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Real-time sentence processing in children with specific language impairment: The contribution of lexicosemantic, syntactic, and world-knowledge information

Published online by Cambridge University Press:  21 December 2011

FABRIZIO PIZZIOLI
Affiliation:
Université Catholique de Louvain
MARIE-ANNE SCHELSTRAETE*
Affiliation:
Université Catholique de Louvain
*
ADDRESS FOR CORRESPONDENCE Marie-Anne Schelstraete, Institut de Recherche en Sciences Psychologiques, Université Catholique de Louvain, 10, Place Cardinal Mercier, B-1348 Louvain-La-Neuve, Belgium. E-mail: marie-anne.schelstraete@uclouvain.be
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Abstract

The present study investigated how lexicosemantic information, syntactic information, and world knowledge are integrated in the course of oral sentence processing in children with specific language impairment (SLI) as compared to children with typical language development. A primed lexical-decision task was used where participants had to make a lexical decision on the last word of a sentence. Thirty-nine children were tested: 13 children with SLI, 13 younger children matched on receptive vocabulary, and 13 age-matched children. We manipulated (a) the semantic fit between the target and the prime sentence, (b) the syntactic structure of the prime (syntactic vs. asyntactic), and (c) the lexical association between the target word and the prime. Despite being slower overall, children with SLI showed a significant priming effect. Syntactic information had a similar impact on thematic integration in control children and children with SLI, although the latter were more sensitive to lexicosemantic association and world knowledge than control groups. In addition, children with SLI appeared to use semantic information even when the sentence was asyntactic. The results suggest thematic integration problems in SLI: syntactic and semantic information contribute independently to the thematic structure but are not integrated to generate the emerging higher order representation.

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Articles
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Copyright © Cambridge University Press 2011
Figure 0

Figure 1. A sentence processing computational model. Adapted from “Aphasic Sentence Comprehension as a Resource Deficit: A Computational Approach,” by H. J. Haarmann, M. A. Just, and P. A. Carpenter, 1997. Brain and Language, 59. Copyright 1997 by Elsevier. Adapted with permission.

Figure 1

Table 1. Individual age, nonverbal IQ (IQ-P), and receptive vocabulary scores (EVIP) for children with SLI and mean for RVC and AC

Figure 2

Figure 2. Mean reaction times (ms) for correct responses for the three tasks of age-control children (AC), receptive vocabulary matched children (RVC), and children with SLI.

Figure 3

Table 2. Examples of sentences for each condition

Figure 4

Figure 3. Magnitude of priming (ms) for each condition for age matched children (AC), receptive vocabulary matched children (RVC), and children with SLI in the four experimental conditions. The asterisks indicate that the response times in the experimental condition were significantly shorter than in the baseline condition.

Figure 5

Table 3. Magnitude of priming (ms) and standard deviations for children with SLI as a function of condition and as compared to AC and RVC