Department of Applied Psychology, Lingnan University, Hong Kong; Wofoo Joseph Lee Consulting and Counselling Psychology Research Centre, Lingnan University, Hong Kong.
Department of Psychology, University of California, Los Angeles, United States of America.
Cognition. 2021 Apr;209:104515. doi: 10.1016/j.cognition.2020.104515. Epub 2020 Dec 23.
Previous research has shown that humans are able to acquire statistical regularities among shape parts that form various spatial configurations, via exposure to these configurations without any task or feedback. The present study extends this approach of visual statistical learning to examine whether prior knowledge of parts, acquired in a separate learning context, facilitates acquisition of multi-layer hierarchical representations of objects. After participants had learned to encode a shape-pair as a chunk into memory, they viewed cluttered scenes containing multiple shape chunks. One of the larger configurations was constructed by combining the learned shape-pair with an unfamiliar, complementary shape-pair. Although the complementary shape-pair had never been presented separately during learning, it was remembered better than other shape pairs that were parts of larger configurations. The greater perceived familiarity of the complementary shape-pair depended on the encoding strength of the previously learned shape-pair. This "parts-beget-parts" effect suggests that statistical learning, in combination with prior knowledge, can represent objects as a coherent whole and also as a spatial configuration of parts by bootstrapping multi-layer hierarchical structures.
先前的研究表明，人类能够通过暴露于各种空间构型而无需任何任务或反馈来习得形状部分之间的统计规律。本研究扩展了这种视觉统计学习方法，以检验在单独的学习环境中获得的零件先验知识是否有助于对象的多层层次表示的习得。在参与者学会将形状对编码为记忆中的一个块之后，他们观察了包含多个形状块的杂乱场景。通过将学习到的形状对与不熟悉的互补形状对组合，形成了一个较大的配置。尽管在学习过程中从未单独呈现过互补形状对，但它比其他作为较大配置一部分的形状对记得更好。互补形状对的感知熟悉度取决于先前学习的形状对的编码强度。这种“部分产生部分”的效应表明，统计学习与先验知识相结合，可以将对象表示为一个整体，也可以表示为零件的空间配置，从而引导出多层层次结构。
