Unicog, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, 91191 Gif/Yvette, France; Collège de France, Université Paris-Sciences-Lettres (PSL), 75005 Paris, France.
Cornell University, Ithaca, NY, United States.
Cogn Psychol. 2022 Dec;139:101527. doi: 10.1016/j.cogpsych.2022.101527. Epub 2022 Nov 17.
In various cultures and at all spatial scales, humans produce a rich complexity of geometric shapes such as lines, circles or spirals. Here, we propose that humans possess a language of thought for geometric shapes that can produce line drawings as recursive combinations of a minimal set of geometric primitives. We present a programming language, similar to Logo, that combines discrete numbers and continuous integration to form higher-level structures based on repetition, concatenation and embedding, and we show that the simplest programs in this language generate the fundamental geometric shapes observed in human cultures. On the perceptual side, we propose that shape perception in humans involves searching for the shortest program that correctly draws the image (program induction). A consequence of this framework is that the mental difficulty of remembering a shape should depend on its minimum description length (MDL) in the proposed language. In two experiments, we show that encoding and processing of geometric shapes is well predicted by MDL. Furthermore, our hypotheses predict additive laws for the psychological complexity of repeated, concatenated or embedded shapes, which we confirm experimentally.
在各种文化和所有空间尺度上，人类都会产生丰富多样的几何形状，例如线条、圆形或螺旋形。在这里，我们提出人类拥有一种用于几何形状的思维语言，这种语言可以通过递归组合最小的一组几何基元来生成线条图。我们提出了一种类似于 Logo 的编程语言，它将离散的数字和连续的积分结合起来，基于重复、串联和嵌入来形成更高层次的结构，我们表明，这种语言中最简单的程序可以生成人类文化中观察到的基本几何形状。在感知方面，我们提出人类的形状感知涉及寻找正确绘制图像的最短程序（程序归纳）。该框架的一个结果是，记住形状的心理难度应该取决于在提议的语言中其最短描述长度（MDL）。在两项实验中，我们表明，几何形状的编码和处理可以很好地由 MDL 预测。此外，我们的假设预测了重复、串联或嵌入形状的心理复杂性的加法法则，我们通过实验证实了这一点。
