A Dynamic and Process-Oriented Approach Provides Insights for Identifying Behavioral and Neural Mechanisms of Social Interaction in Autism

Background: Social interactions typically involve movements of the body that become synchronized over time and both intentional and spontaneous synchrony have been found to be important in human interaction. However, our understanding of the temporal dimensions of social synchrony and its role in social interaction and communication is limited and identification of an objective, bio-behavioral marker for ASD and isolation of underlying mechanisms have been elusive. Methodologies that investigate the dynamic process as how social interactions unfold hold much promise for providing measures with heightened temporal resolution to better index social performance and isolate underlying mechanisms.

Objectives: In Study 1 we compared synchronization ability of adolescents with and without ASD and examined the relationship between social cognition, clinical measures of attention and social responsiveness, and social synchrony. In Study 2 we evaluated differences in neural activity for intentional and spontaneous synchronization in healthy controls to establish an EEG methodology to be used with ASD participants.

Methods: A social movement task that involved swinging a hand-held pendulum and measured wrist movement using goniometers was employed in both studies. In spontaneous coordination, participants swung at his/her own tempo while looking at their partner’s pendulum and in intentional coordination participants synchronized the movements of their pendulums. In Study 1, social cognition was assessed using Frith-Happe´ theory of mind (ToM) animations, the Social Responsiveness Scale, and Autism Diagnostic Observation Schedule. Attention was measured using the Child Behavior Checklist ADHD raw score. There were nine adolescent (12-17 years)-parent pairs in the ASD group and nine age-matched healthy control (HC) pairs. In Study 2, we measured EEG activity at multiple frequency bands as well as social synchrony in seven HC, young adult pairs.

Results: In Study 1 we found that adolescents with ASD demonstrated significantly less synchronization in both spontaneous and intentional tasks. Results also revealed that spontaneous synchrony was related to ToM and intentional synchrony was related to clinical measures of attention and social responsiveness. Facial emotion recognition was not related to either ToM or social synchrony. In Study 2 we found evidence for mu enhancement for spontaneous coordination while mu suppression was found for intentional coordination (both in phase and anti-phase). In addition, higher levels of synchronization were significantly associated with higher levels of mu suppression in the right hemisphere. Through a combination of network theory and topological analysis, we also found consistent clusters of electrodes across synchrony conditions and frequency bands.

Conclusions:

The findings suggest that the processes underlying spontaneous synchrony in ASD are different than the processes underlying difficulties in intentional synchronization, and the two types of synchronization may have different underlying neural circuitry. Our findings also highlight the importance of attention for more fully understanding the social behavior characteristic of ASD. Preliminary data comparing the EEG activity of adolescents with and without ASD will also be presented. The implication of these findings for isolating behavioral and neural measures that may provide an objective bio-behavioral marker for ASD that could lead to better classification and targeted treatments will be discussed.