title: Reliable intrinsic connectivity networks: test-retest evaluation using ICA and dual regression approach.
abstract: Functional connectivity analyses of resting-state fMRI data are rapidly emerging as highly efficient and powerful tools for in vivo mapping of functional networks in the brain, referred to as intrinsic connectivity networks (ICNs). Despite a burgeoning literature, researchers continue to struggle with the challenge of defining computationally efficient and reliable approaches for identifying and characterizing ICNs. Independent component analysis (ICA) has emerged as a powerful tool for exploring ICNs in both healthy and clinical populations. In particular, temporal concatenation group ICA (TC-GICA) coupled with a back-reconstruction step produces participant-level resting state functional connectivity maps for each group-level component. The present work systematically evaluated the test-retest reliability of TC-GICA derived RSFC measures over the short-term (<45 min) and long-term (5-16 months). Additionally, to investigate the degree to which the components revealed by TC-GICA are detectable via single-session ICA, we investigated the reproducibility of TC-GICA findings. First, we found moderate-to-high short- and long-term test-retest reliability for ICNs derived by combining TC-GICA and dual regression. Exceptions to this finding were limited to physiological- and imaging-related artifacts. Second, our reproducibility analyses revealed notable limitations for template matching procedures to accurately detect TC-GICA based components at the individual scan level. Third, we found that TC-GICA component's reliability and reproducibility ranks are highly consistent. In summary, TC-GICA combined with dual regression is an effective and reliable approach to exploratory analyses of resting state fMRI data.
authors.affiliation: Phyllis Green and Randolph Cōwen Institute for Pediatric Neuroscience, New York University Child Study Center, New York, NY, USA. xinian.zuo@nyumc.org
authors.forename: Xi-Nian
authors.initials: XN
authors.lastname: Zuo
authors.forename: Clare
authors.initials: C
authors.lastname: Kelly
authors.forename: Jonathan S
authors.initials: JS
authors.lastname: Adelstein
authors.forename: Donald F
authors.initials: DF
authors.lastname: Klein
authors.forename: F Xavier
authors.initials: FX
authors.lastname: Castellanos
authors.forename: Michael P
authors.initials: MP
authors.lastname: Milham
mesh_terms: D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D009434:Neural Pathways / Q000502:physiology*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D055815:Young Adult