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How much time does it take to discriminate two sets by their numbers of elements?
Attention, Perception, & Psychophysics ( IF 1.7 ) Pub Date : 2022-04-28 , DOI: 10.3758/s13414-022-02474-7
Jüri Allik 1, 2 , Aire Raidvee 1
Affiliation  

The ability to evaluate the number of elements in a set—numerosity—without symbolic representation is a form of primitive perceptual intelligence. A simple binomial model was proposed to explain how observers discriminate the numerical proportion between two sets of elements distinct in color or orientation (Raidvee et al., 2017, Attention Perception & Psychophysics, 79[1], 267–282). The binomial model’s only parameter β is the probability with which each visual element can be noticed and registered by the perceptual system. Here we analyzed the response times (RT) which were ignored in the previous report since there were no instructions concerning response speed. The relationship between the mean RT and the absolute difference |ΔN| between numbers of elements in two sets was described by a linear regression, the slope of which became flatter as the total number of elements N increased. Because the coefficients of regression between the mean RT and |ΔN| were more directly related to the binomial probability β rather than to the standard deviation of the best fitting cumulative normal distribution, it was regarded as evidence that the binomial model with a single parameter — probability β — is a viable alternative to the customary Thurstonian–Gaussian model.



中文翻译:

用元素的数量来区分两个集合需要多少时间?

在没有符号表示的情况下评估集合中元素的数量(数量)的能力是原始感知智能的一种形式。提出了一个简单的二项式模型来解释观察者如何区分颜色或方向不同的两组元素之间的数值比例(Raidvee 等人,2017,注意力感知与心理物理学,79 [1],267-282)。二项式模型的唯一参数 β 是感知系统可以注意到和记录每个视觉元素的概率。在这里,我们分析了上一份报告中忽略的响应时间 (RT),因为没有关于响应速度的说明。平均RT与绝对差的关系| ΔN| 两组元素数量之间的关系通过线性回归来描述,随着元素总数N的增加,其斜率变得更平。因为平均 RT 和 |Δ N |之间的回归系数 与二项式概率 β 而不是与最佳拟合累积正态分布的标准差更直接相关,这被认为是证明具有单个参数的二项式模型 - 概率 β - 是传统 Thurstonian-Gaussian 的可行替代方案模型。

更新日期:2022-04-29
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