Similarity Grouping as Feature-Based Selection

Dian Yu*, Xiao Xiao, Douglas K. Bemis, Steven L. Franconeri

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Across the natural world as well as the artificial worlds of maps, diagrams, and data visualizations, feature similarity (e.g., color and shape) links spatially separate areas into sets. Despite a century of study, it is yet unclear what mechanism underlies this gestalt similarity grouping. One recent proposal is that similarity grouping—for example, seeing a red, vertical, or square group—is just global selection of those features. Although parsimonious, this account makes the counterintuitive prediction that similarity grouping is strictly serial: A green group cannot be constructed at the same time as a red group. We tested this prediction with a novel measure—a grouping illusion within number-estimation tasks that should work only if participants simultaneously construct groups—and found the strongest evidence yet in favor of serial feature-based attention (Ns = 14, 12, and 12 for Experiment 1, Experiment 2, and Experiment 3, respectively).

Original languageEnglish (US)
Pages (from-to)376-385
Number of pages10
JournalPsychological Science
Volume30
Issue number3
DOIs
StatePublished - Mar 1 2019

Keywords

  • feature-based selection
  • grouping
  • number estimation
  • open data
  • open materials
  • perceptual organization
  • visual attention

ASJC Scopus subject areas

  • Psychology(all)

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