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Paper – Statistical software used in brain imaging MRI studies subject to “bad data”

Ever had a brain MRI –  if so, you may want to read this new study: Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates Published online before print June 28, 2016, doi: 10.1073/pnas.1602413113. Proceedings of the National Academy of Sciences. PNAS June 28, 2016.

“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.”

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