NeuroscienceFrontiers in Computational NeurosciencePeer-reviewed
A Computational Model of Learning Flexible Navigation in a Maze by Layout-Conforming Replay of Place Cells
2 citations
Author
Yuanxiang Gao
University of Electronic Science and Technology of ChinaORCID 0000-0002-6587-6973Unclaimed ORCID profile · follow to get notified of new preprints
Biology Disciplines
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2022-2023 · peak 1/yr2 papers
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- NeurosciencebioRxivPreprint
A Computational Theory of Learning Flexible Reward-Seeking Behavior with Place Cells
This paper proposes a computational theory for learning flexible reward-seeking behavior using place cells, showing improved learning efficiency and flexibility in a virtual rat model.
DOI 10.1101/2022.04.23.489289