神经网络中自组织临界态的理论研究

项目名称： 神经网络中自组织临界态的理论研究

项目编号： No.11305098

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 数理科学和化学

项目作者： 王圣军

作者单位： 陕西师范大学

项目金额： 22万元

中文摘要： 实验发现自组织临界态(SOC)广泛地存在于大脑神经网络中，它在神经的一些发育过程中不可或缺，并且在信息处理方面具有功能优势。所以神经网络临界态的产生机制和规律是十分重要的问题。但是多种真实的生物因素导致直接采用SOC的传统模型不能阐明新情形下临界态的涌现机制。本项目拟在我们前期工作的基础上通过系统地模拟和理论分析，深入研究等级模块化网络结构和抑制性神经元在SOC形成机制和活动规律中的作用，阐明能够重现实验结果的理论模型所必须具备的结构属性和动力学特性，揭示神经网络临界态具有鲁棒性的动力学机制以及网络结构对鲁棒性的影响，确定具有神经系统的结构属性和动力学属性的理论模型中的临界条件和临界行为与这些属性的依赖关系，阐明临界雪崩与同步转变点之间的异同，以及针对有限尺寸系统改进KS统计方法。本项目的研究将为理解大脑临界性提供一定的理论支持，为未来的研究提供更坚实的理论基础和更合理的模型。

中文关键词： 自组织临界态；神经网络；负关联网络；；

英文摘要： Experiments have shown that self-organized criticality (SOC) is ubiquitous in brain cortex networks. SOC is an essential active pattern for the developing of cortex networks, and has functional advantage in information processing. So the emerging mechanism and the characteristic of the critical state are important questions. The fundamental principle for SOC in physical systems has been interpreted by detailed numerical simulations and theoretical treatments. However, the biological realistic factors induce that the physical model cannot explain the emergence of SOC in neuronal networks and predict the critical behavior. In this project, based on our previous research, we aim to study the role of the dynamical property of inhibitory neurons dynamical property and the topological property of hierarchical modular structure in the emergence of SOC and the critical behavior. Through detailed simulation and theoretical analysis, we will study the fundamental structure features and the dynamical properties for the neuronal models to generate the behavior that is identical with the measurement in experiments; we will study the propagation of perturbation, and the adaptation mechanics of both its amplification and dissipation of the perturbation, in order to interpret the underlying mechanics of the robustness of SOC in

英文关键词： self-organized criticality；neural networks；disassortative networks；；