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During the sleep-wake cycle, the brain undergoes profound dynamical changes, which manifest subjectively as transitions between conscious experience and unconsciousness. Yet, neurophysiological signatures that can objectively distinguish different consciousness states based are scarce. Here, we show that differences in the level of brain-wide signals can reliably distinguish different stages of sleep and anesthesia from the awake state in human and monkey fMRI resting state data. Moreover, a whole-brain computational model can faithfully reproduce changes in global synchronization and other metrics such as functional connectivity, structure-function relationship, integration and segregation across vigilance states. We demonstrate that the awake brain is close to a Hopf bifurcation, which naturally coincides with the emergence of globally correlated fMRI signals. Furthermore, simulating lesions of individual brain areas highlights the importance of connectivity hubs in the posterior brain and subcortical nuclei for maintaining the model in the awake state, as predicted by graph-theoretical analyses of structural data.
Original language | English |
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Article number | 117470 |
Journal | NeuroImage |
Volume | 226 |
ISSN | 1053-8119 |
DOIs | |
Publication status | Published - Feb 2021 |
Funding Information:
G.D. was supported by the Spanish Research Project AWAKENING: using whole-brain models perturbational approaches for predicting external stimulation to force transitions between different brain states, ref. PID2019-105772GB-I00 /AEI/10.13039/501100011033, financed by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI), and by the Catalan AGAUR program 2017 SGR 1545. G.D., G.H. and G.Z. received support from the European Union's Horizon 2020 research and innovation program under Grant Agreement No. 720270 (Human Brain Project SGA1), No. 785907 (Human Brain Project SGA2) and No. 945539 (Human Brain Project SGA3). G.H. was funded by the grant CONSCBRAIN (n. 661583) of the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie action. G.D. and G.H. received funding from the German Research Council (DFG, No. KN 588/7 – 1) within the priority program Computational Connectomics (SPP 2041). E.T. and H.L. were supported by the Bundesministerium für Bildung und Forschung (grant number 01 EV 0703 ) and the LOEWE Neuronale Koordination Forschungsschwerpunkt Frankfurt (NeFF). M.L.K. is supported by the ERC Consolidator Grant: CAREGIVING (n. 615539 ), Center for Music in the Brain, funded by the Danish National Research Foundation ( DNRF117 ), and centre for Eudaimonia and Human Flourishing funded by the Pettit and Carlsberg Foundations.
Publisher Copyright:
© 2020 The Author(s)
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
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