Group independent component analysis reveals consistent resting-state networks across multiple sessions.

ABSTRACT: Group independent component analysis (gICA) was performed on resting-state data from 14 healthy subjects scanned on 5 fMRI scan sessions across 16 days. The data were reduced and aggregated in 3 steps using Principal Components Analysis (PCA, within scan, within session and across session) and subjected to gICA procedures. The amount of reduction was estimated by an improved method that utilizes a first-order autoregressive fitting technique to the PCA spectrum. Analyses were performed using all sessions in order to maximize sensitivity and alleviate the problem of component identification across session. Across-session consistency was examined by three methods, all using back-reconstruction of the single-session or single-subject/session maps from the grand (5-session) maps. The gICA anal

SUBMITTER: Chen S 

PROVIDER: S-EPMC2784277 | biostudies-literature | 2008 Nov

REPOSITORIES: biostudies-literature