With over three-thousand publications annually in the past decade, including several meta-analyses [27] (Figure 1), the identification of potential publication or reporting biases is of crucial interest for the future of neuroimaging. The first study to evaluate evidence for an excess of statistically significant results in neuroimaging focused on brain volumetric studies based on Region of Interests (ROIs) analyses of psychiatric conditions [28]. The study analyzed 41 meta-analyses (461 datasets) and concluded that there were too many studies with statistically significant results, probably due to selective outcome or analysis reporting [28]. Another evaluation assessed studies employing voxel-based-morphometry (VBM) methods, which are less subject to selective reporting of selected ROIs [29]. Still, in a dataset of 47 whole-brain meta-analyses including 324 individual VBM studies, the number of foci reported in small VBM studies and even in meta-analyses with few studies was often inflated, consistent with reporting biases [30]. Interestingly, this and another investigation suggested that studies with fewer coauthors tend to report larger brain abnormalities [31]. Similar biases were also detected in the use of functional magnetic resonance imaging (fMRI) in
