Combined permutation test and mixed-effect model for group average analysis in fMRI.

Sébastien Mériaux; Alexis Roche; Ghislaine Dehaene-Lambertz; Bertrand Thirion; Jean-Baptiste Poline

doi:10.1002/hbm.20251

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Combined permutation test and mixed-effect model for group average analysis in fMRI.

Sébastien Mériaux·Alexis Roche·Ghislaine Dehaene-Lambertz·Bertrand Thirion·Jean-Baptiste Poline

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Abstract

In group average analyses, we generalize the classical one-sample t test to account for heterogeneous within-subject uncertainties associated with the estimated effects. Our test statistic is defined as the maximum likelihood ratio corresponding to a Gaussian mixed-effect model. The test's significance level is calibrated using the same sign permutation framework as in Holmes et al., allowing for exact specificity control under a mild symmetry assumption about the subjects' distribution. Because our likelihood ratio test does not rely on homoscedasticity, it is potentially more sensitive than both the standard t test and its permutation-based version. We present results from the Functional Imaging Analysis Contest 2005 dataset to support this claim.

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Algorithms Brain Brain Mapping Cognition Computer Simulation Functional Laterality Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Models, Statistical Normal Distribution Software Validation Speech Perception Verbal Behavior Journal Article Research Support, Non-U.S. Gov't

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Sébastien Mériaux, Alexis Roche, Ghislaine Dehaene-Lambertz, Bertrand Thirion, Jean-Baptiste Poline. 2006. Combined permutation test and mixed-effect model for group average analysis in fMRI.. https://doi.org/10.1002/hbm.20251

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