The surface was then divided into distinct cortical ROIs (Fischl et al. 2004). Each vertex was assigned a neuroanatomical label based on 1) the probability of each label at each location in a surface-based atlas space, based on a manually parcellated training set; 2) local curvature information; and 3) contextual information, encoding spatial neighborhood relationships between labels (conditional probability distributions derived from the manual training set). The parcellation scheme (Desikan et al. 2006) labels cortical sulci and gyri, then surface area and thickness values are calculated in the 66 ROIs (33 per hemisphere). Cortical thickness was calculated as the average distance between the gray/white boundary and the pial surface within each ROI. Surface area was calculated as the sum of the areas of each tesselation falling within a given ROI; this is done in each subjects' native space.
