I study brain connectivity, metabolism, and physiology to understand brain function and behaviour. My previous work includes the development of a data-driven multivariate linear model and statistical analysis of task-induced fMRI based on sparse dictionary learning and individually reliable analysis of connector hubs of overlapping networks in resting state fMRI. These new methods have been applied for studying the reorganization of functional hubs in epilepsy, sleep and Alzheimers disease. I'm interested in understanding individual-specific functional brain network dynamics at different brain states and their relation to behaviour with a computational model of multimodal imaging data, and developing pre-treatment biomarkers of neurological disorders and clinically reproducible prediction models of post-treatment outcome or disease progression. My research is mainly based on multimodal functional neuroimaging, including fMRI, EEG, MEG, NIRS, and pupillometry in both clinical and preclinical studies. I support open science, open data, and reproducible research.