Abstract
fMRI localizer tasks are often used to define subject specific functional regions of interest (fROIs) that contain the relevant features for subsequent analyses. fROIs are typically small and show large interindividual differences in extent and effect size. As statistical testing procedures focus on con- trolling false positives, this may lead to an ad-hoc adjustment of thresholding in some individuals. The promising likelihood ratio (LR) testing approach for fMRI (Kang et al. 2015) provides simultaneous control of both false positives and negatives by contrasting evidence in favor of true activation against evidence in favor of the null hypothesis. The authors propose to estimate the expected alternative by a percentile (e.g. 95th) across the voxels of an effect size map. However, in the context of fROIs, pre-defined observed percentiles may induce inconsistent activation across subjects. In this study we show the potential of a maximized LR approach (Bickel, 2012) for this particular application. The maximum LR is calculated over the same interval of functionally relevant alternatives for all subjects, enabling consistent localization of the fROIs in both subjects with low levels and high levels of general activity.
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