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B Rohaut

3 papers in the library · 25 citations · publishing 2013-2024

Papers

Whole brain modelling for simulating pharmacological interventions on patients with disorders of consciousness.

Communications Biology September 19, 2024 I Mindlin, R Herzog, L Belloli et al. 18 citations

Combining whole-brain models with deep learning, researchers mapped the low-dimensional space of patients with disorders of consciousness and simulated pharmacological interventions by altering neuromodulatory levels. Serotonergic and opioid receptor activation shifted the models toward brain dynamics seen in healthier states, with improvements correlating with the mean density of activated receptors across the brain. This approach provides a way to explore therapeutic potential of psychedelic drugs within ethical and methodological constraints, marking progress toward treatments for disorders of consciousness and other brain diseases.

Whole-brain modelling supports the use of serotonergic psychedelics for the treatment of disorders of consciousness

bioRxiv Preprint Server December 29, 2023 I Mindlin, R Herzog, L Belloli et al. 7 citations preprint

Disorders of consciousness involve impaired awareness with few non-invasive treatment options. Researchers used computer models to simulate how activating certain receptors, particularly serotonergic and opioid receptors, alters whole-brain dynamics in patients. The simulations shifted patients' brain activity patterns toward those seen in conscious, awake individuals. This effect depended on the density of activated receptors across the brain. The results suggest whole-brain modeling can help identify new pharmacological treatments and support the potential of serotonergic psychedelics to accelerate recovery of consciousness.

Single-trial decoding of auditory novelty responses facilitates the detection of residual consciousness.

Neuroimage December 1, 2013 J R King, F Faugeras, A Gramfort et al.

A multivariate pattern classifier can decode single-trial EEG responses to auditory novelty, distinguishing local (automatic) from global (conscious) novelty detection. In 38 high-density EEG, MEG, and intracranial EEG recordings, the method overcame individual variability and multiple-comparison issues. Local responses were robust to distraction, while global responses depended on attention. Among 104 patients in vegetative state (VS), minimally conscious state (MCS), and conscious state (CS), local response decoding was significant in about 60% of recordings regardless of consciousness state. For global responses, significant decoding occurred in 14% of VS patients, 31% of MCS patients, and 52% of CS patients, indicating that global novelty decoding tracks consciousness level.