Mosher J C, Spencer M E, Leahy R M, Lewis P S
Signal and Image Processing Institute, University of Southern California, Los Angeles 90089-2564.
Electroencephalogr Clin Neurophysiol. 1993 May;86(5):303-21. doi: 10.1016/0013-4694(93)90043-u.
General formulas are presented for computing a lower bound on localization and moment error for electroencephalographic (EEG) or magnetoencephalographic (MEG) current source dipole models with arbitrary sensor array geometry. Specific EEG and MEG formulas are presented for multiple dipoles in a head model with 4 spherical shells. Localization error bounds are presented for both EEG and MEG for several different sensor configurations. Graphical error contours are presented for 127 sensors covering the upper hemisphere, for both 37 sensors and 127 sensors covering a smaller region, and for the standard 10-20 EEG sensor arrangement. Both 1- and 2-dipole cases were examined for all possible dipole orientations and locations within a head quadrant. The results show a strong dependence on absolute dipole location and orientation. The results also show that fusion of the EEG and MEG measurements into a combined model reduces the lower bound. A Monte Carlo simulation was performed to check the tightness of the bounds for a selected case. The simple head model, the low power noise and the few strong dipoles were all selected in this study as optimistic conditions to establish possibly fundamental resolution limits for any localization effort. Results, under these favorable assumptions, show comparable resolutions between the EEG and the MEG models, but accuracy for a single dipole, in either case, appears limited to several millimeters for a single time slice. The lower bounds increase markedly with just 2 dipoles. Observations are given to support the need for full spatiotemporal modeling to improve these lower bounds. All of the simulation results presented can easily be scaled to other instances of noise power and dipole intensity.
本文给出了通用公式,用于计算具有任意传感器阵列几何结构的脑电图(EEG)或脑磁图(MEG)电流源偶极子模型的定位和矩误差下限。针对具有4个球壳的头部模型中的多个偶极子,给出了特定的EEG和MEG公式。针对几种不同的传感器配置,给出了EEG和MEG的定位误差界限。给出了覆盖上半球的127个传感器、覆盖较小区域的37个传感器和127个传感器以及标准10 - 20 EEG传感器布局的图形误差等高线。研究了头部象限内所有可能的偶极子方向和位置的单偶极子和双偶极子情况。结果表明,定位和矩误差下限强烈依赖于绝对偶极子位置和方向。结果还表明,将EEG和MEG测量融合到一个组合模型中可降低下限。进行了蒙特卡罗模拟,以检查所选情况下界限的紧密程度。本研究选择简单头部模型、低功率噪声和少数强偶极子作为乐观条件,以确定任何定位工作可能的基本分辨率极限。在这些有利假设下的结果表明,EEG和MEG模型之间的分辨率相当,但在任何一种情况下,单个偶极子的精度在单个时间片内似乎限于几毫米。当有2个偶极子时,下限显著增加。给出了一些观察结果,以支持进行全时空建模以改善这些下限的必要性。所呈现的所有模拟结果都可以很容易地按比例缩放至其他噪声功率和偶极子强度的情况。