Katholieke Universiteit Leuven, Department of Electrical Engineering, ESAT-SCD, Leuven, Belgium.
Neuroimage. 2010 Apr 15;50(3):920-34. doi: 10.1016/j.neuroimage.2010.01.010. Epub 2010 Jan 11.
Multimodal approaches are of growing interest in the study of neural processes. To this end much attention has been paid to the integration of electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data because of their complementary properties. However, the simultaneous acquisition of both types of data causes serious artifacts in the EEG, with amplitudes that may be much larger than those of EEG signals themselves. The most challenging of these artifacts is the ballistocardiogram (BCG) artifact, caused by pulse-related electrode movements inside the magnetic field. Despite numerous efforts to find a suitable approach to remove this artifact, still a considerable discrepancy exists between current EEG-fMRI studies. This paper attempts to clarify several methodological issues regarding the different approaches with an extensive validation based on event-related potentials (ERPs). More specifically, Optimal Basis Set (OBS) and Independent Component Analysis (ICA) based methods were investigated. Their validation was not only performed with measures known from previous studies on the average ERPs, but most attention was focused on task-related measures, including their use on trial-to-trial information. These more detailed validation criteria enabled us to find a clearer distinction between the most widely used cleaning methods. Both OBS and ICA proved to be able to yield equally good results. However, ICA methods needed more parameter tuning, thereby making OBS more robust and easy to use. Moreover, applying OBS prior to ICA can optimize the data quality even more, but caution is recommended since the effect of the additional ICA step may be strongly subject-dependent.
多模态方法在神经过程的研究中越来越受到关注。为此，人们非常关注脑电图 (EEG) 和功能磁共振成像 (fMRI) 数据的整合，因为它们具有互补的特性。然而，这两种类型的数据同时采集会导致 EEG 中出现严重的伪影，其幅度可能比 EEG 信号本身大得多。这些伪影中最具挑战性的是心冲击图 (BCG) 伪影，这是由磁场中与脉搏相关的电极运动引起的。尽管人们已经做出了许多努力来寻找一种合适的方法来去除这种伪影，但目前的 EEG-fMRI 研究之间仍然存在很大的差异。本文试图通过基于事件相关电位 (ERP) 的广泛验证来澄清关于不同方法的几个方法学问题。更具体地说，研究了基于最优基集 (OBS) 和独立成分分析 (ICA) 的方法。它们的验证不仅使用了先前关于平均 ERP 的研究中已知的措施，而且还特别关注与任务相关的措施，包括在逐试信息上的使用。这些更详细的验证标准使我们能够在最广泛使用的清洁方法之间做出更清晰的区分。OBS 和 ICA 都被证明能够产生同样好的结果。然而，ICA 方法需要更多的参数调整，从而使 OBS 更健壮和易于使用。此外，在 ICA 之前应用 OBS 可以进一步优化数据质量，但需要谨慎，因为额外的 ICA 步骤的效果可能强烈依赖于个体。
