Subject Order-Independent Group ICA

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)( MICA is the toolbox inplemented SOI-GICA for convenience of usage.

Execution Options

Download Now:


GNU General Public License (GPL)