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URL: http://www.nitrc.org/projects/cogicat/
Proper Citation: Subject Order-Independent Group ICA (RRID:SCR_009514)
Description: While the traditional temporally concatenated Group ICA (TC-GICA) adopting three steps of PCA reduction, it could result in inconsistent and variable components when different subject orders were used, both for the group- and individual-level results. Such instability can further cause instable and thus unreliable statistical results. Subject Order-Independent Group ICA (SOI-GICA) aims to fix this problem by producing stable and reliable GICA results. For details please see the paper Subject Order-Independent Group ICA (SOI-GICA) for Functional MRI Data Analysis (Zhang et al., 2010, NeuroImage)(http://dx.doi.org/10.1016/j.neuroimage.2010.03.039). MICA is the toolbox inplemented SOI-GICA for convenience of usage.
Abbreviations: SOI-GICA
Resource Type: software resource
Defining Citation: PMID:20338245
Keywords: analyze, gnome, independent component analysis, kde, linux, matlab, microsoft, magnetic resonance, nifti, posix/unix-like, software, statistical operation, win32 (ms windows), windows
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