This Is Your Brain On Magnets — Or Maybe Not 59
conspirator23 writes "Jon Hamilton of National Public Radio brings us a story about 'voodoo correlations' in fMRI studies that seek to learn more about emotional states, personality, and social cognition in the human brain. Many of us outside the scientific community have been treated to fascinating images of brain activity and corresponding explanations about how the images reveal which portions of the brain are engaged in certain kinds of thinking. But these images are not actual snapshots; they are visualizations of data generated by repeated scans during experiments. Flaws in the statistical methods used by researchers can result in false images with a variety of inaccuracies. Yet the images produced are so vivid and engaging that even other neuroscientists can be misled by them."
Pretty Familiar to Me (Score:2, Interesting)
Really Useful? (Score:3, Interesting)
I've always wondered how useful these images really are. Perhaps to the trained eye they can reveal a lot about how a persons brain works but they have always struck me as being too abstract. We can point at a portion of the image and say that bit controls movement, for example, but if anything goes wrong we are stuck because at a fundamental level we don't understand how it controls movement. I suppose it's a bit like looking at a block diagram for a CPU and not understanding how each bit works.
It will be interesting to see how we achieve the next level of understanding of the brains functioning. I can't see that we will ever get there with MRI or electrode probes because, I think, they are simply too large to get a true understanding of what is going on. I suspect we will gain our understanding through modelling but I'm not sure I'll be around when we do.
Re:Pretty Familiar to Me (Score:3, Interesting)
These sort of images are pretty familiar to me and I must admit I was never skeptical of research [...] it's a shame that one of the few tools used to determine the hows and whys of it is being called into question.
I don't think this 'uncertainty' is anything new. Computing a tomographic reconstruction is an ill-posed problem, you can do least squares, you can be a Bayesian, but in the end you have to introduce information or assumptions to fill out the "null space" of your measurements.
I think there's been a lack of understanding on the part of many folks in the medical community about just what kinds of assumptions go into making those pretty CT and MRI results. Treating spurious features in reconstructions due to the measurement and regularization technique was an intense area of early research in this field.
Computed Tomography [wikipedia.org]
Tomographic Reconstruction [wikipedia.org]