for non-uniformity artifacts (Sled et al., 1998); and image classification into white matter, grey matter and CSF using a neural-net classifier (Zijdenbos et al., 2002). Next, surface meshes representing the gray/white and gray/pial surfaces were generated with a Constrained Laplacian Anatomic Segmentation Using Proximities surface-extraction procedure (MacDonald et al., 2000). This approach begins with an ellipsoid polyhedral mesh located outside the brain, which is then shrunk to approximate the gray/white surface by minimization of an objective function that includes weighted terms for stretching, bending, self-proximity and prevents self-intersection. This process starts with a coarse mesh that consists of 320 triangles, which through an iterative process of deformation and sub-sampling results in a representation of the surface in question, with a mesh of 81,920 triangles defined by 40,962 vertices. This mesh is then expanded with constraints to define the gray/pial surface. Cortical thickness was calculated in native space as the root mean square of the distance between homologous vertices on each surface. In the absence of prior evidence regarding the spatial extent of genotype effects on cortical maturation, a 30mm-bandwidth blurring kernel was applied over the 2D manifold, based on the findings of an earlier statistical power analysis that identified the
