小鼠视觉感受区电位信号(LFP)与视觉刺激之间的关系研究  

The Study of the Relationship Between Local Field Potential(Lfp) and Visual Stimulation in Mice

作　　者：张良[1] 牛姝媛[2] 侯超[1] 田欣[1] 

机构地区：[1]中国银联股份有限公司技术开发中心,上海201210 [2]华东师范大学生命科学学院,上海200241

出　　处：《数学的实践与认识》2015年第14期108-118,共11页Mathematics in Practice and Theory

摘　　要：脑是支配人和高级动物活动的司令部和信息中心,脑电波是脑科学基础理论研究的重要指标,也是人类思维活动的体现.大量研究都表明脑电波信号与认知等功能活动有关.而脑电波信号是无数神经放电的混合,不同行为产生的电信号的强弱差别也很大,所以通常的盲源分离技术误差较大,很难将脑电波较好的分离出来并与动作相对应.通过建立数学模型,分析了脑电波与行为之间的联系.首先预测并验证了呼吸动作与脑电波之间关系模型,使用DFA模型经过最小二乘法拟合进一步确认了LFP变化的周期性.然后通过计算脑电波曲线的自相关与互相关,得到了脑电波的周期性以及呼吸相关脑电波成分周期性的相关关系.之后建立了独立成分分析(ICA)的模型使用InfoMax的方法对脑电波进行了成分分离,并通过对照实验比较、优化了分离结果.寻求最优的脑电波的分离模型.并在此基础上研究了小鼠的视觉感受区电位信号与视觉刺激间的关联.As we all know,brain is the command and information center of the animal activities.Electroencephalogram（EEG） is an important indicator of the scientific basic theory of brain,and it is also the embodiment of people＇s thinking activity.A lot of studies have indicated that electroencephalogram is related to cognitive and other functional activities.The EEG signal is generated from numerous nerve discharge.The intensity varies so much that common blind source separation technology can not deal with it.Here we established a mathematical model to analyze the relationship between EEG and behavior.First we predicted and validated the breath-EEG model,then we get the correlation of EEG cycle and breath cycle by calculating the autocorrelation and cross-correlation.After this,we use InfoMax method of Independent components analysis（ICA） model to decompose the EEG and improved the method using control experiments results,and try to find the best model of EEG separation.The correlation between visual sensory area potential and visual stimulation was also studied.

关 键 词：脑电波 相关性分析 DFA 独立成分分析 

分 类 号：TN911.7[电子电信—通信与信息系统]