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Updated: Jul 9, 2026
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Published on: November 2, 2012
Where vision meets memory: prefrontal-posterior networks for visual object constancy during categorization and
Haline E Schendan1, Chantal E Stern
1Department of Psychology, Tufts University, 490 Boston Avenue, Medford, MA 02155, USA. Haline_E.Schendan@tufts.edu
Cerebral Cortex (New York, N.Y. : 1991)
|November 24, 2007
Summary
Recognizing objects from unusual angles requires more brain processing, involving visual pathways and prefrontal cortex for cognitive control and mental rotation. This study used fMRI to explore how the brain handles diverse object views.
Area of Science:
- Neuroscience
- Cognitive Psychology
- Visual Perception
Background:
- Object recognition theories suggest unusual views recruit prefrontal and parietal processes for cognitive control and mental rotation.
- Understanding visual object constancy is crucial for explaining how we interact with objects in varied orientations.
Purpose of the Study:
- To investigate the neural mechanisms underlying object recognition from unusual versus canonical views using functional magnetic resonance imaging (fMRI).
- To test the role of prefrontal and parietal networks in visual object constancy and model verification.
Main Methods:
- Participants categorized and recognized familiar objects presented from both canonical and unusual viewpoints.
- fMRI was employed to measure brain activity during these visual recognition tasks.
Main Results:
- Unusual views engaged ventral and dorsal visual pathways, and prefrontal cortex, highlighting their roles in visual object constancy.
- Specific regions, including object-sensitive areas and those involved in mental rotation, were activated by unusual views, supporting model verification processes.
- A "place" area in the collateral-lingual sulci was involved in mental rotation and processing unusual views for successful recognition.
Conclusions:
- Distinct prefrontal-posterior brain networks are essential for enabling robust object recognition and interaction across diverse situations.
- The findings integrate vision and memory theories, providing a framework for understanding how the brain achieves visual object constancy.
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