  This paper describes a new neuroimaging analysis toolbox that allows for the
modeling of nonlinear effects at the voxel level, overcoming limitations of
methods based on linear models like the GLM. We illustrate its features using a
relevant example in which distinct nonlinear trajectories of Alzheimer's
disease related brain atrophy patterns were found across the full biological
spectrum of the disease. The open-source toolbox presented in this paper is
available at https://github.com/imatge-upc/VNeAT.
