Small Semantic Networks in Individuals with Autism Spectrum Disorder Without Intellectual Impairment: A Verbal Fluency Approach

Abstract

AbstractIndividuals with Autism Spectrum Disorder (ASD) experience a variety of symptoms sometimes including atypicalities in language use. The study explored differences in semantic network organisation of adults with ASD without intellectual impairment. We assessed clusters and switches in verbal fluency tasks (‘animals’, ‘human feature’, ‘verbs’, ‘r-words’) via curve fitting in combination with corpus-driven analysis of semantic relatedness and evaluated socio-emotional and motor action related content. Compared to participants without ASD (n = 39), participants with ASD (n = 32) tended to produce smaller clusters, longer switches, and fewer words in semantic conditions (no p values survived Bonferroni-correction), whereas relatedness and content were similar. In ASD, semantic networks underlying cluster formation appeared comparably small without affecting strength of associations or content.