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Multidimensional Representation Dynamics for Abstract Visual Objects in Encoded Tangram Paradigms.

Yongxiang Lian1, Shihao Pan1, Li Shi1

  • 1Department of Automation, Tsinghua University, Beijing 100084, China.

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|September 27, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel tangram paradigm for visual cognition research. It reveals that visual object features like animacy and abstraction are independently encoded and dynamically processed at different cognitive stages.

Keywords:
cognitive-associative encodingelectroencephalographymultidimensional representationtangram paradigmvisual cognition

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Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience
  • Visual Cognition

Background:

  • The human visual system processes complex visual information hierarchically.
  • Current research faces limitations due to simplified stimuli and uncontrolled feature correlations in natural images.

Purpose of the Study:

  • To develop a novel methodology for investigating multidimensional visual representation dynamics.
  • To establish cognitive-associative encoding as a mathematical framework for visual cognition.

Main Methods:

  • Developed a large tangram paradigm with over 900 stimuli.
  • Computed critical representation dimensions: animacy, abstraction level, local feature density.
  • Constructed a hierarchical model of visual representation.

Main Results:

  • Recorded neural responses using Electroencephalography (EEG) on 24 participants.
  • Demonstrated independent encoding and dynamic expression of representational dimensions across cognitive stages.
  • Showcased how higher-order processes like 'change of mind' involve selective feature processing.

Conclusions:

  • Tangram stimuli, guided by cognitive-associative encoding, offer a robust framework for studying visual object cognition.
  • The findings provide insights into the dynamic stages of visual processing and representation.
  • This approach facilitates systematic investigation of how the brain represents complex visual information.