ArticleBrain sciences2025
Multidimensional Representation Dynamics for Abstract Visual Objects in Encoded Tangram Paradigms.
Article in Brain sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe human visual system is capable of processing large quantities of visual objects with varying levels of abstraction. The brain also exhibits hierarchical integration and learning capabilities that combine various attributes of visual objects (e.g., color, shape, local features, and categories) into coherent representations. However, prevailing theories in visual neuroscience employ simple stimuli or natural images with uncontrolled feature correlations, which constrains the systematic investigation of multidimensional representation dynamics.
methodsIn this study, we aimed to bridge this methodological gap by developing a novel large tangram paradigm in visual cognition research and proposing cognitive-associative encoding as a mathematical basis. Critical representation dimensions-including animacy, abstraction level, and local feature density-were computed across a public dataset of over 900 tangrams, enabling the construction of a hierarchical model of visual representation.
resultsNeural responses to 85 representative images were recorded using Electroencephalography (
conclusionsThese findings demonstrate that tangram stimuli, structured through cognitive-associative encoding, provide a generalizable computational framework for investigating the dynamic stages of human visual object cognition.
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