title: Intrinsic functional-connectivity networks for diagnosis: just beautiful pictures?
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.
authors.affiliation: Department of Neurology, Taub Institute, Columbia University, New York, New York 10032, USA. ch629@columbia.edu
authors.forename: Christian
authors.initials: C
authors.lastname: Habeck
authors.forename: James R
authors.initials: JR
authors.lastname: Moeller
mesh_terms: D000818:Animals; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods; D003952:Diagnostic Imaging / Q000379:methods*; D006801:Humans; D008564:Membrane Potentials / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D009434:Neural Pathways / Q000502:physiology