N. De Stefano

TL;DR: A review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data.

TL;DR: Evidence is provided that at least 5 distinct RSN patterns are reproducible across different subjects and that RSNs are a major source of non-modeled signal in BOLD fMRI data, so a full understanding of their dynamics will improve the interpretation of functional brain imaging studies more generally.

TL;DR: It is concluded that indices of axonal damage or loss such as brain N-acetylaspartate may provide a specific measure of pathological changes relevant to disability.

TL;DR: Results add to data suggesting that axonal damage or loss may be responsible for functional impairments in multiple sclerosis, and may be of particular significance for understanding chronic disability in this disease.

TL;DR: A fully automated method of longitudinal change analysis is presented here, which automatically segments brain from nonbrain in each image, registers the two brain images while using estimated skull images to constrain scaling and skew, and finally estimates brain surface motion by tracking surface points to subvoxel accuracy.