Rxivist logo

Multiple testing correction over contrasts for brain imaging

By Bianca A. V. Alberton, Thomas E. Nichols, Humberto R. Gamba, Anderson Winkler

Posted 19 Sep 2019
bioRxiv DOI: 10.1101/775106 (published DOI: 10.1016/j.neuroimage.2020.116760)

The multiple testing problem arises not only when there are many voxels or vertices in an image representation of the brain, but also when multiple contrasts of parameter estimates (that is, hypotheses) are tested in the same general linear model. Here we argue that a correction for this multiplicity must be performed to avoid excess of false positives. Various methods have been proposed in the literature, but few have been applied to brain imaging. Here we discuss and compare different methods to make such correction in different scenarios, showing that one classical and well known method is invalid, and argue that permutation is the best option to perform such correction due to its exactness and flexibility to handle a variety of common imaging situations.

Download data

  • Downloaded 642 times
  • Download rankings, all-time:
    • Site-wide: 21,253 out of 85,120
    • In neuroscience: 3,551 out of 15,149
  • Year to date:
    • Site-wide: 10,186 out of 85,120
  • Since beginning of last month:
    • Site-wide: 9,896 out of 85,120

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide


Sign up for the Rxivist weekly newsletter! (Click here for more details.)