Suppr超能文献

视觉短期记忆的毕生发展:语境和元认知的获益得以保留。

Visual short-term memory through the lifespan: Preserved benefits of context and metacognition.

机构信息

Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge.

Brain and Mind Institute, Western University.

出版信息

Psychol Aging. 2018 Aug;33(5):841-854. doi: 10.1037/pag0000265.

Abstract

Visual short-term memory (VSTM) ability falls throughout the life span in healthy adults. Using a continuous report task, in a large, population-based sample, we first confirmed that this decline affects the quality and quantity of reported memories as well as knowledge of which item went where. Visual and sensorimotor precision also worsened with advancing age, but this did not account for the reduced memory performance. We then considered two strategies that older individuals might be able to adopt, to offset these memory declines: the use of contextual encoding, and metacognitive monitoring of performance. Context and metacognitive awareness were both associated with significantly better performance, however these effects did not interact with age in our sample. This suggests that older adults retain their capacity to boost memory performance through attention to external context and monitoring of their performance. Strategies that focus on taking advantage of these preserved abilities may therefore help to maintain VSTM performance with advancing age. The article reports on analysis of the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data. (PsycINFO Database Record

摘要

视觉短期记忆 (VSTM) 能力在健康成年人的整个生命周期中都会下降。通过使用连续报告任务,在一个大型的基于人群的样本中,我们首先证实,这种下降不仅影响了报告记忆的质量和数量,还影响了对物品去向的了解。视觉和运动感觉精度也随着年龄的增长而恶化,但这并不能解释记忆表现的下降。然后,我们考虑了两种老年人可能采用的策略,以弥补这些记忆衰退:上下文编码的使用和对表现的元认知监控。上下文和元认知意识都与显著更好的表现相关,但在我们的样本中,这些效应与年龄没有相互作用。这表明,老年人通过关注外部环境和监控自己的表现,仍然保留了提高记忆表现的能力。因此,关注利用这些未受影响的能力的策略可能有助于随着年龄的增长维持 VSTM 表现。本文报告了对剑桥老龄化和神经科学中心 (Cam-CAN) 数据的分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f571/6084281/1d4a43fa6c0e/pag_33_5_841_fig1a.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