Over the last two decades, neuroimaging has provided ample knowledge on the structure, function and connectivity of the human brain as well as the aberrations thereof in patients with neurological and psychiatric disorders. In this context, the long predominant paradigm has been to compare (mean) local volume or activity between groups, or to correlate these to behavioral phenotypes. Such approach, however, is intrinsically limited in terms of possible insight into inter-individual differences and application in clinical practice. Recently, the increasing availability of large cohort data and tools for multivariate statistical learning, allowing the prediction of individual cognitive or clinical phenotypes in new subjects, have started a revolution in imaging neuroscience.
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