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Replay and compositional computation

Kurth-Nelson, Zeb; Behrens, Timothy; Wayne, Greg; Miller, Kevin; Luettgau, Lennart; Dolan, Ray; Liu, Yunzhe; (2023) Replay and compositional computation. Neuron , 111 (4) pp. 454-469. 10.1016/j.neuron.2022.12.028. Green open access

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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.

Type: Article
Title: Replay and compositional computation
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neuron.2022.12.028
Publisher version: https://doi.org/10.1016/j.neuron.2022.12.028
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10163495
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