The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers.
The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers.
复制标题
DOI：
10.1371/journal.pcbi.1005273
复制
发表时间：
2017-01
影响因子：
4.3
通讯作者：
Dehaene S
中科院分区：
文献类型：
--
作者：
Amalric M;Wang L;Pica P;Figueira S;Sigman M;Dehaene S
在语言处理过程中，人类从顺序输入形成复杂的嵌入式表示。在这里，我们要问的是，具有递归嵌入的“几何语言”是否也是人类编码空间位置序列的能力的基础。我们引入了一种新的范式，在这种范式中，受试者暴露于八边形上的一系列空间位置，并被要求预测未来的位置。这些序列的复杂程度取决于定义良好的语言，包括基本原语和递归规则。对错误模式的详细分析表明，对称和旋转的原语被亚马逊地区的一个土著群体蒙杜鲁库的成年人、学龄前儿童和成年成员自发地发现和使用，他们的数字和几何词汇有限，上学的机会也有限。此外，受试者很容易将这些几何原语组合成分层组织的表达式。通过评估大量这样的组合，我们获得了解释人类视觉空间序列表示所需的语言的第一个视图，并得出结论，它们通过最小化捕获它们的结构化表达式的复杂性来编码视觉空间序列。儿童的语言习得被认为依赖于从顺序输入中构建分层结构表征的能力。几何规则的习得是否也有类似的机制？在这里，我们引入了一个学习情境，在这个情境中，人类参与者必须掌握简单的空间序列，并试图预测下一个位置。序列是根据一种“几何语言”生成的，这种“几何语言”赋予了对称和旋转的简单基元以及组合规则。对不同人群错误率的分析——一组受过法国教育的成年人，两组5岁的法国儿童，以及一组罕见的来自亚马逊地区的青少年和成年人，蒙德鲁库斯人，他们接受正规教育的机会有限，几何词典也较少——揭示了受试者的学习确实依赖于内部的语言样表征。一个基于最小描述长度的理论模型被证明非常适合参与者的行为，这表明人类受试者将空间序列“压缩”成最小的内部规则或程序。
During language processing, humans form complex embedded representations from sequential inputs. Here, we ask whether a “geometrical language” with recursive embedding also underlies the human ability to encode sequences of spatial locations. We introduce a novel paradigm in which subjects are exposed to a sequence of spatial locations on an octagon, and are asked to predict future locations. The sequences vary in complexity according to a well-defined language comprising elementary primitives and recursive rules. A detailed analysis of error patterns indicates that primitives of symmetry and rotation are spontaneously detected and used by adults, preschoolers, and adult members of an indigene group in the Amazon, the Munduruku, who have a restricted numerical and geometrical lexicon and limited access to schooling. Furthermore, subjects readily combine these geometrical primitives into hierarchically organized expressions. By evaluating a large set of such combinations, we obtained a first view of the language needed to account for the representation of visuospatial sequences in humans, and conclude that they encode visuospatial sequences by minimizing the complexity of the structured expressions that capture them. The child’s acquisition of language has been suggested to rely on the ability to build hierarchically structured representations from sequential inputs. Does a similar mechanism also underlie the acquisition of geometrical rules? Here, we introduce a learning situation in which human participants had to grasp simple spatial sequences and try to predict the next location. Sequences were generated according to a “geometrical language” endowed with simple primitives of symmetries and rotations, and combinatorial rules. Analyses of error rates of various populations—a group of French educated adults, two groups of 5 years-old French children, and a rare group of teenagers and adults from an Amazonian population, the Mundurukus, who have limited access to formal schooling and a reduced geometrical lexicon—revealed that subjects’ learning indeed rests on internal language-like representations. A theoretical model, based on minimum description length, proved to fit well participants’ behavior, suggesting that human subjects “compress” spatial sequences into a minimal internal rule or program.