ArticleCognitive research: principles and implications2021
A starring role for inference in the neurocognition of visual narratives.
Article in Cognitive research: principles and implications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Association of autistic traits with inference generation in visual narratives.Scientific reports · 2025Article
- Processing Incongruity for Mental Events in Comics: Contours of Character Inferences.Metaphor and symbol · 2025Article
- Individual differences in the neural dynamics of visual narrative comprehension: The effects of proficiency and age of acquisition.Psychonomic bulletin & review · 2024Review
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Abstract
Research in verbal and visual narratives has often emphasized backward-looking inferences, where absent information is subsequently inferred. However, comics use conventions like star-shaped "action stars" where a reader knows events are undepicted at that moment, rather than omitted entirely. We contrasted the event-related brain potentials (ERPs) to visual narratives depicting an explicit event, an action star, or a "noise" panel of scrambled lines. Both action stars and noise panels evoked large N400s compared to explicit-events (300-500 ms), but action stars and noise panels then differed in their later effects (500-900 ms). Action stars elicited sustained negativities and P600s, which could indicate further interpretive processes and integration of meaning into a mental model, while noise panels evoked late frontal positivities possibly indexing that they were improbable narrative units. Nevertheless, panels following action stars and noise panels both evoked late sustained negativities, implying further inferential processing. Inference in visual narratives thus uses cascading mechanisms resembling those in language processing that differ based on the inferential techniques.
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