Matching parcels across different subjects is an open problem in neuroscience. Even when produced by the same technique, parcellations tend to differ in the number, shape, and spatial localization of parcels across subject. To the best of our knowledge, no technique has been able to tackle this problem. In this work, we propose and compare four different methods to match parcels across subjects based on their extrinsic connectivity fingerprint. We test their performance by matching parcels of the Desikan atlas [4] across subjects, as its parcels have been shown to have consistent connectivity profiles across subjects [6]. Then, we repeat the experiment for a pre-existing groupwise parcellation based on structural connectivity [5], which has been show to be consistent across groups of subjects. The outline of our work can be seen in Figure 1. Our results show that our methods based on Optimal Transport (OT) and Kullback Leibler (KL) divergence achieve more than 99% of correct matches.