Random field-union intersection tests for EEG/MEG imaging
Random field-union intersection tests for EEG/MEG imaging
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DOI：
10.1016/j.neuroimage.2004.01.020
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发表时间：
2004-05-01
期刊：
影响因子：
5.7
通讯作者：
Parra, M
中科院分区：
文献类型：
--
作者：
Carbonell, F;Galán, L;Parra, M
电生理（EEG/MEG）成像通过提供相同时空数据的两种视图：地形和层析成像来挑战统计学。到目前为止，对这两种情况的统计测试是分开发展的。本文介绍了同时评估时空事件相关电位/事件相关场（ERP/ERF）成分及其来源的显著性的统计检验。检测组件在给定时间瞬间的测试是由霍特林的T-2统计量提供的。该统计量以这样一种方式构造，对任何参考选择都是不变的，并且基于数据的平均参考变换的广义版本。因此，所提出的测试是众所周知的全球场强统计的推广。考虑所有时刻的测试导致使用随机场理论（RFT）来解决多重比较问题。并交（UI）原则是检验关于这些ERP/ERF组件的地形和层析分布的假设的基础。该方法的性能通过从模式反转刺激的视觉实验中获得的实际脑电图记录来说明。(C) 2004爱思唯尔公司版权所有。
Electrophysiological (EEG/MEG) imaging challenges statistics by providing two views of the same spatiotemporal data: topographic and tomographic. Until now, statistical tests for these two situations have developed separately. This work introduces statistical tests for assessing simultaneously the significance of spatiotemporal event-related potential/event-related field (ERP/ERF) components and that of their sources. The test for detecting a component at a given time instant is provided by a Hotelling's T-2 statistic. This statistic is constructed in such a manner to be invariant to any choice of reference and is based upon a generalized version of the average reference transform of the data. As a consequence, the proposed test is a generalization of the well-known Global Field Power statistic. Consideration of tests at all time instants leads to a multiple comparison problem addressed by the use of Random Field Theory (RFT). The Union-Intersection (UI) principle is the basis for testing hypotheses about the topographic and tomographic distributions of such ERP/ERF components. The performance of the method is illustrated with actual EEG recordings obtained from a visual experiment of pattern reversal stimuli. (C) 2004 Elsevier Inc. All rights reserved.