December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Color-concept associations reveal an abstract conceptual space
Author Affiliations & Notes
  • Kushin Mukherjee
    Department of Psychology, University of Wisconsin-Madison, Madison, WI
    Wisconsin Institute for Discovery, Madison, WI
  • Karen Schloss
    Department of Psychology, University of Wisconsin-Madison, Madison, WI
    Wisconsin Institute for Discovery, Madison, WI
  • Laurent Lessard
    Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA
  • Michael Gleicher
    Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI
  • Timothy Rogers
    Department of Psychology, University of Wisconsin-Madison, Madison, WI
    Wisconsin Institute for Discovery, Madison, WI
  • Footnotes
    Acknowledgements  This work was supported by the McPherson Eye Research Institute at the University of Wisconsin-Madison,the Wisconsin Alumni Research Foundation, and the National Science Foundation (BCS-1945303)
Journal of Vision December 2022, Vol.22, 4408. doi:https://doi.org/10.1167/jov.22.14.4408
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      Kushin Mukherjee, Karen Schloss, Laurent Lessard, Michael Gleicher, Timothy Rogers; Color-concept associations reveal an abstract conceptual space. Journal of Vision 2022;22(14):4408. https://doi.org/10.1167/jov.22.14.4408.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

People have systematic associations between concepts and colors, and concepts can be represented as distributions of association strengths across color space (Schloss et al., 2018; Rathore et al., 2018). These patterns of color-concept associations are highly structured, which may be critical in explaining how people flexibly draw conceptual inferences about colors across contexts (Mukherjee et al., 2021). Here we consider the structure of the semantic space defined by color-concept associations, evaluating three hypotheses. First, the structure may be arbitrary, so that items evoking similar color associations are conceptually unrelated. Second, it may be redundant with the conceptual structure apparent in natural language, as estimated via word-embeddings computed from large corpora. Third, it may express a representational space important to human cognition but distinct from those latent in natural language. To adjudicate these possibilities, we selected 30 concepts spanning 6 semantic domains (clothes, emotions, scenes, fruits, directions, times-of-day) and collected association ratings between each concept and 58 colors sampled across CIELAB color space. Pairwise dissimilarities between concepts in this color-concept association space could be well captured by embedding them in a reduced 3-dimensional space, where concepts with similar color-concept associations were embedded near each other. A comparison of these embeddings to those extracted from natural-language corpora revealed highly distinct conceptual spaces. To determine whether the color-concept space is reflected in mental representations of word meanings, we used a triadic comparison task to embed the same items based on direct judgments of semantic similarity. These correlated more strongly with color-concept similarities, suggesting that the color-concept associations express aspects of semantic knowledge beyond color that elude word-embeddings derived from language corpora, supporting our third hypothesis. The results provide an initial basis for understanding abstract conceptual relations in human cognition through the lens of visual properties of concepts — in this case, color-concept associations.

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