title: Toward a neurometric foundation for probabilistic independent component analysis of fMRI data.
abstract: Improved fMRI data analysis methods hold promise for breakthroughs in cognitive and affective neuroscience. Group probabilistic independent component analysis (pICA), such as that implemented by MELODIC (Beckmann & Smith IEEE Transactions on Medical Imaging 23:137-152, 2004), is one popular technique that typifies this development. Recently pICA has been proposed to be a reliable method for studying connectivity networks (Zuo et al. NeuroImage 49:2163-2177, 2010); however, there is no "standard" way to complete a pICA, and the full impact of the options on neurometric properties of resulting components is unknown. In the present study, we sought to assess the robustness, reproducibility, and within-subject test-retest reliability of ICA in two data sets: The first included 30 subjects imaged 3 weeks apart while completing a cognitive control task, and the second included 27 subjects imaged 9 months apart during rest. In addition to examining the impact of analytic parameters on the neurometrics, this study was the first to simultaneously investigate within-subject reliability of ICA-derived components from rest and task fMRI data. Results suggested that for both task and rest, meta-level analyses using 25 subject orders optimized robustness of the components. The impact of dimensionality and voxel threshold for components was subsequently examined regarding properties of reproducibility and within-subject retest reliability. Component thresholds between 0.2 and 0.6 of the maximum value optimized reproducibility across multiple dimensionalities and produced generally fair to moderate reliability estimates (Cicchetti & Sparrow American Journal of Mental Deficiency 86:127-137, 1981). These guidelines strengthen the foundation for this data-driven approach to fMRI analysis by providing prescriptive findings and a descriptive set of neurometrics for resting-state and task fMRI.
authors.affiliation: Department of Psychology, University of Minnesota, N426 Elliott Hall , 75 East River Road, Minneapolis, MN, 55455, USA, poppe076@umn.edu.
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Poppe
authors.forename: Krista
authors.initials: K
authors.lastname: Wisner
authors.forename: Gowtham
authors.initials: G
authors.lastname: Atluri
authors.forename: Kelvin O
authors.initials: KO
authors.lastname: Lim
authors.forename: Vipin
authors.initials: V
authors.lastname: Kumar
authors.forename: Angus W
authors.initials: AW
authors.lastname: Macdonald
mesh_terms: D000328:Adult; D000465:Algorithms; D001699:Biometry; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D011336:Probability; D015203:Reproducibility of Results; D012146:Rest / Q000502:physiology*; D013223:Statistics as Topic / Q000379:methods; D055815:Young Adult