Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates

doi: 10.1073/pnas.1602413113

Exeerpts:

"Through the introduction of international data-sharing initiatives in the neuroimaging field (4–10), it has become possible to evaluate the statistical methods using real data."

"Functional MRI (fMRI) is 25 years old, yet surprisingly its most common statistical methods have not been validated using real data. Here, we used resting-state fMRI data from 499 healthy controls to conduct 3 million task group analyses. Using this null data with different experimental designs, we estimate the incidence of significant results. In theory, we should find 5% false positives (for a significance threshold of 5%), but instead we found that the most common software packages for fMRI analysis (SPM, FSL, AFNI) can result in false-positive rates of up to 70%. These results question the validity of some 40,000 fMRI studies and may have a large impact on the interpretation of neuroimaging results."

http://www.pnas.org/content/113/28/7900