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Abstract

In everyday life, successful decision making requires precise representations of expected values. However, for most behavioral options more than one attribute can be relevant in order to predict the expected reward. Thus, to make good or even optimal choices the reward predictions of multiple attributes need to be integrated into a combined expected value. Importantly, the individual attributes of such multi-attribute objects can agree or disagree in their reward prediction. Here we address where the brain encodes the combined reward prediction (averaged across attributes) and where it encodes the variability of the value predictions of the individual attributes. We acquired fMRI data while subjects performed a task in which they had to integrate reward predictions from multiple attributes into a combined value. Using time-resolved pattern recognition techniques (support vector regression) we find that (1) the combined value is encoded in distributed fMRI patterns in the ventromedial prefrontal cortex (vmPFC) and that (2) the variability of value predictions of the individual attributes is encoded in the dorsolateral prefrontal cortex (dlPFC). The combined value could be used to guide choices, whereas the variability of the value predictions of individual attributes indicates an ambiguity that results in an increased difficulty of the value-integration. These results demonstrate that the different features defining multi-attribute objects are encoded in non-overlapping brain regions and therefore suggest different roles for vmPFC and dlPFC in multi-attribute decision making.