Department of Mathematics, Western University, London, Canada.
Brain and Mind Institute, Western University, London, Canada.
Elife. 2022 Jun 29;11:e75769. doi: 10.7554/eLife.75769.
Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; however, recent work has challenged this idea by reporting isolated sleep rhythms such as slow oscillations and spindles. What is the spatial scale of sleep rhythms? To answer this question, we adapted deep learning algorithms initially developed for detecting earthquakes and gravitational waves in high-noise settings for analysis of neural recordings in sleep. We then studied sleep spindles in non-human primate electrocorticography (ECoG), human electroencephalogram (EEG), and clinical intracranial electroencephalogram (iEEG) recordings in the human. Within each recording type, we find widespread spindles occur much more frequently than previously reported. We then analyzed the spatiotemporal patterns of these large-scale, multi-area spindles and, in the EEG recordings, how spindle patterns change following a visual memory task. Our results reveal a potential role for widespread, multi-area spindles in consolidation of memories in networks widely distributed across primate cortex.
睡眠通常被认为是丘脑和新皮层大范围同步的状态；然而，最近的研究通过报告孤立的睡眠节律，如慢波振荡和纺锤波，对这一观点提出了挑战。睡眠节律的空间尺度是多少？为了回答这个问题，我们改编了最初为在高噪声环境中检测地震和引力波而开发的深度学习算法，用于分析睡眠中的神经记录。然后，我们在非人类灵长类动物皮层电图（ECoG）、人类脑电图（EEG）和人类临床颅内脑电图（iEEG）记录中研究了睡眠纺锤波。在每种记录类型中，我们发现广泛存在的纺锤波比以前报道的更为常见。然后，我们分析了这些大范围、多区域纺锤波的时空模式，以及在 EEG 记录中，纺锤波模式如何在进行视觉记忆任务后发生变化。我们的结果揭示了广泛的、多区域的纺锤波在巩固记忆网络中的潜在作用，这些记忆网络广泛分布在灵长类动物皮层中。
