Graphs

Computing a gradient map on a cortical surface mesh by regressing scalar values onto neighbors projected into the tangent plane. The gradient map is then segmented with a priority-flooding watershed algorithm built on a heap-based priority queue.

Using the squared Mahalanobis distance, which is chi-squared distributed under multivariate normality, to compare connectivity fingerprints between one cortical region and every other region, with Ledoit-Wolf covariance estimates and a check that the empirical distances follow the expected distribution.