Surprising events may be relevant or irrelevant for behavior, requiring either flexible adjustment or stabilization of our model of the world and according response strategies. Cognitive flexibility and stability in response to environmental demands have been described as separable cognitive states, associated with activity of striatal and lateral prefrontal regions, respectively. It so far remains unclear, however, whether these two states act in an antagonistic fashion and which neural mechanisms mediate the selection of respective responses, on the one hand, and a transition between these states, on the other. In this study, we tested whether the functional dichotomy between striatal and prefrontal activity applies for the separate functions of updating (in response to changes in the environment, i.e., switches) and shielding (in response to chance occurrences of events violating expectations, i.e., drifts) of current predictions. We measured brain activity using fMRI while 20 healthy participants performed a task that required to serially predict upcoming items. Switches between predictable sequences had to be indicated via button press while sequence omissions (drifts) had to be ignored. We further varied the probability of switches and drifts to assess the neural network supporting the transition between flexible and stable cognitive states as a function of recent performance history in response to environmental demands. Flexible switching between models was associated with activation in medial pFC (BA 9 and BA 10), whereas stable maintenance of the internal model corresponded to activation in the lateral pFC (BA 6 and inferior frontal gyrus). Our findings extend previous studies on the interplay of flexibility and stability, suggesting that different prefrontal regions are activated by different types of prediction errors, dependent on their behavioral requirements. Furthermore, we found that striatal activation in response to switches and drifts was modulated by participants' successful behavior toward these events, suggesting the striatum to be responsible for response selections following unpredicted stimuli. Finally, we observed that the dopaminergic midbrain modulates the transition between different cognitive states, thresholded by participants' individual performance history in response to temporal environmental demands.

Because everyday actions are statistically structured, knowing which action a person has just completed allows predicting the most likely next action step. Taking even more than the preceding action into account improves this predictability but also causes higher processing costs. Using fMRI, we investigated whether observers exploit second-order statistical regularities preferentially if information on possible upcoming actions provided by first-order regularities is insufficient. We hypothesized that anterior pFC balances whether or not second-order information should be exploited. Participants watched videos of actions that were structured by first- and second-order conditional probabilities. Information provided by the first and by the second order was manipulated independently. BOLD activity in the action observation network was more attenuated the more information on upcoming actions was provided by first-order structure, reflecting expectation suppression for more predictable actions. Activation in posterior parietal sites decreased further with second-order information but increased in temporal areas. As expected, second-order information was integrated more when less first-order information was provided, and this interaction was mediated by anterior pFC (BA 10). Observers spontaneously used both the present and the preceding action to predict the upcoming action, and integration of the preceding action was enhanced when the present action was uninformative.