The Multiple Comparison Problem in Neuroimaging

Functional magnetic resonance imaging (fMRI) is a safe and non-invasive way to assess brain functions by using signal changes associated with the brain activity. Current scientific techniques in fMRI image processing routinely produce hypothesis testing problems with hundreds or thousands of voxels to consider simultaneously. This matter occurs when we want to make statistical inferences about activated voxels simultaneously. This poses new difficulties for the statistician, but also opens new opportunities. In this paper, we will review and discuss the methods that are using as solutions of the multiple comparison problems in neuroimaging.