Statistical Tests and Inferences

Brain imaging techniques have increased in popularity and complexity in recent years. Assessing statistical significance in the face of increasingly large and intricate data sets has become a challenging task. In this article we discuss neuroimaging analysis techniques, with a focus on functional MRI, posed as a problem of massive data reduction. Standard preprocessing steps are outlined in detail along with common methods for modeling data at both the individual subject and group level. Various issues regarding display/communication of neuroimaging data are considered, including choice of statistical threshold, corrections for multiple comparisons, and region-of-interest analyses. Closing remarks briefly highlight other techniques used to make inferences about brain activity.