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Proc. Natl. Acad. Sci. U.S.A.. 2025 Mar 10;. doi: 10.1073/pnas.2417025122
Learning reshapes the hippocampal representation hierarchy
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Abstract
Biological neural networks seem to efficiently select and represent task-relevant features of their inputs, an ability that is highly sought after also in artificial networks. A lot of work has gone into identifying such representations in both sensory and motor systems; however, less is understood about how representations form during complex learning conditions to support behavior, especially in higher associative brain areas. Our work shows that the hippocampus maintains a robust hierarchical representation of task variables and that this structure can support new learning through minimal changes to the neural representations.
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Janelia Authors
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