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Rule Learning by Seven-Month-Old Infants
Abstract
A fundamental task of language acquisition is to extract abstract algebraic rules. Three experiments show that 7-month-old infants attend longer to sentences with unfamiliar structures than to sentences with familiar structures. The design of the artificial language task used in these experiments ensured that this discrimination could not be performed by counting, by a system that is sensitive only to transitional probabilities, or by a popular class of simple neural network models. Instead, these results suggest that infants can represent, extract, and generalize abstract algebraic rules.
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Cited by
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Hauser, M. D., Chomsky, N., & Fitch, W. T. (2002) · Science · doi:10.1126/science.298.5598.1569 · Cited by 5,189
Understanding and sharing intentions: The origins of cultural cognition
Tomasello, M., Carpenter, M., Call, J., Behne, T., & Moll, H. (2005) · Behavioral and Brain Sciences · doi:10.1017/s0140525x05000129 · Cited by 4,882
Early language acquisition: cracking the speech code
Kuhl, P. K. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1533 · Cited by 2,291
Toward a second-person neuroscience
Schilbach, L., Timmermans, B., Reddy, V., Costall, A., Bente, G., Schlicht, T., & Vogeley, K. (2013) · Behavioral and Brain Sciences · doi:10.1017/s0140525x12000660 · Cited by 1,510
Kuhl, P. K., Tsao, F.-M., & Liu, H.-M. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1532872100 · Cited by 1,237
Metadata
- Authors
- Marcus, G. F., Vijayan, S., Bandi Rao, S., & Vishton, P. M.
- Venue
- Science
- Published
- 1999-01
- Volume
- 283
- Issue
- 5398
- Pages
- 77-80
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W1979539191
- Cited by
- 1,244
- References
- 0
- FWCI
- 66.60
- Type
- journal article
- Language
- en
- Open access
- closed
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- Marcus, G. F., Vijayan, S., Bandi Rao, S., & Vishton, P. M. (1999). Rule Learning by Seven-Month-Old Infants. Science. https://doi.org/10.1126/science.283.5398.77
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
