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神经系统信息处理和异常功能的复杂动力学

古华光

古华光. 神经系统信息处理和异常功能的复杂动力学[J]. 力学学报, 2017, 49(2): 410-420. doi: 10.6052/0459-1879-16-315
引用本文: 古华光. 神经系统信息处理和异常功能的复杂动力学[J]. 力学学报, 2017, 49(2): 410-420. doi: 10.6052/0459-1879-16-315
Gu Huaguang. COMPLEX DYNAMICS OF THE NERVOUS SYSTEM FOR INFORMATION PROCESSING AND ABNORMAL FUNCTIONS[J]. Chinese Journal of Theoretical and Applied Mechanics, 2017, 49(2): 410-420. doi: 10.6052/0459-1879-16-315
Citation: Gu Huaguang. COMPLEX DYNAMICS OF THE NERVOUS SYSTEM FOR INFORMATION PROCESSING AND ABNORMAL FUNCTIONS[J]. Chinese Journal of Theoretical and Applied Mechanics, 2017, 49(2): 410-420. doi: 10.6052/0459-1879-16-315

神经系统信息处理和异常功能的复杂动力学

doi: 10.6052/0459-1879-16-315
基金项目: 

国家自然科学基金资助项目 11572225

国家自然科学基金资助项目 11372224

国家自然科学基金资助项目 11072135

国家自然科学基金资助项目 10772101

国家自然科学基金资助项目 30300107

详细信息
    通讯作者:

    2) 古华光, 教授, 主要研究方向:神经动力学、非线性动力学.E-mail:guhuaguang@tongji.edu.cn

  • 中图分类号: O322;Q424

COMPLEX DYNAMICS OF THE NERVOUS SYSTEM FOR INFORMATION PROCESSING AND ABNORMAL FUNCTIONS

  • 摘要: 神经系统通过电活动实现信息处理及生物功能,电活动的节律和时空行为是功能的动力学表征.神经电生理实验结合理论模型,借助于分岔揭示了外界激励、参数和噪声调控下的周期、混沌和随机等多样性的节律模式及其节律的复杂转迁规律,揭示了感觉神经对信息(如血压压力信号和痛觉信息)的节律编码机制,揭示了突触噪声扩大脑神经元的信息传递能力并对能力强弱进行了分类,结果可用于提高信息检测能力和指导镇痛;借助于单神经元节律的动力学——如分岔和簇放电节律的快慢动力学——解释了网络功能异常的时空行为,如药物调控脑皮层的螺旋波/癫痫和慢抑制耦合调控的运动网络的同步转迁/运动模式异常,结果给出了调控系统功能的途径;通过大数据分析获得自闭症患者的脑功能网络的时空行为特征——症状相关脑区的同步活动降低,给出了用于诊断的潜在指标.通过新实验发现、新建理论模型、新分析方法和新观点阐释,揭示了神经系统的复杂动力学,认识和解释了神经系统的信息处理机制和异常生物功能/疾病,具有重要科学意义和潜在应用价值.

     

  • 图  1  HH模型

    Figure  1.  HH model

    图  2  家兔减压神经在不同平均压力水平下的放电

    Figure  2.  Firing patterns at different mean levels of pressure blood of rabbit baroreceptor

    图  3  痛觉实验模型的放电节律模式

    Figure  3.  Firing rhythm patterns of the experimental model for pain

    图  4  放电节律的转迁规律

    Figure  4.  Changing regularities of the firing rhythm patterns

    图  5  Ca2+浓度降低引起的痛觉实验模型放电ISI和平均频率的变化

    Figure  5.  Changes of ISI and mean frequency of firings of the experimental model for pain with decreasing Ca2+ concentration

    图  6  脑神经元的随机放电节律

    Figure  6.  Stochastic firing patterns of the brain neurons

    图  7  On-off节律 (上) 和对应不变圆鞍结分岔的随机节律 (下) 的特征

    Figure  7.  Characteristics of on-off firing (upper) and firing corresponding to saddle-node bifurcation on an invariant cycle (lower)

    图  8  网络内Ⅰ型兴奋神经元数量比例增加诱发螺旋波

    Figure  8.  The spiral waves induced by increasing probability of neurons with type Ⅰ excitability

    图  9  具有时滞抑制耦合神经元的同步

    Figure  9.  Synchronization of the inhibitory coupled neurons with time delay

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出版历程
  • 收稿日期:  2016-11-07
  • 网络出版日期:  2017-01-03
  • 刊出日期:  2017-03-18

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