Memories of experiences are stored in the cerebral cortex. Sleep is critical for the consolidation of hippocampal memory of wake experiences into the neocortex. Understanding representations of neural codes of hippocampal-neocortical networks during sleep would reveal important circuit mechanisms in memory consolidation and provide novel insights into memory and dreams. Although sleep-associated ensemble spike activity has been investigated, identifying the content of memory in sleep remains challenging. Here we revisit important experimental findings on sleep-associated memory (i.e., neural activity patterns in sleep that reflect memory processing) and review computational approaches to the analysis of sleep-associated neural codes (SANCs). We focus on two analysis paradigms for sleep-associated memory and propose a new unsupervised learning framework ('memory first, meaning later') for unbiased assessment of SANCs.

中文翻译：

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破译睡眠期间记忆的神经密码


经历的记忆储存在大脑皮层中。睡眠对于将清醒经历的海马记忆巩固到新皮质至关重要。了解睡眠期间海马-新皮质网络的神经编码表示将揭示记忆巩固中的重要回路机制，并为记忆和梦提供新的见解。尽管已经研究了与睡眠相关的整体尖峰活动，但识别睡眠中的记忆内容仍然具有挑战性。在这里，我们重新审视有关睡眠相关记忆（即睡眠中反映记忆处理的神经活动模式）的重要实验结果，并回顾分析睡眠相关神经代码（SANC）的计算方法。我们重点关注与睡眠相关的记忆的两种分析范式，并提出了一种新的无监督学习框架（“记忆优先，意义稍后”），用于对 SANC 进行公正的评估。