Combined permutation test and mixed-effect model for group average analysis in fMRI.
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.
Mériaux
Sébastien
S
CEA, Service Hospitalier Frédéric Joliot, Orsay, France.
Roche
Alexis
A
Dehaene-Lambertz
Ghislaine
G
Thirion
Bertrand
B
Poline
Jean-Baptiste
JB
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology; D001931:Brain Mapping / Q000379:methods*; D003071:Cognition / Q000502:physiology; D003198:Computer Simulation / Q000592:standards* / Q000639:trends; D007839:Functional Laterality / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000639:trends; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000639:trends; D015233:Models, Statistical; D016011:Normal Distribution; D012986:Software Validation; D013067:Speech Perception / Q000502:physiology; D014705:Verbal Behavior / Q000502:physiology