To begin with we consider the familiar two-level univariate GLM for FMRI. For example, the model that in the first level deals with individual sessions for individual subjects, relating time-series to activation, and in the second level deals with a group of subjects or sessions (or both), relating the combined individual activation estimates to some group parameter, such as mean activation level. Note that all models and inference in this paper are mass-univariate, i.e. each voxel is modelled and processed independently of the others in the data.