Intrinsic Functional-Connectivity Networks for Diagnosis: Just Beautiful Pictures?

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Abstract
Resting-state functional connectivity has become a topic of enormous interest in the Neuroscience community in the last decade. Because resting-state data (1) harbor important information that often is diagnostically relevant and (2) are easy to acquire, there has been a rapid increase in the development of a variety of network analytic techniques for diagnostic applications, stimulating methodological research in general. While we are among those who welcome the increased interest in the resting state and multivariate analytic tools, we would like to draw attention to some entrenched practices that undermine the scientific quality of diagnostic functional-connectivity research, but whose correction is relatively easy to accomplish. With the current commentary we also hope to benefit the field at large and contribute to a healthy debate about research goals and best practices.