Suppr超能文献

任务无关的空间分隔有助于计数和数量估计。

Task-irrelevant spatial dividers facilitate counting and numerosity estimation.

机构信息

Department of Psychology, Graduate School of Humanities and Sociology, The University of Tokyo, Tokyo, Japan.

出版信息

Sci Rep. 2018 Oct 23;8(1):15620. doi: 10.1038/s41598-018-33877-y.

Abstract

Counting is characterized as a slow and error-prone action relying heavily on serial allocation of focused attention. However, quick and accurate counting is required for many real-world tasks (e.g., counting heads to ensure everyone is evacuated to a safe place in an emergency). Previous research suggests that task-irrelevant spatial dividers, which segment visual displays into small areas, facilitate focused attention and improve serial search. The present study investigated whether counting, which is also closely related to focused attention, can be facilitated by spatial dividers. Furthermore, the effect of spatial dividers on numerosity estimation, putatively dependent upon distributed attention, was also examined to provide insights into different types of number systems and different modes of visual attention. The results showed profound performance improvement by task-irrelevant spatial dividers in both counting and numerosity estimation tasks, indicating that spatial dividers may activate interaction between number and visual attention systems. Our findings provide the first evidence that task-irrelevant spatial dividers can be used to facilitate various types of numerical cognition.

摘要

计数的特点是一种缓慢且容易出错的行为,严重依赖于集中注意力的串行分配。然而,许多现实世界的任务都需要快速准确的计数(例如,数人头以确保在紧急情况下所有人都被疏散到安全的地方)。先前的研究表明,与集中注意力密切相关的任务无关的空间分隔符将视觉显示分割成小区域,有利于集中注意力并提高串行搜索。本研究调查了空间分隔符是否可以促进计数,计数也与集中注意力密切相关。此外,还检查了空间分隔符对数量估计的影响,数量估计据称依赖于分布式注意力,以深入了解不同类型的数字系统和不同类型的视觉注意力模式。结果表明,任务无关的空间分隔符在计数和数量估计任务中都能显著提高性能,表明空间分隔符可能激活了数字和视觉注意力系统之间的相互作用。我们的研究结果首次提供了证据表明,任务无关的空间分隔符可用于促进各种类型的数字认知。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05cf/6199305/0a0d055357ea/41598_2018_33877_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验