Investigating infant knowledge with representational similarity analysis.
IF 19.3
1区 材料科学
Q1 CHEMISTRY, PHYSICAL
引用次数: 0
Abstract
Decades of research have pushed us closer to understanding what babies know. However, a powerful approach - representational similarity analysis (RSA) - is underused in developmental research. I discuss the strengths of this approach and what it can tell us about infant conceptual knowledge. As a case study, I focus on numerosity as a domain where RSA can make unique progress.
利用表象相似性分析研究婴儿知识。
数十年的研究使我们更接近于了解婴儿的认知。然而，一种强大的方法--表象相似性分析（RSA）--在发展研究中却未得到充分利用。我将讨论这种方法的优势，以及它能告诉我们什么是婴儿的概念性知识。作为一个案例研究，我将重点放在数字领域，因为在这一领域，RSA 可以取得独特的进展。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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来源期刊
ACS Energy Letters
Energy-Renewable Energy, Sustainability and the Environment
CiteScore
31.20
自引率
5.00%
发文量
469
审稿时长
1 months
期刊介绍：
ACS Energy Letters is a monthly journal that publishes papers reporting new scientific advances in energy research. The journal focuses on topics that are of interest to scientists working in the fundamental and applied sciences. Rapid publication is a central criterion for acceptance, and the journal is known for its quick publication times, with an average of 4-6 weeks from submission to web publication in As Soon As Publishable format.
ACS Energy Letters is ranked as the number one journal in the Web of Science Electrochemistry category. It also ranks within the top 10 journals for Physical Chemistry, Energy & Fuels, and Nanoscience & Nanotechnology.
The journal offers several types of articles, including Letters, Energy Express, Perspectives, Reviews, Editorials, Viewpoints and Energy Focus. Additionally, authors have the option to submit videos that summarize or support the information presented in a Perspective or Review article, which can be highlighted on the journal's website. ACS Energy Letters is abstracted and indexed in Chemical Abstracts Service/SciFinder, EBSCO-summon, PubMed, Web of Science, Scopus and Portico.
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