Effective artifact removal in resting state fMRI data improves detection of DMN functional connectivity alteration in Alzheimer's disease.

ABSTRACT: Artifact removal from resting state fMRI data is an essential step for a better identification of the resting state networks and the evaluation of their functional connectivity (FC), especially in pathological conditions. There is growing interest in the development of cleaning procedures, especially those not requiring external recordings (data-driven), which are able to remove multiple sources of artifacts. It is important that only inter-subject variability due to the artifacts is removed, preserving the between-subject variability of interest-crucial in clinical applications using clinical scanners to discriminate different pathologies and monitor their staging. In Alzheimer's disease (AD) patients, decreased FC is usually observed in the posterior cingulate cortex within the default m

SUBMITTER: Griffanti L 

PROVIDER: S-EPMC4531245 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature