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Category induction via distributional analysis: Evidence from a serial reaction time task
- Source :
- Journal of Memory and Language. Feb, 2010, Vol. 62 Issue 2, p98, 15 p.
- Publication Year :
- 2010
-
Abstract
- To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jml.2009.10.002 Byline: Ruskin H. Hunt, Richard N. Aslin Keywords: Statistical learning; Category induction; Serial reaction time; Distributional analysis; Artificial grammar Abstract: Category formation lies at the heart of a number of higher-order behaviors, including language. We assessed the ability of human adults to learn, from distributional information alone, categories embedded in a sequence of input stimuli using a serial reaction time task. Artificial grammars generated corpora of input strings containing a predetermined and constrained set of sequential statistics. After training, learners were presented with novel input strings, some of which contained violations of the category membership defined by distributional context. Category induction was assessed by comparing performance on novel and familiar strings. Results indicate that learners develop increasing sensitivity to the category structure present in the input, and become sensitive to fine-grained differences in the pre- and post-element contexts that define category membership. Results suggest that distributional analysis plays a significant role in the development of visuomotor categories, and may play a similar role in the induction of linguistic form-class categories. Author Affiliation: Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627, United States Article History: Received 28 August 2008; Revised 16 October 2009
- Subjects :
- Education
Languages and linguistics
Psychology and mental health
Subjects
Details
- Language :
- English
- ISSN :
- 0749596X
- Volume :
- 62
- Issue :
- 2
- Database :
- Gale General OneFile
- Journal :
- Journal of Memory and Language
- Publication Type :
- Academic Journal
- Accession number :
- edsgcl.216857782
- Full Text :
- https://doi.org/10.1016/j.jml.2009.10.002