A physical view of computational neurodynamics | |
Ma, Jun1; Yang, Zhuo-qin2; Yang, Li-jian3; Tang, Jun4 | |
2019-09 | |
发表期刊 | JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE A |
ISSN | 1673-565X |
卷号 | 20期号:9页码:639-659 |
摘要 | The nervous system is made of a large number of neurons. Time-varying balance between excitatory and inhibitory neurons is important to activate appropriate modes of electrical activity. A realistic biological neuron is complex, often presenting various electrophysiological activities and diffusive propagation of ions in the cell. Therefore, the physical effects of electromagnetic induction become very important and should be considered when estimating signal encoding and mode selection. Synaptic plasticity and anatomical structure have been developed to enhance the self-adaption of neurons. Thus, the electrical mode with the most effective links and weights can be selected to benefit information encoding and signal propagation between neurons in the network. As a result, the demand for metabolic energy can be greatly reduced. In this review, neuron model setting with biophysical effects, modulation of astrocytes, autapse formation and biological function, synaptic plasticity, memristive synapses, and field coupling between neurons and networks are reviewed briefly to provide guidance in the field of neurodynamics. |
关键词 | Neuron Neural networks Autapse Hamilton energy Electromagnetic induction O59 TN710 |
DOI | 10.1631/jzus.A1900273 |
收录类别 | SCI ; SCIE |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[11765011] ; National Natural Science Foundation of China[11672122] |
WOS研究方向 | Engineering ; Physics |
WOS类目 | Engineering, Multidisciplinary ; Physics, Applied |
WOS记录号 | WOS:000485263700001 |
出版者 | ZHEJIANG UNIV |
EI入藏号 | 20193707427114 |
EI主题词 | Neural networks |
EI分类号 | 461.1 Biomedical Engineering - 461.9 Biology - 701.1 Electricity: Basic Concepts and Phenomena - 716.1 Information Theory and Signal Processing - 723.2 Data Processing and Image Processing - 723.4 Artificial Intelligence |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/31622 |
专题 | 理学院 |
通讯作者 | Ma, Jun |
作者单位 | 1.Lanzhou Univ Technol, Dept Phys, Lanzhou 730050, Gansu, Peoples R China; 2.Beihang Univ, Sch Math & Syst Sci, Beijing 100191, Peoples R China; 3.Cent China Normal Univ, Dept Phys, Wuhan 430079, Hubei, Peoples R China; 4.China Univ Min & Technol, Sch Phys, Xuzhou 221116, Jiangsu, Peoples R China |
第一作者单位 | 理学院 |
通讯作者单位 | 理学院 |
第一作者的第一单位 | 理学院 |
推荐引用方式 GB/T 7714 | Ma, Jun,Yang, Zhuo-qin,Yang, Li-jian,et al. A physical view of computational neurodynamics[J]. JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE A,2019,20(9):639-659. |
APA | Ma, Jun,Yang, Zhuo-qin,Yang, Li-jian,&Tang, Jun.(2019).A physical view of computational neurodynamics.JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE A,20(9),639-659. |
MLA | Ma, Jun,et al."A physical view of computational neurodynamics".JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE A 20.9(2019):639-659. |
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Ma-2019-A physical v(1016KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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