Abstract
A fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with DoC. The model-free approach allowed us to characterize brain states in DoC and healthy controls as a probabilistic metastable substate (PMS) space. The PMS of each group was defined by a repertoire of unique patterns (i.e., metastable substates) with different probabilities of occurrence. In the model-based approach, we adjusted the PMS of each DoC group to a causal whole-brain model. This allowed us to explore optimal strategies for promoting transitions by applying off-line in silico probing. Furthermore, this approach enabled us to evaluate the impact of local perturbations in terms of their global effects and sensitivity to stimulation, which is a model-based biomarker providing a deeper understanding of the mechanisms underlying DoC. Our results show that transitions were obtained in a synchronous protocol, in which the somatomotor network, thalamus, precuneus and insula were the most sensitive areas to perturbation. This motivates further work to continue understanding brain function and treatments of disorders of consciousness.
Copyright: © 2024 Dagnino et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Publication types
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Research Support, Non-U.S. Gov't
MeSH terms
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Adult
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Aged
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Brain Mapping / methods
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Brain* / diagnostic imaging
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Brain* / physiopathology
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Computational Biology
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Computer Simulation*
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Consciousness / physiology
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Consciousness Disorders* / diagnostic imaging
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Consciousness Disorders* / physiopathology
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Female
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Humans
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Magnetic Resonance Imaging* / methods
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Male
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Middle Aged
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Models, Neurological*
Grants and funding
P.D. was supported by the AGAUR FI-SDUR Grant (no. 2022 FISDU 00229) and by the AGAUR research support grant (ref. 2021 SGR 00917) funded by the Department of Research and Universities of the Generalitat of Catalunya. A.E. was supported by the project eBRAIN-Health - Actionable Multilevel Health Data (id 101058516), funded by the EU Horizon Europe. A.E. and G.D. were supported by the Grant PID2022-136216NB-I00 funded by MICIU/AEI/10.13039/501100011033 and by "ERDF A way of making Europe", ERDF, EU. G.D. and Y.S.P. were supported by the project NEurological MEchanismS of Injury, and Sleep-like cellular dynamics (NEMESIS) (ref. 101071900) funded by the EU ERC Synergy Horizon Europe. Y.S.P. was also supported by the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant 896354. S.L. and J.A. were supported by the HBP SGA3 Human Brain Project Specific Grant Agreement 3 (grant agreement no. 945539), funded by the EU H2020 FET Flagship. The study was supported by the University and University Hospital of Liège, the Belgian National Funds for Scientific Research (F.R.S-FNRS), the MIS FNRS project (F.4521.23), the BIAL Foundation, AstraZeneca Foundation, the Generet funds and the King Baudouin Foundation, the James McDonnell Foundation, and Mind Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.