Single-Unit Recordings Reveal Limitations of fMRI MVPA?

Multi-voxel pattern analysis (MVPA) is an increasingly popular approach for analyzing the results of fMRI scanning experiments that measure brain activity. MVPA searches for patterns of activation that correlate with a particular mental state. This is called 'decoding' neural activity. Now a new paper in the Journal of Neuroscience from Caltech neuroscientists Julien Dubois et al. reports that MVPA is unable to decode certain kinds of information, even though single-unit recordings confirm that the information is present in brain activity. The paper's called Single-Unit Recordings in the Macaque Face Patch System Reveal Limitations of fMRI MVPA. In their study, Dubois et al. showed macaque monkeys images of male human faces. The images showed five men (five different identities) from five different viewpoints (angles). Here's the stimuli: