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Cluster-based computational methods for mass univariate analyses of event-related brain potentials/fields : a simulation study
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Pernet, Cyril, Latinus, Marianne, Nichols, Thomas E. and Rousselet, Guillaume Alexis (2015) Cluster-based computational methods for mass univariate analyses of event-related brain potentials/fields : a simulation study. Journal of Neuroscience Methods, 250 . pp. 85-93. doi:10.1016/j.jneumeth.2014.08.003 ISSN 0165-0270.
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Official URL: http://dx.doi.org/10.1016/j.jneumeth.2014.08.003
Abstract
Background
In recent years, analyses of event related potentials/fields have moved from the selection of a few components and peaks to a mass-univariate approach in which the whole data space is analyzed. Such extensive testing increases the number of false positives and correction for multiple comparisons is needed.
Method
Here we review all cluster-based correction for multiple comparison methods (cluster-height, cluster-size, cluster-mass, and threshold free cluster enhancement – TFCE), in conjunction with two computational approaches (permutation and bootstrap).
Results
Data driven Monte-Carlo simulations comparing two conditions within subjects (two sample Student's t-test) showed that, on average, all cluster-based methods using permutation or bootstrap alike control well the family-wise error rate (FWER), with a few caveats.
Conclusions
(i) A minimum of 800 iterations are necessary to obtain stable results; (ii) below 50 trials, bootstrap methods are too conservative; (iii) for low critical family-wise error rates (e.g. p = 1%), permutations can be too liberal; (iv) TFCE controls best the type 1 error rate with an attenuated extent parameter (i.e. power < 1).
Item Type: | Journal Article | ||||||||||
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Subjects: | R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry | ||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||||
Library of Congress Subject Headings (LCSH): | Evoked potentials (Electrophysiology), Multivariate analysis | ||||||||||
Journal or Publication Title: | Journal of Neuroscience Methods | ||||||||||
Publisher: | Elsevier BV | ||||||||||
ISSN: | 0165-0270 | ||||||||||
Official Date: | 30 July 2015 | ||||||||||
Dates: |
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Volume: | 250 | ||||||||||
Page Range: | pp. 85-93 | ||||||||||
DOI: | 10.1016/j.jneumeth.2014.08.003 | ||||||||||
Status: | Peer Reviewed | ||||||||||
Publication Status: | Published | ||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||
Date of first compliant deposit: | 28 December 2015 | ||||||||||
Date of first compliant Open Access: | 28 December 2015 | ||||||||||
Funder: | Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC) | ||||||||||
Grant number: | BB/K014218/1 (BBSRC), BB/K01420X/1 (BBSRC) |
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