Ghent University. Faculty of Psychology and Educational Sciences
Abstract
This doctoral dissertation investigates the methodology to explore brain dynamics from resting state fMRI data. A standard resting state fMRI study gives rise to massive amounts of noisy data with a complicated spatio-temporal correlation structure. There are two main objectives in the analysis of these noisy data: establishing the link between neural activity and the measured signal, and determining distributed brain networks that correspond to brain function. These measures can then be used as indicators of psychological, cognitive or pathological states. Two main issues will be addressed: retrieving and interpreting the hemodynamic response function (HRF) at rest, and dealing with the redundancy inherent to fMRI data. Novel approaches are introduced, discussed and validated on simulated data and on real datasets, in health and disease, in order to track modulation of brain dynamics and HRF across different pathophysiological conditions
