This post is based on a submission by reader Professor Daniel Bitran.
fMRI is a way of measuring blood-flow in the brain or spinal cord and, by extension, neural activity in those areas. A false positive is the sort of mistake your smoke detector makes when it goes off, but there's no smoke.
The image above is striking because the false positives seem to show neural activity in a dead salmon's brain. According to researchers at UCLA Santa Barbra, these errors are due to a problem of multiple comparisons.
Imagine we're playing One of These Things is not Like the Others with several tin cans of Atlantic salmons. At first, it's hard to tell which one is not like the others—there's a bunch of canned salmon. They have similar color, weight, shape, etc. But as we add different ways of comparing the cans (or more cans to compare), we increase the probability that there will be some way in which one of them differs from the rest—particularly because of small differences, say manufacturing defects.
[Note: Corrections appreciated.] Now imagine we're collecting data for an fMRI.
Each each point (called a
What are other examples of widespread errors of multiple comparisons or false positives?
Thanks to Craig Bennett of Prefrontal.org for providing a high resolution version of the Atlantic salmon fMRI.