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Date of Award
4-29-2022
Document Type
Restricted Thesis: Campus only access
Degree Name
Bachelor of Science
Department
Psychology
First Advisor
Cindy Bukach
Abstract
The main objective of this study was to examine the variability in the structural encoding of faces to identify if traits associated with Autism Spectrum Disorder account for any of the variation in the non-autistic adult population. Structural encoding, the stage of visual processing where perceptual representation of visual data is created in the mind to allow for the recognition of a stimulus as a face, and is measured by the N170 component. This process is impaired in people with ASD, but in the typically developing population, there is still a great amount of variation that has yet to be accounted for. Autistic traits were measured using a five-factor personality measure known as the Autism Spectrum Quotient (AQ), and face-specific structural encoding was assessed using electroencephalography (EEG) to collect neural data as participants were shown images of faces, objects, and textures. 50 participants’ data was used for 3 simple correlations. Results showed no significant correlation between total AQ scores and face-specific N170 amplitude, nor between Attention to Detail AQ Subscale scores and face-specific N170 amplitude. However, the amplitude did have a weak, negative correlation with the Social Skills subscale. The findings are consistent with previous studies that have associated typically developing individuals’ desire to interact and connect with others with variation in N170 amplitude.
Recommended Citation
Smith, Cam, "Structural Encoding of Faces and the Influence of Autistic Traits in the Typically Developing Population: An N170 Study" (2022). Honors Theses. 1655.
https://scholarship.richmond.edu/honors-theses/1655