Poster E47, Saturday, August 18, 3:00 – 4:45 pm, Room 2000AB
Explicit synchrony of speech and gestures in autism spectrum disorder
Inge-Marie Eigsti1, Wim T. J. L. Pouw1;1University of Connecticut
Individuals with autism spectrum disorder (ASD) have difficulty with the temporal coordination of gestures with speech (Canfield & Eigsti, 2016; de Marchena & Eigsti, 2010; Silverman et al., 2010). Such impairments could primarily reflect language deficits (Kelly, Ozyurek, & Maris, 2010) or motor control deficits (e.g., McAuliffe et al., 2017; Vanvuchelen, Roeyers, & De Weerdt, 2007). This study examines the production of co-speech ‘beat’ gestures within a sensorimotor synchronization framework (Repp, 2005). Results are informative about a) the source of gesture impairments in ASD and b) individual differences in speech-gesture synchrony. Participants were adolescents ages 11-17 with ASD (n=9) or typical development (TD; n=10), and 11 TD adults. ASD/TD adolescents did not differ in age, nonverbal IQ, gender, or standardized language scores, p’s>.15. All participants completed a sensorimotor integration task in which they recited six nursery rhymes (Jack Sprat could eat no fat, etc.). They were told to simultaneously "beat" along with their writing hand, as if hammering a hammer. Performance was digitally recorded for subsequent coding. Adolescents also completed standardized assessment of executive functions, including D-KEFS Verbal Fluency (generate items in a semantic category). To date, one rhyme has been analyzed (Jack Sprat); final analyses will include all six rhymes. We obtained a pixel change time series from the video data (25f/s) using frame differencing (Brookshire et al., 2017; Romero et al., 2017). Beat gestures were identified from this time series in ELAN (Crasborn et al., 2006). The apex of the downbeat was operationalized as the peak deceleration of pixel change. For each downbeat, the pitch (F0) peak of the temporally-closest voiced speech event was determined. Each speech-gesture pairing yielded a temporal difference score (peak deceleration to peak pitch). All groups produced a similar number of beat gestures; ASD-adolescents M = 16.22, TD-adolescents = 15.09, Adults = 16.09. A mean negative asynchrony was observed in all groups (e.g, beat peaks preceded spoken pitch peaks): ASD-adolescents M(SD)=-66(43) ms; TD-adolescents -52(29) ms; adults -16(27) ms. Group was a significant predictor for gesture-speech synchrony (lme regression analysis), 2(5)=9.06, p=.01. Both adolescent groups differed from adults, and TD-adolescents asynchrony fell midway between (ASD vs. adults, p=.006; TD vs. adults, p=.02; ASD vs. TD, p=.61). Asynchrony was correlated with verbal fluency at the trend level, r(18)=-.42, p=.09; greater fluency tended to be associated with more synchronicity. In this small sample, asynchrony was not correlated with ASD severity. The current study extends the literature on gestures and sensorimotor synchronization by studying explicit synchrony in ASD, a disorder characterized by impairments in gesture production. Rather than tapping to an external beat, participants gestured with a self-generated spoken rhythm. These preliminary results suggest significantly greater asynchrony in adolescents compared to adults, and raise the possibility of increased asynchrony in ASD. This pattern of results suggest that motor control deficits may play a critical role in gesture impairments in ASD.
Topic Area: Language Disorders