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The empirical replicability of task-based fMRI as a function of sample size

(2020) NeuroImage. 212.
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Abstract
Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good science. As replicability has consequences for theories derived from empirical studies, it is of utmost importance to better understand the underlying mechanisms influencing it. A popular tool for non-invasive neuroimaging studies is functional magnetic resonance imaging (fMRI). While the effect of underpowered studies is well documented, the empirical assessment of the interplay between sample size and replicability of results for task- based fMRI studies remains limited. In this work, we extend existing work on this assessment in two ways. Firstly, we use a large database of 1400 subjects performing four types of tasks from the IMAGEN project to subsample a series of independent samples of increasing size. Secondly, replicability is evaluated using a multi-dimensional framework consisting of 3 different measures: (un)conditional test-retest reliability, coherence and stability. We demonstrate not only a positive effect of sample size, but also a trade-off between spatial resolution and replicability. When replicability is assessed voxelwise or when observing small areas of activation, a larger sample size than typically used in fMRI is required to replicate results. On the other hand, when focussing on clusters of voxels, we observe a higher replicability. In addition, we observe variability in the size of clusters of activation between experimental paradigms or contrasts of parameter estimates within these.
Keywords
Task-based fMRI Replicability Reproducibility Reliability Stability Coherence

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Citation

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MLA
Bossier, Han, et al. “The Empirical Replicability of Task-Based FMRI as a Function of Sample Size.” NeuroImage, vol. 212, 2020.
APA
Bossier, H., Roels, S. P., Seurinck, R., Banaschewski, T., Barker, G. J., Bokde, A. L. W., … Moerkerke, B. (2020). The empirical replicability of task-based fMRI as a function of sample size. NeuroImage, 212.
Chicago author-date
Bossier, Han, Sanne P. Roels, Ruth Seurinck, Tobias Banaschewski, Gareth J. Barker, Arun L.W. Bokde, Erin Burke Quinlan, et al. 2020. “The Empirical Replicability of Task-Based FMRI as a Function of Sample Size.” NeuroImage 212.
Chicago author-date (all authors)
Bossier, Han, Sanne P. Roels, Ruth Seurinck, Tobias Banaschewski, Gareth J. Barker, Arun L.W. Bokde, Erin Burke Quinlan, Sylvane Desrivières, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Bernd Ittermann, Jean-Luc Martinot, Eric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Luise Poustka, Juliane H. Fröhner Dipl-Psych, Michael N. Smolka, Henrik Walter, Robert Whelan, Gunter Schumann, and Beatrijs Moerkerke. 2020. “The Empirical Replicability of Task-Based FMRI as a Function of Sample Size.” NeuroImage 212.
Vancouver
1.
Bossier H, Roels SP, Seurinck R, Banaschewski T, Barker GJ, Bokde ALW, et al. The empirical replicability of task-based fMRI as a function of sample size. NeuroImage. 2020;212.
IEEE
[1]
H. Bossier et al., “The empirical replicability of task-based fMRI as a function of sample size,” NeuroImage, vol. 212, 2020.
@article{8654271,
  abstract     = {Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good
science. As replicability has consequences for theories derived from empirical studies, it is of utmost importance
to better understand the underlying mechanisms influencing it. A popular tool for non-invasive neuroimaging
studies is functional magnetic resonance imaging (fMRI). While the effect of underpowered studies is well
documented, the empirical assessment of the interplay between sample size and replicability of results for task-
based fMRI studies remains limited. In this work, we extend existing work on this assessment in two ways. Firstly,
we use a large database of 1400 subjects performing four types of tasks from the IMAGEN project to subsample a
series of independent samples of increasing size. Secondly, replicability is evaluated using a multi-dimensional
framework consisting of 3 different measures: (un)conditional test-retest reliability, coherence and stability.
We demonstrate not only a positive effect of sample size, but also a trade-off between spatial resolution and
replicability. When replicability is assessed voxelwise or when observing small areas of activation, a larger sample
size than typically used in fMRI is required to replicate results. On the other hand, when focussing on clusters of
voxels, we observe a higher replicability. In addition, we observe variability in the size of clusters of activation
between experimental paradigms or contrasts of parameter estimates within these.},
  articleno    = {116601},
  author       = {Bossier, Han and Roels, Sanne P. and Seurinck, Ruth and Banaschewski, Tobias and Barker, Gareth J. and Bokde, Arun L.W. and Quinlan, Erin Burke and Desrivières, Sylvane and Flor, Herta and Grigis, Antoine and Garavan, Hugh and Gowland, Penny and Heinz, Andreas and Ittermann, Bernd and Martinot, Jean-Luc and Artiges, Eric and Nees, Frauke and Orfanos, Dimitri Papadopoulos and Poustka, Luise and Fröhner Dipl-Psych, Juliane H. and Smolka, Michael N. and Walter, Henrik and Whelan, Robert and Schumann, Gunter and Moerkerke, Beatrijs},
  issn         = {1053-8119},
  journal      = {NeuroImage},
  keywords     = {Task-based fMRI Replicability Reproducibility Reliability Stability Coherence},
  language     = {eng},
  title        = {The empirical replicability of task-based fMRI as a function of sample size},
  url          = {http://dx.doi.org/10.1016/j.neuroimage.2020.116601},
  volume       = {212},
  year         = {2020},
}

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