Visual numerosity perception shows no advantage in real-world scenes compared to artificial displays

Cognition. 2023 Jan:230:105291. doi: 10.1016/j.cognition.2022.105291. Epub 2022 Sep 29.

Abstract

While the human visual system is sensitive to numerosity, the mechanisms that allow perception to extract and represent the number of objects in a scene remains unknown. Prominent theoretical approaches posit that numerosity perception emerges from passive experience with visual scenes throughout development, and that unsupervised deep neural network models mirror all characteristic behavioral features observed in participants. Here, we derive and test a novel prediction: if the visual number sense emerges from exposure to real-world scenes, then the closer a stimulus aligns with the natural statistics of the real world, the better number perception should be. But - in contrast to this prediction - we observe no such advantage (and sometimes even a notable impairment) in number perception for natural scenes compared to artificial dot displays in college-aged adults. These findings are not accounted for by the difficulty in object identification, visual clutter, the parsability of objects from the rest of the scene, or increased occlusion. This pattern of results represents a fundamental challenge to recent models of numerosity perception based in experiential learning of statistical regularities, and instead suggests that the visual number sense is attuned to abstract number of objects, independent of their underlying correlation with non-numeric features. We discuss our results in the context of recent proposals that suggest that object complexity and entropy may play a role in number perception.

Keywords: Approximate number system; Number estimation; Scene perception.

MeSH terms

  • Adult
  • Cognition*
  • Humans
  • Neural Networks, Computer
  • Pattern Recognition, Visual
  • Visual Perception*
  • Young Adult