Network analysis of emerging vocabularies reveals different developmental trajectories in children with autism spectrum disorders
Network analyses of typical language development indicate that words associated with many other words are acquired earlier, implying that typically developing (TD) children are sensitive to the semantic structure of their environment. Children with autism spectrum disorders (ASD) often lag behind their TD peers with respect to language acquisition, despite relatively spared statistical learning and fast-mapping skills. Recent work indicates that children with ASD may struggle with processing the semantic relationships that are the basis for word meaning. We acquired parent-report vocabulary checklists (Communicative Development Inventory; CDI) for 203 ASD children aged 11 – 173 months from the National Database of Autism Research and for 1,096 vocabulary matched TD children aged 11 – 30 months from WordBank to establish vocabulary composition. To estimate the semantic structure of these vocabularies, we referenced child-oriented word association data to construct an associative network from each child’s vocabulary. Network structure statistics were modeled as a function of group (TD/ASD) and vocabulary size (linear, quadradic, and cubic trends). Network structure developed along different trajectories for each group as vocabularies grew. This began early in vocabulary acquisition, with vocabularies in the ASD group developing clusters more rapidly than the TD group until acquiring about 150 words. After that point, network statistics converged between groups as vocabularies become more similar (i.e., they begin to saturate the CDI wordlist). This suggests that children with ASD have a distinctive trajectory of vocabulary growth that, relative to TD children, is more oriented towards clusters of semantically related words early in language acquisition.