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Meta-learned models as tools to test theories of cognitive development

Published online by Cambridge University Press:  23 September 2024

Kate Nussenbaum Open the ORCID record for Kate Nussenbaum [Opens in a new window]  and
Catherine A. Hartley Open the ORCID record for Catherine A. Hartley [Opens in a new window]
Kate Nussenbaum*
Affiliation:
Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA katenuss@princeton.edu https://www.katenuss.com/
Catherine A. Hartley*
Affiliation:
Department of Psychology, New York University, New York, NY, USA cate@nyu.edu https://www.hartleylab.org/
*
*Corresponding authors.
*Corresponding authors.
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Abstract

Binz et al. argue that meta-learned models are essential tools for understanding adult cognition. Here, we propose that these models are particularly useful for testing hypotheses about why learning processes change across development. By leveraging their ability to discover optimal algorithms and account for capacity limitations, researchers can use these models to test competing theories of developmental change in learning.

Information

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 47 , 2024 , e157
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Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

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