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. 2025 May 22;15(1):17746.
doi: 10.1038/s41598-025-01252-3.

Association of autistic traits with inference generation in visual narratives

Affiliations

Association of autistic traits with inference generation in visual narratives

Stasha Medeiros et al. Sci Rep. .

Abstract

Individuals with higher levels of autistic traits sometimes demonstrate differences with narrative comprehension compared to those with lower levels of autistic traits. One particular aspect of narrative processing that is thought to be affected by autistic traits is inferencing. Some studies using verbal narratives (i.e., written or spoken stories) have documented differences in inferencing skills among autistic participants. However, fewer studies have investigated how inferencing abilities using visual narratives (e.g., comics) are modulated by autistic traits, despite mounting evidence that narrative comprehension shares similar cognitive mechanisms across verbal and visual domains. Here, we report two studies examining inference generation during visual narrative comprehension in adults with a range of autistic traits. Experiment 1 used a deletion recognition paradigm to examine participants' accuracy (ACC) and reaction time (RT) to identify where a panel had been removed from a visual sequence. Experiment 2 used a self-paced viewing paradigm to examine viewing times on sequences that required an inference; ACC and RT on comprehension questions were also examined. In both experiments, individual differences in autistic traits and visual language fluency were examined. In Experiment 1 we did not see any effects of these predictors; however, for Experiment 2 we found that autistic traits and visual language fluency may be influential in narrative comprehension for measures of offline processing. Subsequent analyses identified differences in imaginative abilities as potentially underlying these modulations.

Keywords: Accuracy; Autism quotient; Inference; Reaction time; Visual language fluency index; Visual narrative.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Examples of stimuli used for the deletion recognition paradigm. Participants were shown a comic strip with a panel removed and asked to press a number to indicate where they thought it was located in the original strip. Panel (a) depicts the original comic strip, which participants were not shown; panels (b)-(d) are examples of stimuli that participants would see from three individual experimental trials representing a deleted Initial, Peak, and Release, respectively.
Fig. 2
Fig. 2
Bar charts of the average a) accuracy (ACC; %) and b) reaction time (RT; in seconds), for each deletion position (Initial, Peak, and Release). Error bars show the standard error of the mean.
Fig. 3
Fig. 3
Example of the stimuli used for the self-paced viewing paradigm in Experiment 2. Each of the three sequence types are present. The boxes that are outlined with dots represent Peak panels and the boxes that are outlined with dashes represent Target panels.
Fig. 4
Fig. 4
Bar chart of the average viewing time for each sequence type (inference, normal, and violation) and panel position (Peak, Target), in seconds. Error bars show the standard error of the mean.
Fig. 5
Fig. 5
Bar chart of the average comprehension question (a) accuracy (ACC) and (b) reaction time (RT) for each sequence type (inference, normal, violation). Error bars show the standard error of the mean.
Fig. 6
Fig. 6
Comparison of accuracy (ACC; %) and VLFI scores across low and high AQ groups for (a) inference, (b) normal, and (c) violation sequence types. (d) Comparison of the difference in accuracy scores between the violation and normal sequence types against VLFI scores for low and high AQ groups.

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