Large-scale sparse functional networks from resting state fMRI.

ABSTRACT: Delineation of large-scale functional networks (FNs) from resting state functional MRI data has become a standard tool to explore the functional brain organization in neuroscience. However, existing methods sacrifice subject specific variation in order to maintain the across-subject correspondence necessary for group-level analyses. In order to obtain subject specific FNs that are comparable across subjects, existing brain decomposition techniques typically adopt heuristic strategies or assume a specific statistical distribution for the FNs across subjects, and therefore might yield biased results. Here we present a novel data-driven method for detecting subject specific FNs while establishing group level correspondence. Our method simultaneously computes subject specific FNs for a group o

SUBMITTER: Li H 

PROVIDER: S-EPMC5568802 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature