Chen Shuqiang, He Mingjian, Brown Ritchie E, Eden Uri T, Prerau Michael J
Graduate Program for Neuroscience, Boston University, Boston, MA 02215.
Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114.
Proc Natl Acad Sci U S A. 2025 Jan 14;122(2):e2405276121. doi: 10.1073/pnas.2405276121. Epub 2025 Jan 7.
Sleep spindles are cortical electrical oscillations considered critical for memory consolidation and sleep stability. The timing and pattern of sleep spindles are likely to be important in driving synaptic plasticity during sleep as well as preventing disruption of sleep by sensory and internal stimuli. However, the relative importance of factors such as sleep depth, cortical up/down-state, and temporal clustering in governing sleep spindle dynamics remains poorly understood. Here, we analyze sleep data from 1,025 participants, statistically modeling the simultaneous influences of multiple factors on moment-to-moment spindle production using a point process-generalized linear model framework. Results reveal fingerprint-like timing patterns, characterized by a refractory period followed by a period of increased spindle activity, which are highly individualized yet consistent night-to-night, with increased variability with age. Strikingly, short-term (<15 s) temporal patterns of past spindle history are the main determinant of spindle timing, accounting for over 70% of the statistical deviance-surpassing the contribution of factors such as cortical up/down-state (slow oscillation phase), sleep depth, and long-term history (15 to 90 s, including ~50 s infraslow activity). Short-term history has a statistically significant influence in over 98% of the population, suggesting it is a near-universal feature of spindle activity. Short-term history and slow oscillation phase exert independent effects on spindle timing. Our results establish a robust statistical framework to examine abnormalities in sleep spindle timing observed in neurological disorders and aging, as well as the relationship between individualized sleep spindle timing, cognition, and sleep stability.
睡眠纺锤波是一种皮层电振荡，被认为对记忆巩固和睡眠稳定性至关重要。睡眠纺锤波的时间和模式在睡眠期间驱动突触可塑性以及防止感觉和内部刺激干扰睡眠方面可能很重要。然而，睡眠深度、皮层上/下状态和时间聚类等因素在控制睡眠纺锤波动态中的相对重要性仍知之甚少。在这里，我们分析了来自1025名参与者的睡眠数据，使用点过程广义线性模型框架对多个因素对瞬间纺锤波产生的同时影响进行了统计建模。结果揭示了类似指纹的时间模式，其特征是有一个不应期，随后是纺锤波活动增加的时期，这种模式高度个体化但每晚一致，且随年龄增长变异性增加。引人注目的是，过去纺锤波历史的短期（<15秒）时间模式是纺锤波时间的主要决定因素，占统计偏差的70%以上，超过了皮层上/下状态（慢振荡阶段）、睡眠深度和长期历史（15至90秒，包括约50秒的超慢活动）等因素的贡献。短期历史在超过98%的人群中具有统计学上的显著影响，表明它是纺锤波活动的一个几乎普遍的特征。短期历史和慢振荡阶段对纺锤波时间有独立影响。我们的结果建立了一个强大的统计框架，以检查在神经系统疾病和衰老中观察到的睡眠纺锤波时间异常，以及个体化睡眠纺锤波时间、认知和睡眠稳定性之间的关系。
