School of Psychological Sciences, Zochonis, Building, University of Manchester, Brunswick Street, Manchester M13 9PL, UK.
School of Psychological Sciences, Zochonis, Building, University of Manchester, Brunswick Street, Manchester M13 9PL, UK.
Neuropsychologia. 2011 Apr;49(5):1322-1331. doi: 10.1016/j.neuropsychologia.2011.02.015. Epub 2011 Feb 16.
The importance of sleep for memory consolidation has been firmly established over the past decade. Recent work has extended this by suggesting that sleep is also critical for the integration of disparate fragments of information into a unified schema, and for the abstraction of underlying rules. The question of which aspects of sleep play a significant role in integration and abstraction is, however, currently unresolved. Here, we examined the role of sleep in abstraction of the implicit probabilistic structure in sequential stimuli using a statistical learning paradigm, and tested for its role in such abstraction by searching for a predictive relationship between the type of sleep obtained and subsequent performance improvements using polysomnography. In our experiments, participants were exposed to a series of tones in a probabilistically determined sequential structure, and subsequently tested for recognition of novel short sequences adhering to this same statistical pattern in both immediate- and delayed-recall sessions. Participants who consolidated over a night of sleep improved significantly more than those who consolidated over an equivalent period of daytime wakefulness. Similarly, participants who consolidated across a 4-h afternoon delay containing a nap improved significantly more than those who consolidated across an equivalent period without a nap. Importantly, polysomnography revealed a significant correlation between the level of improvement and the amount of slow-wave sleep obtained. We also found evidence of a time-based consolidation process which operates alongside sleep-specific consolidation. These results demonstrate that abstraction of statistical patterns benefits from sleep, and provide the first clear support for the role of slow-wave sleep in this consolidation.
在过去的十年中，睡眠对记忆巩固的重要性已得到充分证实。最近的研究进一步表明，睡眠对于将信息的不相关片段整合到一个统一的模式中，以及对于抽象潜在规则也是至关重要的。然而，目前尚未解决睡眠的哪些方面在整合和抽象中起着重要作用的问题。在这里，我们使用统计学习范式研究了睡眠在整合和抽象顺序刺激中的隐含概率结构方面的作用，并通过使用多导睡眠图来搜索获得的睡眠类型与随后的性能提高之间的预测关系，测试了其在这种抽象中的作用。在我们的实验中，参与者暴露于一系列以概率确定的顺序结构中的音调中，然后在即时和延迟回忆测试中测试他们对遵循相同统计模式的新短序列的识别。在一夜睡眠中巩固的参与者比在同等的白天清醒时间中巩固的参与者显著提高。同样，在包含小睡的 4 小时下午延迟中巩固的参与者比在没有小睡的等效时间段中巩固的参与者显著提高。重要的是，多导睡眠图显示出改善水平与获得的慢波睡眠量之间存在显著相关性。我们还发现了证据表明，存在一种与睡眠特异性巩固并行的基于时间的巩固过程。这些结果表明，统计模式的抽象得益于睡眠，并为慢波睡眠在这种巩固中的作用提供了第一个明确的支持。
