Author

Nathan F. Lepora

University of BristolORCID 0000-0001-5327-1523Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:electronic health records· 2 Organism:rat· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Approach:statistical model· 1 Research Focus:trajectory inference· 1

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Matthew W. JonesiD· 2 shared Cian O’DonnelliD· 1 shared Emma L. RoscowiD· 1 shared Kipp FreudiD· 1 shared Timothy HoweiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

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5 top collaborators · 6 mutual co-author links

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2 shared papersNeuroscience

Matthew W. JonesORCID

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2 papers

Recent·Most cited

NeuroscienceNature CommunicationsPeer-reviewedNov 24, 2025

Post-learning replay of hippocampal-striatal activity is biased by reward-prediction signals

Emma L. Roscow, Timothy Howe, Nathan F. Lepora, Matthew W. Jones

This paper shows that post-learning neural replay in rats is biased by reward-prediction errors, not reward itself, using a reinforcement learning task and neural recordings.

9 citations

ratelectronic health records

𝕏 PostBluesky

NeurosciencebioRxivPreprintFeb 1, 2024

Deep learning-based location decoding reveals that across-day representational drift is better predicted by rewarded experience than time

Kipp Freud, Nathan F. Lepora, Matthew W. Jones, Cian O’Donnell

The paper uses deep learning to measure representational drift in neural recordings and finds that rewarded experiences better predict drift than time or session count.

DOI 10.1101/2024.02.01.578423

ratelectronic health records

𝕏 PostBluesky