Software Open Access
Multi-scale Independent Component Clustering Algorithm (MICCA)
Naveau, Mikaël; Joliot, Marc
MICCA is a Matlab toolbox that implements a multi-scale unsupervised clustering algorithm of independent components detected using single-subject independent component analysis (ICA) from a subject cohort. ICA is a powerful way to investigate functional connectivity of the human brain recorded by functional magnetic resonance imaging (fMRI).
Article:
A novel group ICA approach based on multi-scale individual component clustering. Application to a large sample of fMRI data, Mikaël Naveau, Gaëlle Doucet, Nicolas Delcroix, Laurent Petit, Laure Zago, Fabrice Crivello, Gaël Jobard, Emmanuel Mellet, Nathalie Tzourio-Mazoyer, Bernard Mazoyer, Marc Joliot, Neuroinformatics (2012) 10:269-285.
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MICCA_distrib.zip
md5:cd9d504a0ec8f105fc472b44dbfe8267 |
66.5 kB | Download |
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| Views | 22 | 22 |
| Downloads | 1 | 2 |
| Data volume | 66.5 kB | 132.9 kB |
| Unique views | 14 | 14 |
| Unique downloads | 1 | 2 |
- Publication date:
- January 11, 2022
- DOI:
-
- Keyword(s):
- Resting-state fMRI Atlas
- Related identifiers:
- Supplement to
- 10.1007/s12021-012-9145-2 (Journal article)
- License (for files):
- Creative Commons Attribution 4.0 International