We propose a novel method for functional segmentation of fMRI data that incorporates multiple functional attributes such as activation effects and functional connectivity, under a ...
Bernard Ng, Rafeef Abugharbieh, Martin J. McKeow...
Multi-subject analysis of functional Magnetic Resonance Imaging (fMRI) data relies on within-subject studies, which are usually conducted using a massively univariate approach. In...
Philippe Ciuciu, Thomas Vincent, Anne-Laure Fouque...
Data-driven analysis methods, in particular independent component analysis (ICA) has proven quite useful for the analysis of functional magnetic imaging (fMRI) data. In addition, ...
Traditional fMRI analysis has focused on modeling temporal changes in BOLD signals on a voxel-by-voxel basis to infer brain activation. To incorporate spatial information, we have...
We construct a biologically motivated stochastic differential model of the neural and hemodynamic activity underlying the observed Blood Oxygen Level Dependent (BOLD) signal in Fu...