EEC Source Localization Based on Multiple fMRI Spatial Patterns

摘要：

EEG source localization is an ill-posed problem, and constraints are required to ensure the uniqueness of the solution. In this paper, using independent component analysis (ICA), multiple fMRI spatial patterns are employed as the covariance priors of the EEG source distribution. With the empirical Bayes (EB) framework, spatial patterns are automatically selected and EEG sources are estimated with Restricted Maximum Likelihood (ReML). The computer simulation suggests that, in contrast to the previous methods of EB in EEG source imaging, our approach is distinctly valuable in improvement of distributed source localization.

关键词： EEG fMRI Network EEG source imaging Restricted maximum likelihood Source reconstruction Distributed solution

作者: Xu Lei Dezhong Yao

作者单位: Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China

会议类型: 国际会议

会议名称: The Second International Conference on Cognitive Neurodynamics--2009(第二届国际认知神经动力学会议)

会议地点: 杭州

会议语种:英文

页码: 381-386

在线出版日期: 2009-11-15（万方平台首次上网日期，不代表论文的发表时间）