A main focus in economics is on binary choice situations, in which human agents have to choose between two alternative options. The classical view is that decision making consists of valuating each option, comparing the two expected values, and selecting the higher one. Some neural correlates of option values have been described in animals, but little is known about how they are represented in the human brain: are they integrated into a single center or distributed over different areas? To address this issue, we examined whether the expected values of two options, which were cued by visual symbols and chosen with either the left or right hand, could be distinguished using functional magnetic resonance imaging. The two options were linked to monetary rewards through probabilistic contingencies that subjects had to learn so as to maximize payoff. Learning curves were fitted with a standard computational model that updates, on a trial-by-trial basis, the value of the chosen option in proportion to a reward prediction error. Results show that during learning, left and right option values were specifically expressed in the contralateral ventral prefrontal cortex, regardless of the upcoming choice. We therefore suggest that expected values are represented in a distributed manner that respects the topography of the brain systems elicited by the available options.