A hierarchical density-based clustering analysis of auditory fMRI activation data

A novel tool for analysing functional magnetic resonance imaging (fMRI) data is introduced. The tool is based on the hierarchical clustering of the Fourier-transformed regression coefficients obtained by regressing the known task sequence with the individual fMRI signals. The clustering analysis is density-based and performed with topographic maps. The tool is tested on a standard data set and the results are compared with those obtained by statistical parametric mapping (SPM), the most widely used tool in the field.