Electromagnetic brain mapping
Electromagnetic brain mapping
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DOI：
10.1109/79.962275
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发表时间：
2001-11-01
影响因子：
14.9
通讯作者：
Leahy, RM
中科院分区：
文献类型：
--
作者：
Baillet, S;Mosher, JC;Leahy, RM
我们制作人脑功能图像的能力已经有了巨大的进步。功能性脑成像的应用从提高我们对认知过程的基本机制的理解扩展到更好地表征损害正常功能的病理。脑磁图（MEG）和脑电图（EEG）（MEG/EEG）使用外部电磁信号的非侵入性测量来定位神经电活动。在现有的功能成像技术中，MEG和EEG具有独特的时间分辨率低于100 ms。这种时间精度使我们能够在细胞组装水平上探索基本神经过程的时间。MEG/EEG源定位利用了广泛的信号处理技术，包括数字滤波、三维图像分析、阵列信号处理、图像建模和重建以及盲源分离和相位同步估计。我们描述了目前在MEG/EEG源估计中使用的基本模型，并描述了计算这些源所需的各种信号处理步骤。特别是，我们描述了用于计算已知源分布和参数和基于成像的方法来反问题的正向场的方法。
There has been tremendous advances in our ability to produce images of human brain function. Applications of functional brain imaging extend from improving our understanding of the basic mechanisms of cognitive processes to better characterization of pathologies that impair normal function. Magnetoencephalography (MEG) and electroencephalography (EEG) (MEG/EEG) localize neural electrical activity using noninvasive measurements of external electromagnetic signals. Among the available functional imaging techniques, MEG and EEG uniquely have temporal resolutions below 100 ms. This temporal precision allows us to explore the timing of basic neural processes at the level of cell assemblies. MEG/EEG source localization draws on a wide range of signal processing techniques including digital filtering, three-dimensional image analysis, array signal processing, image modeling and reconstruction, and, blind source separation and phase synchrony estimation. We describe the underlying models currently used in MEG/EEG source estimation and describe the various signal processing steps required to compute these sources. In particular we describe methods for computing the forward fields for known source distributions and parametric and imaging-based approaches to the inverse problem.