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In this case, the input data was brain scans from children, teenagers and adults, and the corresponding ages of each brain. The pattern the SVM was asked to find was the relationship between age and some complex set of parameters about the brain.
The scan was resting state functional connectivity fMRI. This measures the degree to which different areas of the brain tend to activate or deactivate together while you're just lying there (hence "resting"). A high connectivity between two regions means that they're probably "talking to each other", although not necessarily directly.
It worked fairly well:
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The authors then tested it on two other large datasets: one was resting state, but conducted on a less powerful scanner (1.5T vs 3.0T) (n=195), and the other was not designed as a resting state scan at all, but did happen to include some resting state-like data (n=186). Despite the fact that these data were, therefore, very different to the original dataset, the SVM was able to predict age with r2 over 0.5 as well.
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What use would this be? Well, good question. It would be all too easy to, say, find a scan of your colleague's brain, run it through the Mature-O-Meter, and announce with glee that they have a neurological age of 12, which explains a lot. For example.
However, while this would be funny, it wouldn't necessarily tell you anything about them. We already know everyone's neurological age. It's... their age. Your brain is an old as you are. These data raise the interesting possibility that people with a higher Maturity Index, for their age, are actually more "mature" people, whatever that means. But that might not be true at all. We'll have to wait and see.
How does this help us to understand the brain? An SVM is an incredibly powerful mathematical tool for detecting non-linear correlations in complex data. But just running an SVM on some data doesn't mean we've learned anything: only the SVM has. It's a machine learning algorithm, that's what it does. There's a risk that we'll get "science without understanding" as I've written a while back.
In fact the authors did make a start on this and the results were pretty neat. They found that as the brain matures, long-range functional connections within the brain become stronger, but short-range interactions between neighbours get weaker and this local disconnection with age is the most reliable change.
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It's like how when you're a kid, you play with the kids next door, but when you grow up you spend all your time on the internet talking to people thousands of miles away, and never speak to your neighbours. Kind of.
Link: Also blogged about here.
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