Orbitofrontal Cortex and Learning Predictions of State Transitions

The orbitofrontal cortex (OFC) has been implicated in goal-directed planning and model-based decisionmaking. One key prerequisite for model-based decision-making is learning the transition structure of the environment—the probabilities of transitioning from one environmental state to another. In this work, we investigated how the OFC might be involved in learning this transition structure, by using fMRI to assess OFC activity while humans experienced probabilistic cue–outcome transitions. We found that OFC activity was indeed correlated with behavioral measures of learning about transition structure. On a trial-by-trial basis, OFC activity was associated with subsequently increased expectation of the more probable outcome; that is, with subsequently more optimal cue–outcome predictions. Interestingly, this relationship was observed no matter what outcome occurred at the time of the OFC activity, and thus is inconsistent with an interpretation of the OFC activity as representing a “state prediction error” that would facilitate learning transitions via error-correcting mechanisms. Finally, OFC activity was related to more optimal predictions only for subsequent trials involving the same cue that was observed at the time of OFC activity—this relationship was not observed for subsequent trials involving a different cue. All together, these results indicate that the OFC is involved in updating or reinforcing a learned transition model on a trial-by-trial basis, specifically for the currently observed cue–outcome associations.