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Basic-level categorization of intermediate complexity fragments reveals top-down effects of expertise in visual perception

机译:中级复杂性片段的基本级别分类揭示了视觉感知专业知识的自上而下的效果

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摘要

Visual expertise is usually defined as the superior ability to distinguish between exemplars of a homogeneous category. Here, we ask how real-world expertise manifests at basic-level categorization and assess the contribution of stimulus-driven and top-down knowledge-based factors to this manifestation. Car experts and novices categorized computer-selected image fragments of cars, airplanes, and faces. Within each category, the fragments varied in their mutual information (MI), an objective quantifiable measure of feature diagnosticity. Categorization of face and airplane fragments was similar within and between groups, showing better performance with increasing MI levels. Novices categorized car fragments more slowly than face and airplane fragments, while experts categorized car fragments as fast as face and airplane fragments. The experts’ advantage with car fragments was similar across MI levels, with similar functions relating RT with MI level for both groups. Accuracy was equal between groups for cars as well as faces and airplanes, but experts’ response criteria were biased toward cars. These findings suggest that expertise does not entail only specific perceptual strategies. Rather, at the basic level, expertise manifests as a general processing advantage arguably involving application of top-down mechanisms, such as knowledge and attention, which helps experts to distinguish between object categories.
机译:视觉专业知识通常被定义为区分同类同类示例的卓越能力。在这里,我们询问现实世界的专业知识如何在基本级别的分类中体现出来,并评估刺激驱动的和自上而下的基于知识的因素对这种体现的贡献。汽车专家和新手对计算机,汽车,飞机和面部的图像片段进行了分类。在每个类别中,片段的相互信息(MI)有所不同,这是特征诊断的客观可量化度量。各组之间以及各组之间的面部和飞机碎片的分类相似,随着MI水平的提高,表现出更好的性能。新手对汽车碎片的分类比面部和飞机碎片的分类速度慢,而专家对汽车碎片的分类速度与面部和飞机碎片的分类速度一样快。专家们在各个MI级别使用汽车碎片的优势是相似的,两组的RT和MI级别相关的功能相似。汽车,人脸和飞机的分组之间的准确度均等,但是专家的回应标准偏向汽车。这些发现表明,专业知识并不仅需要特定的感知策略。而是在基本级别上,专业知识表现为一般的处理优势,可以说涉及应用自上而下的机制,例如知识和注意力,这可以帮助专家区分对象类别。

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