Reconciling categorization and memory via environmental statistics.

IF 3.2 3区 心理学 Q1 PSYCHOLOGY, EXPERIMENTAL
Psychonomic Bulletin & Review Pub Date : 2024-10-01 Epub Date: 2024-02-16 DOI:10.3758/s13423-023-02448-2
Arjun Devraj, Thomas L Griffiths, Qiong Zhang
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Abstract

How people represent categories and how those representations change over time is a basic question about human cognition. Previous research has demonstrated that people categorize objects by comparing them to category prototypes in early stages of learning but consider the individual exemplars within each category in later stages. However, these results do not seem consistent with findings in the memory literature showing that it becomes increasingly easier to access representations of general knowledge than representations of specific items over time. Why would one rely more on exemplar-based representations in later stages of categorization when it is more difficult to access these exemplars in memory? To reconcile these incongruities, our study proposed that previous findings on categorization are a result of human participants adapting to a specific experimental environment, in which the probability of encountering an object stays uniform over time. In a more realistic environment, however, one would be less likely to encounter the same object if a long time has passed. Confirming our hypothesis, we demonstrated that under environmental statistics identical to typical categorization experiments the advantage of exemplar-based categorization over prototype-based categorization increases over time, replicating previous research in categorization. In contrast, under realistic environmental statistics simulated by our experiments the advantage of exemplar-based categorization over prototype-based categorization decreases over time. A second set of experiments replicated our results, while additionally demonstrating that human categorization is sensitive to the category structure presented to the participants. These results provide converging evidence that human categorization adapts appropriately to environmental statistics.

Abstract Image

通过环境统计调和分类与记忆。
人们如何表征类别以及这些表征如何随时间发生变化,是人类认知的一个基本问题。以往的研究表明,在学习的早期阶段,人们通过将物体与类别原型进行比较来对物体进行分类,但在后期阶段,人们则会考虑每个类别中的单个范例。然而,这些结果似乎与记忆文献的研究结果不一致,这些文献显示,随着时间的推移,获取一般知识的表征比获取特定项目的表征越来越容易。为什么在分类的后期阶段,人们会更依赖于基于范例的表征,而在记忆中获取这些范例却更加困难呢?为了调和这些矛盾,我们的研究提出,以前关于分类的发现是人类参与者适应特定实验环境的结果,在这种环境中,遇到物体的概率随着时间的推移保持一致。然而,在一个更真实的环境中,如果时间过去了很久,人们遇到同一物体的可能性就会降低。为了证实我们的假设,我们证明了在与典型归类实验相同的环境统计条件下,与基于原型的归类相比,基于范例的归类的优势会随着时间的推移而增加,这与之前的归类研究如出一辙。相反,在我们的实验所模拟的现实环境统计中,基于范例的分类法相对于基于原型的分类法的优势随着时间的推移而减小。第二组实验重复了我们的结果,同时还证明了人类的分类对呈现给参与者的类别结构非常敏感。这些结果提供了一致的证据,证明人类的分类能力能够适当地适应环境统计。
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来源期刊
CiteScore
6.70
自引率
2.90%
发文量
165
期刊介绍: The journal provides coverage spanning a broad spectrum of topics in all areas of experimental psychology. The journal is primarily dedicated to the publication of theory and review articles and brief reports of outstanding experimental work. Areas of coverage include cognitive psychology broadly construed, including but not limited to action, perception, & attention, language, learning & memory, reasoning & decision making, and social cognition. We welcome submissions that approach these issues from a variety of perspectives such as behavioral measurements, comparative psychology, development, evolutionary psychology, genetics, neuroscience, and quantitative/computational modeling. We particularly encourage integrative research that crosses traditional content and methodological boundaries.
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