Although there are a number of statistical software tools for voxel-based massively univariate analysis of neuroimaging data, such as fMRI (functional MRI), PET (positron emission tomography), and VBM (voxel-based morphometry), very few software tools exist for power and sample size calculation for neuroimaging studies. Unlike typical biomedical studies, outcomes from neuroimaging studies are 3D images of correlated voxels, requiring a correction for massive multiple comparisons. Thus, a specialized power calculation tool is needed for planning neuroimaging studies. To facilitate this process, we developed a software tool specifically designed for neuroimaging data. The software tool, called PowerMap, implements theoretical power calculation algorithms based on non-central random field theory. It can also calculate power for statistical analyses with FDR (false discovery rate) corrections. This GUI (graphical user interface)-based tool enables neuroimaging researchers without advanced knowledge in imaging statistics to calculate power and sample size in the form of 3D images. In this paper, we provide an overview of the statistical framework behind the PowerMap tool. Three worked examples are also provided, a regression analysis, an ANOVA (analysis of variance), and a two-sample T-test, in order to demonstrate the study planning process with PowerMap. We envision that PowerMap will be a great aide for future neuroimaging research.

## PubMed Commons