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在球面和椭球面上使用样条生成表面拉普拉斯算子的高分辨率脑电图。

High-resolution EEG using spline generated surface Laplacians on spherical and ellipsoidal surfaces.

作者信息

Law S K, Nunez P L, Wijesinghe R S

机构信息

Section of Brain Electrophysiology and Imaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892.

出版信息

IEEE Trans Biomed Eng. 1993 Feb;40(2):145-53. doi: 10.1109/10.212068.

Abstract

Spline generated surface Laplacians are introduced as an effective method for estimating neocortical source activity at moderate scales. The method appears to be robust to the unavoidable perturbations of measured potentials and errors of head geometry and resistivity that are certain to occur in clinical or research settings. In particular, we have derived the surface Laplacian for general ellipsoidal surfaces in terms of the spline function. The spline-Laplacian accurately estimates isolated dipoles or distributed sources, is insensitive to subcortical sources and to sources which originate outside the boundaries of the electrode array, and acts as a bandpass spatial filter whose characteristics appear to provide a good match to the volume conduction of intracranial sources through human heads. As a result, spatial resolution is improved over that obtained with conventional EEG by at least a factor of three. This improvement, whether obtained with spline-Laplacian or model-dependent methods, is likely to have a significant impact on both medical and cognitive studies involving EEG.

摘要

样条生成表面拉普拉斯算子被引入作为一种在中等尺度上估计新皮质源活动的有效方法。该方法对于临床或研究环境中必然会出现的测量电位的不可避免扰动以及头部几何形状和电阻率误差似乎具有鲁棒性。特别是,我们根据样条函数推导了一般椭球表面的表面拉普拉斯算子。样条拉普拉斯算子能准确估计孤立偶极子或分布式源,对皮质下源和起源于电极阵列边界之外的源不敏感,并且起到带通空间滤波器的作用,其特性似乎与颅内源通过人头的体积传导良好匹配。结果,与传统脑电图相比,空间分辨率提高了至少三倍。这种改进,无论是通过样条拉普拉斯算子还是基于模型的方法获得,都可能对涉及脑电图的医学和认知研究产生重大影响。

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