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微调用于脑磁图的时空信号空间分离的相关极限

Fine tuning the correlation limit of spatio-temporal signal space separation for magnetoencephalography.

作者信息

Medvedovsky Mordekhay, Taulu Samu, Bikmullina Rozaliya, Ahonen Antti, Paetau Ritva

机构信息

BioMag Laboratory, HUSLAB, The Hospital District of Helsinki and Uusimaa, P.O. Box 340, FIN-00029 Helsinki, Finland.

出版信息

J Neurosci Methods. 2009 Feb 15;177(1):203-11. doi: 10.1016/j.jneumeth.2008.09.035. Epub 2008 Oct 18.

Abstract

Head, jaw and tongue movements contribute to speech artifacts in magnetoencephalography (MEG). Their sources lay close to MEG sensors, therefore, the spatio-temporal signal space separation method (tSSS), specifically suppressing nearby artifacts, can be used for speech artifact suppression. After data reconstruction by signal space separation (referred as SSS), tSSS identifies artifacts by their correlated temporal behavior inside and outside the sensor helmet. The artifacts to be eliminated are thresholded by the quantitative level of this correlation determined by correlation limit (CL). Unnecessarily high CL value may result in suboptimal interference suppression. We evaluated the performance of tSSS with different CLs on MEG data containing speech artifacts. MEG was recorded with 204 planar gradiometers and 102 magnetometers in two subjects counting aloud. The recorded data were processed by tSSS using CLs 0.98, 0.8 and 0.6, and traces were compared. The speech artifact was increasingly suppressed with decreasing CL, but sufficient suppression was achieved at different CL in each subject. Alpha rhythm was not suppressed with CL 0.98 or 0.8; some amplitude reduction with CL 0.6 occurred in one subject. The tSSS is a robust tool suppressing MEG artifacts. It can be fine tuned for challenging artifacts which, after insufficient rejection might resemble brain signals.

摘要

头部、下颌和舌头的运动是脑磁图(MEG)中言语伪迹的成因。这些伪迹源靠近MEG传感器,因此,专门用于抑制附近伪迹的时空信号空间分离方法(tSSS)可用于抑制言语伪迹。通过信号空间分离(称为SSS)进行数据重建后,tSSS通过传感器头盔内外伪迹的相关时间行为来识别伪迹。待消除的伪迹通过由相关极限(CL)确定的这种相关性的定量水平进行阈值处理。过高的CL值可能导致干扰抑制效果欠佳。我们评估了不同CL值的tSSS对包含言语伪迹的MEG数据的处理性能。在两名大声计数的受试者中,使用204个平面梯度仪和102个磁力计记录MEG。记录的数据通过tSSS使用CL值0.98、0.8和0.6进行处理,并对轨迹进行比较。随着CL值降低,言语伪迹得到越来越强的抑制,但每个受试者在不同的CL值下都实现了充分抑制。CL值为0.98或0.8时,α节律未被抑制;一名受试者在CL值为0.6时出现了一些幅度降低。tSSS是一种抑制MEG伪迹的强大工具。对于具有挑战性的伪迹,即抑制不足时可能类似于脑信号的伪迹,它可以进行微调。

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