NEURAL MASS MODEL DRIVEN NONLINEAR EEG ANALYSIS

摘要：

　　Although EEG signals are highly complex,there are still some neural mass models that describe its systematic dynamics.In this paper,we presented an empirical exploration to the theoretical prediction of such a model by fitting the actual EEG signal to the model,with a particular concern on the influence of the extrinsic input p(t) to EEG signal.The results suggest that the neural mass model can produce good approximation to the actual EEG signal,and the mean of estimated input signal fell well within the interval for the simulate study recommended by previous reports.However,it is also found that the variance of the input signal commonly accepted for simulating EEG rhythmic activity is far higher than the value in real data,thus may lead to the generation of unreliable synthetic data,and bias the analysis result.

关键词： Electroencephalogram (EEG) Neural Mass Model Nonlinear Estimation

作者: Yan Zhang Zhenghui Hu

作者单位: College of Optical and Electronic Technology China Jiliang University Hangzhou 310018,China Department of Optical Engineering Zhejiang University Hangzhou 310027,China

会议类型: 国内会议

会议名称: 长江2011国际医学影像物理和工程应用大会暨第六届中国医学影像物理学术年会

会议地点: 杭州

会议语种:英文

页码: 60-63

在线出版日期: 2011-10-22（万方平台首次上网日期，不代表论文的发表时间）