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用于波束形成器分析的源定位尺度校正。

Source localization scale correction for Beamformer analysis.

作者信息

Shapira Lots Inbal, Zeev-Wolf Maor, Harpaz Yuval, Abeles Moshe

机构信息

Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel.

Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel; The Hebrew University of Jerusalem, Jerusalem, Israel.

出版信息

J Neurosci Methods. 2016 Nov 1;273:10-19. doi: 10.1016/j.jneumeth.2016.07.013. Epub 2016 Jul 22.

Abstract

BACKGROUND

Magnetoencephalography measurements are often processed by using imaging algorithms such as beamforming. The estimated source magnitude tends to suffer from unbalanced scaling across different brain locations. Hence, when examining current estimates for source activity it is vital to rescale the estimated source magnitude, in order to obtain a uniformly scaled image.

NEW METHOD

We present a generalized scale correction method (N) that uses empty room MEG measurements to evaluate the noise level.

RESULTS

The location bias and spatial resolution of the estimated signal indicated that some scaling correction needs to be applied. Of all the scale correction methods that were tested, the best correction was achieved when using N.

COMPARISON WITH EXISTING METHODS

We show that a diagonal matrix does not reflect the true nature of the noise covariance matrix. Hence, diagonal matrix based methods are sub-optimal.

CONCLUSION

We recommend adding empty room MEG measurements to each experimental recording session, for purposes of both scale correction and beamformer performance verification.

摘要

背景

脑磁图测量通常通过使用诸如波束形成等成像算法进行处理。估计的源强度往往在不同脑区存在缩放不平衡的问题。因此,在检查当前的源活动估计时,为了获得均匀缩放的图像,重新缩放估计的源强度至关重要。

新方法

我们提出了一种广义缩放校正方法(N),该方法使用空房间脑磁图测量来评估噪声水平。

结果

估计信号的位置偏差和空间分辨率表明需要进行一些缩放校正。在所有测试的缩放校正方法中,使用N时校正效果最佳。

与现有方法的比较

我们表明对角矩阵不能反映噪声协方差矩阵的真实性质。因此,基于对角矩阵的方法是次优的。

结论

我们建议在每个实验记录环节中加入空房间脑磁图测量,用于缩放校正和波束形成器性能验证。

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