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Neural knowledge assembly in humans and neural networks

Nelli, Stephanie; Braun, Lukas; Dumbalska, Tsvetomira; Saxe, Andrew; Summerfield, Christopher; (2023) Neural knowledge assembly in humans and neural networks. Neuron 10.1016/j.neuron.2023.02.014. (In press). Green open access

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Abstract

Human understanding of the world can change rapidly when new information comes to light, such as when a plot twist occurs in a work of fiction. This flexible "knowledge assembly" requires few-shot reorganization of neural codes for relations among objects and events. However, existing computational theories are largely silent about how this could occur. Here, participants learned a transitive ordering among novel objects within two distinct contexts before exposure to new knowledge that revealed how they were linked. Blood-oxygen-level-dependent (BOLD) signals in dorsal frontoparietal cortical areas revealed that objects were rapidly and dramatically rearranged on the neural manifold after minimal exposure to linking information. We then adapt online stochastic gradient descent to permit similar rapid knowledge assembly in a neural network model.

Type: Article
Title: Neural knowledge assembly in humans and neural networks
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neuron.2023.02.014
Publisher version: https://doi.org/10.1016/j.neuron.2023.02.014
Language: English
Additional information: © 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Abstraction, continual learning, decision making, generalization, neural networks, neuroimaging
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 Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neurosci Unit
URI: https://discovery.ucl.ac.uk/id/eprint/10166617
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