ArticleiScience2023
The neural correlates of individual differences in numerosity perception: A voxel-based morphometry study.
Article in iScience, 2023. 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.
- Cortical Microstructural Variations Correlate With Individual Differences in Gamified Exploration-Exploitation Behaviours.Computational psychiatry (Cambridge, Mass.) · 2026Article
- Structural and transcriptional signatures of arithmetic abilities in children.NPJ science of learning · 2024Article
- Brain structure correlates of social information use: an exploratory machine learning approach.Frontiers in human neuroscience · 2024Article
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Authors and funding
5 authors.
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Abstract
Numerosity perception is a fundamental cognitive function in humans and animals. Using an individual difference approach with a comprehensive dataset (N = 249), we performed a voxel-based morphometry analysis to unravel the neuroanatomical substrates associated with individual differences in numerosity perception sensitivity, measured by a classical non-symbolic numerical judgment task. Results showed that greater gray matter volume (GMV) in the left cerebellum, right temporal pole, and right parahippocampal was positively correlated to higher perceptual sensitivity to numerosity. In contrast, the GMV in the left intraparietal sulcus, and bilateral precentral/postcentral gyrus was negatively correlated to the sensitivity of numerosity perception. These findings indicate that a wide range of brain structures, rather than a specific anatomical structure or circuit, forms the neuroanatomical basis of numerosity perception, lending support to the emerging network view of the neural representation of numerosity. This work contributes to a more comprehensive understanding of how the brain processes numerical information.
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