Ｎｕｍｅｒｉｃａｌ　Ｍａｇｎｉｔｕｄｅ　ａｎｄ　Ｉｔｓ　Ｄｙｎａｍｉｃｓ

先前的研究表明，当集合中的几个点用一条细线连接起来时，人们往往会低估集合总数的数量。换句话说，随着连接性的增加，显示器的数量往往会减少。然而，将点与实际上与任务无关的线连接起来可能是一个令人讨厌的变量，因为线可能在集合中充当干扰因素，因此会使数值估计产生偏差。目前的研究测试了在没有实际亮度变化（视线）的情况下，具有强大连接特性的kanitzza型错觉轮廓是否会影响对数字的感知。在三个实验中，参与者被要求从两个由诱导器制成的显示器中选择较大的一组。研究发现，当其中一个集合中的一些诱导剂形成虚幻的轮廓时，该集合的总数被低估了。这些发现很重要，有助于理解我们的视觉系统如何估计大量的集合，这很可能是基于离散的视觉输入，而不是像集合的总面积这样的属性。换句话说，场景分割对于识别物体和空间位置很重要，但最重要的是，分割似乎是提取视觉非符号数的基本原理。

Previous research has shown that when several dots in collection are connected with a thin line, people tend to underestimate the numerosity of the total collection. In other words, with the increasing connectedness, displays tend to be perceived as less numerous. However, connecting dots with lines that are actually irrelevant to the task may be a nuisance variable because lines could act as distractors in the set and therefore, bias the numerical estimations. Current research tested whether Kanitsza-type illusory contours that posses powerful connecting properties in absence of actual luminance changes (apparent lines), affect the perception of numerosity. In three experiments, participants were asked to choose the larger collection out of two displays made of inducers. It was found that when some of the inducers in one of the collections formed illusory contours, the total numerosity of that collection was underestimated. These findings are important and contribute to the understanding of how our visual systems estimate the numerously of collections, which most likely are based on discrete visual inputs, rather than properties like total area of the collection. In other words, scene segmentation is important for recognizing objects and spatial positions, but most of all, segmentation seems to be a fundamental principle behind the extraction of visual non-symbolic numerosities.