Center for Mathematical Sciences, Huazhong University of Science and Technology, Wuhan, China.
Hubei Key Lab of Engineering Modeling and Scientific Computing, Huazhong University of Science and Technology, Wuhan, China.
Sci Rep. 2018 Oct 23;8(1):15666. doi: 10.1038/s41598-018-34050-1.
Neuronal morphology is an essential element for brain activity and function. We take advantage of current availability of brain-wide neuron digital reconstructions of the Pyramidal cells from a mouse brain, and analyze several emergent features of brain-wide neuronal morphology. We observe that axonal trees are self-affine while dendritic trees are self-similar. We also show that tree size appear to be random, independent of the number of dendrites within single neurons. Moreover, we consider inhomogeneous branching model which stochastically generates rooted 3-Cayley trees for the brain-wide neuron topology. Based on estimated order-dependent branching probability from actual axonal and dendritic trees, our inhomogeneous model quantitatively captures a number of topological features including size and shape of both axons and dendrites. This sheds lights on a universal mechanism behind the topological formation of brain-wide axonal and dendritic trees.
神经元形态是大脑活动和功能的重要组成部分。我们利用当前可获得的来自小鼠大脑的全脑神经元数字重建，分析了全脑神经元形态的几个新出现的特征。我们观察到轴突树是自仿射的，而树突树是自相似的。我们还表明，树的大小似乎是随机的，与单个神经元内的树突数量无关。此外，我们考虑了非均匀分支模型，该模型随机生成用于全脑神经元拓扑的有根 3-Cayley 树。基于从实际的轴突和树突中估计的与顺序相关的分支概率，我们的非均匀模型定量地捕获了许多拓扑特征，包括轴突和树突的大小和形状。这揭示了全脑轴突和树突拓扑形成背后的通用机制。
