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意外捕获与无意视盲。

Surprise capture and inattentional blindness.

作者信息

Horstmann Gernot, Ansorge Ulrich

机构信息

Department of Psychology, Bielefeld University, Germany; Centre for Interdisciplinary Research, Bielefeld University, Germany; Cognitive Interaction Technology - Excellence Cluster, Bielefeld University, Germany.

Faculty of Psychology, University of Vienna, Vienna, Austria.

出版信息

Cognition. 2016 Dec;157:237-249. doi: 10.1016/j.cognition.2016.09.005. Epub 2016 Sep 22.

DOI:10.1016/j.cognition.2016.09.005
PMID:27665396
Abstract

Inattentional blindness (IB) is the phenomenon where unattended objects are not noticed. IB is typically tested within a surprise presentation procedure: A novel object is presented on a critical trial for the first time without prior announcement. Previous research indicates that IB is high unless the novel object is (a) similar to the target of the present task or (b) perceptually salient. The present study seeks evidence that the expectancy congruence of the novel object is a further important determinant of IB, and that the novel object is frequently noticed if it has a feature that is expectancy discrepant. An influence of perceptual saliency is excluded by presenting only two objects in each display. Experiment 1 reveals that an expectancy discrepant novel feature is noticed even if it is completely dissimilar to the target. Experiment 2 shows that expectancy discrepancy and match to target features can prioritize an object at the same time. Experiment 3 shows that IB is related to the degree of expectancy discrepancy. Results indicate that IB is prevented by two factors: match to target set and expectancy discrepancy. A revised model for IB is suggested.

摘要

无意视盲(IB)是指未被注意的物体未被察觉到的现象。IB通常在一个意外呈现程序中进行测试:在关键试验中首次呈现一个新物体,事先未作任何预告。先前的研究表明,除非新物体(a)与当前任务的目标相似或(b)在感知上很突出,否则无意视盲的发生率很高。本研究旨在寻找证据,证明新物体的预期一致性是无意视盲的另一个重要决定因素,并且如果新物体具有与预期不符的特征,它就会经常被注意到。通过在每个显示屏上仅呈现两个物体,排除了感知显著性的影响。实验1表明,即使一个与预期不符的新特征与目标完全不同,也会被注意到。实验2表明,预期差异和与目标特征的匹配可以同时使一个物体具有优先性。实验3表明,无意视盲与预期差异的程度有关。结果表明,有两个因素可以防止无意视盲:与目标集的匹配和预期差异。本文提出了一个修订后的无意视盲模型。

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