ArticleNature communications2024
Computational reconstruction of mental representations using human behavior.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Perceptual and conceptual influences on memory judgments.Communications psychology · 2026Article
- Drawings of THINGS: A large-scale drawing dataset of 1854 object concepts.Behavior research methods · 2026Article
- Deep learning-empowered triboelectric acoustic textile for voice perception and intuitive generative AI-voice access on clothing.Science advances · 2025Article
- Computational reconstruction of mental representations using human behavior.Nature communications · 2024Article
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Authors and funding
2 authors.
Funding
Abstract
Revealing how the mind represents information is a longstanding goal of cognitive science. However, there is currently no framework for reconstructing the broad range of mental representations that humans possess. Here, we ask participants to indicate what they perceive in images made of random visual features in a deep neural network. We then infer associations between the semantic features of their responses and the visual features of the images. This allows us to reconstruct the mental representations of multiple visual concepts, both those supplied by participants and other concepts extrapolated from the same semantic space. We validate these reconstructions in separate participants and further generalize our approach to predict behavior for new stimuli and in a new task. Finally, we reconstruct the mental representations of individual observers and of a neural network. This framework enables a large-scale investigation of conceptual representations.
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