Functional Connectivity Analysis of Children With Autism Under Emotional Clips

Abstract

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with marked impairments in neural system functioning. Electroencephalography (EEG) offers a promising approach to investigate the neurophysiological basis of ASD, however, most EEG studies in ASD focus on spontaneous brain activity. Emotional processing deficits are a core feature of ASD, but related connectivity patterns remain underexplored due to challenges in data collection and analysis. This study investigates functional brain connectivity differences between children with ASD (n = 32) and typically developing (TD) children (n = 32) across five frequency bands and four connectivity indices. We designed an SVM-MRMR pipeline to classify ASD and TD children using these features. Our findings reveal that ASD children exhibit more coordinated intra-brain networks and oscillatory patterns in the high-frequency range. Additionally, they show an increased number of long-range connections in the Theta band, particularly between the left and right hemispheres. ASD children also demonstrate increased frontal lobe connectivity during positive emotions and heightened temporal lobe activity during negative emotions. Functional connectivity under positive and negative emotional clips achieved a classification accuracy exceeding 85%. These findings suggest that functional connectivity derived from portable EEG devices may serve as a potential biomarker for diagnosing and classifying ASD in real-world applications.