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Split-test Bonferroni correction for QEEG statistical maps

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Abstract

With statistical testing, corrections for multiple comparisons, such as Bonferroni adjustments, have given rise to controversies in the scientific community, because of their negative impact on statistical power. This impact is especially problematic for high-multidimensional data, such as multi-electrode brain recordings. With brain imaging data, a reliable method is needed to assess statistical significance of the data without losing statistical power. Conjunction analysis allows the combination of significance and consistency of an effect. Through a balanced combination of information from retest experiments (multiple trials split testing), we present an intuitively appealing, novel approach for brain imaging conjunction. The method is then tested and validated on synthetic data followed by a real-world test on QEEG data from patients with Alzheimer’s disease. This latter application requires both reliable type-I error and type-II error rates, because of the poor signal-to-noise ratio inherent in EEG signals.

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Authors and Affiliations

  1. RIKEN Brain Science Institute, L.ABSP, 2-6 Hirosawa, Wako-Shi, Saitama-Ken, 351-0198, Japan

    Francois-Benoit Vialatte & Andrzej Cichocki

Authors
  1. Francois-Benoit Vialatte
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  2. Andrzej Cichocki
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Correspondence to Francois-Benoit Vialatte.

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This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

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Vialatte, FB., Cichocki, A. Split-test Bonferroni correction for QEEG statistical maps. Biol Cybern 98, 295–303 (2008). https://doi.org/10.1007/s00422-008-0210-8

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  • DOI: https://doi.org/10.1007/s00422-008-0210-8

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