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从 TMS 诱发的 EEG 中预测肌肉伪迹。

Projecting out muscle artifacts from TMS-evoked EEG.

机构信息

Department of Biomedical Engineering and Computational Science (BECS), Aalto University, Aalto, Espoo, Finland.

出版信息

Neuroimage. 2011 Feb 14;54(4):2706-10. doi: 10.1016/j.neuroimage.2010.11.041. Epub 2010 Nov 18.

Abstract

Transcranial magnetic stimulation combined with electroencephalography is a powerful tool for probing cortical excitability and connectivity; we can perturb one brain area and study the reactions at the stimulated and interconnected sites. When stimulating areas near cranial muscles, their activation produces a large artifact in the electroencephalographic signal, lasting tens of milliseconds and masking the early brain signals. We present an artifact removal method based on projecting out the topographic patterns of the muscle activity. Although the brain and muscle components overlap both temporally and spectrally, the fact that muscle activity is present also at frequencies higher than 100 Hz, while brain signal is mostly restricted to frequencies lower than that, allows us to study the high-frequency muscle activity without brain contribution. We determined the muscle activity topographies from data highpass-filtered at a 100-Hz cutoff frequency using principal component analysis. Projecting out the topographies of the principal components which explain most of the variance of the high-frequency data reduces not only the high-frequency activity but also the low-frequency muscle contribution, because the topography produced by a muscle source can be expected to be the same regardless of the frequency. The method greatly reduced the muscle artifact evoked by stimulation of Broca's area, while a significant brain signal contribution remained. Improvement in the signal-to-artifact ratio, defined as the relative amplitudes of brain signals peaking after 50 ms and the first artifact deflection, was of the order of 10-100 depending on the number of projections. The presented artifact removal method enables one to study the cortical state when stimulating areas near the cranial muscles.

摘要

经颅磁刺激结合脑电图是探测皮质兴奋性和连通性的有力工具;我们可以干扰一个脑区,并研究受刺激和相互连接的部位的反应。当刺激颅肌附近的区域时,它们的激活会在脑电图信号中产生一个大的伪影,持续数十毫秒,掩盖了早期的脑信号。我们提出了一种基于突出肌肉活动的地形模式的去伪影方法。虽然大脑和肌肉成分在时间和频谱上都重叠,但肌肉活动也存在于高于 100 Hz 的频率,而大脑信号主要限制在低于该频率的范围内,这使得我们可以在没有大脑贡献的情况下研究高频肌肉活动。我们使用主成分分析,从截止频率为 100 Hz 的高通滤波数据中确定肌肉活动的地形。突出解释高频数据大部分方差的主成分的地形不仅可以减少高频活动,还可以减少低频肌肉贡献,因为肌肉源产生的地形可以预期与频率无关。该方法大大减少了由 Broca 区刺激引起的肌肉伪影,同时仍保留了显著的脑信号贡献。信号-伪影比的改善,定义为刺激后 50 ms 出现的脑信号峰值与第一个伪影偏转的相对幅度,取决于投影的数量,约为 10-100。所提出的去伪影方法使人们能够在刺激颅肌附近区域时研究皮质状态。

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