海马 CA3 区记忆支持神经元动力学机制

IF 5.7 1区 化学 Q2 CHEMISTRY, PHYSICAL Journal of Chemical Theory and Computation Pub Date : 2024-10-24 DOI:10.1016/j.cell.2024.09.041
Yiding Li, John J. Briguglio, Sandro Romani, Jeffrey C. Magee
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引用次数: 0

摘要

海马 CA3 是记忆形成和检索的核心。尽管人们提出了各种网络机制,但缺乏直接证据。通过在行为小鼠体内进行细胞内Vm记录和光遗传学操作,我们发现CA3位置场活动是由CA3锥体神经元之间的递归突触上的对称形式的行为时标突触可塑性(BTSP)产生的,而不是由来自齿状回(DG)的突触产生的。其他操作显示,根据动物的运动更新位置细胞的活动需要来自内侧皮层(EC)而非 DG 的兴奋性输入。这些数据被一个计算模型所捕获,该模型使用 BTSP 和外部更新输入来产生在线学习条件下的吸引子动力学。理论分析进一步凸显了这种网络的超强记忆存储能力,尤其是在处理相关输入模式时。这些证据阐明了海马学习和记忆形成的细胞和电路机制。
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Mechanisms of memory-supporting neuronal dynamics in hippocampal area CA3
Hippocampal CA3 is central to memory formation and retrieval. Although various network mechanisms have been proposed, direct evidence is lacking. Using intracellular Vm recordings and optogenetic manipulations in behaving mice, we found that CA3 place-field activity is produced by a symmetric form of behavioral timescale synaptic plasticity (BTSP) at recurrent synapses among CA3 pyramidal neurons but not at synapses from the dentate gyrus (DG). Additional manipulations revealed that excitatory input from the entorhinal cortex (EC) but not the DG was required to update place cell activity based on the animal’s movement. These data were captured by a computational model that used BTSP and an external updating input to produce attractor dynamics under online learning conditions. Theoretical analyses further highlight the superior memory storage capacity of such networks, especially when dealing with correlated input patterns. This evidence elucidates the cellular and circuit mechanisms of learning and memory formation in the hippocampus.
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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
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