Clustering leads to underestimation of numerosity, but crowding is not the cause

Chakravarthi, Ramakrishna and Bertamini, Marco ORCID: 0000-0001-8617-6864 (2020) Clustering leads to underestimation of numerosity, but crowding is not the cause. Cognition, 198. 104195-.

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Abstract

Humans have the remarkable ability to rapidly estimate the number of objects in a visual scene without relying on counting, something referred to as the number sense. It has been well documented that the more clustered the elements are, the lower their perceived numerosity is. A recent account of this observation is the crowding hypothesis, which posits that the perceived underestimation is driven by visual crowding: the inability to recognise objects in clutter. Crowding can impair individuation of the elements, which would explain the underestimation. Here, we tested the crowding hypothesis by assessing numerosity estimation and crowding for the same stimulus configurations in the same participants. Experiment 1 compared the two tasks when numerosity can be considered to be estimated directly by the visual system (reference patch density = 0.12 items/deg2), while Experiment 2 used high density stimuli (density = 0.88 items/deg2), where numerosity may be estimated indirectly. In both cases, we found that spacing and similarity between elements affected estimation and crowding tasks in markedly different ways. These results are incompatible with a crowding account of numerosity underestimation and point to separate mechanisms for object identification and number estimation, although grouping may play a moderating role in both cases.

Item Type:	Article
Uncontrolled Keywords:	Humans, Cluster Analysis, Crowding, Pattern Recognition, Visual, Visual Perception
Depositing User:	Symplectic Admin
Date Deposited:	10 Feb 2020 10:02
Last Modified:	19 Jan 2023 00:03
DOI:	10.1016/j.cognition.2020.104195
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3074094