Date of Completion

2023

Document Type

Honors College Thesis

Department

Department of Communication Sciences & Disorders

Thesis Type

Honors College, College of Arts and Science Honors

First Advisor

Emily Coderre

Second Advisor

Alicia Ebert

Third Advisor

Tiffany Hutchins

Keywords

Narrative comprehension, prediction, autism, semantic processing, electroencephalography, event-related potentials

Abstract

Autistic individuals have shown differences from non-autistic individuals when understanding stories, regardless of whether those stories are told through words or pictures. One aspect of narrative comprehension that is thought to facilitate comprehension is the prediction of upcoming words or events in a story. Prediction is typically assessed using cloze probabilities: the predictability of a word in a linguistic narrative, or a panel in a visual narrative. In studies measuring event-related potentials (ERPs) with non-autistic adults, more predictable (“high cloze”) words/panels elicit reduced N400 amplitudes compared to less predictable (“low cloze”) words/panels. Autistic individuals may have differences in predictive processes compared to non- autistic individuals, which could contribute to differences in narrative comprehension across modalities. Here, we report two studies using the cloze probability paradigm to investigate predictive processing mechanisms in the context of linguistic and visual narrative comprehension among autistic and non-autistic adults. Non-autistic adults showed modulations of the N400 ERP component by cloze in both linguistic and visual domains, which replicates prior literature. Autistic adults showed earlier N400 modulations by cloze in both modalities. This suggests that autistic adults employ a more bottom-up processing style during narrative comprehension which supports models that propose differences with prediction in autistic individuals.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

Available for download on Thursday, May 08, 2025

Share

COinS