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BIBTEX RIS

Variability in the analysis of a single neuroimaging dataset by many teams

2020; Nature Portfolio; Volume: 582; Issue: 7810 Linguagem: Inglês

10.1038/s41586-020-2314-9

1476-4687

Rotem Botvinik‐Nezer, Felix Holzmeister, Colin F. Camerer, Anna Dreber, Jürgen Huber, Magnus Johannesson, Michael Kirchler, Roni Iwanir, Jeanette A. Mumford, R. Alison Adcock, Paolo Avesani, Błażej M. Bączkowski, Aahana Bajracharya, Leah Bakst, Sheryl Ball, Marco Barilari, Nadège Bault, Derek Beaton, Julia Beitner, Roland G. Benoit, Ruud Berkers, Jamil P. Bhanji, Bharat B. Biswal, Sebastian Bobadilla-Suarez, Tiago Bortolini, Katherine L. Bottenhorn, Alexander Bowring, Senne Braem, Hayley R. Brooks, Emily G. Brudner, Cristian Buc Calderon, Julia A. Camilleri, Jaime J. Castrellon, Luca Cecchetti, Edna C. Cieslik, Zachary J. Cole, Olivier Collignon, Robert W. Cox, William A. Cunningham, Stefan Czoschke, Kamalaker Dadi, Charles P. Davis, Alberto De Luca, Mauricio R. Delgado, Lysia Demetriou, Jeffrey B. Dennison, Xin Di, Erin W. Dickie, Ekaterina Dobryakova, Claire Donnat, Juergen Dukart, Niall W. Duncan, Joke Durnez, Amr Eed, Simon B. Eickhoff, Andrew Erhart, Laura Fontanesi, G. Matthew Fricke, Shiguang Fu, Adriana Gálvan, Rémi Gau, Sarah Genon, Tristan Glatard, Enrico Glerean, Jelle J. Goeman, Sergej Golowin, Carlos González‐García, Krzysztof J. Gorgolewski, Cheryl L. Grady, Mikella A Green, João F. Guassi Moreira, Olivia Guest, Shabnam Hakimi, J. Paul Hamilton, Roeland Hancock, Giacomo Handjaras, Bronson Harry, Colin Hawco, Peer Herholz, Gabrielle Herman, Stephan Heunis, Felix Hoffstaedter, Jeremy Hogeveen, Susan Holmes, Hu Chuan-Peng, Scott A. Huettel, Matthew Hughes, Vittorio Iacovella, Alexandru D. Iordan, Peder Mortvedt Isager, Ayse Ilkay Isik, Andrew Jahn, Matthew R. Johnson, Tom Johnstone, Michael Joseph, Anthony Juliano, Joseph W. Kable, Michalis Kassinopoulos, Cemal Koba, Xiangzhen Kong, Timothy R. Koscik, Nuri Erkut Kucukboyaci, Brice A. Kuhl, Sebastian Kupek, Angela R. Laird, Claus Lamm, Robert Langner, Nina Lauharatanahirun, Hongmi Lee, Sangil Lee, Alexander Leemans, Andrea Leo, Elise Lesage, Flora Li, Monica Y. C. Li, Phui Cheng Lim, Evan Nathaniel Lintz, Schuyler Liphardt, Annabel B. Losecaat Vermeer, Bradley C. Love, Michael L. Mack, Norberto Malpica, Theo Marins, Camille Maumet, Kelsey McDonald, Joseph T. McGuire, Helena Melero, Adriana S. Méndez Leal, Benjamin Meyer, Kristin N. Meyer, Glad Mihai, Georgios D. Mitsis, Jorge Moll, Dylan M. Nielson, Gustav Nilsonne, Michael Notter, Emanuele Olivetti, Adrian Onicas, Paolo Papale, Kaustubh R. Patil, Jonathan E. Peelle, Alexandre Pérez, Doris Pischedda, Jean‐Baptiste Poline, Yanina Prystauka, Shruti Ray, Patricia A. Reuter‐Lorenz, Richard C. Reynolds, Emiliano Ricciardi, Jenny Rieck, Anais Rodriguez-Thompson, Anthony Romyn, Taylor Salo, Gregory R. Samanez‐Larkin, Emilio Sanz‐Morales, Margaret L. Schlichting, Douglas H. Schultz, Qiang Shen, Margaret A. Sheridan, Jennifer A. Silvers, Kenny Skagerlund, Alec Smith, David V. Smith, Peter Sokol‐Hessner, Simon R. Steinkamp, Sarah M. Tashjian, Bertrand Thirion, John Thorp, Gustav Tinghög, Loreen Tisdall, Steven Tompson, Claudio Toro‐Serey, Juan Jesús Torre, Leonardo Tozzi, Vuong Truong, Luca Turella, Anna van 't Veer, Tom Verguts, Jean M. Vettel, Sagana Vijayarajah, Khoi Vo, Matthew B. Wall, Wouter D. Weeda, Susanne Weis, David White, David Wisniewski, Alba Xifra‐Porxas, Emily A. Yearling, Sangsuk Yoon, Rui Yuan, Kenneth S.L. Yuen, Lei Zhang, Xu Zhang, Joshua Zosky, Thomas E. Nichols, Russell A. Poldrack, Tom Schönberg,

Mental Health Research Topics

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. 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 dataset2–5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed. The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.