Estimating the value of potential actions is crucial for learning and adaptive behavior. We know little about how the human brain represents action-specific value outside of motor areas. This is, in part, due to a difficulty in detecting the neural correlates of value using conventional (region of interest) functional magnetic resonance imaging (fMRI) analyses, due to a potential distributed representation of value. We address this limitation by applying a recently developed multivariate decoding method to high-resolution fMRI data in subjects performing an instrumental learning task. We found evidence for action-specific value signals in circumscribed regions, specifically ventromedial prefrontal cortex, putamen, thalamus, and insula cortex. In contrast, action-independent value signals were more widely represented across a large set of brain areas. Using multivariate Bayesian model comparison, we formally tested whether value-specific responses are spatially distributed or coherent. We found strong evidence that both action-specific and action-independent value signals are represented in a distributed fashion. Our results suggest that a surprisingly large number of classical reward-related areas contain distributed representations of action-specific values, representations that are likely to mediate between reward and adaptive behavior.