Multi-scale coordination of distinctive movement patterns during embodied interaction between adults with high-functioning autism and neurotypicals.
by Leonardo Zapata–Fonseca, Dobromir Dotov, Ruben Fossión, Tom Froese, Leonhard Schilbach, Kai Vogeley, & Bert Timmermans
What can analysis of movement patterns tell us about disorders of social interaction? Can analysis of coordination patterns in interaction help us detect different task approaches between persons with high functioning autism (HFA) and neurotypical controls? Using dynamic interaction a minimal virtual environment, the current study shows that in spite of ostensibly comparable task performance in a social interaction task, analyses of underlying movement patterns instead reveal a different approach by persons with HFA, who appear less inclined to sustain mutual interaction over time and instead explore the virtual environment more generally.
Abstract: Autism Spectrum Disorder (ASD) can be understood as a social interaction disorder. This requires researchers to take a “second-person” stance and to use experimental setups based on bidirectional interactions. The present work offers a quantitative description of movement patterns exhibited during computer-mediated real-time sensorimotor interaction in 10 dyads of adult participants, each consisting of one control individual (CTRL) and one individual with high-functioning autism (HFA). We applied time-series analyses to their movements and found two main results. First, multi-scale coordination between participants was present. Second, despite this dyadic alignment and our previous finding that individuals with HFA can be equally sensitive to the other’s presence, individuals’ movements differed in style: in contrast to CTRLs, HFA participants appeared less inclined to sustain mutual interaction and instead explored the virtual environment more generally. This finding is consistent with social motivation deficit accounts of ASD, as well as with hypersensitivity-motivated avoidance of overstimulation. Our research demonstrates the utility of time series analyses for the second-person stance and complements previous work focused on non-dynamical and performance-based variables.
Accepted for publication 21 December 2018, published 11 January 2019, in Frontiers in Psychology, 9:2760. DOI: 10.3389/fpsyg.2018.02760.