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An Interdisciplinary Journal of the Language Sciences

Editor-in-Chief: Gast, Volker

IMPACT FACTOR 2018: 1.066

CiteScore 2018: 0.97

SCImago Journal Rank (SJR) 2018: 0.384
Source Normalized Impact per Paper (SNIP) 2018: 1.409

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Volume 47, Issue 5


Acquisition of aspect in self-organizing connectionist models

Xiaowei Zhao / Ping Li
Published Online: 2009-09-15 | DOI: https://doi.org/10.1515/LING.2009.038


Two connectionist networks, DISLEX and DevLex-II, were used in this study to model the acquisition of lexical and grammatical aspect. Both models use multi-layered self-organizing feature maps, connected by associative links trained according to the Hebbian learning rule. Previous empirical research has identified a strong association between lexical aspect and grammatical aspect in child language, on the basis of which some researchers argue for innate semantic categories or prelinguistic predispositions. Our simulations indicate that such an association can emerge from dynamic self-organization and Hebbian learning in connectionist networks, without the need of a priori assumptions about the structure of innate knowledge. Our modeling results further attest to the utility of self-organizing neural networks in the study of language acquisition.

About the article

Department of Psychology, Pennsylvania State University, 614 Moore Building; University Park, PA 16802-3106, USA. E-mail:

Received: 2006-03-07

Revised: 2006-10-29

Published Online: 2009-09-15

Published in Print: 2009-09-01

Citation Information: Linguistics, Volume 47, Issue 5, Pages 1075–1112, ISSN (Online) 1613-396X, ISSN (Print) 0024-3949, DOI: https://doi.org/10.1515/LING.2009.038.

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