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Child language and autism diagnosis impact hierarchical temporal structure of parent-child vocal interactions in early childhood.

Olivia A BooromCamila AlviarYumeng ZhangValerie A MuñozChristopher T KelloMiriam D Lense
Published in: Autism research : official journal of the International Society for Autism Research (2022)
Timing is critical to successful social interactions. The temporal structure of dyadic vocal interactions emerges from the rhythm, timing, and frequency of each individuals' vocalizations and reflects how the dyad dynamically organizes and adapts during an interaction. This study investigated the temporal structure of vocal interactions longitudinally in parent-child dyads of typically developing (TD) infants (n = 49; 9-18 months; 48% male) and toddlers with ASD (n = 23; 27.2 ± 5.0 months; 91.3% male) to identify how developing language and social skills impact the temporal dynamics of the interaction. Acoustic hierarchical temporal structure (HTS), a measure of the nested clustering of acoustic events across multiple timescales, was measured in free play interactions using Allan Factor. HTS reflects a signal's temporal complexity and variability, with greater HTS indicating reduced flexibility of the dyadic system. Child expressive language significantly predicted HTS (ß = -0.2) longitudinally across TD infants, with greater dyadic HTS associated with lower child language skills. ASD dyads exhibited greater HTS (i.e., more rigid temporal structure) than nonverbal matched (d = 0.41) and expressive language matched TD dyads (d = 0.28). Increased HTS in ASD dyads occurred at timescales >1 s, suggesting greater structuring of pragmatic aspects of interaction. Results provide a new window into how language development and social reciprocity serve as constraints to shape parent-child interaction dynamics and showcase a novel automated approach to characterizing vocal interactions across multiple timescales during early childhood.
Keyphrases
  • autism spectrum disorder
  • mental health
  • intellectual disability
  • attention deficit hyperactivity disorder
  • healthcare
  • machine learning
  • clinical trial
  • single cell
  • randomized controlled trial
  • deep learning