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