No abstract

Background: Knowing the development pattern of children’s language is applicable in developmental psychology. Network models of language are helpful for the identification of these patterns. Objectives: We examined the small-world properties of featured semantic networks of developing children. Materials & Methods: In this longitudinal study, the featured semantic networks of children aged 18-30 months were obtained using R software version 3.5.2 and the igraph software package. The data of 2000 English (British)-speaking children, half boy and half girls, were gathered from existing databases of MCDI (between 2000 and 2007) and McRae feature norms. The growth pattern of these networks was illustrated by graph measures. Comparing these measures with those of the reference random networks, the small-world structure can be examined. Results: To have a comparison between path length and clustering coefficient of featured semantic networks with those of random networks, we computed the Q quotient. The results showed that the values of the Q quotient at 18, 22, 26, and 30 months of age were all more than 1, which confirms the small-world characteristic of the networks. Conclusion: Featured semantic networks of children exhibited a small-world structure, in which there was a local structure in the form of clusters of words. For global access, some words act as bridges connecting semantically distant clusters. These networks possess small-world property from the early months of age. The small-world structure cannot be seen in the less dense networks built with a higher cut-off threshold.

Autism Spectrum Disorders (ASD) refers to a wide range of circumstances characterized by challenges with social skills, repetitive behaviours, language, and nonverbal communication. While structural language is known to vary broadly in children with ASD, pragmatic language has been claimed to be consistently impaired within this population. To have a better understanding of the language development and the related impairments, "dynamical systems theory" can be helpful. Language development, as a dynamical system, has a trajectory of variations. For the autistic individuals, we hypothesize that this trajectory reaches a bottleneck in higher-level aspects of language like pragmatics. Language development trajectory of autistic children typically passes the lower-level aspects of language such as semantic/lexicon processing. But, it slows down when reaches the higher levels like pragmatics and traps in a bottleneck. It means that the trajectory spends lots of time in this stage and cannot fully complete the stage to acquire the pragmatic competence. The time that the developmental trajectory spends in the bottleneck is related to the environmental and social conditions of the children with ASD. Appropriate intervention packages, can lower the trapping time in bottleneck by improving social and environmental circumstances and making the trajectory faster.