@albertcardona I pretty much agree with you, but I think it depends also on what you're looking for.
To use a programming/computer hardware analogy, if you want to figure out an algorithm, fMRI is useless. If you want to know whether your computation is hitting RAM hard or requires a lot of floating point operations or is engaging the graphics card a lot (and whether shaders are used), it's pretty handy.
Rather than fMRI being a case of looking for the wallet where the light is, it's more like it's showing you where to put the light to look for wallets (if it's done well).
However, the number of overinterpreted fMRI studies does rather disappoint me. The inference "we didn't see a fMRI signal in this area so it's not important in this task" seems to happen far too often.
Then again, this is one of the biggest mistakes of scientists in every area: assuming that absence of evidence is evidence of absence when the tools and/or statistics were not specifically being deployed to address that exact question (i.e. putting bounds on how absent something is).
As a rough heuristic, I find it depressingly accurate to assume that a sentence starting with "This isn't significant, so" is one that will end with an unjustified conclusion.
@albertcardona I guess I could go through a representative sample of recent fMRI papers and check. Knowing whether a process is RAM-intensive or uses shaders does give you new understanding of the function of your computational device, even if it's not an algorithm; there I think the track record is not bad (especially if you ignore the discussion section). But this is just a general impression; to get at anything like "what percentage" we'd have to actually pick out papers and score them, I think.
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@ichoran Thanks Rex for your insight. Overinterpretation of data and the pressure to publish positive findings or to simply publish-or-perish has brought us here. I wonder, though, what percentage of #fMRI papers would pass your filter: "if you want to figure out an algorithm, fMRI is useless". Many seem to claim new understanding of brain function.
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