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教程:使用NEURON进行神经机械模拟

Chris Fietkiewicz¹, Robert A McDougal^2,3,4,5, David Corrales Marco¹

¹Department of Mathematics and Computer Science, Hobart and William Smith Colleges, Geneva, NY, United States.

Frontiers in computational neuroscience

|August 16, 2023

概括

本教程展示了使用NEURON平台集成大脑和身体模拟的方法. 它介绍了一个神经机械建模的框架,通过结合的神经和生物机械动力学来实现复杂的适应性行为.

科学领域:

计算神经科学是一种计算神经科学.
生物物理学的生物物理.
系统生物学系统生物学

背景情况:

大脑和身体的动态是密切相关的,驱动复杂的适应性行为.
现有的模拟工具往往单独关注神经或生物机械动力学,缺乏综合方法.
弥合这个差距对于理解大脑与身体的相互作用至关重要.

研究的目的:

为提供关于使用NEURON模拟平台进行综合神经机械建模的教程.
在NEURON中提出一个用于合神经 (大脑) 和生物机械 (身体) 系统的框架.
用NEURON的指针结构来展示代码模块化和集成能力.

主要方法:

利用NEURON的指针结构,以促进大脑和身体模块之间的信息共享.
开发了一种双向通信的框架:大脑通过感官反影响身体动态,身体通过感官反影响大脑动态.
实施了五种越来越复杂的计算模型来证明概念.

主要成果:

在NEURON中成功展示了神经和生物机械模型的集成.
展示了NEURON指针结构对于模块化代码设计和复杂模拟中重复使用的实用性.
介绍了各种模型,包括神经肌肉,振荡器,呼吸控制,非平滑系统和Aplysia养行为.

结论:

NEURON模拟平台有效地支持综合神经机械建模.
本文所介绍的框架和指针构造使大脑与身体模拟的模块化和可重复使用的代码成为可能.
这种方法有助于开发各种复杂的,生物启发的神经机械模型.

关键词:

生物力学生物力学身体身体身体身体身体身体身体身体大脑大脑大脑的大脑大脑封闭循环的封闭循环.发动机控制器的控制器神经网络的神经网络的神经网络

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