The use of anatomical constraints with MEG beamformers
The use of anatomical constraints with MEG beamformers
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DOI：
10.1016/j.neuroimage.2003.07.031
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发表时间：
2003-12-01
期刊：
影响因子：
5.7
通讯作者：
Barnes, GR
中科院分区：
文献类型：
--
作者：
Hillebrand, A;Barnes, GR
合成孔径磁强计（SAM）是一种用于从EEG/MEG数据定位神经元活动的波束形成器方法。SAM通过非线性搜索使波束形成器输出最大化的方向来估计预定义的源空间中的每个源的最佳方向。然而，脑磁图是最敏感的皮质来源，这些来源通常是垂直于表面取向。因此，重建的神经元活动可以合理地被约束到皮质表面，垂直于它取向，因此消除了对波束形成器权重的计算的最佳取向的搜索。本文阐述了一个约束和无约束波束形成器（SAM）的性能进行比较，相对于源重建和空间分辨率的定位精度。50个信号源被随机放置在从MRI估计的皮质表面上，我们模拟了每个信号源在不同信噪比（SNR）范围内的数据。使用无约束波束形成器（SAM）和约束波束形成器（源垂直于皮质表面）对这些数据集进行分析。表面位置和表面法线的估计误差对约束波束形成器的性能的影响，代表MEG/MRI配准和分割误差，也进行了检查。波束形成器的空间分辨率通常通过应用解剖学约束而提高四倍，并且定位精度略微提高。然而，空间分辨率的优势消失时，引入误差的方向和位置的约束，而且，不准确的约束波束形成器的定位精度迅速下降。我们的结论是，只有当MEG/MRI配准误差小于2 ram，皮质表面方向估计误差小于10度时，使用解剖约束才是有利的。(C)2003年爱思唯尔公司All rights reserved.
Synthetic Aperture Magnetometry (SAM) is a beamformer approach for the localisation of neuronal activity from EEG/MEG data. SAM estimates the optimum orientation of each source in a predefined source space by a nonlinear search for the orientation that maximises the beamformer output. However, MEG is most sensitive to cortical sources and these sources are generally oriented perpendicular to the surface. The reconstructed neuronal activity can therefore reasonably be constrained to the cortical surface, orientated perpendicular to it, therefore removing the search for the optimum orientation for the computation of the beamformer weights. This paper sets out to compare the performance of a constrained and unconstrained beamformer (SAM), with respect to the localisation accuracy of the source reconstructions and the spatial resolution. Fifty sources were randomly placed on a cortical surface estimated from an MRI, and we simulated data over a range of different signal-to-noise ratios (SNRs) for each source. These datasets were analysed using both an unconstrained beamformer (SAM) and a constrained beamformer (with the sources orientated perpendicular to the cortical surface). The influence of errors in the estimation of the surface location and surface normals on the performance of the constrained beamformer, representing MEG/MRI coregistration and segmentation errors, were also examined. The spatial resolution of the beamformer improves, typically by a factor of four by applying anatomical constraints, and the localisation accuracy improves marginally. However, the advantage in spatial resolution disappears when errors are introduced into the orientation and location constraints, and, moreover, the localisation accuracy of the inaccurately constrained beamformer degrades rapidly. We conclude that the use of anatomical constraints is only advantageous if the MEG/MRI coregistration error is smaller than 2 ram and the error in the estimation of the cortical surface orientation is smaller than 10degrees. (C) 2003 Elsevier Inc. All rights reserved.