McMenamin Brenton W, Shackman Alexander J, Greischar Lawrence L, Davidson Richard J
Center for Cognitive Sciences and Department of Psychology, University of Minnesota-Twin Cities.
Neuroimage. 2011 Jan 1;54(1):4-9. doi: 10.1016/j.neuroimage.2010.07.057. Epub 2010 Aug 2.
Recent years have witnessed a renewed interest in using oscillatory brain electrical activity to understand the neural bases of cognition and emotion. Electrical signals originating from pericranial muscles represent a profound threat to the validity of such research. Recently, McMenamin et al (2010) examined whether independent component analysis (ICA) provides a sensitive and specific means of correcting electromyogenic (EMG) artifacts. This report sparked the accompanying commentary (Olbrich, Jödicke, Sander, Himmerich & Hegerl, in press), and here we revisit the question of how EMG can alter inferences drawn from the EEG and what can be done to minimize its pernicious effects. Accordingly, we briefly summarize salient features of the EMG problem and review recent research investigating the utility of ICA for correcting EMG and other artifacts. We then directly address the key concerns articulated by Olbrich and provide a critique of their efforts at validating ICA. We conclude by identifying key areas for future methodological work and offer some practical recommendations for intelligently addressing EMG artifact.
近年来,人们对利用振荡性脑电活动来理解认知和情感的神经基础重新产生了兴趣。源自颅周肌肉的电信号对这类研究的有效性构成了严重威胁。最近,麦克梅纳明等人(2010年)研究了独立成分分析(ICA)是否提供了一种灵敏且特异的方法来校正肌源性(EMG)伪迹。这篇报告引发了随之而来的评论(奥尔布里希、约迪克、桑德、希默里希和黑格勒,即将发表),在此我们再次探讨肌电图如何改变从脑电图得出的推论,以及可以采取哪些措施来尽量减少其有害影响。因此,我们简要总结肌电图问题的显著特征,并回顾近期研究,这些研究调查了ICA在校正肌电图和其他伪迹方面的效用。然后,我们直接回应奥尔布里希提出的关键问题,并对他们验证ICA的工作进行批评。我们通过确定未来方法学工作的关键领域来得出结论,并为明智地处理肌电图伪迹提供一些实用建议。