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Deciphering autism spectrum disorder: Clues from visual profiles

Tuesday, February 4, 2014 - 11:00
Ipek Oruc, Assistant Professor, Department of Ophthamology & Visial Sciences, University of British Columbia
Statistics Seminar
Room 4192, Earth Sciences Building (2207 Main Mall)

Autism spectrum disorder (ASD), characterized by difficulties in social communication and interaction, as well as repetitive and restrictive behaviours, encompasses a heterogeneous and varied set of symptoms and levels of severity. The latest revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) included the decision to collapse previous diagnostic groupings into a single umbrella diagnosis of ASD. Although the idea of categorizing individuals on the ASD spectrum into well-circumscribed sub-groups is highly attractive, scientific evidence necessary to make such distinctions is currently lacking. We examined visual function of a group of adults with ASD using a battery of psychophysical tasks. Data showed two distinct clusters based on performance in an orientation discrimination task. One cluster had results consistent with the oblique effect, i.e., superior precision around cardinal axes, compared to oblique angles. The other cluster of ASD participants showed a complete lack of the oblique effect with flat profiles across all orientations. We hypothesize that this clustering may be a reflection of true etiological sub-groups within ASD. To examine potential links between these clusters defined based on visual performance and ASD symptomology we collected the following neuropsychological measures on the same group of adults with ASD (N=19): 1) Wechsler Abbreviated Scale of Intelligence (WASI-II), 2) Autism Quotient (AQ), 3) Multidimensional Social Competence Scale (MSCS), and 4) Autism Diagnostic Observation Schedule (ADOS). A support vector machine pattern classifier was able to correctly predict which cluster an individual belongs to with generalization accuracy of 89.47% (p =0.01) based solely on Full IQ and gender.  In addition, these clusters were also independently identified with 76.92% generalization accuracy based only on a single subscale of the MSCS assessing social motivation (p< 0.05) based on a subset of our ASD group (N=13) who completed this measure. Our results suggest that visual performance profiles provide valuable information in identifying true etiological subgroups within ASD. In addition, they suggest that these visual protocols can serve as potential tools to improve diagnostic specificity.