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  Replay and compositional computation

Kurth-Nelson, Z., Behrens, T., Wayne, G., Miller, K., Luettgau, L., Dolan, R., et al. (2023). Replay and compositional computation. Neuron, 111(4), 454-469. doi:10.1016/j.neuron.2022.12.028.

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Kurth-Nelson, Z, Author
Behrens, T, Author
Wayne, G, Author
Miller, K, Author
Luettgau, L, Author
Dolan, R, Author
Liu, Y, Author
Schwartenbeck, P1, Author                 
Affiliations:
1Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3017468              

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 Abstract: Replay in the brain has been viewed as rehearsal or, more recently, as sampling from a transition model. Here, we propose a new hypothesis: that replay is able to implement a form of compositional computation where entities are assembled into relationally bound structures to derive qualitatively new knowledge. This idea builds on recent advances in neuroscience, which indicate that the hippocampus flexibly binds objects to generalizable roles and that replay strings these role-bound objects into compound statements. We suggest experiments to test our hypothesis, and we end by noting the implications for AI systems which lack the human ability to radically generalize past experience to solve new problems.

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 Dates: 2023-012023-02
 Publication Status: Issued
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 Identifiers: DOI: 10.1016/j.neuron.2022.12.028
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Title: Neuron
Source Genre: Journal
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Publ. Info: Cambridge, Mass. : Cell Press
Pages: - Volume / Issue: 111 (4) Sequence Number: - Start / End Page: 454 - 469 Identifier: ISSN: 0896-6273
CoNE: https://pure.mpg.de/cone/journals/resource/954925560565