Mass univariate analysis of event-related brain potentials/fields II: Simulation studies.
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[1] Kyung In Kim,et al. Effects of dependence in high-dimensional multiple testing problems , 2008, BMC Bioinformatics.
[2] J. Pernier,et al. ERP Manifestations of Processing Printed Words at Different Psycholinguistic Levels: Time Course and Scalp Distribution , 1999, Journal of Cognitive Neuroscience.
[3] John Suckling,et al. Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain , 1999, IEEE Transactions on Medical Imaging.
[4] S. Weiss,et al. New concepts of multiple tests and their use for evaluating high-dimensional EEG data , 2005, Journal of Neuroscience Methods.
[5] Eduardo Martínez-Montes,et al. False discovery rate and permutation test: An evaluation in ERP data analysis , 2010, Statistics in medicine.
[6] B. Murphy,et al. Some two-sample tests when the variances are unequal: a simulation study. , 1967, Biometrika.
[7] Marta Kutas,et al. The phonemic restoration effect reveals pre-N400 effect of supportive sentence context in speech perception , 2010, Brain Research.
[8] B. Efron. Large-Scale Simultaneous Hypothesis Testing , 2004 .
[9] Sabine Weiss,et al. Multivariate tests for the evaluation of high-dimensional EEG data , 2004, Journal of Neuroscience Methods.
[10] I. Winkler,et al. The concept of auditory stimulus representation in cognitive neuroscience. , 1999, Psychological bulletin.
[11] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[12] Arnaud Delorme,et al. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.
[13] S. Holm. A Simple Sequentially Rejective Multiple Test Procedure , 1979 .
[14] R. Blair,et al. An alternative method for significance testing of waveform difference potentials. , 1993, Psychophysiology.
[15] Y. Benjamini,et al. THE CONTROL OF THE FALSE DISCOVERY RATE IN MULTIPLE TESTING UNDER DEPENDENCY , 2001 .
[16] R. Simon,et al. Controlling the number of false discoveries: application to high-dimensional genomic data , 2004 .
[17] Zijiang J. He,et al. Vertical and horizontal references determined by linear perspective and optic flow information , 2010 .
[18] Y. Benjamini,et al. Adaptive linear step-up procedures that control the false discovery rate , 2006 .
[19] P. Hall,et al. Robustness of multiple testing procedures against dependence , 2009, 0903.0464.
[20] Robert Oostenveld,et al. FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data , 2010, Comput. Intell. Neurosci..
[21] S. Luck. An Introduction to the Event-Related Potential Technique , 2005 .
[22] David M. Groppe,et al. Mass univariate analysis of event-related brain potentials/fields I: a critical tutorial review. , 2011, Psychophysiology.
[23] S. Hillyard,et al. Electrical Signs of Selective Attention in the Human Brain , 1973, Science.
[24] Terrence J. Sejnowski,et al. Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources , 1999, Neural Computation.
[25] R. Oostenveld,et al. Nonparametric statistical testing of EEG- and MEG-data , 2007, Journal of Neuroscience Methods.
[26] Bruno A Olshausen,et al. Timecourse of neural signatures of object recognition. , 2003, Journal of vision.