A sensor-weighted overlapping-sphere head model and exhaustive head model comparison for MEG
A sensor-weighted overlapping-sphere head model and exhaustive head model comparison for MEG
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DOI：
10.1088/0031-9155/44/2/010
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发表时间：
1999-02-01
影响因子：
3.5
通讯作者：
Leahy, RM
中科院分区：
文献类型：
--
作者：
Huang, MX;Mosher, JC;Leahy, RM
脑磁图（MEG）中的球形头模型作为一种简单的前向模型，用于计算由神经活动引起的外部磁场。对于更真实的头部形状，使用边界元法（BEM）或类似的数值方法，但大大增加了计算成本。我们引入了一个传感器加权的球（OS）的头部模型，更逼真的头部形状的快速计算。与初级神经活动相关联的体积电流用于为每个单独的MEG传感器拟合球形头部模型，使得头部更真实地建模为一组重叠的球体，而不是单个球体。为了帮助评估这个OS模型与BEM和其他头部模型，我们还介绍了一种新的比较技术，该技术是基于广义特征值分解和帐户的存在下的噪声的MEG数据。通过这种技术，我们可以在真实的大脑体积中检查数千个偶极子位置的最坏可能的错误。我们测试了传统的单球模型，三壳和单壳边界元，以及新的OS模型。结果表明，OS模型具有类似于边界元的精度，但计算速度要快几个数量级。
The spherical head model has been used in magnetoencephalography (MEG) as a simple forward model for calculating the external magnetic fields resulting from neural activity. For more realistic head shapes, the boundary element method (BEM) or similar numerical methods are used, but at greatly increased computational cost. We introduce a sensor-weighted overlapping-sphere (OS) head model for rapid calculation of more realistic head shapes. The volume currents associated with primary neural activity are used to fit spherical head models for each individual MEG sensor such that the head is more realistically modelled as a set of overlapping spheres, rather than a single sphere. To assist in the evaluation of this OS model with BEM and other head models, we also introduce a novel comparison technique that is based on a generalized eigenvalue decomposition and accounts for the presence of noise in the MEG data. With this technique we can examine the worst possible errors for thousands of dipole locations in a realistic brain volume. We test the traditional single-sphere model, three-shell and single-shell BEM, and the new OS model. The results show that the OS model has accuracy similar to the BEM but is orders of magnitude faster to compute.