We propose a method to analyze the relationship between the shape of cortical regions and cognitive measures such as reading ability and vocabulary knowledge. Functional regions on cortical surfaces can vary not only in size and shape but also in topology and position relative to neighboring regions. Standard diffeomorphism-based shape analysis tools do not work well here because diffeomorphisms are unable to capture these topological differences which include region splitting and merging across subjects. To address this, we propose Icosahedral Spatial Pyramid Matching of region borders computed on the surface of a sphere to capture this variation in regional topology, position, and shape. We then analyze how this variation corresponds to measures of language performance. Analysis is performed using a subset of 27 retest subjects from the Human Connectome Project in order to understand the reproducibility and potential of this method.