A Computer-Assisted Social Intervention for College Students with ASD: Assessment of Longitudinal Changes in White Matter Integrity in a Small, Randomized Controlled Trial

Background:  

The number of college students with Autism Spectrum Disorders (ASD) enrolled in public and private higher education institutions has been growing steadily over the last several years (White, Ollendick & Bray, 2011). These young adults face considerable interpersonal and daily living obstacles, despite intact cognitive abilities, yet there are no empirically supported interventions to support social and academic function in young adults with ASD.  In the current study, we evaluated the feasibility and preliminary efficacy of a new, computer-based protocol for college students with ASD, along with neuroimaging data before and after treatment. In a pilot randomized controlled trial (n = 8), we evaluated a 12- week, novel virtual-reality brain-computer interface (VRBCI) intervention against a psychosocial intervention of the same duration: College and Living Success (CLS).  All participants (5 males, 3 females) were college undergraduates, free of intellectual disability, and confirmed to have ASD via ADOS. At baseline, we conducted several neuroimaging protocols including anatomical (T1-weighted), resting-state fMRI and diffusion tensor imaging (DTI). We hypothesize that at post-treatment the VRBCI group will demonstrate changes in superior longitudinal fasciculus and uncinate fasciculus as compared to CLS. This hypothesis is based on a recent meta-analysis of 25 DTI studies in autism (Aoki et al., 2013) that highlight potential roles for these regions of interest.  This prediction is also based on emergent evidence that these major white-matter tracts may play a role in communicative abilities (Nagae et al., 2012; Pardini et al., 2012), which are a target in our VRBCI intervention.

 Objectives:  

Evaluate preliminary neuroimaging results for evidence of structural (MRI, DTI) and functional (rs-fMRI) reorganization as a function of intervention condition.

 Methods:  

We computed global probabilistic tractography using anatomical priors in FSL and Freesurfer (BEDPOSTX and TRACULA, respectively).  Bayesian estimation of diffusion priors and subsequent estimates of connectivity distributions in FSL were used to estimate first level diffusion parameters, which were then passed to the second level for random effects analysis.

Results:  

At baseline, preliminary results indicate no difference between the groups in fractional anisotropy (FA) values, suggesting at a minimum that random assignment was effective.  At post treatment (December, 2013), we will collect follow-up data on all subjects and evaluate potential differences in structural and functional reorganization of the longitudinal fasciculus and uncinate fasciculus between treatment conditions.

Conclusions:  

Although our data come from a small pilot trial and statistical power is known to be limited as a result, we expect that some measurable differences will be observed as a function of random assignment, providing preliminary evidence for treatment effects at the neural systems level.