Decoding material-specific memory reprocessing during sleep in humans.
Decoding material-specific memory reprocessing during sleep in humans.
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DOI：
10.1038/ncomms15404
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发表时间：
2017-05-17
影响因子：
16.6
通讯作者：
Gais S
中科院分区：
文献类型：
--
作者：
Schönauer M;Alizadeh S;Jamalabadi H;Abraham A;Pawlizki A;Gais S
神经元的学习活动在睡眠期间被重新激活，但人类对这种重新激活的动力学仍然知之甚少。在这里，我们使用多变量模式分类来解码睡眠期间的脑电活动，并确定参与者在之前的学习会话中观看了什么类型的图像。我们在快速眼动（REM）和非快速眼动（NREM）睡眠期间发现了与学习相关的处理的重要模式，这些模式在受试者中具有普遍性。这个过程发生在一个周期性的方式在时间窗口一致的关键时期的突触可塑性。它在头皮上的空间分布和相关频率在NREM和REM睡眠中不同。此外，只有在慢波睡眠中再加工的强度会影响后来的记忆表现，这说明这些状态之间至少有两种不同的潜在机制。因此，我们表明，记忆再加工发生在人类的NREM和REM睡眠，它涉及到巩固过程的不同方面。神经元的学习活动在睡眠期间被重新激活，但人类对这种重新激活的动力学仍然知之甚少。在这里，作者表明，记忆处理发生在人类睡眠的所有阶段，但在REM和非REM睡眠中对记忆内容的再加工对后期记忆表现有不同的影响。
Neuronal learning activity is reactivated during sleep but the dynamics of this reactivation in humans are still poorly understood. Here we use multivariate pattern classification to decode electrical brain activity during sleep and determine what type of images participants had viewed in a preceding learning session. We find significant patterns of learning-related processing during rapid eye movement (REM) and non-REM (NREM) sleep, which are generalizable across subjects. This processing occurs in a cyclic fashion during time windows congruous to critical periods of synaptic plasticity. Its spatial distribution over the scalp and relevant frequencies differ between NREM and REM sleep. Moreover, only the strength of reprocessing in slow-wave sleep influenced later memory performance, speaking for at least two distinct underlying mechanisms between these states. We thus show that memory reprocessing occurs in both NREM and REM sleep in humans and that it pertains to different aspects of the consolidation process. Neuronal learning activity is reactivated during sleep but the dynamics of this reactivation in humans are still poorly understood. Here the authors show that memory processing occurs during all stages of sleep in humans but that reprocessing of memory content in REM and non-REM sleep has different effects on later memory performance.