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发情周期调节海马体棘突动力学、树突处理和空间编码。

The estrous cycle modulates hippocampal spine dynamics, dendritic processing, and spatial coding.

作者信息

Wolcott Nora S, Redman William T, Karpinska Marie, Jacobs Emily G, Goard Michael J

机构信息

Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA.

Interdepartmental Graduate Program in Dynamical Neuroscience, University of California, Santa Barbara, Santa Barbara, CA 93106, USA; Intelligent Systems Center, Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723, USA.

出版信息

Neuron. 2025 May 7. doi: 10.1016/j.neuron.2025.04.014.

Abstract

Histological evidence suggests that the estrous cycle exerts a powerful influence on CA1 neurons in the mammalian hippocampus. Decades have passed since this landmark observation, yet how the estrous cycle shapes dendritic spine dynamics and hippocampal spatial coding in vivo remains a mystery. Here, we used a custom hippocampal microperiscope and two-photon calcium imaging to track CA1 pyramidal neurons in female mice across multiple cycles. Estrous cycle stage had a potent effect on spine dynamics, with spine density peaking during proestrus when estradiol levels are highest. These morphological changes coincided with greater somatodendritic coupling and increased infiltration of back-propagating action potentials into the apical dendrite. Finally, tracking CA1 response properties during navigation revealed greater place field stability during proestrus, evident at both the single-cell and population levels. These findings demonstrate that the estrous cycle drives large-scale structural and functional plasticity in hippocampal neurons essential for learning and memory.

摘要

组织学证据表明,发情周期对哺乳动物海马体中的CA1神经元有强大影响。自这一具有里程碑意义的观察结果出现以来,几十年过去了,但发情周期如何塑造体内树突棘动力学和海马体空间编码仍是一个谜。在这里,我们使用定制的海马体微型显微镜和双光子钙成像技术,在多个周期中追踪雌性小鼠的CA1锥体神经元。发情周期阶段对树突棘动力学有显著影响,当雌二醇水平最高的发情前期,树突棘密度达到峰值。这些形态学变化与更强的体树突耦合以及反向传播动作电位向顶端树突的渗透增加相吻合。最后,在导航过程中追踪CA1反应特性发现,发情前期位置场稳定性更高,在单细胞和群体水平上均很明显。这些发现表明,发情周期驱动海马体神经元发生大规模的结构和功能可塑性变化,这对学习和记忆至关重要。

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