In a highly cited paper in 2005, John Ioannidis answered the question ‘Why most published research findings are false’  (PLoS Med. 2, e124). The answer, in one sentence, is ‘because of low statistical power and bias’. A current analysis in Nature Reviews Neuroscience ‘Power failure: why small sample size undermines the reliability of neuroscience’ (advance online publication, Ioannidis is a coauthor) now focuses on the neurosciences, and provides empirical evidence that in a wide variety of neuroscience fields (including imaging and animal modeling) exceedingly low statistical power and hence very low positive predictive values are the norm. This explains low reproducibility (e.g. special issue in Exp. Neurol. with (lack of) reproduction in spinal cord injury research, Exp Neurol. 2012 Feb;233(2):597-605) and inflated effect sizes. Besides this meta-analysis on power in neuroscience research, the article also contains a highly readable primer on the concepts of power, positive predictive value, type I and II error, as well as effect size. Must read.