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Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons

机译:人皮层锥体神经元中沿着树突网络的脊柱三维空间建模

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摘要

We modeled spine distribution along the dendritic networks of pyramidal neurons in both basal and apical dendrites. To do this, we applied network spatial analysis because spines can only lie on the dendritic shaft. We expanded the existing 2D computational techniques for spatial analysis along networks to perform a 3D network spatial analysis. We analyzed five detailed reconstructions of adult human pyramidal neurons of the temporal cortex with a total of more than 32,000 spines. We confirmed that there is a spatial variation in spine density that is dependent on the distance to the cell body in all dendrites. Considering the dendritic arborizations of each pyramidal cell as a group of instances of the same observation (the neuron), we used replicated point patterns together with network spatial analysis for the first time to search for significant differences in the spine distribution of basal dendrites between different cells and between all the basal and apical dendrites. To do this, we used a recent variant of Ripley’s K function defined to work along networks. The results showed that there were no significant differences in spine distribution along basal arbors of the same neuron and along basal arbors of different pyramidal neurons. This suggests that dendritic spine distribution in basal dendritic arbors adheres to common rules. However, we did find significant differences in spine distribution along basal versus apical networks. Therefore, not only do apical and basal dendritic arborizations have distinct morphologies but they also obey different rules of spine distribution. Specifically, the results suggested that spines are more clustered along apical than in basal dendrites. Collectively, the results further highlighted that synaptic input information processing is different between these two dendritic domains.
机译:我们对沿锥体神经元的树突网络在基底和顶端树突中的脊柱分布进行建模。为此,我们应用了网络空间分析,因为刺只能位于树突状轴上。我们扩展了用于网络空间分析的现有2D计算技术,以执行3D网络空间分析。我们分析了五个颞叶皮层成年人锥体神经元的详细重建,共有超过32,000根脊柱。我们证实,在所有树突中,脊柱密度存在空间变化,这取决于到细胞体的距离。将每个锥体细胞的树突状乔木化视为同一观察结果(神经元)的一组实例,我们首次将复制的点模式与网络空间分析一起用于搜索不同物种之间基础树突的脊柱分布的显着差异细胞和所有基础和顶端树突之间。为此,我们使用了Ripley K函数的最新变体,该函数定义为可用于网络。结果表明,沿着同一神经元的基底柄和不同的锥体神经元的基底柄的脊柱分布没有显着差异。这表明在基础树突状乔木中的树突状脊柱分布遵循共同的规则。但是,我们确实发现沿基部和根部网络的脊柱分布存在显着差异。因此,不仅根尖和基部树状乔木具有独特的形态,而且它们还遵循不同的脊柱分布规则。具体而言,结果表明,与基部树突相比,脊椎在根尖的聚集更多。总体而言,结果进一步突出了这两个树突域之间的突触输入信息处理是不同的。

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