Random field-union intersection tests for EEG/MEG imaging.
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.
Carbonell
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F
Departamento de Sistemas Adaptivos, Institute for Cybernetics, Mathematics and Physics, Calle 15, No. 551, e/C y D, Vedado, Havana 4, C.P. 10400, Cuba. felix@icmf.inf.cu
Galán
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L
Valdés
P
P
Worsley
K
K
Biscay
R J
RJ
Díaz-Comas
L
L
Bobes
M A
MA
Parra
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M
D000465:Algorithms; D001931:Brain Mapping; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000706:statistics & numerical data*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015225:Magnetoencephalography / Q000706:statistics & numerical data*; D009778:Occipital Lobe / Q000502:physiology; D012016:Reference Values