Brain and Mental Health Laboratory, School of Psychological Sciences and Monash Biomedical Imaging, Monash Institute of Cognitive and Clinical Neuroscience, Monash University, Australia.
Monash Alfred Psychiatry Research Centre, Central Clinical School, Monash University, Australia.
Neuroimage. 2017 Feb 15;147:934-951. doi: 10.1016/j.neuroimage.2016.10.031. Epub 2016 Oct 20.
The concurrent use of transcranial magnetic stimulation with electroencephalography (TMS-EEG) is growing in popularity as a method for assessing various cortical properties such as excitability, oscillations and connectivity. However, this combination of methods is technically challenging, resulting in artifacts both during recording and following typical EEG analysis methods, which can distort the underlying neural signal. In this article, we review the causes of artifacts in EEG recordings resulting from TMS, as well as artifacts introduced during analysis (e.g. as the result of filtering over high-frequency, large amplitude artifacts). We then discuss methods for removing artifacts, and ways of designing pipelines to minimise analysis-related artifacts. Finally, we introduce the TMS-EEG signal analyser (TESA), an open-source extension for EEGLAB, which includes functions that are specific for TMS-EEG analysis, such as removing and interpolating the TMS pulse artifact, removing and minimising TMS-evoked muscle activity, and analysing TMS-evoked potentials. The aims of TESA are to provide users with easy access to current TMS-EEG analysis methods and to encourage direct comparisons of these methods and pipelines. It is hoped that providing open-source functions will aid in both improving and standardising analysis across the field of TMS-EEG research.
经颅磁刺激与脑电图(TMS-EEG)的联合使用作为评估各种皮质特性(如兴奋性、振荡和连通性)的方法越来越受欢迎。然而,这种方法组合在技术上具有挑战性,导致在记录过程中和在典型的 EEG 分析方法之后都会产生伪影,从而扭曲潜在的神经信号。在本文中,我们回顾了由 TMS 引起的 EEG 记录中的伪影的原因,以及在分析过程中引入的伪影(例如,由于过滤高频、大振幅伪影)。然后,我们讨论了去除伪影的方法,以及设计最小化分析相关伪影的管道的方法。最后,我们引入了 TMS-EEG 信号分析器(TESA),这是 EEGLAB 的一个开源扩展,其中包括专门用于 TMS-EEG 分析的功能,例如去除和插值 TMS 脉冲伪影、去除和最小化 TMS 诱发的肌肉活动,以及分析 TMS 诱发的电位。TESA 的目的是为用户提供对当前 TMS-EEG 分析方法的便捷访问,并鼓励对这些方法和管道进行直接比较。希望提供开源功能将有助于改进和标准化 TMS-EEG 研究领域的分析。