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It is proposed that a cognitive map encoding the relationships between entities in the world supports flexible behavior, but the majority of the neural evidence for such a system comes from studies of spatial navigation. Recent work describing neuronal parallels between spatial and non-spatial behaviors has rekindled the notion of a systematic organization of knowledge across multiple domains. We review experimental evidence and theoretical frameworks that point to principles unifying these apparently disparate functions. These principles describe how to learn and use abstract, generalizable knowledge and suggest that map-like representations observed in a spatial context may be an instance of general coding mechanisms capable of organizing knowledge of all kinds. We highlight how artificial agents endowed with such principles exhibit flexible behavior and learn map-like representations observed in the brain. Finally, we speculate on how these principles may offer insight into the extreme generalizations, abstractions, and inferences that characterize human cognition.

Original publication

DOI

10.1016/j.neuron.2018.10.002

Type

Journal article

Journal

Neuron

Publication Date

24/10/2018

Volume

100

Pages

490 - 509

Keywords

Cognitive Map, Decision Making, Generalization, Hippocampal Formation, Inference, Prefrontal Cortex, Reinforcement Learning, Spatial Cognition, Statistical Learning, Structure Learning