Filosofía y Lógica y Filosofía de la Ciencia

URI permanente para esta comunidadhttps://hdl.handle.net/11441/10737

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Examinando Filosofía y Lógica y Filosofía de la Ciencia por Agencia financiadora "Fundación Alicia Koplowitz"

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    What lies underneath: Precise classification of brain states using time-dependent topological structure of dynamics
    (PLOS, 2022) Soler Toscano, Fernando; Galadí García, Javier Alejandro; Escrichs, Anira; Sanz Perl, Y.; López González, Ane; Sitt, Jacobo D.; Annen, Jitka; Gosseries, Olivia; Thibaut, Aurore; Panda, Rajanikant; Esteban, Francisco J.; Laureys, Steven; Kringelbach, M.L.; Langa Rosado, José Antonio; Deco, Gustavo; Universidad de Sevilla. Departamento de Filosofía y Lógica y Filosofía de la Ciencia; Universidad de Sevilla. Departamento de Ecuaciones Diferenciales y Análisis Numérico; Junta de Andalucía; Ministerio de Ciencia, Innovación y Universidades (MICINN). España; Universidad de Jaén; Fundación Alicia Koplowitz; Unión Europea. Horizonte 2020; Swiss National Science Foundation; Fonds de la Recherche Scientifique (FNRS). Bélgica; National Natural Science Foundation of China
    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.