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Lynn Uhrig

Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, 91191, Gif-sur-Yvette, France.

4 papers in the library · 46 citations · publishing 2020-2024

Papers

Local orchestration of distributed functional patterns supporting loss and restoration of consciousness in the primate brain.

Nature communications March 11, 2024 Andrea I Luppi, Lynn Uhrig, Jordy Tasserie et al. 43 citations

Loss of consciousness under anesthesia increasingly constrains brain activity to follow the brain's physical structure, collapsing hierarchical cortical organization across scales. This effect was observed with three different anesthetics—propofol, sevoflurane, and ketamine—and was reversed by electrically stimulating the central thalamus, which also restored behavioral signs of arousal. Stimulating the ventral lateral thalamus did not produce these effects, showing specificity. The findings identify distributed brain signatures of consciousness that are orchestrated by particular thalamic nuclei.

Deep learning models reveal the link between dynamic brain connectivity patterns and states of consciousness.

Scientific reports December 30, 2024 Chloé Gomez, Lynn Uhrig, Vincent Frouin et al. 2 citations

A low-dimensional variational autoencoder (VAE) can model dynamic functional connectivity from resting-state fMRI to capture brain patterns related to consciousness. The VAE balanced reconstruction and classification performance compared to other models. Its latent representations stratified brain patterns and experimental conditions. Receptive field analysis identified latent directions for transitioning between patterns, and an ablation study virtually inactivated brain areas. The model summarized consciousness-specific information in key inter-areal connections, consistent with the global neuronal workspace theory. This framework may support development of an interpretable computational brain model for disorders of consciousness.

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

PloS one January 1, 2024 Antoine Grigis, Chloé Gomez, Vincent Frouin et al. 1 citation

A new framework uses a linear latent variable model to identify and quantify resting-state brain networks from fMRI recordings, addressing the atlas selection problem and enabling statistical inference on network activities. Applied to monkey data under different anesthetics with static functional connectivity, the method suggests that two networks—one fronto-parietal and cingular, another posterior (temporo-parieto-occipital)—strongly influence shifts in consciousness, particularly between anesthesia and wakefulness. This aligns with the global neural workspace and integrated information theories of consciousness. The approach can also decode anesthesia level from network activities and may aid studies of disorders of consciousness.

Hierarchical disruption in the cortex of anesthetized monkeys as a new signature of consciousness loss

bioRxiv Preprint Server June 4, 2020 Camilo Miguel Signorelli, Lynn Uhrig, Morten Kringelbach et al. preprint

Anesthesia disrupts the brain's hierarchical organization, which may be a key mechanism behind loss of consciousness. By analyzing resting-state fMRI data from awake and anesthetized macaques, the authors found that anesthesia reduces the flexibility and richness of brain dynamics, making them more rigid and driven by brain structure. The depth of anesthesia and the specific anesthetic agent used both modulate these effects. Spatial and temporal aspects of cortical hierarchy are affected differently, involving distinct brain networks. The findings suggest that a breakdown in brain hierarchy is a new signature of unconsciousness.