Neuroscience of consciousness
January 1, 2022
Joachim Bellet, Marion Gay, Abhilash Dwarakanath et al.
57 citations
Neuronal populations in the macaque prefrontal cortex (PFC) reliably encode visual stimuli even under conditions that challenge conscious perception and reduce post-perceptual processing. Recordings from the ventrolateral PFC during isolated trials and rapid serial visual presentation (RSVP) showed that stimulus identity could be decoded from population activity, with first signals at 60 ms and peak information at 150 ms. In RSVP, decoding accuracy dropped to chance by 200 ms as the next stimulus became decodable. Decoding in ventrolateral PFC was stronger than in posterior parietal cortex. The findings indicate PFC encodes visual information under conditions that limit conscious access and post-perceptual elaboration, raising questions about whether this reflects conscious access, phenomenal consciousness, or preconscious bottom-up processing.
NeuroImage
November 1, 2020
Gerald J. Hahn, Gorka Zamora‐lópez, Lynn Uhrig et al.
55 citations
Brain-wide signal levels can reliably distinguish sleep and anesthesia from the awake state in human and monkey fMRI resting state data. A whole-brain computational model reproduces changes in global synchronization, functional connectivity, structure-function relationship, integration, and segregation across vigilance states. The awake brain operates near a Hopf bifurcation, which coincides with globally correlated fMRI signals. Simulated lesions of connectivity hubs in the posterior brain and subcortical nuclei disrupt the model's awake state, matching predictions from graph-theoretical analyses of structural data.
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.
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.
September 2, 2025
Zefan Zheng, Robert Chis-Ciure, Peter Thestrup Waade et al.
1 citation
preprint
Consciousness science is fragmented, with theories operating orthogonally and accumulating anomalies. The principle of recurrency—functional and architectural feedback loops—offers a unifying scaffold. All theories tacitly invoke feedback loops and can be re-expressed along a single axis of recursion. Four nested levels (cellular, local inter-areal, global, and lateral) map onto state, phenomenal content, manipulative access, and experiential similarity, tying evolved anatomy to phenomenon. The phenomenal-versus-access distinction dissolves into a graded cascade where deeper recursion expands reportable variables. Recurrence is evolutionarily favored, rebutting feed-forward objections, while brain-body loops ground selfhood. Clinically, targeting recurrent pathways promises new biomarkers and alleviation in disorders of 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.
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.