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Related Experiment Video

Updated: May 16, 2026

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

Published on: August 1, 2018

Set size, individuation, and attention to shape.

Lisa Cantrell¹, Linda B Smith

¹Indiana University, Department of Psychological and Brain Sciences, 1101 E Tenth St., Bloomington, IN 47405-7007, United States. cantrell@indiana.edu

|November 22, 2012

Summary

Shape bias in object categorization is influenced by numerical cognition. Set size impacts how adults and children generalize object names and categorize items, linking shape and number representation precision.

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Area of Science:

Cognitive Psychology
Developmental Psychology
Numerical Cognition

Background:

Research indicates a shape bias in object categorization and naming.
Numerical cognition research suggests distinct processes for small (precise) and large (imprecise) set quantification.

Purpose of the Study:

To investigate the link between numerical cognition processes and the shape bias in object categorization.
To determine if set size influences shape-based generalization and categorization.

Main Methods:

Three experiments utilized forced-choice categorization tasks with naming and non-naming procedures.
Participants included adults and preschool children across different language backgrounds.
Stimuli involved novel object names and varying set sizes.

Main Results:

Adults generalized object names based on shape only for small set sizes (1-4 items).
Preschool children's categorization was also influenced by set size.
The set size effect was observed in both naming and non-naming tasks, and with count-noun syntax.

Conclusions:

Object representation precision is related to numerical representation precision for both small and large numbers.
Set size plays a crucial role in the interplay between shape bias and numerical cognition.
Findings suggest a unified mechanism underlying how humans represent and categorize objects and quantities.