title: Assessment of cluster homogeneity in fMRI data using Kendall's coefficient of concordance.
abstract: In fMRI both model-led and exploratory data-driven methods are used to identify groups of voxels according to their correlation either with an external reference or with some similarity measure. Here we present a technique to assess intragroup homogeneity using Kendall's coefficient of concordance W once groups have been identified. We show that the time-courses belonging to the group may be ranked according to their contribution to the overall concordance and describe an algorithm for group purification. We suggest the use of W as a cluster validation index in exploratory data analysis approaches, such as fuzzy or hard clustering, principal component analysis, independent component analysis and Kohonen maps.
authors.affiliation: Institute for Biodiagnostics, National Research Council Canada, Winnipeg, Manitoba.
authors.forename: R
authors.initials: R
authors.lastname: Baumgartner
authors.forename: R
authors.initials: R
authors.lastname: Somorjai
authors.forename: R
authors.initials: R
authors.lastname: Summers
authors.forename: W
authors.initials: W
authors.lastname: Richter
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D016000:Cluster Analysis; D017352:Echo-Planar Imaging; D006801:Humans; D008962:Models, Theoretical; D009044:Motor Cortex / Q000033:anatomy & histology; D019047:Phantoms, Imaging