Randomization tests for ERP topographies and whole spatiotemporal data matrices

Authors


  • Thanks to Dick Willems for his assistence in this project, Marijtje Jongsma for the use of the data of the first application, Inge Keus for her assistence in the collection of the data of the second application, and Chan Wai Yen for proofreading the manuscript.

Address reprint requests to: Eric Maris, Nijmegen Institute of Cognition and Information (NICI), University of Nijmegen, P.O. Box 9104, 6500 HE Nijmegen, The Netherlands. E-mail: maris@nici.kun.nl

Abstract

In ERP studies, the comparison of topographies (multichannel measurements) or whole spatiotemporal data matrices (multichannel time series of measurements), the classical statistical tests very often cannot be used. It is argued that, for these comparisons, randomization tests are an excellent alternative. It is also argued that the randomization test is superior to another resampling method, the bootstrap, because exact probability statements (e.g., p values) can be made. A review is given of the literature on randomization tests designed for electrophysiological data. New randomization tests are presented and applied to two data sets, one coming from a psychopharmacological experiment and the other from an ERP experiment in visual word recognition.

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