基于神经元连接模式的脑网络减边演化博弈算法  

The Algorithm of Cutting Edge Evolution and Evolution Game of Brain Network Based on the Connection Mode between Neurons

作　　者：逯鹏[1,2] 刘素杰 张利亚 牛新[1] 

机构地区：[1]郑州大学电气工程学院郑州450001 [2]互联网医疗与健康服务河南省协同创新中心,郑州450001

出　　处：《科学技术与工程》2018年第5期86-91,共6页Science Technology and Engineering

基　　金：国家自然基金(60841004,60971110,61172152,61473265); 河南省科技攻关项目(172102310393); 河南省高校科技创新团队支持计划(17IRTSTHN013); 河南省高校重点支持项目基金资助

摘　　要：神经元间的连接以先增大后减小的方式演化,提示了大脑神经元网络在演化过程中存在"剪除"过程。以"剪除"为启发,首先使用数学方法对大脑网络进行建模;然后基于大脑网络中的神经元连接方式,设计了网络减边演化算法。最后,考虑布线消耗和信息传输之间的效率,建立了大神经元优先与距离优先的演化博弈模型,探索该模型对脑网络拓扑结构特性的影响。实验结果显示,在此演化过程中,呈现了中心节点度约为200、小世界特性S>1和高效率代价比等性质,表明该算法能够有效模拟仿神经元剪除机制。上述算法和模型为有效模拟高效低能耗的脑网络提供了一种新途径。The connections between neurons develops according to a model of increasing at first and then decreasing,which suggests that there is a pruning process during the evolution of neural networks. Inspired by the pruning process,the numerical simulation be first carried out to the network,and then established the network cutting edge and evolutionary algorithm based on the neurons connections pattern in the brain network. Finally,based on the tradeoff between the cost of routing and the efficiency of information transmission,the evolutionary game model of large neurons priority and distance priority was established,which in order to explore the influence of the model on network topology. The experimental results show that,during the process of evolution,some properties appear such as central node degree is about 200,the small world characteristic S 1 and the high efficiency cost ratio,which indicate that this algorithm can simulate the neurons pruning mechanism effectively. The algorithm and model provides a new approach for simulating high efficiency and low energy brain network effectively.

关 键 词：脑网络 神经连接 减边机制 演化博弈 

分 类 号：R338[医药卫生—人体生理学] TP301.6[医药卫生—基础医学]