Common statistical methods that are used to analyze functional MR (fMRI) images of someone’s brain activity may produce wrong results, researchers have discovered.

Anders Eklund and Hans Knutsson from Linköping University, and Thomas Nichols from the University of Warwick tested the analysis methods on “known, reliable data” and the researchers found that the methods showed false brain activity on 60 percent of images when a reasonable percentage is five.

Eklund proposed a new method for validating the fMRI information which uses fewer assumptions and “a thousand times more” calculations than the conventional method that produces errors. Along with the proposed methods, the time that it takes to process an image could also decrease due to newer, more modern graphic cards.
“Thanks to modern graphic cards, large calculations can be run,” said Eklund in a statement. “It would take 1,000 times longer to run the calculations using a normal computer, but thanks to the graphic cards, I reduced the processing time from 10 years to 20 days.”

The researchers 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 percent false positives, ... 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 percent," they wrote in their study.

Eklund had also used his newer method on the same data that was analyzed on the older method and found that the new method yielded much better results with differences in five percent of cases.

When asked the question of how previous studies conducted with fMRI may need to be redone, he said, “I can’t answer that; many of them were done 10 to 15 years ago and it’s not certain that the basic data still exist. The important thing is that researchers think about what method they use in the future.”

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