Figure 3.

The winning model, the exceedance probabilities across models as a fraction of change, and a magnification of the winning model exceedance probability. A, The observed exceedance probabilities (EP; ie, the relative likelihood that a given model is the generative model for the observed functional magnetic resonance imaging data) across all 136 models are depicted relative to the flat a priori probability. Given 136 models in the space, the expected random a priori chance EP is .007 (given flat prior probabilities on the model space). When observed EPs are expressed relative to this chance EP value, the a priori probability represents unity (dotted line). Models with fractional values higher than 1 are more likely relative to their competition in the space (ie, the posterior is higher than the flat prior probability). B, The inset in part A is magnified to emphasize the winning model. The winning model is approximately 25% higher than chance and higher than its closest competitors in the space. C, The winning model structure is depicted with the observed driving inputs, intrinsic connections, and contextual modulatory effects. DPFC indicates dorsal prefrontal cortex; FG, fusiform gyrus; V1, primary visual cortex; and VPFC, ventral prefrontal cortex.