There’s no denying that, in the past two decades, functional magnetic resonance imaging (fMRI) has revolutionized neuroscience. Its colorful, fine-resolution pictures allow scientists to compare patterns of activity in different brain regions during specific tasks.Every technique has its drawbacks, of course, and many of fMRI’s flaws — such as the fact that it measures blood flow, an indirect measure of neuron activity — are often mentioned in papers and discussed at conferences.But one flaw is rarely brought up and is apparently more widespread than anyone realized: when choosing from the enormous amounts of data generated from an fMRI experiment, scientists often ‘double dip’, or use the same subset for setting up a hypothesis and for confirming it.Read more at...SFARI, May 2009.