Quantifying the Relationship Between Search Efficiency and Perceptual Similarity in Color Space Across Different Efficient Search Tasks.

When looking for a specific object in the environment, the visual system guides attention toward objects in the scene that contain features that are similar to those of the object in mind, also known as the target template. However, the precise relation between search performance and perceptual simi...

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Published in:Journal of Experimental Psychology. Human Perception & Performance Vol. 51; no. 7; pp. 850 - 875
Main Authors: Lleras, Alejandro, Xu, Zoe, Tan, Howard Jia He, Shao, Yujie, Buetti, Simona
Format: Article
Published: American Psychological Association Jul2025
Online Access:View this record in EBSCOhost
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      dt: Jul2025
      vid: 51
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      pub: American Psychological Association
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        10.1037/xhp0001327
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        atl: Quantifying the Relationship Between Search Efficiency and Perceptual Similarity in Color Space Across Different Efficient Search Tasks.
      aug:
        au:
          Lleras, Alejandro
          Xu, Zoe
          Tan, Howard Jia He
          Shao, Yujie
          Buetti, Simona
        affil: Department of Psychology, University of Illinois
      keyword:
        color vision
        feature-based attention
        parallel processing
        peripheral vision
        visual search
        color vision
        feature-based attention
        parallel processing
        peripheral vision
        visual search
      ab: When looking for a specific object in the environment, the visual system guides attention toward objects in the scene that contain features that are similar to those of the object in mind, also known as the target template. However, the precise relation between search performance and perceptual similarity (between objects in the scene and the target template) has not been properly characterized. Recently, target-contrast signal theory proposed an explicit relationship linking search performance to the concept of top-down "target–distractor contrast," with contrast being a measure of the amount of perceptual evidence that allows peripheral processing to differentiate target from distractors. We used a well-characterized color space to investigate the relationship between target–distractor similarity and search efficiency. We compared three different models relating color distance to search performance: the universal law of generalization, and two implementations of target-contrast signal theory. In the first, target–distractor distance indexes the target–distractor contrast, while the second uses the signal-to-noise ratio (SNR) between the neuronal responses to the attended color and the distractor color to index target–distractor contrast. When the target color is known but the distractor color cannot be anticipated, perceptual distance best predicts performance (Experiments 1, 2A, and 2B). When target and distractor colors repeat from trial to trial, the SNR measure best captures performance (Experiments 3A and 3B). Finally, when neither the target nor the distractor color is known to observers, performance deteriorates significantly and is no longer indexed by either of these two measures of target–distractor contrast (Experiment 4). Public Significance Statement: In this study, we tested three models to understand the visual signal that drives search efficiency, across six separate experiments, through a parametric manipulation of colors. The results suggest that perceptual distance in color space is the signal that drives attention when the target color is known and the distractor colors vary randomly. This situation most resembles visual search in everyday life. In contrast, when both target and distractor colors are known and repeat from trial to trial, a signal-to-noise ratio comparing target and distractor activation better characterizes performance. Finally, when neither target nor color is known, search performance incurs severe costs, even when target and distractor colors are quite distinct. The results emphasize the importance experimental conditions play in determining how visual signals impact performance.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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