[en] The self-organising global dynamics underlying brain states emerge from complex recursive nonlinear interactions between interconnected brain regions. Until now, most efforts of capturing the causal mechanistic generating principles have supposed underlying stationarity, being unable to describe the non-stationarity of brain dynamics, i.e. time-dependent changes. Here, we present a novel framework able to characterise brain states with high specificity, precisely by modelling the time-dependent dynamics. Through describing a topological structure associated to the brain state at each moment in time (its attractor or 'information structure'), we are able to classify different brain states by using the statistics across time of these structures hitherto hidden in the neuroimaging dynamics. Proving the strong potential of this framework, we were able to classify resting-state BOLD fMRI signals from two classes of post-comatose patients (minimally conscious state and unresponsive wakefulness syndrome) compared with healthy controls with very high precision.
Disciplines :
Neurosciences & behavior
Author, co-author :
Soler-Toscano, Fernando ; Grupo de Lógica, Lenguaje e Información, Universidad de Sevilla, Seville, Spain.
Galadí, Javier A ; Departamento de Ecuaciones Diferenciales y Análisis Numérico, Universidad de ; Computational Neuroscience Group, Center for Brain and Cognition, Universitat
Escrichs, Anira ; Computational Neuroscience Group, Center for Brain and Cognition, Universitat
Sanz Perl, Yonatan ; Computational Neuroscience Group, Center for Brain and Cognition, Universitat ; Institut du Cerveau et de la Moelle épinière, ICM Paris, Paris, France. ; Universidad de San Andrés, Buenos Aires, Argentina.
López-González, Ane ; Computational Neuroscience Group, Center for Brain and Cognition, Universitat
Sitt, Jacobo D; Institut du Cerveau et de la Moelle épinière, ICM Paris, Paris, France. ; Inserm U 1127, Paris, France. ; CNRS UMR 7225, Paris, France.
Annen, Jitka ; Université de Liège - ULiège > GIGA > GIGA Consciousness - Coma Science Group
Gosseries, Olivia ; Université de Liège - ULiège > GIGA > GIGA Consciousness - Coma Science Group
Thibaut, Aurore ; Université de Liège - ULiège > GIGA > GIGA Consciousness - Coma Science Group
Panda, Rajanikant ; Université de Liège - ULiège > GIGA > GIGA Consciousness - Coma Science Group
Esteban, Francisco J ; Departamento de Biología Experimental, Universidad de Jaén, Jaén, Spain.
Laureys, Steven ; Centre Hospitalier Universitaire de Liège - CHU > > Centre du Cerveau²
Kringelbach, Morten L ; Centre for Eudaimonia and Human Flourishing, Linacre College, University of ; Department of Psychiatry, University of Oxford, Oxford, United Kingdom. ; Center for Music in the Brain, Department of Clinical Medicine, Aarhus
Langa, José A ; Departamento de Ecuaciones Diferenciales y Análisis Numérico, Universidad de
Deco, Gustavo ; Computational Neuroscience Group, Center for Brain and Cognition, Universitat ; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu
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