Department of Psychiatric Neurophysiology, University Hospital of Psychiatry, University of Bern, Bern, Switzerland.
Brain Topogr. 2010 Sep;23(3):233-42. doi: 10.1007/s10548-010-0142-1. Epub 2010 Apr 8.
We present a simple and effective method to test whether an event consistently activates a set of brain electric sources across repeated measurements of event-related scalp field data. These repeated measurements can be single trials, single subject ERPs, or ERPs from different studies. The method considers all sensors simultaneously, but can be applied separately to each time frame or frequency band of the data. This allows limiting the analysis to time periods and frequency bands where there is positive evidence of a consistent relation between the event and some brain electric sources. The test may therefore avoid false conclusions about the data resulting from an inadequate selection of the analysis window and bandpass filter, and permit the exploration of alternate hypotheses when group/condition differences are observed in evoked field data. The test will be called topographic consistency test (TCT). The statistical inference is based on simple randomization techniques. Apart form the methodological introduction, the paper contains a series of simulations testing the statistical power of the method as function of number of sensors and observations, a sample analysis of EEG potentials related to self-initiated finger movements, and Matlab source code to facilitate the implementation. Furthermore a series of measures to control for multiple testing are introduced and applied to the sample data.
我们提出了一种简单而有效的方法来检验事件是否在相关头皮场数据的重复测量中一致地激活一组脑电源。这些重复测量可以是单个试验、单个个体 ERP 或来自不同研究的 ERP。该方法同时考虑所有传感器，但也可以分别应用于数据的每个时间帧或频带。这允许将分析限制在有阳性证据表明事件与某些脑电源之间存在一致关系的时间段和频带。因此，该测试可以避免由于分析窗口和带通滤波器的选择不当而导致对数据产生错误结论，并在诱发电场数据中观察到组/条件差异时允许探索替代假设。该测试将被称为地形一致性测试（TCT）。统计推断基于简单的随机化技术。除了方法学介绍，本文还包含一系列模拟测试，以检验该方法的统计功效作为传感器和观察数量的函数，以及对与自我发起的手指运动相关的 EEG 电位的样本分析，以及 Matlab 源代码以方便实施。此外，还引入了一系列用于控制多重检验的措施，并将其应用于样本数据。
