Mass univariate analysis of event-related brain potentials/fields I: A critical tutorial review
Top Cited Papers
- 30 November 2011
- journal article
- review article
- Published by Wiley in Psychophysiology
- Vol. 48 (12), 1711-1725
- https://doi.org/10.1111/j.1469-8986.2011.01273.x
Abstract
Event-related potentials (ERPs) and magnetic fields (ERFs) are typically analyzed via ANOVAs on mean activity in a priori windows. Advances in computing power and statistics have produced an alternative, mass univariate analyses consisting of thousands of statistical tests and powerful corrections for multiple comparisons. Such analyses are most useful when one has little a priori knowledge of effect locations or latencies, and for delineating effect boundaries. Mass univariate analyses complement and, at times, obviate traditional analyses. Here we review this approach as applied to ERP/ERF data and four methods for multiple comparison correction: strong control of the familywise error rate (FWER) via permutation tests, weak control of FWER via cluster-based permutation tests, false discovery rate control, and control of the generalized FWER. We end with recommendations for their use and introduce free MATLAB software for their implementation.Keywords
This publication has 37 references indexed in Scilit:
- FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological DataComputational Intelligence and Neuroscience, 2010
- The phonemic restoration effect reveals pre-N400 effect of supportive sentence context in speech perceptionBrain Research, 2010
- Everything You Never Wanted to Know about Circular Analysis, but Were Afraid to AskJournal of Cerebral Blood Flow & Metabolism, 2010
- False discovery rate and permutation test: An evaluation in ERP data analysisStatistics in Medicine, 2009
- Identifying reliable independent components via split-half comparisonsNeuroImage, 2009
- Circular analysis in systems neuroscience: the dangers of double dippingNature Neuroscience, 2009
- Statistical parametric mapping for event-related potentials: I. Generic considerationsNeuroImage, 2004
- The control of the false discovery rate in multiple testing under dependencyThe Annals of Statistics, 2001
- Permutation tests for univariate or multivariate analysis of variance and regressionCanadian Journal of Fisheries and Aquatic Sciences, 2001
- Stepwise normal theory multiple test procedures controlling the false discovery rateJournal of Statistical Planning and Inference, 2000