Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, 15213, USA.
School of Mechanical Engineering, Purdue University, West Lafayette, 47907, USA.
Sci Rep. 2022 May 17;12(1):8120. doi: 10.1038/s41598-022-12073-z.
We present a new computational framework of neuron growth based on the phase field method and develop an open-source software package called "NeuronGrowth_IGAcollocation". Neurons consist of a cell body, dendrites, and axons. Axons and dendrites are long processes extending from the cell body and enabling information transfer to and from other neurons. There is high variation in neuron morphology based on their location and function, thus increasing the complexity in mathematical modeling of neuron growth. In this paper, we propose a novel phase field model with isogeometric collocation to simulate different stages of neuron growth by considering the effect of tubulin. The stages modeled include lamellipodia formation, initial neurite outgrowth, axon differentiation, and dendrite formation considering the effect of intracellular transport of tubulin on neurite outgrowth. Through comparison with experimental observations, we can demonstrate qualitatively and quantitatively similar reproduction of neuron morphologies at different stages of growth and allow extension towards the formation of neurite networks.
我们提出了一个基于相场方法的神经元生长的新计算框架，并开发了一个名为"NeuronGrowth_IGAcollocation"的开源软件包。神经元由细胞体、树突和轴突组成。轴突和树突是从细胞体延伸出来的长突起，能够将信息传递到其他神经元和从其他神经元接收信息。基于其位置和功能的不同，神经元形态存在高度变化，从而增加了神经元生长的数学建模的复杂性。在本文中，我们提出了一种新的相场模型，通过使用等几何配置来模拟神经元生长的不同阶段，同时考虑微管蛋白的影响。所建模的阶段包括片状伪足的形成、初始神经突的生长、轴突的分化以及考虑微管蛋白的细胞内运输对神经突生长的影响的树突的形成。通过与实验观察进行比较，我们可以定性和定量地再现生长过程中不同阶段的神经元形态，并且允许向形成神经突网络的方向扩展。
