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成年新生未成熟颗粒细胞对海马齿状回模式分离的影响。

Effect of adult-born immature granule cells on pattern separation in the hippocampal dentate gyrus.

作者信息

Kim Sang-Yoon, Lim Woochang

机构信息

Institute for Computational Neuroscience and Department of Science Education, Daegu National University of Education, Daegu, 42411 Korea.

出版信息

Cogn Neurodyn. 2024 Aug;18(4):2077-2093. doi: 10.1007/s11571-023-09985-5. Epub 2023 Jul 1.

DOI:10.1007/s11571-023-09985-5
PMID:39104672
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11297892/
Abstract

Young immature granule cells (imGCs) appear via adult neurogenesis in the hippocampal dentate gyrus (DG). In comparison to mature GCs (mGCs) (born during development), the imGCs exhibit two competing distinct properties such as high excitability (increasing activation degree) and low excitatory innervation (reducing activation degree). We develop a spiking neural network for the DG, incorporating both the mGCs and the imGCs. The mGCs are well known to perform "pattern separation" (i.e., a process of transforming similar input patterns into less similar output patterns) to facilitate pattern storage in the hippocampal CA3. In this paper, we investigate the effect of the young imGCs on pattern separation of the mGCs. The pattern separation efficacy (PSE) of the mGCs is found to vary through competition between high excitability and low excitatory innervation of the imGCs. Their PSE becomes enhanced (worsened) when the effect of high excitability is higher (lower) than the effect of low excitatory innervation. In contrast to the mGCs, the imGCs are found to perform "pattern integration" (i.e., making association between dissimilar patterns). Finally, we speculate that memory resolution in the hippocampal CA3 might be optimally maximized via mixed cooperative encoding through pattern separation and pattern integration.

摘要

年轻的未成熟颗粒细胞(imGCs)通过成体神经发生出现在海马齿状回(DG)中。与成熟颗粒细胞(mGCs)(发育期间产生)相比,imGCs表现出两种相互竞争的不同特性,即高兴奋性(增加激活程度)和低兴奋性神经支配(降低激活程度)。我们为DG开发了一种脉冲神经网络,其中纳入了mGCs和imGCs。众所周知,mGCs执行“模式分离”(即将相似的输入模式转换为不太相似的输出模式的过程)以促进模式存储在海马CA3中。在本文中,我们研究了年轻的imGCs对mGCs模式分离的影响。发现mGCs的模式分离效率(PSE)通过imGCs的高兴奋性和低兴奋性神经支配之间的竞争而变化。当高兴奋性的影响高于(低于)低兴奋性神经支配的影响时,它们的PSE会增强(恶化)。与mGCs相反,发现imGCs执行“模式整合”(即建立不同模式之间的关联)。最后,我们推测海马CA3中的记忆分辨率可能通过模式分离和模式整合的混合协作编码而最佳地最大化。

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本文引用的文献

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Cogn Neurodyn. 2022 Dec;16(6):1427-1447. doi: 10.1007/s11571-022-09797-z. Epub 2022 Mar 24.
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Spike-Based Winner-Take-All Computation: Fundamental Limits and Order-Optimal Circuits.基于尖峰的胜者全拿计算:基本限制和阶最优电路。
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