Critical dynamics in spontaneous EEG predict anesthetic-induced loss of consciousness and perturbational complexity
Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigate dynamical properties of the resting-state electroencephalogram (EEG) of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. Importantly, all participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams), enabling an experimental dissociation between unresponsiveness and unconsciousness. For each condition, we measure (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related metrics, revealing that states of unconsciousness are characterized by a distancing from both avalanche criticality and the edge of chaos. We then ask whether these same dynamical properties are predictive of the perturbational complexity index (PCI), a TMS-based measure that has shown remarkably high sensitivity in detecting consciousness independently of behavior. We successfully predict individual subjects' PCI values with considerably high accuracy from resting-state EEG dynamical properties alone. Our results establish a firm link between perturbational complexity and criticality, and provide further evidence that criticality is a necessary condition for the emergence of consciousness.
Authors
- Olivia Gosseries (ORCID: https://orcid.org/0000-0001-9011-7496)
- Steven Laureys (ORCID: https://orcid.org/0000-0002-3096-3807)
- Charlotte Maschke (ORCID: https://orcid.org/0000-0002-6105-8471)
- Mario Rosanova (ORCID: https://orcid.org/0000-0001-7486-7617)
- Jordan O’Byrne (ORCID: https://orcid.org/0000-0002-4924-4220)
- Karim Jerbi (ORCID: https://orcid.org/0000-0002-3790-9651)
- Stefanie Blain‐Moraes (ORCID: https://orcid.org/0000-0001-7837-6700)
- Mélanie Boly (ORCID: https://orcid.org/0000-0001-9584-0907)
- Michele Colombo
Institutions
- University of Wisconsin–Madison (US)
- University of Liège (BE)
- Hangzhou Normal University (CN)
- University of Milan (IT)
- Montreal General Hospital (CA)
- McGill University Health Centre (CA)
- Mila - Quebec Artificial Intelligence Institute (CA)
- Artificial Intelligence in Medicine (Canada) (CA)
- Université Laval (CA)
- McGill University (CA)
- Université de Montréal (CA)
Publication Details
- Journal
- Communications Biology
- Published
- 2024-08-05
- DOI
- https://doi.org/10.1038/s42003-024-06613-8
- Citations
- 39
- Primary Topic
- Neural dynamics and brain function
- Type
- article
- Field-Weighted Citation Impact
- 13.37
Funders
- McGill University
- Canada Research Chairs
- Fonds De La Recherche Scientifique - FNRS
- Canada Excellence Research Chairs, Government of Canada
- Fondazione Europea Ricerca Biomedica
- Regione Lombardia
- Canada First Research Excellence Fund
- Institut de Valorisation des Données
- Fondazione Regionale per la Ricerca Biomedica
- Canadian Institutes of Health Research
- Natural Sciences and Engineering Research Council of Canada
- Fonds de Recherche du Québec - Santé
- Fonds de recherche du Québec – Nature et technologies
- National Institute of Neurological Disorders and Stroke