Translational and multimodal brain imaging investigation of the neural correlate of arousal and awareness – IMAGINA

In the last decades, advances in Intensive Care Unit management have led to decreased mortality. However, significant morbidity remains as patients survive after a lesional coma with uncertain quality of awakening and high risk of functional disability. The possible dissociated consciousness recovery after survival (patients entering in a chronic disorder of consciousness - DOC) offers a framework that tackles a challenging problem: is it possible to identify neuronal basis of arousal and awareness in acute coma and post-coma? Can biomarkers predict awakening and recovery? Many imaging studies have been conducted in patients with DOC to explore the neuronal correlate of consciousness and have led to two main hypothesis : the “mesocircuit hypothesis” (involving subcortical structures as the thalamus) and the “global neuronal workspace hypothesis” (involving cortical areas of the Default Mode Network). Among these different levels of integration in the conscious process, the thalamus appears at crossroads through its cortical projections and its awakening inputs from the reticular formation. However, the current correlation approach (between the observed heterogeneity of lesion and clinical status) should be overtaken to look for a model of causal inferences between specific lesional patterns and their behavioural consequences. Our project aims at investigating the neuronal correlates of consciousness and identifying biomarkers of arousal and awareness in coma and post-coma. It is supported by a rich multi-level approach involving animal models and human and combining several methods: PET-MR imaging, focal pharmacological interventions in strategic areas, electrophysiology, behavioural/clinical assessments, innovative statistical and computational tools. The preclinical study will be a proof of concept of modelling mesocircuit dysfunction in an animal model to modulate arousal. Relying on multimodal approach combining pharmacological, behavioural, imaging and neurophysiological techniques, we will investigate the impact of local and reversible activation/deactivation of an arousal-related structure within the mesocircuit using intra-cerebral microinjections. These activation/deactivation effects will be assessed by a behavioural scale, electrophysiological recording and PET-MR imaging. In parallel, the clinical study will consist in a multimodal study using clinical, electrophysiological and imaging data in a cohort of acute coma and chronic DOC. We will investigate the link between brain injuries, their functional consequences and the outcome of consciousness impairment. To note, the preclinical and clinical imaging studies will be conducted in the same innovative PET-MR device allowing simultaneous co-acquisition of PET and MRI with the same sequences for animals and human. Finally, we will develop a prognostic tool from preclinical and clinical data using innovative mathematical approaches for imaging and multivariate statistics analysis. We will use supervised statistical parametric maps and recent advances in machine learning to identify the most discriminant information from the PET-MR in patients, including a specific translational analysis based on preclinical data. We will build a complete multi-parametric clinical database to test the synergic effect of each parameter to reliably predict the prognosis (for acute coma) and define the accurate diagnosis (for chronic DOC). One important clinical application is to propose free access algorithms integrating variables according to available tools in expert or less expert centres. This innovative translational project will likely generate a rich set of data that will yield knowledge on neural basis of arousal and awareness in coma and post-coma. Among the huge heterogeneity of coma-related injuries in patients, recognising the universality of a common functional pattern and identifying biomarkers of coma prognosis will constitute a great interest for our understanding of DOC.