ArticleProceedings of the National Academy of Sciences of the United States of America2024
Decomposing dynamical subprocesses for compositional generalization.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The compositionality continuum as a principle for studying the neural basis of intelligence.Nature neuroscience · 2026Review
- Memory reactivation during sleep promotes structure abstraction.bioRxiv : the preprint server for biology · 2026Article
- Building hierarchically nested structure by rapid neural sequences.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Neural evidence that humans reuse strategies to solve new tasks.PLoS biology · 2025Article
- Humans learn generalizable representations through efficient coding.Nature communications · 2025Article
- Decomposing dynamical subprocesses for compositional generalization.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Cognitive Graphs: Representational Substrates for Planning.Decision (Washington, D.C.) · 2024Article
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Authors and funding
7 authors.
Funding
Abstract
A striking feature of human cognition is an exceptional ability to rapidly adapt to novel situations. It is proposed this relies on abstracting and generalizing past experiences. While previous research has explored how humans detect and generalize single sequential processes, we have a limited understanding of how humans adapt to more naturalistic scenarios, for example, complex, multisubprocess environments. Here, we propose a candidate computational mechanism that posits compositional generalization of knowledge about subprocess dynamics. In two samples (
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