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Related Experiment Video

Updated: Jul 16, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

General recognition theory of categorization: a MATLAB toolbox.

Leola A Alfonso-Reese¹

¹Department of Psychology, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4611, USA. leola@alum.mit.edu

Behavior Research Methods

|March 31, 2007

Summary

The General Recognition Theory (GRT) toolbox offers MATLAB tools for designing, simulating, and analyzing human categorization experiments. This framework aids researchers in understanding categorization behavior and fitting classification models.

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Area of Science:

Cognitive Science
Computational Psychology
Machine Learning

Background:

General Recognition Theory (GRT) provides a theoretical framework for understanding human categorization.
Studying categorization behavior requires specialized tools for experimental design and data analysis.
Existing computational tools may not fully integrate experimental design, simulation, and analysis.

Purpose of the Study:

To introduce the GRT toolbox, a comprehensive set of MATLAB scripts.
To facilitate the design, simulation, analysis, and visualization of categorization experiments.
To support researchers in applying GRT to human categorization behavior.

Main Methods:

The GRT toolbox comprises MATLAB scripts and subroutines.
It enables experiment design, stimulus generation, response simulation, and data analysis.
The toolbox supports typical two-category tasks with multivariate normal distributions.
It includes functions for fitting general linear and quadratic classifiers.

Main Results:

The GRT toolbox provides a unified environment for categorization research.
It streamlines the workflow from experiment design to data analysis.
The toolbox allows for the simulation of participant responses based on GRT principles.
It facilitates the application of established classification models to experimental data.

Conclusions:

The GRT toolbox is a valuable resource for researchers studying human categorization.
It enhances the efficiency and rigor of categorization experiments.
The toolbox supports both theoretical modeling and empirical investigation within GRT.
It offers practical solutions for analyzing and interpreting categorization data.