Behavioral and neural underpinnings of learning in autism predict response to intervention
Weill Medical College of Cornell University
Early intervention is considered critical for the treatment of Autism Spectrum Disorders (ASD). Yet, recent reports suggest that there is significant variability in how children respond to classic behavioral intervention programs. Two distinct learning pedagogies are the foundation of most behavioral interventions: associative and reinforcement learning, but there is little understanding of whether there are differences in the behavior and neural systems of children with ASD in these learning domains. Novel paradigms appropriate for children as young as 2 years old, will be developed to delineate fundamental learning skills as differentiated between developmentally delayed (DD) and children with ASD. A cohort of children with ASD will be treated with a modified version of the Early Social Interaction – Community Outreach (ESI-CO) intervention and after 3 and 6 months to determine if improvement, measured with ADOS-Change social communication scores, is predicted by abilities on the learning paradigms. A cohort of Typically Developing (TD), DD and children with ASD (4-6yrs) will be tested, in parallel, with neuroimaging to determine the preliminary neural underpinnings of these learning mechanisms. Resting state functional connectivity and Diffusion Tensor Imaging (DTI) will be used to provide a comprehensive understanding of any changes which may be observed in learning related neural circuitry in ASD versus TD and DD. These studies will provide the foundation to examine learning in animal models of ASD. To understand the behavioral and neural basis of learning in ASD, a translational approach is utilized to create a novel tool to individualize interventions, measure the effectiveness of treatment and improve patient care and outcome. To accomplish these research objectives, mentoring will involve a unique multidisciplinary team in order to facilitate the development of novel instruments that will directly assess learning in ASD and provide training in the theoretical and methodological analyses for interpreting the three complementary measures of neuroimaging data. The training gained in this program of research would enable the fellow to pursue a career as an independent scientist in the field of the neuroscience of ASD.