4.6 Article

Sleep and Motor Learning: Is There Room for Consolidation?

期刊

PSYCHOLOGICAL BULLETIN
卷 141, 期 4, 页码 812-834

出版社

AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/bul0000009

关键词

sleep consolidation; learning; motor skills; motor sequence learning; sleep enhancement

资金

  1. National Science Foundation (NSF) Graduate Research Fellowship

向作者/读者索取更多资源

It is widely believed that sleep is critical to the consolidation of learning and memory. In some skill domains, performance has been shown to improve by 20% or more following sleep, suggesting that sleep enhances learning. However, recent work suggests that those performance gains may be driven by several factors that are unrelated to sleep consolidation, inviting a reconsideration of sleep's theoretical role in the consolidation of procedural memories. Here we report the first comprehensive investigation of that possibility for the case of motor sequence learning. Quantitative meta-analyses involving 34 articles, 88 experimental groups and 1,296 subjects confirmed the empirical pattern of a large performance gain following sleep and a significantly smaller gain following wakefulness. However, the results also confirm strong moderating effects of 4 previously hypothesized variables: averaging in the calculation of prepost gain scores, build-up of reactive inhibition over training, time of testing, and training duration, along with 1 supplemental variable, elderly status. With those variables accounted for, there was no evidence that sleep enhances learning. Thus, the literature speaks against, rather than for, the enhancement hypothesis. Overall there was relatively better performance after sleep than after wakefulness, suggesting that sleep may stabilize memory. That effect, however, was not consistent across different experimental designs. We conclude that sleep does not enhance motor learning and that the role of sleep in the stabilization of memory cannot be conclusively determined based on the literature to date. We discuss challenges and opportunities for the field, make recommendations for improved experimental design, and suggest approaches to data analysis that eliminate confounds due to averaging over online learning.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据