i, Alexandre Gramfortd j k, Laurent Cohenc f g, Mariano Sigmanl m n, Stanislas Dehaeneb d o p q, Lionel Naccachec h i
- a1 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
- bCognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale, U992, F-91191 Gif/Yvette, France
- cInserm 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
- dNeuroSpin Centre, Institute of BioImaging Commissariat à l'Energie Atomique, F-91191 Gif/Yvette, France
- e3 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
- f3 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
Papers open inside SciRah from the original publisher or repository; SciRah never hosts them.
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.