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Publication Detail
Neural knowledge assembly in humans and neural networks
  • Publication Type:
    Journal article
  • Authors:
    Nelli S, Braun L, Dumbalska T, Saxe A, Summerfield C
  • Publisher:
    Elsevier BV
  • Publication date:
  • Journal:
  • Status:
  • Country:
    United States
  • PII:
  • Language:
  • Keywords:
    Abstraction, continual learning, decision making, generalization, neural networks, neuroimaging
  • Notes:
    © 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/).
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.
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