Ben Deen and Kevin Pelphrey in Nature: "Perspective: Brain scans need a rethink" .
Recent studies, however, have found that when a person moves their head while undergoing functional magnetic resonance imaging (fMRI) -- a method that maps how different neuroanatomical structures of the brain interact in real time, its functional connectivity -- it looks like the neural activity observed in autism. That's a sobering discovery: it means that a major source of evidence for a leading hypothesis on autism, and one that several research teams have pursued for years, may arise from an artifact.
Remember the "dead salmon" study, in which inert tissue placed in the scanner produced results? The statistical methods underlying comparisons of fMRI between cases and controls rely on averaging a multidimensional space across many individuals. A bias doesn't have to be very large to lead to a significant difference between groups:
[A]s one of the new studies showed, even a difference as small as 0.004 millimetre in average head motion across groups of patients can lead to significant differences in correlation strengths.
That's four microns! That is, of course, an average across a large sample, each child has his or her own motion. Imagine trying to get them to average out so that the average motto is precisely equal across a few dozen individuals. And then, as the article discusses ways that might correct for linear biases, you are still left with the possibility that head motion has a nonlinear effect on result, so that the bias survives your attempt to correct for it.
How remarkable, the very complex approaches necessary to deal with a relatively simple phenomenon.