A preliminary study of brain connectivity in autism using affection-evoked movie clips

Recent study have shown that electroencephalogram (EEG) is an effective and efficient strategy to analyze the abnormality of children with autism. Much of the work on Autism Spectrum Disorders (ASD) focused on analysing simple features of EEG signals and using them for classification problems. How-ever, there is growing evidence that ASD is a psychiatric disorder in which the brain is abnormally connected functionally and brain areas do not communicate properly with each other. In this paper, we explore the brain functional connectivity of children with autism by comparing the difference between children with ASD and typically developing children (TD). Specifically, we collect EEG data from 62 children (31 ASD, 31 TD) under affection-evoked movie clips, and compute the brain functional connectivity using four commonly-used connectivity models (i.e., Coherence, Phased Lag Index, Weighted Phased Lag Index, Phase Locking Value) in five different frequency bands (theta (4–8 Hz), alpha (8–12 Hz), low beta (12–16 Hz), high beta (16–25 Hz), and gamma (25–45 Hz)). Then we compare the difference by using statistical analysis in each frequency band. The results indicate that difference in brain functional connectivity in children with ASD and TD are existed in all five frequency bands, which shows a potential as the biomarker for diagnosis and classification of ASD.