Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
Bioscience and Biomedical Engineering Thrust, Systems Hub, Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China.
Nat Neurosci. 2024 Sep;27(9):1816-1828. doi: 10.1038/s41593-024-01703-6. Epub 2024 Jul 19.
Animals encounter and remember multiple experiences daily. During sleep, hippocampal neuronal ensembles replay past experiences and preplay future ones. Although most previous studies investigated p/replay of a single experience, it remains unclear how the hippocampus represents many experiences without major interference during sleep. By monitoring hippocampal neuronal ensembles as rats encountered 15 distinct linear track experiences, we uncovered principles for efficient multi-experience compressed p/replay representation. First, we found a serial position effect whereby the earliest and the most recent experiences had the strongest representations. Second, distinct experiences were co-represented in a multiplexed, flickering manner during nested p/replay events, which greatly enhanced the network's representational capacity. Third, spatially contiguous and disjunct track pairs were bound together into contiguous conjunctive representations during sleep. Finally, sequences spanning day-long multi-track experiences were p/replayed at hyper-compressed ratios during sleep. These coding schemes efficiently parallelize, bind and compress multiple sequential representations with reduced interference and enhanced capacity during sleep.
动物每天都会遇到并记住多种经历。在睡眠中,海马体神经元集合会重演过去的经历并预演未来的经历。尽管大多数先前的研究都调查了单一经历的 p/replay,但在睡眠期间,海马体如何在没有重大干扰的情况下表示多种经历仍不清楚。通过监测大鼠在遇到 15 种不同线性轨迹经历时的海马体神经元集合,我们揭示了高效的多经历压缩 p/replay 表示的原则。首先,我们发现了一种序列位置效应,即最早和最近的经历具有最强的表示。其次,在嵌套的 p/replay 事件中,不同的经历以多路复用、闪烁的方式共同表示,这极大地增强了网络的表示能力。第三,在睡眠中,空间上连续和不连续的轨迹对被绑定在一起形成连续的联合表示。最后,跨越一整天多轨迹经历的序列在睡眠中以超压缩的比例被 p/replayed。这些编码方案在睡眠期间有效地并行化、绑定和压缩多个顺序表示,同时减少干扰并增强了容量。