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Preconfigured patterns are the primary driver of offline multi-neuronal sequence replay

机译:预配置模式是离线多神经元序列重播的主要驱动程序

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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 naive 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.
机译:据信,海马的自发神经元集合活性是由预先配置的内部产生动态的组合和最近经验驱动的独特活动模式。以前的研究已经建立了预先配置的顺序神经元模式(即,PROPLAY)有助于将来的表达细胞序列的表达,这反过来有助于表达经验后的序贯神经元模式(即重播)。预先配置和经验相关因素的相对贡献在运行后睡眠期间重播和整体顺序活动,据信高度偏向最近的经验,尽管从未直接测试过。在这里,我们使用多神经元序列分析通过射击率来计算,并直接比较内部产生的和最近的经验驱动因子对幼稚成年大鼠后睡眠中的顺序神经元活动的贡献。我们发现后睡眠期间的多神经元序列是通过预先预先配置的模式的主要贡献,并通过地区序列和相关的唤醒休息多神经元序列在de nogo运行期间经历的相关性睡眠,这是与经营前和后期睡眠多神经元序列弱和类似地相关。这些发现表明海马网络的稳健默认内部组织成持续的神经元集合,其抵消了DE Novo空间体验,并表明在德无外的经验期间的新颖信息集成导致顺序网络模式的持续变化比以前假设更微妙。

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