Medical Image Analysis //
Multimodal Data Fusion for Brain Connectivity Analysis
Despite enormous strides in our understanding of neural physiology, the transition from cellular and subcellular functional variability to variations in human behavior is poorly understood. Current evidence ties this transition to complex interactions within brain functional networks. These networks are not easy to estimate from the data due to their dynamic nature. However, accurately characterizing them is of the uttermost importance for diagnosis and prediction of mental disorders at their early stages (e.g. schizophrenia). This project is aiming to improve estimation of brain functional networks by taking advantage of the complementary nature of multiple brain imaging modalities. The main application is in the study of mental disorders linked to brain network dysfunction (schizophrenia, Alzheimer's, ADHD, bipolar disorder and others).