Authors: Zhenrui Liao, Attila Losonczy

Abstract: The ability to recall, structure, and reason about learned knowledge is the {\it sine qua non} of general intelligence. Memory is not solely a task of faithfully replaying past experiences, but of constructing models (stories'') to understand them. We present a theory of how sophisticated world models can be constructed from the selfsame primitives of place cells, sequences, and cognitive maps well-known from rodent studies. Our central hypothesis is that the hippocampus is able to learn general metric spaces as cognitive maps. We test this theory by training mice to learn and solve relational queries in a virtual reality (VR) concept space which cannot be embedded in 2D Euclidean space. By performing two-photon calcium imaging of hippocampal area CA1 during this task, we find that neural representations agree with the predictions of our theory. This work experimentally tests a formalization of the widely-used conceptual model of thecognitive map'' decoupled from Euclidean space, with implications for how such maps are used to solve abstract reasoning tasks.