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相关概念视频

Neuronal Communication01:28

Neuronal Communication

1.0K
Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
1.0K
Neuron Structure01:30

Neuron Structure

13.1K
Neurons are the main type of cell in the nervous system that generate and transmit electrochemical signals. They primarily communicate with each other using neurotransmitters at specific junctions called synapses. Neurons come in many shapes that often relate to their function, but most share three main structures: an axon and dendrites that extend out from a cell body.
Structure and Function of Neurons
The neuronal cell body—the soma— houses the nucleus and organelles vital to...
13.1K
The Neuromuscular Junction01:19

The Neuromuscular Junction

9.9K
The nervous system consists of complex motor neuron circuits, including upper motor neurons originating from the cerebral cortex and lower motor neurons starting in the spinal cord, coordinating both voluntary and involuntary movements. Among these, somatic motor neurons activate skeletal muscles and are classified into alpha, beta, and gamma types. Alpha neurons are vital for voluntary movement coordination, while gamma neurons adjust muscle spindle sensitivity, and the function of beta...
9.9K

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NEURONpyxl: fast, flexible, Python-integrated simulation of biophysical neural networks with complex plastic synapses.

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Capillary Density and Neuronal Homeostasis in Human Primary Visual Cortex.

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All Models are Wrong, Some are Annotated: Automating Metadata in Biomedical Repositories.

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Learning under constraints: a theoretical framework for comparing resource-constrained learning in biological and artificial systems.

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Modeling multiscale neural dynamics for EEG-based emotion recognition using an attentive wavelet-transformer framework.

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相关实验视频

Updated: Jul 19, 2025

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
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Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K

教程:使用NEURON进行神经机械模拟.

Chris Fietkiewicz1, Robert A McDougal2,3,4,5, 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
PubMed
概括
此摘要是机器生成的。

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.

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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Designing and Implementing Nervous System Simulations on LEGO Robots
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Designing and Implementing Nervous System Simulations on LEGO Robots

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Physiological, Morphological and Neurochemical Characterization of Neurons Modulated by Movement
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Physiological, Morphological and Neurochemical Characterization of Neurons Modulated by Movement

Published on: April 21, 2011

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相关实验视频

Last Updated: Jul 19, 2025

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

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Designing and Implementing Nervous System Simulations on LEGO Robots
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Designing and Implementing Nervous System Simulations on LEGO Robots

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Physiological, Morphological and Neurochemical Characterization of Neurons Modulated by Movement
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Physiological, Morphological and Neurochemical Characterization of Neurons Modulated by Movement

Published on: April 21, 2011

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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.