Beran Michael J, Parrish Audrey E
Language Research Center, Georgia State University, University Plaza, Atlanta, GA, 30302, USA,
Atten Percept Psychophys. 2013 Aug;75(6):1243-51. doi: 10.3758/s13414-013-0474-5.
Nonhuman animals are highly proficient at judging relative quantities presented in a variety of formats, including visual, auditory, and even cross-modal formats. Performance typically is constrained by the ratio between sets, as would be expected under Weber's law and as is described in the approximate number system (ANS) hypothesis. In most cases, tests are designed to avoid any perceptual confusion for animals regarding the stimulus sets, but despite this, animals show some of the perceptual biases that humans show based on organization of stimuli. Here, we demonstrate an additional perceptual bias that emerges from the illusion of nested sets. When arrays of circles were presented on a computer screen and were to be classified as larger than or smaller than an established central value, rhesus monkeys (Macaca mulatta) underestimated quantities when circles were nested within each other. This matched a previous report with adult humans (Chesney & Gelman, Attention, Perception, & Psychophysics 24:1104-1113, 2012), indicating that macaques, like humans, show the pattern of biased perception predicted by ANS estimation. Although some macaques overcame this perceptual bias, demonstrating that they could come to view nested stimuli as individual elements to be included in the estimates of quantity used for classifying arrays, the majority of the monkeys showed the bias of underestimating nested arrays throughout the experiment.
非人类动物非常擅长判断以各种形式呈现的相对数量,包括视觉、听觉,甚至跨模态形式。正如韦伯定律所预期的以及近似数字系统(ANS)假说中所描述的那样,表现通常受集合之间比例的限制。在大多数情况下,测试旨在避免动物对刺激集产生任何感知混淆,但尽管如此,动物仍表现出一些基于刺激组织的人类所具有的感知偏差。在这里,我们展示了一种由嵌套集错觉产生的额外感知偏差。当在电脑屏幕上呈现圆圈阵列并要求将其分类为大于或小于既定中心值时,恒河猴(猕猴)在圆圈相互嵌套时会低估数量。这与之前对成年人类的一份报告相符(切斯尼和盖尔曼,《注意力、感知与心理物理学》24:1104 - 1113,2012),表明猕猴和人类一样,表现出由ANS估计预测的偏差感知模式。尽管一些猕猴克服了这种感知偏差,表明它们可以将嵌套刺激视为用于分类阵列的数量估计中要包含的单个元素,但在整个实验过程中,大多数猴子都表现出低估嵌套阵列的偏差。