Artículo
What lies underneath: Precise classification of brain states using time-dependent topological structure of dynamics
Autor/es | 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 |
Departamento | Universidad de Sevilla. Departamento de Filosofía y Lógica y Filosofía de la Ciencia Universidad de Sevilla. Departamento de Ecuaciones Diferenciales y Análisis Numérico |
Fecha de publicación | 2022 |
Fecha de depósito | 2023-08-03 |
Publicado en |
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Resumen | 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 ... 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. |
Agencias financiadoras | 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 |
Identificador del proyecto | P20_00592
PGC2018-096540-B-I00 US-1254251 MSALAS-2022-19827 PAIUJA-EI_CTS02_2021 OTR08262-2021 PID2019-105772GB-I00 /AEI/10.13039/501100011033 Marie Sklodowska-Curie grant 896354 Sinergia grant no. 170873 Human Brain Project SGA3 Luminous project H2020-FETOPEN-2014-2015-RIA FP7-HEALTH-602150 Joint Research Project 81471100 EU-2020-MSCA-RISE-778234 |
Cita | Soler Toscano, F., Galadí García, J.A., Escrichs, A., Sanz Perl, Y., López González, A., Sitt, J.D.,...,Deco, G. (2022). What lies underneath: Precise classification of brain states using time-dependent topological structure of dynamics. PLoS Computational Biology, 18 (9), e1010412, 1-20. https://doi.org/10.1371/journal.pcbi.1010412. |
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journal.pcbi.1010412.pdf | 2.878Mb | [PDF] | Ver/ | |