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)(http://dx.doi.org/10.1016/j.neuroimage.2010.03.039). MICA is the toolbox inplemented SOI-GICA for convenience of usage.
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Category:Independent Component Analysis
License:GNU General Public License (GPL)
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mica: MICA_manual_beta1.2_20100729_en release

MICA_manual_beta1.2_20100729_en.pdf posted by Han Zhang on Jul 28, 2010

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mica: MICA_beta1.2_20100718 release

MICA_beta1.2_20100718.zip posted by Han Zhang on Jul 21, 2010

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MICA_manual_beta1.2_20100614_cn.pdf posted by Han Zhang on Jun 13, 2010

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mica: MICA beta1.2 release

MICA_beta1.2_20100110.zip posted by Han Zhang on Jun 11, 2010