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Updated: Jul 7, 2026
14:38
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Published on: November 2, 2012
Class information predicts activation by object fragments in human object areas.
Yulia Lerner1, Boris Epshtein, Shimon Ullman
1Weizmann Institute of Science, Rehovot, Israel.
Journal of Cognitive Neuroscience
|February 21, 2008
Summary
Researchers identified key object features in the human brain
Area of Science:
- Neuroscience
- Cognitive Science
- Computer Vision
Background:
- Ventral visual system areas activate for objects vs. noise.
- The specific object features processed remain unclear.
Purpose of the Study:
- To determine which object features are extracted and represented in object-related brain areas.
- To investigate if information-maximizing object fragments elicit differential activation.
Main Methods:
- Used functional magnetic resonance imaging (fMRI) to measure brain activation.
- Selected object fragments based on maximizing class information.
- Compared activation for informative vs. non-informative fragments in visual areas.
Main Results:
- V1 activation was similar for informative and non-informative fragments.
- Lateral occipital area and posterior fusiform gyrus showed higher activation for informative fragments.
- Behavioral studies confirmed a strong correlation between fragment information and classification performance.
Conclusions:
- Objective measures of class information predict human object classification performance.
- Informative object features drive activation in higher-level visual object areas.
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