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Humans are able to flexibly devise and implement rules to reach their desired goals. For simple situations, we can use single rules, such as "if traffic light is green then cross the street." In most cases, however, more complex rule sets are required, involving the integration of multiple layers of control. Although it has been shown that prefrontal cortex is important for rule representation, it has remained unclear how the brain encodes more complex rule sets. Here, we investigate how the brain represents the order in which different parts of a rule set are evaluated. Participants had to follow compound rule sets that involved the concurrent application of two single rules in a specific order, where one of the rules always had to be evaluated first. The rules and their assigned order were independently manipulated. By applying multivariate decoding to fMRI data, we found that the identity of the current rule was encoded in a frontostriatal network involving right ventrolateral prefrontal cortex, right superior frontal gyrus, and dorsal striatum. In contrast, rule order could be decoded in the dorsal striatum and in the right premotor cortex. The nonhomogeneous distribution of information across brain areas was confirmed by follow-up analyses focused on relevant regions of interest. We argue that the brain encodes complex rule sets by "decomposing" them in their constituent features, which are represented in different brain areas, according to the aspect of information to be maintained.

In changing environments we need to dynamically re-organize our behavior in order to reach desired goals. This requires strategic switches between different tasks. However, little is known about the neural basis of such adaptation processes. We developed a novel, motivated choice paradigm and used multivariate pattern analysis of fMRI data (MVPA) to investigate this. Subjects chose between three different tasks on a trial-by-trial basis. Task difficulty varied independently for all three tasks, increasing for the chosen task set and decreasing for the non-chosen task sets. This created an exploration-exploitation dilemma for which subjects needed to find a solution. To keep difficulty and error rates low, they had to produce a motivated decision on which task to perform next, based on their estimation of the changing environmental variables. Using MVPA, we were able to predict subjects’ choices from medial PFC, and parietal cortex. Furthermore, we could predict the current difficulty level – the motivational factor driving choices – from reward related areas. Interestingly, the ventro-medial PFC (vmPFC) encoded both the choices and the diffi- culty. This area was previously associated with the processing of stimu- lus-values. Our results suggest that vmPFC is also involved in encoding motivated choices. Further planned analyses will investigate the interaction between areas encoding choices and areas encoding motivational factors in more detail. This should provide important clues on how humans endogenously adapt their behavior to cope with changing environments.