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通过嵌套频谱成分解析海马θ振荡在空间探索和记忆引导行为中的作用。

Parsing Hippocampal Theta Oscillations by Nested Spectral Components during Spatial Exploration and Memory-Guided Behavior.

机构信息

Medical Research Council Brain Network Dynamics Unit, Department of Pharmacology, University of Oxford, Oxford OX1 3TH, UK.

Medical Research Council Brain Network Dynamics Unit, Department of Pharmacology, University of Oxford, Oxford OX1 3TH, UK.

出版信息

Neuron. 2018 Nov 21;100(4):940-952.e7. doi: 10.1016/j.neuron.2018.09.031. Epub 2018 Oct 18.

DOI:10.1016/j.neuron.2018.09.031
PMID:30344040
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6277817/
Abstract

Theta oscillations reflect rhythmic inputs that continuously converge to the hippocampus during exploratory and memory-guided behavior. The theta-nested operations that organize hippocampal spiking could either occur regularly from one cycle to the next or be tuned on a cycle-by-cycle basis. To resolve this, we identified spectral components nested in individual theta cycles recorded from the mouse CA1 hippocampus. Our single-cycle profiling revealed theta spectral components associated with different firing modulations and distinguishable ensembles of principal cells. Moreover, novel co-firing patterns of principal cells in theta cycles nesting mid-gamma oscillations were the most strongly reactivated in subsequent offline sharp-wave/ripple events. Finally, theta-nested spectral components were differentially altered by behavioral stages of a memory task; the 80-Hz mid-gamma component was strengthened during learning, whereas the 22-Hz beta, 35-Hz slow gamma, and 54-Hz mid-gamma components increased during retrieval. We conclude that cycle-to-cycle variability of theta-nested spectral components allows parsing of theta oscillations into transient operating modes with complementary mnemonic roles.

摘要

θ 振荡反映了在探索和记忆引导行为过程中持续汇聚到海马体的节律输入。组织海马体放电的θ 嵌套操作可以从一个周期到下一个周期有规律地发生,也可以在逐个周期的基础上进行调整。为了解决这个问题,我们从记录的小鼠 CA1 海马体的单个θ 周期中识别出嵌套的频谱成分。我们的单周期分析揭示了与不同放电调制相关的θ 频谱成分,以及可区分的主细胞集合。此外,在嵌套中γ 振荡的θ 周期中主细胞的新的共发射模式在随后的离线尖峰/涟漪事件中被最强地重新激活。最后,θ 嵌套频谱成分因记忆任务的行为阶段而有差异地改变;在学习过程中,80-Hz 中γ 成分增强,而 22-Hzβ、35-Hz 慢γ和 54-Hz 中γ 成分在检索过程中增加。我们的结论是,θ 嵌套频谱成分的周期到周期变化允许将θ 振荡解析为具有互补记忆作用的瞬态操作模式。

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