We are leveraging our research findings to inform and improve existing treatments and explore new avenues for prevention and intervention. We aim to inform clinicians about behavioral, physiological and neural mechanisms that determine whether a treatment will —or will not—be most effective for autistics.
Interventions that have been shown to produce changes in the neural underpinnings of social information processing include virtual reality cognition training (Yang et al., 2018) and oxytocin treatment (Gordon et al., 2016).
Currently we are validating the effectiveness of the following interventions:
- Interactive robot intervention: Following promising findings in using robots to teach autistic children how to recognize emotional cues (Jeon et al., 2015; Javed et al., 2018), Dr. Chung-Hyuk Park is in the process of designing a study that would integrate music alongside the use of robots to enhance multimodal emotion processing in autistic children. The study will also serve to teach autistic children how to react appropriately to situations that would normally trigger a sensory overload by using the robot’s reactions as a model for correct behavior.
- In light of the promising early results of experiments with oxytocin treatment (Gordon et al, 2016), ANDI has received a grant to conduct a double-blind clinical trial testing the effectiveness of oxytocin therapy when used in conjunction with pivotal response treatment (PRT). PRT is a naturalistic treatment, which emerged out of applied behavior analysis. PRT has been previously shown to have positive effects on the development of social skills in autistic children. It is expected that oxytocin treatment will further enhance those effects by enabling increased activity in neural networks specialized for social information processing.
Brian J, Doyle-Thomas K, Baribeau D, Anagnostou E (2016) Novel mechanisms and treatment approaches in autism spectrum disorder.
Gordon I, Jack A, Pretzsch CM, Vander Wyk BC, Leckman JF, Feldman R, Pelphrey KA (2016) Intranasal oxytocin enhances connectivity in the neural circuitry supporting social motivation and social perception in children with autism. Sci Rep.
Javed H, Jeon M, Howard A, Park CH (2018) Robot-Assisted Socio-Emotional Intervention Framework for Children with Autism Spectrum Disorder. In: Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, pp 131–132 HRI ’18. New York, NY, USA: ACM. Available at: http://doi.acm.org/10.1145/3173386.3177082.
Jeon M, Zhang R, Lehman W, Fakhrhosseini S, Barnes J, Park CH (2015) Development and Evaluation of Emotional Robots for Children with Autism Spectrum Disorders. In: HCI International 2015 - Posters’ Extended Abstracts (Stephanidis C, ed), pp 372–376. Cham: Springer International Publishing.
Shattuck PT, Narendorf SC, Cooper B, Sterzing PR, Wagner M, Taylor JL (2012) Postsecondary Education and Employment Among Youth With an Autism Spectrum Disorder. Pediatrics.
Smith LE, Greenberg JS, Mailick MR (2012) Adults with autism: Outcomes, family effects, and the multi-family group psychoeducation model. Curr Psychiatry Rep.
Yang D, Pelphrey KA, Sukhodolsky DG, Crowley MJ, Dayan E, Dvornek NC, Venkataraman A, Duncan J, Staib L, Ventola P (2016) Brain responses to biological motion predict treatment outcome in young children with autism. Transl Psychiatry.
Yang YJD, Allen T, Abdullahi SM, Pelphrey KA, Volkmar FR, Chapman SB (2018) Neural mechanisms of behavioral change in young adults with high-functioning autism receiving virtual reality social cognition training: A pilot study. Autism Res.