AbstractUnderstanding the structure of a problem, such as the relationships between stimuli, supports fast learning and flexible reasoning. Recent theoretical suggestions have highlighted the usefulness of explicit structural representations that are fully divorced from sensory details for generalisation. Rodent work has suggested that abstraction of structure occurs gradually, over time, in cortex. However, direct evidence of such explicit relational representations in humans is scarce, and its relationship to consolidation mechanisms is underexplored. Here, we use a graph-learning paradigm to find such a relational map in the human medial prefrontal cortex. Importantly, this representation was absent early after learning but emerged on the time scale of days. These results shed new light on neural representations underlying the remarkable human ability to draw accurate inferences from little data.