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Not all summary statistics are made equal: Evidence from extracting summaries across time

机译:并非所有汇总统计信息都相等:跨时间提取汇总的证据

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Over the past 15 years, a number of behavioral studies have shown that the human visual system can extract the average value of a set of items along a variety of feature dimensions, often with great facility and accuracy. These efficient representations of sets of items are commonly referred to as summary representations, but very little is known about whether their computation constitutes a single unitary process or if it involves different mechanisms in different domains. Here, we asked participants to report the average value of a set of items presented serially over time in four different feature dimensions. We then measured the contribution of different parts of the information stream to the reported summaries. We found that this temporal weighting profile differs greatly across domains. Specifically, summaries of mean object location (Experiment 1) were influenced approximately 2.5 times more by earlier items than by later items. Summaries of mean object size (Experiment 1), mean facial expression (Experiment 2), and mean motion direction (Experiment 3), however, were more influenced by later items. These primacy and recency effects show that summary representations computed across time do not incorporate all items equally. Furthermore, our results support the hypothesis that summary representations operate differently in different feature domains, and may be subserved by distinct mechanisms.
机译:在过去的15年中,许多行为研究表明,人类视觉系统可以提取具有各种特征尺寸的一组项目的平均值,通常具有很高的便利性和准确性。这些项目集的有效表示通常称为摘要表示,但是对于它们的计算是否构成一个单一的过程或是否涉及不同领域的不同机制知之甚少。在这里,我们要求参与者报告随时间推移依次呈现的四个不同特征维度的一组项目的平均值。然后,我们测量了信息流不同部分对报告摘要的贡献。我们发现,此时间权重配置文件在各个域之间差异很大。具体来说,较早项目的平均对象位置摘要(实验1)受到的影响比较晚项目的大约2.5倍。但是,平均物体大小(实验1),平均面部表情(实验2)和平均运动方向(实验3)的摘要受后面项目的影响更大。这些优先和新近度效应表明,跨时间计算出的摘要表示不能平等地合并所有项目。此外,我们的结果支持以下假设:摘要表示在不同的特征域中以不同的方式运行,并且可能由不同的机制来保留。

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