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Project Topic
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Post-coma patients with disorders of consciousness (DoC) suffer from brain lesions that can be restricted or extensive, leading to vegetative (or unresponsive) or minimally consciousness states.
Because some brain regions – sometimes a large part of the brain - are essentially intact, there is a hope to restore consciousness in such patients but a clear procedure and associated neurobiological mechanism are still lacking. In the present project we aim to test different ways of restoring brain activity leading to consciousness, using a combination of analyses on existing data, and computational modelling. We will analyse data from different laboratories, where the brain is activated using different means, such as administration of psychedelic and dissociative drugs (e.g., psilocybin, ketamine) or non- pharmacological interventions (e.g., transcranial direct-current stimulation, tDCS). In some of these experiments, the level of excitatory glutamate was estimated using MRS spectroscopy, while in others, the brain was stimulated using transcranial magnetic stimulation (TMS). Resting-state activity and evoked responses were measured using either functional imaging (fMRI) or EEG source imaging. These data will be analyzed to quantify the dynamic changes of functional connectivity (FC), in both resting state and TMS-evoked responses, using measures of complexity of pattern propagation, such as the perturbational complexity index (PCI), and will determine how the artificial activation of the brain using drugs or tDCS, can be linked to particular patterns of complexity dynamics. Computational models will take advantage of the mean-field approach to integrate changes at the microscopic level (typically synaptic receptors) and evaluate the emergent behaviour that can be induced at large scales, at the level of interacting brain regions. We have shown that simulating the alteration of GABA-A receptors by anesthetics such as propofol, can lead to a transition from desynchronized activity to synchronized slow waves across the brain. Similarly, we will model here the effect of psychedelic and dissociative drugs on synaptic receptors such as NMDA (ketamine) or serotonergic 5HT2A receptors (psilocybin), and how these stimulations can interact with the natural, neuromodulatory-driven mechanisms of brain activation. The model will directly use the quantifications of excitatory glutamate concentrations in the brain provided by MRS spectroscopy. The effect of tDCS on neuronal membrane potentials will also be integrated in the mean-field model and its emerging effect will be evaluated. We will use the same measures as for experimental data, such as dynamic FC or PCI, and determine how the receptor stimulation (or antagonism) can lead to reverse the transitions seen with anaesthetics, here from slow-wave (or burst suppression) to desynchronized activity typical of conscious states. The models will also simulate the combined action of drugs and tDCS, with the aim to predict a protocol that can be used later on a patient-specific way, to restore signs of consciousness. At the end of the project, we will provide a set of open-access tools to construct whole-brain models specific to each patient, and use the model to estimate the effect of psychedelic and dissociative drugs and tDCS (or their combination) to restore consciousness. This tool is aimed to help clinicians to estimate the optimal protocol for each patient.
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