Abstract
OPINION article Front. Neurosci., 27 August 2013Sec. Brain Imaging Methods https://doi.org/10.3389/fnins.2013.00154
Highlights
SICA has become widely used for functional magnetic resonance imaging (fMRI) analysis since its original application to fMRI 15 year ago (Calhoun and Adali, 2012)
They developed a tool called Contributive Sources Analysis (CSA) for estimating the amplitude of fMRI signal changes in each functional networks (FNs). They first used the general linear model (GLM)-based analysis to define clusters showing significant task-related activity as regions of interests (ROIs) and used CSA to extract measures of task-related changes in fMRI signal within these ROIs from all FNs overlapping with these ROIs
Independent component analysis (ICA) reveals hidden functional activity voxels/regions, and that this feature of brain functional organization may not be detected by GLM based analysis
Summary
SICA has become widely used for fMRI analysis since its original application to fMRI 15 year ago (Calhoun and Adali, 2012). Several studies compared sICA and GLM based analyses and reported that sICA revealed more brain regions showing task-related activation relative to GLM based analysis, supporting the prediction of McKeown et al (Calhoun et al, 2001; Malinen et al, 2007; Tie et al, 2008; Kim et al, 2011).
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