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

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

• Publisher: John Wiley and Sons
• Year: 2006
• Tongue: English
• Weight: 244 KB
• Volume: 27
• Category: Article
• ISSN: 1065-9471
• DOI: 10.1002/hbm.20251

✦ Synopsis

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. Hum Brain Mapp 27:402–410, 2006. © 2006 Wiley‐Liss, Inc.