Publications
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and restricted and repetitive patterns of behavior. Autism is estimated to affect 1 in 59 children in the United States and costs roughly $35 billion dollars to the society. Read more “Deep Learning Based Multimedia Data Mining for Autism Spectrum Disorder (ASD) Diagnosis”
Publications
Abstract Although difficulties with social relationships are key to autism spectrum disorder (ASD), no previous study has examined infant attachment security prior to ASD diagnosis. We prospectively assessed attachment security at 15 months in high‐risk infants with later ASD (high‐risk/ASD, n = 16), high‐risk infants Read more “Attachment Security Differs by Later Autism Spectrum Disorder: A Prospective Study”
Publications
Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with different genetic etiologies. Prospective examination of familial-risk infants informs understanding of developmental trajectories preceding ASD diagnosis, potentially improving early detection. Read more “Developmental Trajectories of Infants with Multiplex Family Risk for Autism: A Baby Siblings Research Consortium Study”
Publications
Behavioral assessments remain the gold standard for autism spectrum disorder (ASD) diagnosis, and prospective analysis permits objective and longitudinal assessment for the earliest symptoms. Published estimates of sibling recurrence for ASD range from 6.9 to 19.5%. Read more “Predictive Impact of Rare Genomic Copy Number Variations in Siblings of Individuals with Autism Spectrum Disorders”
Publications
Children with autism spectrum disorder (ASD) exhibit significant difficulties with emotion regulation and reactivity, which may be linked to underlying psychophysiology. The present study examined associations between autonomic nervous system activity and individual differences in externalizing behavior problems in children with ASD. Read more “Sympathetic-Parasympathetic Interaction and Externalizing Problems in Children with Autism Spectrum Disorder”
Publications
Atypical head movement pattern characterization is a potentially important cue for identifying children with autism spectrum disorder. In this paper, we implemented a computational framework for extracting the temporal patterns of head movement and utilizing the imbalance of temporal pattern distribution between diagnostic categories (e.g., children with or without autism spectrum disorder) as potential diagnostic cues. Read more “Categorical Timeline Allocation and Alignment for Diagnostic Head Movement Tracking Feature Analysis”