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神经元生长的数学模型。

Mathematical models of neuronal growth.

机构信息

Mathematical Institute, University of Oxford, Oxford, OX2 6GG, UK.

出版信息

Biomech Model Mechanobiol. 2022 Feb;21(1):89-118. doi: 10.1007/s10237-021-01539-0. Epub 2022 Jan 7.

Abstract

The establishment of a functioning neuronal network is a crucial step in neural development. During this process, neurons extend neurites-axons and dendrites-to meet other neurons and interconnect. Therefore, these neurites need to migrate, grow, branch and find the correct path to their target by processing sensory cues from their environment. These processes rely on many coupled biophysical effects including elasticity, viscosity, growth, active forces, chemical signaling, adhesion and cellular transport. Mathematical models offer a direct way to test hypotheses and understand the underlying mechanisms responsible for neuron development. Here, we critically review the main models of neurite growth and morphogenesis from a mathematical viewpoint. We present different models for growth, guidance and morphogenesis, with a particular emphasis on mechanics and mechanisms, and on simple mathematical models that can be partially treated analytically.

摘要

建立一个功能正常的神经网络是神经发育的关键步骤。在这个过程中,神经元会延伸出轴突和树突,以与其他神经元接触并相互连接。因此,这些轴突需要迁移、生长、分支,并通过处理来自环境的感觉线索找到到达目标的正确路径。这些过程依赖于许多耦合的生物物理效应,包括弹性、粘性、生长、主动力、化学信号、黏附和细胞运输。数学模型提供了一种直接检验假设和理解负责神经元发育的潜在机制的方法。在这里,我们从数学的角度批判性地回顾了轴突生长和形态发生的主要模型。我们介绍了不同的生长、导向和形态发生模型,特别强调力学和机制,以及可以部分进行分析处理的简单数学模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9025/8807500/8727797bd2ab/10237_2021_1539_Fig1_HTML.jpg

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