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Pré-Publication, Document De Travail Année : 2024

Revisiting the standard for modeling functional brain network activity: application to consciousness

Grigis Antoine
  • Fonction : Auteur
Gomez Chloé
  • Fonction : Auteur
  • PersonId : 1366205
  • IdHAL : chloe-gomez
Frouin Vincent
  • Fonction : Auteur
Uhrig Lynn
  • Fonction : Auteur

Résumé

Consciousness can be characterized by studying spontaneous fluctuations in brain activity, commonly measured with resting-state functional Magnetic Resonance Imaging (rs-fMRI). Previous rs-fMRI studies in monkeys and humans have shown that different levels of consciousness are defined by the relative prevalence of different dynamical functional connectivity patterns, also called brain patterns. These patterns closely match the underlying structural connectivity when consciousness is lost. The results suggest that changes in the state of consciousness lead to changes in connectivity patterns, not only at the level of co-activation strength between regions, but also at the level of entire networks. Here, we use a linear latent variable model that provides interpretable brain networks to reveal a new signature of consciousness and its chemically induced loss during anesthesia. To identify interpretable spatial signatures of consciousness, we apply a four-step framework by i) generating a list of atlases, ii) filtering and extracting the time series associated with the brain Regions of Interest (ROIs) of each atlas, iii) decomposing the signals into tailored brain networks with associated Brain Network Activities (BNAs), and iv) performing statistical inference and multivariate analysis of the BNAs. The novelty of the framework lies in the adoption of a constrained linear latent variable model that provides BNAs based on identifiable and disjoint ROIs, called brain networks, and the ability to offer a sound basis for atlas selection given the underlying clinical question. The model yields a set of tailored brain networks and associated BNAs that characterize states of consciousness. Our results suggest that a network composed of fronto-parietal and cingular cortices strongly influences the shift of consciousness state, especially between anesthesia and wakefulness. Interestingly, this observation is consistent with the global neural workspace theory of consciousness. We also decipher the level of anesthesia from rs-fMRI-derived BNAs. We identify neurobiologically relevant brain networks that provide novel interpretable signatures of consciousness and its loss during anesthesia. These findings pave the way for translational applications such as the diagnosis of consciousness disorders.
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Dates et versions

hal-04511450 , version 1 (19-03-2024)

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  • HAL Id : hal-04511450 , version 1

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Grigis Antoine, Gomez Chloé, Frouin Vincent, Uhrig Lynn, Jarraya Béchir. Revisiting the standard for modeling functional brain network activity: application to consciousness. 2024. ⟨hal-04511450⟩
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