The first step toward reconstructing visual perception and cognition in Autism

Currently in the United States, the most commonly diagnosed developmental disorder in young children is Autism Spectrum Disorder (ASD). ASD is a neurodevelopmental syndrome marked by qualitative impairments of social communication skills and restricted, repetitive patterns of behavior. However, due to the heterogeneous nature of the disorder, to date existing therapies/interventions for children with ASD have failed to identify why some subjects with ASD experience more positive response to therapies than others. Additionally, there is the lack of consensus on how to identify and evaluate scientifically valid and effective interventions. The contribution of this work is to investigate a computational model driven intervention technology to ease subjects´ anxiety when facing a new situation, e.g., dental visit. Via this computational model, we can explain why subjects with ASD do not positively respond to the intervention. Our experimental results show our proposed approach can shed the light on the development of mathematical modeling for visual perception and cognition in individuals with ASD.