Risk of false positives in fMRI of post-mortem Atlantic salmon (2010) [pdf]
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I'll be honest - when the paper was published I was thinking "no shit - why do we need a paper to tell us what we all learned in stats 101 about multiple comparisons??" And then realized the quantity of fMRI papers that used uncorrected thresholds.
Very similar feeling when the "Voodoo Correlations" paper came out. Except I was admittedly guilty of having presented correlation coefficients from clusters that had already been identified using thresholding. So that paper really did make me take a closer look at some of my figures/conclusions.
I suppose it was meant to convince statistically naive readers that the dead salmon thing didn't apply to their methodology.
There were mainly two approaches to multiple comparison corrections: Bonferroni and setting an uncorrected threshold. People here might say, well yeah, use Bonferroni.
However, Bonferroni is really only appropriate when comparisons are independent. Voxels (3D pixels) which are adjacent are highly dependent, and indeed the brain is generally correlated. This dependency makes Bonferrnoi correction (very) inappropriately conservative. Given the average dependence of voxels, some researchers estimated that the average number of true comparisons might be on the order of hundreds to a few thousand. In practice, researchers corrected with Bonferroni, either found a really strong effect, or reset using uncorrected threshold. Some reported results using both. People who read the results interpreted results that way too. Bonferroni = reliable, uncorrected = provisional
The contribution of the salmon study and other research papers is that they truly demonstrated that the typical uncorrected thresholds in use were insufficient to control false positives.
If I recall correctly, all the major neuroimaging packages (AFNI, SPM, FSL) had options for cluster-size thresholding at the time. Along with tools like alpha sim to estimate cluster-level FDR (but I think that ultimately had issues with it's algorithm, discovered only a few years later...).
I just remember thinking that if the salmon paper had a reasonable cluster-threshold, none of the spurious voxels would have been considered in the final analysis.
Granted, several years later, a paper came out suggesting that method would inflate false positives (http://www.pnas.org/content/113/28/7900.full).
I imagine the neuroimaging field, particularly the stats part, has changed rapidly since I left.
I believe that you are correct that about the time of the salmon poster there were other methods available for multiple comparison correction. The work in the early- to mid-2000's was much more "wild-west" however.
Indeed cluster correction may have its own issues, re your link. I think that a good approach these days is to eschew whole-brain approaches for theory-drive, a prior i ROIs, then supplement those analyses with a whole brain exploratory analysis.
Glad to see this on Hacker News so many years after the poster first went up!
We did a review of the literature as part of our paper. In 2008 something like 30% of papers in major journals used uncorrected stats. In 2012 it was under 10%. The field was certainly already moving in the right direction, but I think we managed to help things along.
Our paper came out and got a lot of attention, which was good press for the journal. After that the JSUR founders found that they didn't have much time available and the journal folded a few years later. In the end, we were the only paper it published.
But it's a shame they couldn't continue, I would have loved to have something filling that niche.
Also, which FMRI papers have real results that you think are significant?
There are a huge number of fMRI papers that have significant results, statistically and in terms of impact. I have been out of the field for about five years now, so I am not up-to-date with the latest work. I am sure there is some amazing stuff going on.
Derren Brown - Pushed to the Edge. (It's very educational and fun)
(it's not a true story)
https://www.theguardian.com/culture/2003/jun/06/artsfeatures...
Understandable, obvious, and not just relevant, actually providing a meaningful contribution to their field by virtue of quantifying existing techniques as not sufficient to fully eliminate spurious data from the 'noise floor' inherent in fMRI machine data.
tl;dr: correcting for multiple comparisons is important.
Here's a link from my server that should just work: http://prefrontal.org/files/papers/Bennett-Salmon-2010.pdf