title: A defense of using resting-state fMRI as null data for estimating false positive rates.
abstract: A recent Editorial in Cognitive Neuroscience reconsiders the findings of our work on the accuracy of false positive rate control with cluster inference in functional magnetic resonance imaging (fMRI), in particular criticizing our use of resting-state fMRI as a source for null data in the evaluation of task fMRI methods. We defend this use of resting fMRI data, as while there is much structure in this data, we argue it is representative of task data noise and task analysis software should be able to accommodate this noise. We also discuss a potential problem with Slotnick's own method.
authors.affiliation: a Department of Statistics , University of Warwick , Coventry , UK.|b WMG , University of Warwick , Coventry , UK.
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Nichols
authors.affiliation: c Division of Medical Informatics, Department of Biomedical Engineering , Linköping University , Linköping , Sweden.|d Division of Statistics and Machine Learning, Department of Computer and Information Science , Linköping University , Linköping , Sweden.|e Center for Medical Image Science and Visualization , Linköping University , Linköping , Sweden.
authors.forename: Anders
authors.initials: A
authors.lastname: Eklund
authors.affiliation: c Division of Medical Informatics, Department of Biomedical Engineering , Linköping University , Linköping , Sweden.|e Center for Medical Image Science and Visualization , Linköping University , Linköping , Sweden.
authors.forename: Hans
authors.initials: H
authors.lastname: Knutsson
mesh_terms: D006801:Humans; D008279:Magnetic Resonance Imaging; D012146:Rest
keywords: cluster inference; fMRI; open data