Controversy in statistical analysis of functional magnetic resonance imaging data
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PNAS-2017-Brown-E3368-9.pdf
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Author(s)
Behrmann, Marlene
Brown, Emery Neal
Date Issued
April 2017
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Brown, Emery N., and Behrmann, Marlene. “Controversy in Statistical Analysis of Functional Magnetic Resonance Imaging Data.” Proceedings of the National Academy of Sciences 114, 17 (April 2017): E3368–E3369 © 2017 National Academy of Sciences
Version
Final published version
Abstract
To test the validity of statistical methods for fMRI data analysis, Eklund et al. (1) used, for the first time, large-scale experimental data rather than simulated data. Using resting-state fMRI measurements to represent a null hypothesis of no task-induced activation, the authors compare familywise error rates for voxel-based and cluster-based inferences for both parametric and nonparametric methods. Eklund et al.’s study used three fMRI statistical analysis packages. They found that, for a target familywise error rate of 5%, the parametric methods gave invalid cluster-based inferences and conservative voxel-based inferences.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1073/PNAS.1705513114
