RT Journal Article
SR Electronic
T1 Interpreting Null Models of Resting-State Functional MRI
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.03.30.437514
DO 10.1101/2021.03.30.437514
A1 Liégeois, Raphaël
A1 Yeo, B. T. Thomas
A1 Van De Ville, Dimitri
YR 2021
UL http://biorxiv.org/content/early/2021/03/31/2021.03.30.437514.abstract
AB Null models are necessary for assessing whether a dataset exhibits non-trivial statistical properties. These models have recently gained interest in the neuroimaging community as means to explore dynamic properties of functional Magnetic Resonance Imaging (fMRI) time series. Interpretation of null-model testing in this context may not be straightforward because (i) null hypotheses associated to different null models are sometimes unclear and (ii) fMRI metrics might be ‘trivial’, i.e. preserved under the null hypothesis, and still be useful in neuroimaging applications. In this commentary, we review several commonly used null models of fMRI time series and discuss the interpretation of the corresponding tests. We argue that, while null-model testing allows for a better characterization of the statistical properties of fMRI time series and associated metrics, it should not be considered as a mandatory validation step to assess their relevance in neuroimaging applications.Competing Interest StatementThe authors have declared no competing interest.