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韩芳, 王青云. 神经动力学研究进展和若干思考. 力学学报, 2023, 55(4): 805-813. DOI: 10.6052/0459-1879-22-404
引用本文: 韩芳, 王青云. 神经动力学研究进展和若干思考. 力学学报, 2023, 55(4): 805-813. DOI: 10.6052/0459-1879-22-404
Han Fang, Wang Qingyun. Research advances and some thoughts on neurodynamics. Chinese Journal of Theoretical and Applied Mechanics, 2023, 55(4): 805-813. DOI: 10.6052/0459-1879-22-404
Citation: Han Fang, Wang Qingyun. Research advances and some thoughts on neurodynamics. Chinese Journal of Theoretical and Applied Mechanics, 2023, 55(4): 805-813. DOI: 10.6052/0459-1879-22-404

神经动力学研究进展和若干思考

RESEARCH ADVANCES AND SOME THOUGHTS ON NEURODYNAMICS

  • 摘要: 神经动力学是动力学与控制学科的基础性分支, 属于力学与脑科学、智能科学的国际前沿交叉学科领域, 主要是通过动力学与控制的基本理论和方法, 建立合理的模型来探究神经系统电生理动力学行为和脑认知功能的机理. 近年来, 国内外学者在神经动力学的基础研究方面取得了显著成果, 包括神经元和神经元网络动力学行为的深入研究、大脑不同功能结构的建模分析以及神经疾病关联脑区的网络动力学建模与控制等. 本文首先对国内外神经动力学研究领域取得的进展做了较全面的概括分析, 特别是给出了建模方面的发展历程. 进而, 基于解析生物神经网络及其动力学的研究成果, 对神经动力学未来的研究方向提出了一些思考展望, 期望神经动力学的研究将助力具备较强可解释性和泛化能力的类脑智能原理和方法的突破及在重大工程中的应用.

     

    Abstract: Neurodynamics is a foundational branch of dynamics and control, which belongs to the international frontier of the interdisciplinary field of mechanics, brain science and intelligence science. Based on the basic theories and methods of dynamics and control, the study of neurodynamics mainly focuses on establishing reasonable models to explore the mechanisms of electrophysiological dynamic behaviors of nervous system and brain cognitive functions. In recent years, scholars at home and abroad have obtained remarkable achievements in the foundational research of neurodynamics, including the in-depth study of the dynamical behavior of neurons and neural networks, the modeling and analysis of different functional structures of the brain, and the network dynamics modeling and control of brain regions associated with nervous disease. In this paper, we firstly overviewed elaborately the recent advancements in the field of neurodynamics. Especially, development history for advancement of neural modeling is exhibited. Then, by analyzing the research outcomes of biological neural networks and their dynamics, some thoughts and prospects for future research are put forward. It is expected that neurodynamics will contribute to the breakthroughs of the theories and methods of brain-like intelligence and intelligent equipment with strong interpretability and generalization ability, and finally their applications in major engineering projects.

     

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