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用贝叶斯网络比较人和小鼠海马 CA1 锥体神经元的基底树突分支。

Comparing basal dendrite branches in human and mouse hippocampal CA1 pyramidal neurons with Bayesian networks.

机构信息

Computational Intelligence Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Boadilla del Monte, 28660, Madrid, Spain.

Laboratorio Cajal de Circuitos Corticales, Universidad Politécnica de Madrid and Instituto Cajal (CSIC), Pozuelo de Alarcón, 28223, Madrid, Spain.

出版信息

Sci Rep. 2020 Oct 29;10(1):18592. doi: 10.1038/s41598-020-73617-9.

DOI:10.1038/s41598-020-73617-9
PMID:33122691
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7596062/
Abstract

Pyramidal neurons are the most common cell type in the cerebral cortex. Understanding how they differ between species is a key challenge in neuroscience. A recent study provided a unique set of human and mouse pyramidal neurons of the CA1 region of the hippocampus, and used it to compare the morphology of apical and basal dendritic branches of the two species. The study found inter-species differences in the magnitude of the morphometrics and similarities regarding their variation with respect to morphological determinants such as branch type and branch order. We use the same data set to perform additional comparisons of basal dendrites. In order to isolate the heterogeneity due to intrinsic differences between species from the heterogeneity due to differences in morphological determinants, we fit multivariate models over the morphometrics and the determinants. In particular, we use conditional linear Gaussian Bayesian networks, which provide a concise graphical representation of the independencies and correlations among the variables. We also extend the previous study by considering additional morphometrics and by formally testing whether a morphometric increases or decreases with the distance from the soma. This study introduces a multivariate methodology for inter-species comparison of morphology.

摘要

锥体神经元是大脑皮层中最常见的细胞类型。了解它们在物种间的差异是神经科学的一个关键挑战。最近的一项研究提供了一组独特的人类和小鼠海马 CA1 区的锥体神经元,并利用它比较了这两个物种的树突顶和基底分支的形态。研究发现,物种间在形态计量学的大小上存在差异,但在形态决定因素(如分支类型和分支顺序)方面的变化存在相似性。我们使用相同的数据集来进一步比较基底树突。为了将由于物种间内在差异引起的异质性与由于形态决定因素的差异引起的异质性区分开来,我们对形态计量学和决定因素进行了多元模型拟合。特别是,我们使用条件线性高斯贝叶斯网络,它为变量之间的独立性和相关性提供了简洁的图形表示。我们还通过考虑其他形态计量学并正式测试形态计量学是否随体细胞距离的增加而增加或减少,扩展了之前的研究。这项研究为物种间形态比较引入了一种多元方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94f5/7596062/c7b681a1fc7b/41598_2020_73617_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94f5/7596062/c7b681a1fc7b/41598_2020_73617_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94f5/7596062/c7b681a1fc7b/41598_2020_73617_Fig3_HTML.jpg

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