Voxelwise nonlinear regression toolbox for neuroimage analysis: Application to aging and neurodegenerative disease modeling

TL;DR

This paper introduces an open-source voxelwise nonlinear regression toolbox for neuroimage analysis, enabling modeling of complex nonlinear effects, demonstrated through Alzheimer's disease brain atrophy patterns.

Contribution

It presents a novel neuroimaging toolbox that allows for voxelwise nonlinear modeling, overcoming linear model limitations in neurodegenerative disease studies.

Findings

Identified distinct nonlinear trajectories of Alzheimer's disease brain atrophy

Demonstrated the toolbox's capability in modeling complex neurodegenerative patterns

Provided an accessible tool for advanced neuroimaging analysis

Abstract

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.