Cue relevance drives early quitting in visual search.

IF 3.4 2区 心理学 Q1 PSYCHOLOGY, EXPERIMENTAL Cognitive Research-Principles and Implications Pub Date : 2024-08-26 DOI:10.1186/s41235-024-00587-1
Jeff Moher, Anna Delos Reyes, Trafton Drew
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Abstract

Irrelevant salient distractors can trigger early quitting in visual search, causing observers to miss targets they might otherwise find. Here, we asked whether task-relevant salient cues can produce a similar early quitting effect on the subset of trials where those cues fail to highlight the target. We presented participants with a difficult visual search task and used two cueing conditions. In the high-predictive condition, a salient cue in the form of a red circle highlighted the target most of the time a target was present. In the low-predictive condition, the cue was far less accurate and did not reliably predict the target (i.e., the cue was often a false positive). These were contrasted against a control condition in which no cues were presented. In the high-predictive condition, we found clear evidence of early quitting on trials where the cue was a false positive, as evidenced by both increased miss errors and shorter response times on target absent trials. No such effects were observed with low-predictive cues. Together, these results suggest that salient cues which are false positives can trigger early quitting, though perhaps only when the cues have a high-predictive value. These results have implications for real-world searches, such as medical image screening, where salient cues (referred to as computer-aided detection or CAD) may be used to highlight potentially relevant areas of images but are sometimes inaccurate.

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视觉搜索中的线索相关性会导致过早退出。
在视觉搜索中,不相关的突出干扰物可能会引发早期放弃,导致观察者错过本可以找到的目标。在这里,我们想知道,与任务相关的突出线索是否会在这些线索未能突出目标的试验中产生类似的提早放弃效应。我们向参与者提出了一个困难的视觉搜索任务,并使用了两种提示条件。在高预测条件下,目标出现的大部分时间里,红色圆圈形式的突出提示都会突出目标。在低预测条件下,提示的准确性要低得多,而且不能可靠地预测目标(即提示经常是假阳性)。这些情况与没有提示的对照条件形成了鲜明对比。在高预测条件下,我们发现有明显的证据表明,在提示为假阳性的试验中,会出现过早放弃的情况,这表现在目标缺失试验中的失误增加和反应时间缩短。而在低预测性线索条件下,则没有观察到这种影响。总之,这些结果表明,假阳性的突出线索可能会引发早期放弃,但也许只有当这些线索具有较高的预测价值时才会如此。这些结果对现实世界中的搜索(如医学影像筛查)有一定的影响,在现实世界中,突出线索(称为计算机辅助检测或CAD)可用于突出图像中潜在的相关区域,但有时并不准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.80
自引率
7.30%
发文量
96
审稿时长
25 weeks
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