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Concepts and Prototypes

Concepts and Prototypes

The human nervous system handles vast amounts of information by translating sensory stimuli into neural impulses, which the brain processes, creating thoughts expressed through language or stored as memories. The brain also synthesizes information from emotions and memories, which significantly influence thoughts and behaviors. This intricate process creates a comprehensive mental picture.
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Natural and Artificial Concepts

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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint Vincent in...

Causes of Similarity-Dissimilarity Effect

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Stereotype Content Model

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Related Experiment Video

Updated: Jul 4, 2026

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

Exemplars and prototypes in natural language concepts: a typicality-based evaluation.

Wouter Voorspoels¹, Wolf Vanpaemel, Gert Storms

¹Departmentof Psychology, University of Leuven, Leuven, Belgium. wouter.voorspoels@psy.kuleuven.be

Psychonomic Bulletin & Review

|June 24, 2008

Summary

This summary is machine-generated.

Natural language concepts are represented by specific examples, not general summaries. This study found that exemplar models better predict typicality ratings than prototype models for superordinate concepts.

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Area of Science:

Cognitive Psychology
Natural Language Processing
Computational Linguistics

Background:

Understanding how humans categorize information is crucial for cognitive science.
Previous models proposed either exemplar-based or prototype-based representations for concepts.

Purpose of the Study:

To investigate whether natural language categories are represented by specific instances (exemplars) or by a general summary.
To compare the predictive accuracy of exemplar and prototype models for natural language concepts.

Main Methods:

Utilized exemplar and prototype models within the generalized context model framework.
Collected typicality ratings for 12 superordinate natural language concepts.
Fitted models to both averaged and individual participant data.

Main Results:

Both analyses favored the exemplar model over the prototype model.
Exemplar models demonstrated superior predictive power for typicality ratings.

Conclusions:

Higher-level natural language concepts appear to be represented by their subordinate members (exemplars).
Findings challenge the notion of a purely summary representation for abstract concepts.