VB_toolbox: A tool for investigating neural feature gradients in Python and MATLAB

There has been an increasing interest in "gradient analysis". Although the technique has been used in the neuroimaging literature since Johansen-Berg et al. (2004), a recent surge in interest occurred when Margulies et al. (2016) embedded the default mode network within a gradient of macroscopic cortical organisation. Gradient analyses in the literature rely on spectral graph theory and the eigendecomposition of the graph laplacian. The second smallest eigenpair of this matrix represents the principal gradient of similarity. In this abstract we introduce a new toolbox built in Python and MATLAB for carrying out gradient analysis using a simple command line interface. The toolbox performs gradient analyses on cortical surfaces and is able to perform them at a whole brain level, using ROI approaches, or a searchlight across the cortex (Kriegeskorte et al. 2006).