PT  - JOURNAL ARTICLE
AU  - Liégeois, Raphaël
AU  - Yeo, B. T. Thomas
AU  - Van De Ville, Dimitri
TI  - Interpreting Null Models of Resting-State Functional MRI
AID  - 10.1101/2021.03.30.437514
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.03.30.437514
4099  - http://biorxiv.org/content/early/2021/03/31/2021.03.30.437514.short
4100  - http://biorxiv.org/content/early/2021/03/31/2021.03.30.437514.full
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.