Whole Brain Clustering on the Basis of Resting-State FMRI Data

Hubert Martinus Fonteijn¹, David Gordon Norris²

Resting-state fMRI fluctuations show correlation patterns which to some extent resemble known anatomical connectivity patterns in the brain. In this abstract we address the question at what level these fluctuations are organized by using a clustering algorithm on RS fMRI data. More specifically, an infinite mixture model is fitted on data of 8 from which automatically determines the number of clusters needed to represent the data correctly. A highly symmetric pattern of clusters is observed for all subjects and the number of clusters found in each subject is comparable to the number of areas used in anatomical parcellation schemes.