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Abstract

In a dynamic and uncertain environment it is beneficial to learn the causal structure of the environment in order to minimize uncertainty. This requires determining estimates of probable outcomes, which will guide expectations about incoming information. One key factor in this learning process is to detect whether an unexpected event constitutes a low probability, but valid outcome, or an outright error. The present 7T-fMRI study investigated the role of subcortical structures in regulating this probabilistic inferential learning process. A new task was designed, in which participants learned to calculate the value, and therefore to anticipate the outcome of different visual sequences. Three types of sequences provided unambiguous, ambiguous, and incongruent contextual evidence and each sequence had two outcomes, which differed in their probability of occurrence. We hypothesized that subcortical regions are necessary when expectations are violated, and that their involvement will depend on the nature of the unexpected event. The results show increased dorsomedial striatal and thalamic activation for less probable sequences; in addition, ambiguous sequences also display larger activation in the red nuclei. Incongruent sequences displayed a pattern of subcortical activation restricted to the dorsolateral and the posterior dorsomedial striatum. These results confirm that different subcortical structures regulate uncertainty and expectancy deviations; this is crucial not only for learning to predict events in the environment, but also for flexible cognitive control in general.