Neurotherapy to Promote Emotion Recognition in Autism
Overview
- Phase
- N/A
- Intervention
- Not specified
- Conditions
- Autism Spectrum Disorder
- Sponsor
- Virginia Polytechnic Institute and State University
- Enrollment
- 28
- Locations
- 1
- Primary Endpoint
- facial emotion recognition (RMET)
- Status
- Completed
- Last Updated
- 5 years ago
Overview
Brief Summary
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder, more prevalent than previously thought and heterogeneous in expression, though uniformly characterized by severe social disability. The social disability that defines ASD pervades other areas of adaptive behavior, is predictive of secondary mental health problems, and adversely affects long-term outcome. Although ASD is a chronic condition, there has been little research on interventions for adults with ASD. This study proposes to first establish the neural plasticity of specific brain mechanisms underlying difficulties with facial emotion recognition, a core deficit believed to be pivotal in the behavioral expression of ASD-social disability. The investigators will then develop a novel, computer-based intervention using real-time feedback, to the user, to ameliorate emotion recognition deficits.
Detailed Description
Individuals with autism spectrum disorder (ASD) are known to have difficulty in the recognition of facial emotion. Such deficits in facial emotion recognition (FER) are thought to cause or exacerbate social disability in ASD by preventing 1) accurate detection of social/emotional information conveyed through the face and, subsequently 2) the deployment of emotionally appropriate responses. Consistent with this model, FER deficits are correlated with social disability in ASD and confer morbidity above and beyond core symptoms. The long-term goal is to understand how FER networks can be manipulated for therapeutic and preventative purposes. In this trial, investigators are testing the feasibility of an intervention that capitalizes on our previously developed brain-computer interface (BCI) to promote FER in a mixed virtual reality world. The new "FER Assistant" tool (deployed on a tablet - iPad) is intended to aid users in detecting emotions and intents of 'avatars' inhabiting a virtual world, and will provide users with a highly realistic testbed for practicing FER skills in concert with BCI.
Investigators
John Richey
Associate Professor
Virginia Polytechnic Institute and State University
Eligibility Criteria
Inclusion Criteria
- •diagnosis of ASD
Exclusion Criteria
- •No severe psychopathology which warrants other immediate treatment
Outcomes
Primary Outcomes
facial emotion recognition (RMET)
Time Frame: 5 weeks
Change in facial emotion recognition 5 weeks after baseline appointment