Encoding models in functional magnetic resonance imaging: the Voxelwise Encoding Model framework (Visconti di Oleggio Castello, Deniz, et al., PsyArXiv preprint, 2025)
September 17, 2025
This review paper provides the first comprehensive guide to the Voxelwise Encoding Model (VEM) framework. The VEM framework is a framework for fitting encoding models to fMRI data. This framework is currently the most sensitive and powerful approach available for modeling fMRI data. It can be used to fit dozens of distinct models simultaneously, each model having up to several thousand distinct features. The Voxelwise Encoding Model framework also conforms to all best practices in data science, which maximizes sensitivity, reliability and generalizability of the resulting models.