False positive rates in science have been an issue recently; and although we all had a good laugh when it happened to the social psychologists two years ago, now that it's happening to us, it's not so funny.
Anders Eklund and colleagues published a paper last summer showing that cluster correction - one method that FMRI researchers use to test whether their results are statistically significant or not - can lead to high false positive rates, or saying that a result is real, when actually it is a random occurrence that looks like a real result.
Their calculations showed that about 10% of FMRI studies are affected by this error (http://tinyurl.com/jaomsgs). However, keep in mind that even if a study is at risk for reporting a false positive, doesn't mean that their result is necessarily spurious. As with all results, one must go to the original study and take into account the rigor of the experimental design and whether the result looks legitimate.
These flaws have been addressed in recent versions of AFNI, an FMRI software package. The steps to use these updated programs can be found on the blog here: http://tinyurl.com/j5vafsb