Despite the known behavioral benefits of rapid eye movement (REM) sleep, discrete neural oscillatory events in human scalp electroencephalography (EEG) linked with behavior have not been discovered. This knowledge gap hinders mechanistic understanding of the function of sleep, as well as the development of biophysical models and REM-based causal interventions. We designed a detection algorithm to identify bursts of activity in high-density, scalp EEG within theta (4–8 Hz) and alpha (8–13 Hz) bands during REM sleep. Across 38 nights of sleep, we characterized the burst events (i.e., count, duration, density, peak frequency, amplitude) in healthy, young male and female human participants (38; 21F) and investigated burst activity in relation to sleep-dependent memory tasks: hippocampal-dependent episodic verbal memory and nonhippocampal visual perceptual learning. We found greater burst count during the more REM-intensive second half of the night (p < 0.05), longer burst duration during the first half of the night (p < 0.05), but no differences across the night in density or power (p > 0.05). Moreover, increased alpha burst power was associated with increased overnight forgetting for episodic memory (p < 0.05). Furthermore, we show that increased REM theta burst activity in retinotopically specific regions was associated with better visual perceptual performance. Our work provides a critical bridge between discrete REM sleep events in human scalp EEG that support cognitive processes and the identification of similar activity patterns in animal models that allow for further mechanistic characterization.

尽管快速眼动 (REM) 睡眠具有已知的行为益处，但人类头皮脑电图 (EEG) 中与行为相关的离散神经振荡事件尚未被发现。这种知识差距阻碍了对睡眠功能的机械理解，也阻碍了生物物理模型和基于快速眼动的因果干预措施的发展。我们设计了一种检测算法来识别快速眼动睡眠期间 θ（4-8 Hz）和 α（8-13 Hz）频段内高密度头皮脑电图的活动爆发。在 38 个晚上的睡眠中，我们对健康年轻男性和女性参与者 (38; 21F) 的爆发事件（即计数、持续时间、密度、峰值频率、振幅）进行了表征，并研究了与睡眠依赖性记忆相关的爆发活动任务：海马依赖性情景言语记忆和非海马视觉感知学习。我们发现在 REM 更密集的后半夜爆发次数较多 (p < 0.05)，前半夜的爆发持续时间较长 (p < 0.05)，但整个晚上的密度或功率没有差异 (p < 0.05) > 0.05）。此外，阿尔法爆发力的增加与情景记忆的夜间遗忘增加相关（p < 0.05）。此外，我们发现视网膜局部特定区域的 REM θ 爆发活动增加与更好的视觉感知表现相关。我们的工作在人类头皮脑电图的离散快速眼动睡眠事件（支持认知过程）和动物模型中识别类似的活动模式（允许进一步的机制表征）之间架起了一座重要的桥梁。