Learning and interpreting the structure of the environment is an innate feature of biological systems, and is integral to guiding flexible behaviors for evolutionary viability. The concept of a cognitive map has emerged as one of the leading metaphors for these capacities, and unraveling the learning and neural representation of such a map has become a central focus of neuroscience. In recent years, many models have been developed to explain cellular responses in the hippocampus and other brain areas. Because it can be difficult to see how these models differ, how they relate and what each model can contribute, this Review aims to organize these models into a clear ontology. This ontology reveals parallels between existing empirical results, and implies new approaches to understand hippocampal–cortical interactions and beyond.
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Python and TensorFlow code are available at https://github.com/djcrw/generalising-structural-knowledge.
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We thank N. Burgess and C. Sun for helpful comments on earlier drafts of the manuscript. We thank the following funding sources: Sir Henry Wellcome Post-doctoral Fellowship (222817/Z/21/Z) to J.C.R.W.; Wellcome Trust DPhil Scholarship to D.M.; and Wellcome Principal Research Fellowship (219525/Z/19/Z), Wellcome Collaborator award (214314/Z/18/Z), and JS McDonnell Foundation award (JSMF220020372) to T.E.J.B.. The Wellcome Centre for Integrative Neuroimaging and Wellcome Centre for Human Neuroimaging are each supported by core funding from the Wellcome Trust (203139/Z/16/Z, 203147/Z/16/Z).
The authors declare no competing interests.
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Whittington, J.C.R., McCaffary, D., Bakermans, J.J.W. et al. How to build a cognitive map. Nat Neurosci 25, 1257–1272 (2022). https://doi.org/10.1038/s41593-022-01153-y
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