GNU General Public License (GPL) Yes NITRC Subject Order-Independent Group ICA Linux, Windows Yes MATLAB Han Zhang 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. 2012-11-30 4 - Beta MICA_beta1.22_20120523 2012-4-05 4 - Beta MICA_beta1.21_20120120 2010-7-29 4 - Beta MICA_manual_beta1.2_20100729_en 2010-7-22 4 - Beta MICA_beta1.2_20100718 2010-6-14 4 - Beta MICA_manual_beta1.2_20100614_cn 2010-6-12 4 - Beta MICA beta1.2 Subject Order-Independent Group ICA GNU General Public License (GPL), Independent Component Analysis, Windows, Linux, MR, Win32 (MS Windows), Gnome, KDE, English, 4 - Beta, MATLAB, NIfTI-1, ANALYZE, Developers, End Users, Parkinson Disease, Diabetes Mellitus, Alzheimer Disease, Attention Deficit Disorder with Hyperactivity, Brain Injuries, Dyslexia, Schizophrenia, Epilepsy, Substance-Related Disorders, Brain Concussion, Bipolar Disorder, Depression, Huntington Disease, Stroke, Tourette Syndrome, Multiple Sclerosis, Hypertension, Amyotrophic Lateral Sclerosis, Asperger Syndrome, Autistic Disorder http://www.nitrc.org/projects/cogicat/, http://www.nitrc.org/projects/cogicat/ napoleon1982@gmail.com