ArticleScientific reports2023
Aging and temporal integration in the visual perception of object shape.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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
1 citing paper in PubMed, 1 citations in OpenAlex.
- Continuous temporal integration in the human visual system.Journal of vision · 2024Article
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4 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
It has been known for more than 160 years that highly occluded objects that would normally be visually unrecognizable can be successfully identified when they move. This anorthoscopic perception relies on the visual system's ability to integrate information over time to complete the perception of an entire object's shape. In this experiment, 16 younger and older adults (mean ages were 20.5 and 74.6 years, respectively) were familiarized with the (unoccluded) shapes of five naturally-shaped objects (bell peppers, Capsicum annuum) until they could be easily identified (i.e., with accuracies of at least 90 percent correct). All observers then viewed the stimulus objects anorthoscopically as they moved behind narrow slits; only small object fragments could be seen at any given time, because the objects were almost totally occluded from view. Even though the object identification performance for all observers was equivalent when whole object shapes were visible, a large age-related deficit in object identification emerged during anorthoscopic viewing such that the younger adults' identification performance was 45.4 percent higher than that of the older adults. This first ever study of aging and anorthoscopic perception demonstrates that there is an age-related deficit in performing the temporal integration needed for successful object recognition.
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