Neuron
Volume 107, Issue 6, 23 September 2020, Pages 1226-1238.e8
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Article
Map Making: Constructing, Combining, and Inferring on Abstract Cognitive Maps

https://doi.org/10.1016/j.neuron.2020.06.030Get rights and content
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Highlights

  • Human brains map abstract relationships among entities from piecemeal learning

  • Separately learnt dimensions are combined and represented in a 2D social hierarchy

  • To make novel inferences, HC reinstates a hub that connects two social hierarchies

  • EC and vmPFC encode Euclidean distances of inferred vectors for novel inferences

Summary

Cognitive maps enable efficient inferences from limited experience that can guide novel decisions. We tested whether the hippocampus (HC), entorhinal cortex (EC), and ventromedial prefrontal cortex (vmPFC)/medial orbitofrontal cortex (mOFC) organize abstract and discrete relational information into a cognitive map to guide novel inferences. Subjects learned the status of people in two unseen 2D social hierarchies, with each dimension learned on a separate day. Although one dimension was behaviorally relevant, multivariate activity patterns in HC, EC, and vmPFC/mOFC were linearly related to the Euclidean distance between people in the mentally reconstructed 2D space. Hubs created unique comparisons between the hierarchies, enabling inferences between novel pairs. We found that both behavior and neural activity in EC and vmPFC/mOFC reflected the Euclidean distance to the retrieved hub, which was reinstated in HC. These findings reveal how abstract and discrete relational structures are represented, are combined, and enable novel inferences in the human brain.

Keywords

Cognitive map
Generalization
Social network
2D space
Euclidean
Inference
Model based
Hippocampus
Entorhinal cortex
Orbitofrontal cortex

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