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Generating a taxonomy of spatially cued attention for visual discrimination: effects of judgment precision and set size on attention

机译:生成视觉提示的空间提示注意力分类法:判断精度和设定大小对注意力的影响

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摘要

Attention precues improve the performance of perceptual tasks in many but not all circumstances. These spatial attention effects may depend upon display set size or workload, and have been variously attributed to external noise filtering, stimulus enhancement, contrast gain, or response gain, or to uncertainty or other decision effects. In this study, we document systematically different effects of spatial attention in low- and high-precision judgments, with and without external noise, and in different set sizes in order to contribute to the development of a taxonomy of spatial attention. An elaborated perceptual template model (ePTM) provides an integrated account of a complex set of effects of spatial attention with just two attention factors: a set-size dependent exclusion or filtering of external noise and a narrowing of the perceptual template to focus on the signal stimulus. These results are related to the previous literature by classifying the judgment precision and presence of external noise masks in those experiments, suggesting a taxonomy of spatially cued attention in discrimination accuracy.
机译:注意预防可以在许多但不是所有情况下提高感知任务的性能。这些空间注意效果可能取决于显示集的大小或工作负荷,并已不同地归因于外部噪声过滤,刺激增强,对比度增益或响应增益,或不确定性或其他决策效果。在这项研究中,我们有系统地记录了空间注意在低精度和高精度判断中的影响(有无外部噪声)以及不同的集合大小,从而有助于发展空间注意分类法。精心设计的感知模板模型(ePTM)提供了一组综合的空间关注效应集,其中仅包含两个关注因素:一组与集大小相关的外部噪声排除或过滤功能以及缩小的感知模板以专注于信号刺激。这些结果与以前的文献有关,通过对那些实验中的判断精度和外部噪声掩膜的存在进行分类,从而提出了在空间上提示注意力的分类方法。

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