Common statistical methods used to analyse brain activity through images taken with MRI scanners cannot be trusted, as shown by Anders Eklund and Hans Knutsson of Linköping University, and Thomas Nichols of the University of Warwick, in the highly-ranked journal PNAS.
Functional MRI (fMRI) is 25 years old, yet surprisingly its most common statistical methods have not been validated using real data. Validations have instead mainly been performed using simulated data, but it is obviously very hard to simulate the complex spatiotemporal noise that arises from a living human subject in an MR scanner.
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%
a 15-year-old bug was found in 3dClustSim while testing the three software packages (the bug was fixed by the AFNI group as of May 2015, during preparation of this manuscript)
It is not feasible to redo 40,000 fMRI studies, and lamentable archiving and data-sharing practices mean most could not be reanalyzed either
TL;DR: Research suggest the neuroimaging results from the past 15 years are unreliable