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A variety of methods have been developed to identify brain networks with spontaneous, coherent activity in resting-state functional magnetic resonance imaging (fMRI). We propose here a generic statistical framework to quantify the stability of such resting-state networks (RSNs), which was implemented with k-means clustering. The core of the method consists in bootstrapping the available datasets to replicate the clustering process a large number of times and quantify the stable features acrossdoi:10.1016/j.neuroimage.2010.02.082 pmid:20226257 fatcat:qjzx3mcrtney3otdbnmnhw32zm