Objective
The diagnosis of individuals with disorders of consciousness has fundamental implications in terms of prognosis, treatment, palliative care and even proper end-of-life decisions. Diagnosis based on behavioural assessment is difficult and it is believed that misdiagnosis occurs in a large percentage of cases (> 40%). Non-invasive functional brain imaging has recently emerged as a promising tool for the diagnosis of individuals with disorders of consciousness; however, different imaging methods allow descriptions at limited spatial and temporal resolutions, and it is unknown how these findings relate to each other, to the underlying brain anatomy, and whether they are manifestations of a single fundamental mechanism underlying the impairment of conscious awareness.
The proposed research project aims to investigate individuals with disorders of consciousness by simultaneously applying these different neuroimaging techniques, thus integrating neurophysiological data across description levels and evaluating their synergy for the objective diagnosis and prognosis of patients. We address the hypotheses that alterations in brain rhythms (measured with electroencephalography) typical of individuals with disorders of consciousness (such as the emergence of low-complexity and low-frequency neural oscillations) are related to diminished fronto-parietal activity and a breakdown of thalamo-cortical functional and anatomical connectivity (functional magnetic resonance imaging; diffusion tensor imaging) and that these signatures of consciousness correlate with the severity of the disorder and the degree of conscious awareness of the patients.
In addition, we are proposing a career development plan for the applicant that includes training on scientific and transferable skills. This plan will both widen his scientific competences and provide him with the tools and experience necessary to secure a position as a leading independent researcher by establishing his own group.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesneurobiology
- medical and health sciencesbasic medicineanatomy and morphology
- medical and health sciencesclinical medicinecritical care medicine
- engineering and technologymedical engineeringdiagnostic imagingmagnetic resonance imaging
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
You need to log in or register to use this function
Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EFCoordinator
75654 Paris
France