Assessing dynamic effects on a Bayesian matrix-variate dynamic linear model: An application to task-based fMRI data analysis

A modeling procedure for task-based functional magnetic resonance imaging (fMRI) data analysis using a Bayesian matrix-variate dynamic linear model (MVDLM) is presented. With this type of model, less complex than the more traditional temporal-spatial models, it is possible to take into account the temporal and, at least locally, the spatial structures that are usually present in this type of data. Thus, every voxel in the brain image is jointly...