ArticleJournal of vision2025
Symmetrical and asymmetrical distortions in time and numerosity perception induced by chunked stimuli.
Article in Journal of vision, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Beware bisection: the direction of time-numerosity interactions depends on objective reference.Psychological research · 2026Article
- Psychometric functions for temporal discrimination: Duration or log duration?Behavior research methods · 2026Article
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Authors and funding
3 authors.
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Abstract
The (co)representation of time and numerosity has long been a topic of enduring interest. While a theory of magnitude (ATOM) posits that these dimensions are governed by a shared representational system, empirical findings offer both supporting and conflicting evidence. Previous challenging research has highlighted that time and numerosity perception can be distorted in opposite directions by explicitly introducing emotional or cognitive interference. However, it remains unclear whether time and numerosity can spontaneously dissociate during stimulus processing. To this end, we tested the time and numerosity distortions caused by different kinds of chunked stimuli, including collinearity, illusory contours (ICs), and biological motion (BM). The results showed that collinearity caused the same amount of overestimation for both time and numerosity, whereas ICs caused only numerosity underestimation and BM caused only time overestimation. Notably, no consistent correlations emerged between the magnitudes of temporal and numerical distortion across the three stimulus types. These findings suggest that time and numerosity perception can be symmetrically or asymmetrically distorted depending on the nature of chunked stimuli, providing converging evidence for partially dissociable representations of time and numerosity. The close relationship observed between these two dimensions may instead reflect shared constraints within a broader framework of information processing.
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