  One of the primary objectives of human brain mapping is the division of the
cortical surface into functionally distinct regions, i.e. parcellation. While
it is generally agreed that at macro-scale different regions of the cortex have
different functions, the exact number and configuration of these regions is not
known. Methods for the discovery of these regions are thus important,
particularly as the volume of available information grows. Towards this end, we
present a parcellation method based on a Bayesian non-parametric mixture model
of cortical connectivity.
