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Multi-scale Independent Component Clustering Algorithm (MICCA)

Authors: Naveau, Mika��l; Joliot, Marc;

Multi-scale Independent Component Clustering Algorithm (MICCA)

Abstract

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, Mika��l Naveau, Ga��lle Doucet, Nicolas Delcroix, Laurent Petit, Laure Zago, Fabrice Crivello, Ga��l Jobard, Emmanuel Mellet, Nathalie Tzourio-Mazoyer, Bernard Mazoyer, Marc Joliot, Neuroinformatics (2012) 10:269-285. https://dx.doi.org/10.1007/s12021-012-9145-2

Keywords

Resting-state, fMRI, Atlas

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citations
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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