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Language meaning elicited by viewing animations of geometric shapes in autistic and non-autistic individuals

Poster A88 in Poster Session A, Tuesday, October 24, 10:15 am - 12:00 pm CEST, Espace Vieux-Port

Brea Chouinard1, Melih Keskin1, Louise Gallagher2, Clare Kelly2, Alona Fyshe1; 1University of Alberta, 2Trinity College Dublin

Background: In the 1940s, Heider and Simmel (1944) showed short animations of geometric shapes moving around and asked participants to explain what was happening. All but one of their participants attributed human-like characteristics to the shapes and movements (e.g., “…two men have a fight… the girl starts to…get out of the way...She apparently does not want to be with the first man” (Heider & Simmel, 1944, page 247). Decades later, Ami (2000) showed the same animations to autistic and non-autistic individuals. The answers produced by non-autistic individuals included words that fell into the following domains: actions, social interactions, feelings, and social reasoning. In contrast, autistic individuals (i) identified fewer social elements and (ii) less often afforded social-reasoning skills to the shapes. In our study, we collected neuroimaging data from autistic and non-autistic adolescents while they watched a Heider-and-Simmel-like movie. We used an encoding model to characterize the neural representations of language meaning within the brain imaging data. Methods: In a 1.5T scanner, 30 adolescents (n=15 non-autistic) passively viewed a 7-minute movie of moving geometric shapes, which was accompanied by music, but had no dialogue. The movie depicted the story of a child (i.e., a small triangle) and included interactions such as chatting with a grown-up (i.e., a big triangle), having nightmares of a monster, and finding a friend (i.e., a small square). We created a design matrix representing 1) anthropomorphized nouns and actions seen in each second of the movie, 2) pre-processing motion parameters of the neuroimaging data, and 3) time delays to account for the shape of the hemodynamic response. For each participant, we then ran an encoding analysis to see which voxels responded most consistently to the information in the design matrix (i.e., Fisher p-value<0.05 and correlation coefficient r >0). Following that, on a group-by-group basis, we concatenated the beta weights of the responsive voxels from all participants in that group and ran a principal components analysis, thus carrying out one PCA for each group. Finally, for each of the first four principal components in each group, we used regression to determine how much of the variance in the given component was related to each of 13 different dimensions that paralleled those found by Ami (2000). Results: For autistic adolescents, the two dimensions accounting for most of the brain data variance were ‘the Character Shapes’, and ‘Animacy’; lowest was ‘social interaction’. For non-autistic adolescents, top dimensions were ‘Theory of Mind’, and ‘Change’; lowest was ‘the Character Shapes’. Conclusion: We uncovered two very different profiles representing what was most salient to each group while viewing geometric animations. For autistic adolescents, the brain activity was primarily responsive to the three anthropomorphizable shapes and their movements, with very little autistic brain activation accounting for higher level social reasoning. In contrast, for non-autistic adolescents, the most-salient constructs were social reasoning (e.g., “trick”, “plan”), strong feelings (e.g., “anxious”, “sad”), or when items in the movie morphed from one thing into another (e.g., house morphing into a giant monster).

Topic Areas: Computational Approaches, Disorders: Developmental

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