Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates
Abstract
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 a number of fMRI studies and may have a large impact on the interpretation of weakly significant neuroimaging results.
- Publication:
-
Proceedings of the National Academy of Science
- Pub Date:
- July 2016
- DOI:
- 10.1073/pnas.1602413113
- Bibcode:
- 2016PNAS..113.7900E