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  • Journal of the International Neuropsychological Society, Volume 14, Issue 6
  • November 2008, pp. 956-966

Neurocognitive predictors of social and communicative developmental trajectories in preschoolers with autism spectrum disorders

  • JEFFREY MUNSON (a1) (a2), SUSAN FAJA (a1) (a3), ANDREW MELTZOFF (a3) (a4), ROBERT ABBOTT (a1) (a4) and GERALDINE DAWSON (a1)
  • DOI: http://dx.doi.org/10.1017/S1355617708081393
  • Published online: 27 October 2008
Abstract
Abstract

Currently, the heterogeneity in the developmental trajectories of autism spectrum disorders (ASD) is poorly understood. Preschool children with ASD participating in a longitudinal study received a battery of neurocognitive tasks that measured the learning of reward associations (Lrn-Rew), spatial working memory (SpatWM), and imitation from memory and novelty preference (Mem/Nov), as well as a measure of nonverbal problem-solving ability (NVDQ). Growth curve analyses via HLM were used to predict the variability in growth rates between age 4 to age 6.5 in Vineland Socialization and Communication scores. Individual differences in both Lrn-Rew and Mem/Nov were significantly related to Socialization and Communication growth rates above and beyond NVDQ, whereas SpatWM was not. Thus, specific aspects of neurocognitive functioning appear to be important predictors of developmental variability during the preschool years in children with ASD. We speculate that these findings support the combined role of ventromedial prefrontal and medial temporal lobe systems in the early pathogenesis of ASD and may be useful in predicting developmental trajectory. The benefits and challenges of assessing specific neurocognitive functions in children with autism is discussed with regard to general cognitive/developmental ability and the behavioral requirements of most assessment settings. (JINS, 2008, 14, 956–966.)

Copyright
Corresponding author
Correspondence and reprint requests to: Jeffrey Munson, UW Autism Center, Box 357920, University of Washington, Seattle, WA 98195. E-mail: jeffmun@u.washington.edu
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