A Dynamic Approach to Measuring Temporal Binding Windows in Adults with Autism Spectrum Disorder: Differences with the Commonly Used Synchrony Judgement Task

Background: Being able to integrate information from multiple sensory modalities, such as hearing and sight, is essential for everyday functioning. Individuals with autism spectrum disorder (ASD) have difficulties in audiovisual integration (e.g., Bahrick, 2010; Bebko et al., 2006). These difficulties likely contribute to their social-communicative deficits (Wallace & Stevenson, 2014) and therefore, a better understanding of audiovisual integration in ASD could hold valuable information for interventions.

A way of measuring audiovisual integration is through the temporal binding window (TBW); a window of time in which separate sensory information are perceived as one, synchronous event, despite some degree of asynchrony (Dixon & Spitz, 1980). A common way to measure the TBW is the synchrony judgment (SJ) task (Exner, 1875), where participants decide whether audio and visual components of a stimulus are synchronous or not. The SJ task could be considered “static” as it does not enable a dynamic manipulation of the TBW size. In the current study a method developed by Segers & Bebko (2013) allowing active manipulation of the auditory timing was used to more precisely measure the audiovisual TBW.

Objectives: To build on previously-presented work at INSAR by Segers & Bebko (2013), by using a more refined version of the new “dynamic” method. Specific objectives include: a) how does the TBW of ASD adults compare to non-ASD adults across the new dynamic task and the commonly used static SJ task, and b) determining what can influence TBW size in ASD.

Methods: Data from 21 TD and 11 ASD adults have been collected and analyzed, with additional ASD participants nearing completion. Participants performed two types of audiovisual integration tasks: a) the dynamic task, where participants manually adjusted the soundtrack of a video by 50ms increments until a point of perceived synchrony with the visual information, and b) the SJ task. Two stimulus types were used: social-linguistic (SL: someone reading a story), and non-social-non-linguistic (NSNL: e.g., a hand playing the piano). Participants also completed questionnaires on sensory information and autism-like traits.

Results: A 2-way-repeated-measures ANOVA yielded significant main effects of task, F(1,25) = 19.85, p < 0.01, and stimulus type, F(1,25) = 28.05, p < 0.01. When using the dynamic task, participants produced significantly smaller TBWs (M = 377ms) than when using the SJ task (M =522ms). Furthermore, smaller TBWs were produced for SL stimuli (M =405ms) compare to NSNL stimuli (M = 493ms). In contrast to previous studies, there was no significant difference in the TBW size between ASD and TD participants across the tasks (p >.10).

Conclusions: Giving participants the ability to control the soundtrack appears to produce smaller TBWs in both ASD and TD participants and may lead to more precise measurement of the TBWs than more passive, static tasks. It is possible that helping to focus the participants’ attention to the task by requesting them to actively manipulate the audio file was sufficient to help ASD participants overcome underlying audiovisual integration issues. This nonverbal dynamic procedure offers considerable promise for research into perceptual systems in ASD.