Fig. 1.

Localized components analysis (LoCA) processing steps. Each hippocampus volumetric segmentation in a sample (n) is converted to a radial mesh and oriented along the central axis. Then the meshes are registered to a common graph space where a mean mesh is created for 1:1 correspondence of vectors. Principal components analysis of the radial distances produces the basis vectors, which are then normalized by the maximum radial distance. The other output of LoCA is the individual participant coefficients for each basis vector. Only the first 5 basis vectors were used as variables for analyses of variance and general linear models.