This is an article taken from Derren Brown’s blog. As you probably know, Derren is a very talented magician and illusionist who recently received great publicity for correctly predicting the UK lottery results. I am a great admirer of his work, as I’m sure many of you are. Here Derren considers the Multiple Comparisons Problem when looking at the results of an MRI scan on a dead fish.
This is a poster presented by Bennett and colleagues at this year’s Human Brain Mapping conference. It’s about fMRI scanning on a dead fish, specifically a salmon. They put the salmon in an MRI scanner and “the salmon was shown a series of photographs depicting human individuals in social situations. The salmon wasasked to determine what emotion the individual in the photo must have been experiencing.”
I’d say that this research was justified on comedic grounds alone, but they were also making an important scientific point. The (fish-)bone of contention here is multiple comparisons correction. The “multiple comparisons problem” is simply the fact that if you do a lot of different statistical tests, some of them will, just by chance, give interesting results.
In fMRI, the problem is particularly severe. An MRI scan divides the brain up into cubic units called voxels. There are over 40,000 in a typical scan. Most fMRI analysis treats every voxel independently, and tests to see if each voxel is “activated” by a certain stimulus or task. So that’s at least 40,000 separate comparisons going on – potentially many more, depending upon the details of the experiment.
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