Variability in the analysis of a single neuroimaging dataset by many teams
Colin F. Camerer,
Jeanette A. Mumford,
Alberto De Luca,
Niall W Duncan,
G. Matthew Fricke,
João Guassi Moreira,
J. Paul Hamilton,
Susan P Holmes,
Ayse Ilkay Isik,
Nuri Erkut Kucukboyaci,
Phui Cheng Lim,
Annabel Losecaat Vermeer,
Adriana Méndez Leal,
Jonathan E Peelle,
Anna E. van’t Veer,
Wouter D. Weeda,
Posted 15 Nov 2019
bioRxiv DOI: 10.1101/843193 (published DOI: 10.1038/s41586-020-2314-9)
Posted 15 Nov 2019
Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed.
- Downloaded 6,763 times
- Download rankings, all-time:
- Site-wide: 1,508
- In neuroscience: 72
- Year to date:
- Site-wide: 12,794
- Since beginning of last month:
- Site-wide: 21,429
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!