Department of Psychology, Vanderbilt University, 111 21st Avenue South, Nashville, TN, 37240, USA.
Atten Percept Psychophys. 2021 Apr;83(3):1275-1281. doi: 10.3758/s13414-020-02188-8. Epub 2020 Nov 8.
When objects from two categories of expertise (e.g., faces and cars in dual car/face experts) are processed simultaneously, competition occurs across a variety of tasks. Here, we investigate whether competition between face and car processing also occurs during ensemble coding. The relationship between single object recognition and ensemble coding is debated, but if ensemble coding relies on the same ability as object recognition, we expect cars to interfere with ensemble coding of faces as a function of car expertise. We measured the ability to judge the variability in identity of arrays of faces, in the presence of task-irrelevant distractors (cars or novel objects). On each trial, participants viewed two sequential arrays containing four faces and four distractors, judging which array was the more diverse in terms of face identity. We measured participants' car expertise, object recognition ability, and face recognition ability. Using Bayesian statistics, we found evidence against competition as a function of car expertise during ensemble coding of faces. Face recognition ability predicted ensemble judgments for faces, regardless of the category of task-irrelevant distractors. The result suggests that ensemble coding is not susceptible to competition between different domains of similar expertise, unlike single-object recognition.
当来自两个专业领域的物体（例如，双重汽车/面孔专家中的面孔和汽车）同时被处理时，各种任务之间会发生竞争。在这里，我们研究在整体编码过程中是否也会发生面孔和汽车处理之间的竞争。单个物体识别与整体编码之间的关系存在争议，但是如果整体编码依赖于与物体识别相同的能力，那么我们期望汽车会干扰面孔的整体编码，这是因为汽车专业知识的作用。我们衡量了在存在任务无关的干扰物（汽车或新物体）的情况下判断面孔数组身份变化的能力。在每次试验中，参与者观看了包含四个面孔和四个干扰物的两个连续数组，并判断哪个数组在面孔身份方面更加多样化。我们衡量了参与者的汽车专业知识，物体识别能力和面孔识别能力。使用贝叶斯统计，我们发现有证据表明，在面孔的整体编码过程中，汽车专业知识不会导致竞争。无论任务无关干扰物的类别如何，面孔识别能力都可以预测整体判断。该结果表明，与单个物体识别不同，整体编码不易受到不同相似专业领域之间的竞争影响。
