Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut.
Department of Neuroscience and Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut.
Hippocampus. 2019 Mar;29(3):275-283. doi: 10.1002/hipo.23034. Epub 2018 Nov 22.
Spontaneous neuronal ensemble activity in the hippocampus is believed to result from a combination of preconfigured internally generated dynamics and the unique patterns of activity driven by recent experience. Previous research has established that preconfigured sequential neuronal patterns (i.e., preplay) contribute to the expression of future place cell sequences, which in turn contribute to the sequential neuronal patterns expressed post-experience (i.e., replay). The relative contribution of preconfigured and of experience-related factors to replay and to overall sequential activity during post-run sleep is believed to be highly biased toward the recent run experience, despite never being tested directly. Here, we use multi-neuronal sequence analysis unbiased by firing rate to compute and directly compare the contributions of internally generated and of recent experience-driven factors to the sequential neuronal activity in post-run sleep in naïve adult rats. We find that multi-neuronal sequences during post-run sleep are dominantly contributed by the pre-run preconfigured patterns and to a much smaller extent by the place cell sequences and associated awake rest multi-neuronal sequences experienced during de novo run session, which are weakly and similarly correlated with pre- and post-run sleep multi-neuronal sequences. These findings indicate a robust default internal organization of the hippocampal network into sequential neuronal ensembles that withstands a de novo spatial experience and suggest that integration of novel information during de novo experience leading to lasting changes in sequential network patterns is much more subtle than previously assumed.
海马体中自发的神经元集合活动被认为是由预先配置的内部产生的动力学和最近经验驱动的独特活动模式的组合产生的。先前的研究已经确定,预先配置的顺序神经元模式(即预演)有助于未来位置细胞序列的表达,而这些序列反过来又有助于经验后(即重演)表达的顺序神经元模式。尽管从未直接进行测试,但人们认为,在经历后睡眠期间,预先配置和与经验相关的因素对重演和整体顺序活动的相对贡献高度偏向于最近的运行经验。在这里,我们使用不受放电率影响的多神经元序列分析来计算并直接比较内部生成和最近经验驱动因素对经历后睡眠中经历后睡眠中顺序神经元活动的贡献。我们发现,经历后睡眠中的多神经元序列主要由预跑预先配置的模式贡献,而由位置细胞序列和在新运行会话期间经历的相关清醒休息多神经元序列贡献的程度要小得多,这些序列与预跑和经历后睡眠的多神经元序列弱相关且相似。这些发现表明,海马体网络具有强大的默认内部组织,将其组织成顺序神经元集合,可以抵抗新的空间经验,并且表明在导致序列网络模式持久变化的新经验过程中整合新信息比之前假设的要微妙得多。