TY - JOUR T1 - Transferring structural knowledge across cognitive maps in humans and models JF - bioRxiv DO - 10.1101/860478 SP - 860478 AU - Shirley Mark AU - Rani Moran AU - Thomas Parr AU - Steve Kennerley AU - Tim Behrens Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/11/30/860478.abstract N2 - Relations between task elements often follow hidden underlying structural forms such as periodicities or hierarchies, whose inferences fosters performance. However, transferring structural knowledge to novel environments requires flexible representations that are generalizable over particularities of the current environment, such as its stimuli and size. We suggest that humans represent structural forms as abstract basis sets and that in novel tasks, the structural form is inferred and the relevant basis set is transferred. Using a computational model, we show that such representation allows inference of the underlying structural form, important task states, effective behavioural policies and the existence of unobserved state-trajectories. In two experiments, participants learned three abstract graphs during two successive days. We tested how structural knowledge acquired on Day-1 affected Day-2 performance. In line with our model, participants who had a correct structural prior were able to infer the existence of unobserved state-trajectories and appropriate behavioural policies. ER -