Department of Psychology, UC Berkeley, Berkeley, CA, USA.
Nat Hum Behav. 2020 Dec;4(12):1265-1272. doi: 10.1038/s41562-020-00946-0. Epub 2020 Sep 14.
People can identify the number of objects in sets of four or fewer items with near-perfect accuracy but exhibit linearly increasing error for larger sets. Some researchers have taken this discontinuity as evidence of two distinct representational systems. Here, we present a mathematical derivation showing that this behaviour is an optimal representation of cardinalities under a limited informational capacity, indicating that this behaviour can emerge from a single system. Our derivation predicts how the amount of information accessible to viewers should influence the perception of quantity for both large and small sets. In a series of four preregistered experiments (N = 100 each), we varied the amount of information accessible to participants in number estimation. We find tight alignment between the model and human performance for both small and large quantities, implicating efficient representation as the common origin behind key phenomena of human and animal numerical cognition.
人们可以近乎完美地准确识别四件或四件以下物品的数量,但对于更大的数量,准确性则呈线性递增。一些研究人员将这种不连续性视为两种截然不同的表示系统的证据。在这里,我们提供了一个数学推导,表明这种行为是在有限信息容量下对基数的最佳表示,这表明这种行为可以从单个系统中出现。我们的推导预测了观众可访问的信息量应该如何影响大小集合的数量感知。在一系列四个预先注册的实验中(每组 100 人),我们改变了参与者在数量估计中可访问的信息量。我们发现,模型和人类表现之间在小数量和大数量上都有紧密的一致性,这意味着高效的表示是人类和动物数字认知的关键现象背后的共同起源。