Fractal Analysis of Autonomic Nervous System Function in ASD

Thursday, May 14, 2015: 11:30 AM-1:30 PM
Imperial Ballroom (Grand America Hotel)
H. Saghir1,2, T. Chau2,3 and A. Kushki2,4, (1)Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada, (2)Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada, (3)Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada, (4)Autism Research Centre, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
Background:  Emerging evidence suggests that autism spectrum disorder (ASD) may be associated with dysfunction of the autonomic nervous system (ANS). However, it remains unclear how the observed atypicalities are related to atypicalities in individual branches of the ANS (sympathetic versus parasympathetic). The interplay between these two branches is particularly challenging to investigate as the nonlinear relationship between the activity of the two branches of the autonomic nervous system challenges the reliability of commonly used linear tools (e.g., HRV spectrum analysis).  In this paper, we employ fractal analysis of cardiac interbeat intervals to investigate this issue. In typical populations, fractal analysis have revealed the presence of long-range, power-law correlations in this time series which are altered with disease and aging. Fractal analysis of cardiac signals in ASD have not been reported to date. This new approach to analysis ANS function may provide further insight on the nature of these atypicalities.

Objectives: To investigate ASD-related alterations in the fractal structure of interbeat intervals during baseline and response to an anxiogenic stimulus.

Methods: A sample of typically-developing children (n=33, age: 12.5 +/-2.9 years, full-scale IQ: 112.9 +/- 14.1, 19 male), and those with a diagnosis of ASD (n=40, age: 12.0 +/- 2.9 years, full-scale IQ: 92.9 +/- 20.6, 33 male) completed an anxiogenic task (Stroop test),  preceded and followed by a 15-minute and 5-minute baseline task (movie watching), respectively. Throughout the experimental session, electrocardiogram (ECG) was measured and used to extract inter-beat interval time-series. Deterended fluctuation analysis (DFA) was used to obtain the scaling exponent, an index of complexity in the signal. Repeated measures multiple regression analysis was performed to examine the effect of group and group x time interaction on the scaling exponent while controlling for age, gender, and full-scale IQ.

Results: Multiple regression analysis revealed a significant group x time interaction for the scaling exponent (p=0.04 ) (Figure 1), suggesting atypical fractal dynamics in the ASD group.

Conclusions: Our results suggest that ASD may be associated with atypical fractal structure in the cardiac interbeat sequences.  Specifically, the results point to altered, and possibility decreased, flexibility and adaptability of the autonomic response in ASD. This study adds to the body of evidence supporting atypical ANS function in ASD. Future studies with longer time-series are needed to further characterize the nature of nonlinear atypicalities in this domain.