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Comprehensive exploration of visual working memory mechanisms using large-scale behavioral experiment

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  • Liqiang Huang

    (The Chinese University of Hong Kong)

Abstract

Two decades of research on visual working memory have produced substantial yet fragmented knowledge. This study aims to integrate these findings into a cohesive framework. Drawing on a large-scale behavioral experiment involving 40 million responses to 10,000 color patterns, a quasi-comprehensive exploration model of visual working memory, termed QCE-VWM, is developed. Despite its significantly reduced complexity (57 parameters versus 30,796), QCE-VWM outperforms neural networks in data fitting. The model provides an integrative framework for understanding human visual working memory, incorporating a dozen mechanisms—some directly adopted from previous studies, some modified, and others newly identified. This work underscores the value of large-scale behavioral experiments in advancing comprehensive models of cognitive mechanisms.

Suggested Citation

  • Liqiang Huang, 2025. "Comprehensive exploration of visual working memory mechanisms using large-scale behavioral experiment," Nature Communications, Nature, vol. 16(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-56700-5
    DOI: 10.1038/s41467-025-56700-5
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    References listed on IDEAS

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    2. Liqiang Huang, 2023. "A quasi-comprehensive exploration of the mechanisms of spatial working memory," Nature Human Behaviour, Nature, vol. 7(5), pages 729-739, May.
    3. Daryl Fougnie & Jordan W. Suchow & George A. Alvarez, 2012. "Variability in the quality of visual working memory," Nature Communications, Nature, vol. 3(1), pages 1-8, January.
    4. Edmond Awad & Sohan Dsouza & Richard Kim & Jonathan Schulz & Joseph Henrich & Azim Shariff & Jean-François Bonnefon & Iyad Rahwan, 2018. "The Moral Machine experiment," Nature, Nature, vol. 563(7729), pages 59-64, November.
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