Variability in the analysis of a single neuroimaging dataset by many teams
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 hypotheses 1...
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| Veröffentlicht in: | Nature (London) Jg. 582; H. 7810; S. 84 - 88 |
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| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
London
Nature Publishing Group UK
04.06.2020
Nature Publishing Group |
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| ISSN: | 0028-0836, 1476-4687, 1476-4687 |
| Online-Zugang: | Volltext |
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| Abstract | 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 hypotheses
1
. 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 dataset
2
–
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. |
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| AbstractList | 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 hypotheses.sup.1. 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 dataset.sup.2-5. 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. 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. 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 hypotheses.sup.1. 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 dataset.sup.2-5. 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. 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 hypotheses . 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 dataset . 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. 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.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. 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 ofthe 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 ofresearchers 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. 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 hypotheses(1). 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 dataset(2-5). 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. 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 hypotheses 1 . 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 dataset 2 – 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. 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 hypotheses(1). 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 dataset(2-5). 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. 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 hypotheses1. 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, a meta-analytic approach 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 dataset2-5. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors possibly 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. |
| Audience | Academic |
| Author | Dickie, Erin W. Sanz-Morales, Emilio Baczkowski, Blazej M. Green, Mikella A. Lintz, Evan N. Ray, Shruti Sokol-Hessner, Peter Huber, Juergen Pischedda, Doris Melero, Helena Schultz, Douglas H. Adcock, R. Alison Nichols, Thomas E. Beitner, Julia Kong, Xiang-Zhen Barilari, Marco Notter, Michael P. Poldrack, Russell A. Herholz, Peer Rodriguez-Thompson, Anais M. Guassi Moreira, João F. Galván, Adriana Eickhoff, Simon B. Bobadilla-Suarez, Sebastian Tompson, Steven H. Nilsonne, Gustav Verguts, Tom Glatard, Tristan Bakst, Leah Hu, Chuan-Peng Collignon, Olivier Fontanesi, Laura Brooks, Hayley R. Salo, Taylor Dukart, Juergen McGuire, Joseph T. Dreber, Anna Johnson, Matthew R. Hughes, Matthew E. Poline, Jean-Baptiste Harry, Bronson B. Holmes, Susan McDonald, Kelsey Glerean, Enrico Zosky, Joshua E. Meyer, Benjamin Berkers, Ruud M. W. J. Jahn, Andrew Shen, Qiang Camerer, Colin F. Bajracharya, Aahana Fricke, G. Matthew Yuan, Rui Romyn, Anthony Maumet, Camille Thirion, Bertrand Biswal, Bharat B. Kirchler, Michael Donnat, Claire L. Davis, Charles P. Gau, Remi J |
| AuthorAffiliation | 24 Max Planck Research Group: Adaptive Memory, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany 150 University of Pennsylvania, PA, USA 48 PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands 119 Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany 71 Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, Ontario, Canada 39 Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA 31 Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, UK 98 Department of PM&R, Rutgers New Jersey Medical School, Newark, NJ 5 HSS and CNS, California Institute of Technology, Pasadena CA, USA 61 Faculty of Psychology, University of Basel, Basel, Switzerland 96 Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands 114 Departamento de Psicobiologí |
| AuthorAffiliation_xml | – name: 25 Department of Psychology, Rutgers University-Newark, Newark, NJ, USA – name: 130 Henry H. Wheeler, Jr. Brain Imaging Center, Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA – name: 57 Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan – name: 137 Center for Social and Affective Neuroscience, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden – name: 13 Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany – name: 21 Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada – name: 121 Department of Bioengineering, McGill University, QC, Canada – name: 156 Centre for Human Psychopharmacology, Swinburne University, Hawthorn, VIC, Australia – name: 100 Faculty of Economics and Statistics, University of Innsbruck, Innsbruck, Austria – name: 139 Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Forschungszentrum Jülich, Jülich, Germany – name: 88 fMRI Laboratory, University of Michigan, Ann Arbor, MI, USA – name: 10 Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA – name: 23 Department of Psychology, Scene Grammar Lab, Goethe University, Frankfurt am Main, Germany – name: 40 Center for Mind and Brain Science, University of Trento, Trento, Italy – name: 66 Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, Canada – name: 150 University of Pennsylvania, PA, USA – name: 158 Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA – name: 43 Institute of Medical Psychology, Goethe University, Frankfurt am Main, Germany – name: 14 Department of Otolaryngology, Washington University in Saint Louis, Saint Louis, MO, USA – name: 55 Center for Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ, USA – name: 81 Leibniz-institut für Resilienzforschung (LIR), Mainz, Germany – name: 12 Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy – name: 37 Department of Psychology and Neuroscience, Duke University, Durham, NC, USA – name: 54 Department of Psychiatry, University of Toronto, Canada – name: 65 Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA – name: 5 HSS and CNS, California Institute of Technology, Pasadena CA, USA – name: 9 Center for Cognitive Neuroscience, Duke University, Durham, NC, USA – name: 62 Computer Science Department, University of New Mexico, Albuquerque, NM, USA – name: 53 Krembil Centre for Neuroinformatics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada – name: 76 McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), Faculty of Medicine, McGill University, Montreal, QC, Canada – name: 103 Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria – name: 126 Department of Vision & Cognition, Netherlands Institute for Neuroscience, Meibergdreef 47, 1105 BA, Amsterdam, The Netherlands – name: 27 School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China – name: 32 Department of Experimental Psychology, Ghent University, Ghent, Belgium – name: 143 Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden – name: 132 Scientific and Statistical Computing Core, National Institute of Mental Health, NIH, Bethesda, MD, USA – name: 122 Data Science and Sharing Team, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA – name: 116 Neuroimaging Center (NIC), Focus Program Translational Neurosciences (FTN), Johannes Gutenberg University Medical Center Mainz, Germany – name: 49 Section of Endocrinology & Investigative Medicine, Faculty of Medicine, Imperial College London, London, UK – name: 142 Department of Management and Engineering, Linköping University, Linköping, Sweden – name: 75 Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada – name: 56 Department of Statistics, Stanford University, Stanford, CA, USA – name: 114 Departamento de Psicobiología, División de Psicología, CES Cardenal Cisneros, Madrid, Spain – name: 146 Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA – name: 31 Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, UK – name: 90 School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC, Australia – name: 151 Department of Psychology and Neuroscience, Duke University, NC, USA – name: 20 School of Psychology, University of Plymouth, Plymouth, UK – name: 47 Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA – name: 91 Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada – name: 39 Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA – name: 34 Department of Psychology, University of Denver, Denver, CO, USA – name: 16 Center for Systems Neuroscience, Boston University, Boston, MA, USA – name: 79 Department of Psychology & Psychology Clinical Neuroscience Center, University of New Mexico, Albuquerque, NM, USA – name: 123 Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden – name: 138 Department of Economics and School of Neuroscience, Virginia Tech, Blacksburg, VA USA – name: 11 Neuroinformatics Laboratory, Fondazione Bruno Kessler, Trento, Italy – name: 18 School of Neuroscience, Virginia Tech, Blacksburg, VA, USA – name: 58 Brain and Consciousness Research Centre, TMU-ShuangHo Hospital, New Taipei City, Taiwan – name: 109 Haskins Laboratories, New Haven, CT, USA – name: 101 Department of Physics, Florida International University, Miami, Florida, USA – name: 124 Department of Psychology, Stockholm University, Stockholm, Sweden – name: 71 Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, Ontario, Canada – name: 131 Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA – name: 145 Department of Psychology, Stanford University, Stanford, CA, USA – name: 2 Faculty of Life Sciences, Department of Neurobiology, Tel Aviv University, Israel – name: 97 University of Iowa Carver College of Medicine, Department of Psychiatry, Iowa City, IA, USA – name: 15 Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA – name: 22 Department of Psychology, Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands – name: 99 Department of Psychology, University of Oregon, Eugene, OR, USA – name: 29 D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil – name: 148 US Combat Capabilities Development Command Army Research Laboratory, USA – name: 110 Biology Department, University of New Mexico, Albuquerque, NM, USA – name: 6 Department of Economics, Stockholm School of Economics, Stockholm, Sweden – name: 3 Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA – name: 35 Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Juelich, Juelich, Germany – name: 93 Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA – name: 136 Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden – name: 86 Department of Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, Eindhoven, The Netherlands – name: 113 Inria, Univ Rennes, CNRS, Inserm, IRISA UMR 6074, Empenn ERL U 1228, Rennes, France – name: 129 NeuroMI - Milan Center for Neuroscience, Milan, Italy – name: 48 PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands – name: 112 Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain – name: 102 Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria – name: 68 Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands – name: 46 Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA – name: 140 Inria, CEA, Université Paris-Saclay, France – name: 157 Department of Management and Marketing, School of Business, University of Dayton, Dayton, OH, USA – name: 159 Biomedical Engineering Department, University of Connecticut, Storrs, CT, USA – name: 117 Leibniz-Institut für Resilienzforschung (LIR), Mainz, Germany – name: 120 Technische Universität Dresden, Germany – name: 152 Center for Cognitive Neuroscience, Duke University, NC, USA – name: 87 Neuroscience Department, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany – name: 42 Department of Psychology, University of Toronto, Toronto, ON, Canada – name: 135 Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, USA – name: 82 The Department of Psychology and Neuroscience, Duke University, Durham, NC, USA – name: 119 Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany – name: 118 Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA – name: 104 U.S. CCDC Army Research Laboratory, Human Research and Engineering Directorate, Aberdeen Proving Ground, MD, USA – name: 107 Fralin Biomedical Research Institute, Roanoke, VA, USA |
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Wise Faculty of Life Sciences, Tel Aviv University, Department of Psychological and Brain Sciences, Dartmouth College – sequence: 2 givenname: Felix orcidid: 0000-0001-9606-0427 surname: Holzmeister fullname: Holzmeister, Felix organization: Department of Banking and Finance, University of Innsbruck – sequence: 3 givenname: Colin F. orcidid: 0000-0003-4049-1871 surname: Camerer fullname: Camerer, Colin F. organization: HSS and CNS, California Institute of Technology – sequence: 4 givenname: Anna orcidid: 0000-0003-3989-9941 surname: Dreber fullname: Dreber, Anna organization: Department of Economics, Stockholm School of Economics, Department of Economics, University of Innsbruck – sequence: 6 givenname: Magnus orcidid: 0000-0001-8759-6393 surname: Johannesson fullname: Johannesson, Magnus organization: Department of Economics, Stockholm School of Economics – sequence: 7 givenname: Michael orcidid: 0000-0002-5416-2545 surname: Kirchler fullname: Kirchler, Michael organization: Department of Banking and Finance, University of Innsbruck – sequence: 8 givenname: Roni surname: Iwanir fullname: Iwanir, Roni organization: Sagol School of Neuroscience, Tel Aviv University, Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University – sequence: 11 givenname: Paolo orcidid: 0000-0001-8943-8911 surname: Avesani fullname: Avesani, Paolo organization: Neuroinformatics Laboratory, Fondazione Bruno Kessler, Center for Mind/Brain Sciences - CIMeC, University of Trento – sequence: 12 givenname: Blazej M. orcidid: 0000-0001-9827-797X surname: Baczkowski fullname: Baczkowski, Blazej M. organization: Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences – sequence: 14 givenname: Leah orcidid: 0000-0003-2741-5532 surname: Bakst fullname: Bakst, Leah organization: Department of Psychological and Brain Sciences, Boston University, Center for Systems Neuroscience, Boston University – sequence: 15 givenname: Sheryl surname: Ball fullname: Ball, Sheryl organization: Department of Economics, Virginia Tech, School of Neuroscience, Virginia Tech – sequence: 17 givenname: Nadège orcidid: 0000-0001-8244-6062 surname: Bault fullname: Bault, Nadège organization: School of Psychology, University of Plymouth – sequence: 18 givenname: Derek orcidid: 0000-0001-6118-4366 surname: Beaton fullname: Beaton, Derek organization: Rotman Research Institute, Baycrest Health Sciences Centre – sequence: 21 givenname: Ruud M. W. J. orcidid: 0000-0002-0347-2375 surname: Berkers fullname: Berkers, Ruud M. W. J. organization: Max Planck Research Group: Adaptive Memory, Max Planck Institute for Human Cognitive and Brain Sciences – sequence: 23 givenname: Bharat B. surname: Biswal fullname: Biswal, Bharat B. organization: Department of Biomedical Engineering, New Jersey Institute of Technology, School of Life Science and Technology, University of Electronic Science and Technology of China – sequence: 25 givenname: Tiago orcidid: 0000-0003-2097-5537 surname: Bortolini fullname: Bortolini, Tiago organization: D’Or Institute for Research and Education (IDOR) – sequence: 27 givenname: Alexander orcidid: 0000-0002-5553-7249 surname: Bowring fullname: Bowring, Alexander organization: Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford – sequence: 28 givenname: Senne surname: Braem fullname: Braem, Senne organization: Department of Experimental Psychology, Ghent University, Department of Psychology, Vrije Universiteit Brussel – sequence: 29 givenname: Hayley R. orcidid: 0000-0001-5371-2624 surname: Brooks fullname: Brooks, Hayley R. organization: Department of Psychology, University of Denver – sequence: 30 givenname: Emily G. orcidid: 0000-0002-9981-3807 surname: Brudner fullname: Brudner, Emily G. organization: Department of Psychology, Rutgers University–Newark – sequence: 31 givenname: Cristian B. surname: Calderon fullname: Calderon, Cristian B. organization: Department of Experimental Psychology, Ghent University – sequence: 32 givenname: Julia A. surname: Camilleri fullname: Camilleri, Julia A. organization: Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf – sequence: 33 givenname: Jaime J. orcidid: 0000-0001-5834-7101 surname: Castrellon fullname: Castrellon, Jaime J. organization: Center for Cognitive Neuroscience, Duke University, Department of Psychology and Neuroscience, Duke University – sequence: 41 givenname: Kamalaker surname: Dadi fullname: Dadi, Kamalaker organization: Inria, CEA, Université Paris-Saclay – sequence: 42 givenname: Charles P. orcidid: 0000-0002-7293-2769 surname: Davis fullname: Davis, Charles P. organization: Department of Psychological Sciences, University of Connecticut, Brain Imaging Research Center, University of Connecticut, Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut – sequence: 43 givenname: Alberto De orcidid: 0000-0002-2553-7299 surname: Luca fullname: Luca, Alberto De organization: PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht – sequence: 44 givenname: Mauricio R. surname: Delgado fullname: Delgado, Mauricio R. organization: Department of Psychology, Rutgers University–Newark – sequence: 45 givenname: Lysia orcidid: 0000-0001-5249-0900 surname: Demetriou fullname: Demetriou, Lysia organization: Section of Endocrinology and Investigative Medicine, Faculty of Medicine, Imperial College London, Nuffield Department of Women’s and Reproductive Health, University of Oxford – sequence: 46 givenname: Jeffrey B. orcidid: 0000-0003-0557-3548 surname: Dennison fullname: Dennison, Jeffrey B. organization: Department of Psychology, Temple University – sequence: 48 givenname: Erin W. orcidid: 0000-0003-3028-9864 surname: Dickie fullname: Dickie, Erin W. organization: Krembil Centre for Neuroinformatics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto – sequence: 49 givenname: Ekaterina orcidid: 0000-0002-6005-2115 surname: Dobryakova fullname: Dobryakova, Ekaterina organization: Center for Traumatic Brain Injury Research, Kessler Foundation – sequence: 51 givenname: Juergen orcidid: 0000-0003-0492-5644 surname: Dukart fullname: Dukart, Juergen organization: Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf – sequence: 52 givenname: Niall W. orcidid: 0000-0002-3225-9119 surname: Duncan fullname: Duncan, Niall W. organization: Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Brain and Consciousness Research Centre, TMU-ShuangHo Hospital – sequence: 58 givenname: G. Matthew orcidid: 0000-0002-4466-8649 surname: Fricke fullname: Fricke, G. Matthew organization: Computer Science Department, University of New Mexico – sequence: 59 givenname: Shiguang orcidid: 0000-0002-1313-0176 surname: Fu fullname: Fu, Shiguang organization: School of Management, Zhejiang University of Technology, Institute of Neuromanagement, Zhejiang University of Technology – sequence: 62 givenname: Sarah orcidid: 0000-0002-7087-7882 surname: Genon fullname: Genon, Sarah organization: Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf – sequence: 63 givenname: Tristan orcidid: 0000-0003-2620-5883 surname: Glatard fullname: Glatard, Tristan organization: Department of Computer Science and Software Engineering, Concordia University – sequence: 66 givenname: Sergej A. E. surname: Golowin fullname: Golowin, Sergej A. E. organization: Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University – sequence: 68 givenname: Krzysztof J. orcidid: 0000-0003-3321-7583 surname: Gorgolewski fullname: Gorgolewski, Krzysztof J. organization: Department of Psychology, Stanford University – sequence: 71 givenname: João F. orcidid: 0000-0001-8312-4487 surname: Guassi Moreira fullname: Guassi Moreira, João F. organization: Department of Psychology, University of California Los Angeles – sequence: 77 givenname: Bronson B. orcidid: 0000-0003-0389-0945 surname: Harry fullname: Harry, Bronson B. organization: The MARCS Institute for Brain, Behaviour and Development, Western Sydney University – sequence: 79 givenname: Peer orcidid: 0000-0002-9840-6257 surname: Herholz fullname: Herholz, Peer organization: McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), Faculty of Medicine, McGill University – sequence: 80 givenname: Gabrielle orcidid: 0000-0003-4695-5251 surname: Herman fullname: Herman, Gabrielle organization: Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health – sequence: 82 givenname: Felix surname: Hoffstaedter fullname: Hoffstaedter, Felix organization: Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf – sequence: 86 givenname: Scott A. orcidid: 0000-0002-5092-4936 surname: Huettel fullname: Huettel, Scott A. organization: Department of Psychology and Neuroscience, Duke University – sequence: 87 givenname: Matthew E. orcidid: 0000-0001-5057-5556 surname: Hughes fullname: Hughes, Matthew E. organization: School of Health Sciences, Swinburne University of Technology – sequence: 89 givenname: Alexandru D. orcidid: 0000-0002-1391-785X surname: Iordan fullname: Iordan, Alexandru D. organization: Department of Psychology, University of Michigan – sequence: 90 givenname: Peder M. orcidid: 0000-0002-6922-3590 surname: Isager fullname: Isager, Peder M. organization: Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology – sequence: 91 givenname: Ayse I. orcidid: 0000-0002-1652-9297 surname: Isik fullname: Isik, Ayse I. organization: Department of Neuroscience, Max Planck Institute for Empirical Aesthetics – sequence: 95 givenname: Michael J. E. orcidid: 0000-0002-0068-230X surname: Joseph fullname: Joseph, Michael J. E. organization: Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health – sequence: 96 givenname: Anthony C. orcidid: 0000-0001-7433-6891 surname: Juliano fullname: Juliano, Anthony C. organization: Center for Neuropsychology and Neuroscience Research, Kessler Foundation – sequence: 98 givenname: Michalis orcidid: 0000-0003-4312-4401 surname: Kassinopoulos fullname: Kassinopoulos, Michalis organization: Graduate Program in Biological and Biomedical Engineering, McGill University – sequence: 99 givenname: Cemal orcidid: 0000-0001-7097-1441 surname: Koba fullname: Koba, Cemal organization: MoMiLab Research Unit, IMT School for Advanced Studies Lucca – sequence: 101 givenname: Timothy R. orcidid: 0000-0002-2551-8127 surname: Koscik fullname: Koscik, Timothy R. organization: Department of Psychiatry, University of Iowa Carver College of Medicine – sequence: 103 givenname: Brice A. orcidid: 0000-0001-5229-5400 surname: Kuhl fullname: Kuhl, Brice A. organization: Department of Psychology, University of Oregon – sequence: 108 givenname: Nina surname: Lauharatanahirun fullname: Lauharatanahirun, Nina organization: US CCDC Army Research Laboratory, Human Research and Engineering Directorate, Annenberg School for Communication, University of Pennsylvania – sequence: 109 givenname: Hongmi orcidid: 0000-0001-8023-0727 surname: Lee fullname: Lee, Hongmi organization: Department of Psychological and Brain Sciences, Johns Hopkins University – sequence: 111 givenname: Alexander orcidid: 0000-0002-9306-6126 surname: Leemans fullname: Leemans, Alexander organization: PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht – sequence: 115 givenname: Monica Y. C. orcidid: 0000-0003-1775-4434 surname: Li fullname: Li, Monica Y. C. organization: Department of Psychological Sciences, University of Connecticut, Brain Imaging Research Center, University of Connecticut, Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Haskins Laboratories – sequence: 118 givenname: Schuyler W. orcidid: 0000-0001-8370-8722 surname: Liphardt fullname: Liphardt, Schuyler W. organization: Biology Department, University of New Mexico – sequence: 119 givenname: Annabel B. orcidid: 0000-0001-5631-0233 surname: Losecaat Vermeer fullname: Losecaat Vermeer, Annabel B. organization: Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna – sequence: 121 givenname: Michael L. orcidid: 0000-0001-5155-7413 surname: Mack fullname: Mack, Michael L. organization: Department of Psychology, University of Toronto – sequence: 122 givenname: Norberto orcidid: 0000-0003-4618-7459 surname: Malpica fullname: Malpica, Norberto organization: Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos – sequence: 127 givenname: Helena orcidid: 0000-0002-5373-6711 surname: Melero fullname: Melero, Helena organization: Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Departamento de Psicobiología, División de Psicología, CES Cardenal Cisneros, Northeastern University Biomedical Imaging Center, Northeastern University – sequence: 129 givenname: Benjamin surname: Meyer fullname: Meyer, Benjamin organization: Leibniz-Institut für Resilienzforschung (LIR), Neuroimaging Center (NIC), Focus Program Translational Neurosciences (FTN), Johannes Gutenberg University Medical Center Mainz – sequence: 130 givenname: Kristin N. orcidid: 0000-0003-0190-7678 surname: Meyer fullname: Meyer, Kristin N. organization: Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill – sequence: 131 givenname: Glad orcidid: 0000-0001-5715-6442 surname: Mihai fullname: Mihai, Glad organization: Max Planck Research Group: Neural Mechanisms of Human Communication, Max Planck Institute for Human Cognitive and Brain Sciences, Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität Dresden – sequence: 135 givenname: Gustav orcidid: 0000-0001-5273-0150 surname: Nilsonne fullname: Nilsonne, Gustav organization: Department of Clinical Neuroscience, Karolinska Institutet, Department of Psychology, Stockholm University – sequence: 136 givenname: Michael P. orcidid: 0000-0002-5866-047X surname: Notter fullname: Notter, Michael P. organization: The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology, University Hospital Center and University of Lausanne – sequence: 138 givenname: Adrian I. orcidid: 0000-0002-5953-8548 surname: Onicas fullname: Onicas, Adrian I. organization: MoMiLab Research Unit, IMT School for Advanced Studies Lucca – sequence: 139 givenname: Paolo orcidid: 0000-0002-6249-841X surname: Papale fullname: Papale, Paolo organization: MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Department of Vision and Cognition, Netherlands Institute for Neuroscience – sequence: 142 givenname: Alexandre orcidid: 0000-0003-0556-0763 surname: Pérez fullname: Pérez, Alexandre organization: McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), Faculty of Medicine, McGill University – sequence: 143 givenname: Doris orcidid: 0000-0003-4694-2493 surname: Pischedda fullname: Pischedda, Doris organization: Bernstein Center for Computational Neuroscience and Berlin Center for Advanced Neuroimaging and Clinic for Neurology, Charité Universitätsmedizin, corporate member of Freie Universität Berlin, Humboldt Universität zu Berlin, and Berlin Institute of Health, Cluster of Excellence Science of Intelligence, Technische Universität Berlin and Humboldt Universität zu Berlin, NeuroMI - Milan Center for Neuroscience – sequence: 148 givenname: Richard C. orcidid: 0000-0002-7267-5563 surname: Reynolds fullname: Reynolds, Richard C. organization: Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health – sequence: 149 givenname: Emiliano orcidid: 0000-0002-7178-9534 surname: Ricciardi fullname: Ricciardi, Emiliano organization: MoMiLab Research Unit, IMT School for Advanced Studies Lucca – sequence: 150 givenname: Jenny R. orcidid: 0000-0002-3242-6407 surname: Rieck fullname: Rieck, Jenny R. organization: Rotman Research Institute, Baycrest Health Sciences Centre – sequence: 156 givenname: Margaret L. orcidid: 0000-0002-5433-8870 surname: Schlichting fullname: Schlichting, Margaret L. organization: Department of Psychology, University of Toronto – sequence: 159 givenname: Margaret A. surname: Sheridan fullname: Sheridan, Margaret A. organization: Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill – sequence: 161 givenname: Kenny orcidid: 0000-0003-1894-3595 surname: Skagerlund fullname: Skagerlund, Kenny organization: Department of Behavioural Sciences and Learning, Linköping University, Center for Social and Affective Neuroscience, Department of Clinical and Experimental Medicine, Linköping University – sequence: 162 givenname: Alec orcidid: 0000-0002-1938-4660 surname: Smith fullname: Smith, Alec organization: Department of Economics, Virginia Tech, School of Neuroscience, Virginia Tech – sequence: 164 givenname: Peter orcidid: 0000-0003-0895-5576 surname: Sokol-Hessner fullname: Sokol-Hessner, Peter organization: Department of Psychology, University of Denver – sequence: 166 givenname: Sarah M. orcidid: 0000-0002-0946-6662 surname: Tashjian fullname: Tashjian, Sarah M. organization: Department of Psychology, University of California Los Angeles – sequence: 170 givenname: Loreen orcidid: 0000-0001-6303-6148 surname: Tisdall fullname: Tisdall, Loreen organization: Department of Psychology, Stanford University, Center for Cognitive and Decision Sciences, University of Basel – sequence: 174 givenname: Leonardo orcidid: 0000-0002-9429-6476 surname: Tozzi fullname: Tozzi, Leonardo organization: Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine – sequence: 176 givenname: Luca orcidid: 0000-0003-1096-2150 surname: Turella fullname: Turella, Luca organization: Center for Mind/Brain Sciences - CIMeC, University of Trento – sequence: 180 givenname: Sagana surname: Vijayarajah fullname: Vijayarajah, Sagana organization: Department of Psychology, University of Toronto – sequence: 183 givenname: Wouter D. orcidid: 0000-0001-8619-2645 surname: Weeda fullname: Weeda, Wouter D. organization: Methodology and Statistics Unit, Institute of Psychology, Leiden University – sequence: 185 givenname: David J. orcidid: 0000-0001-8694-1474 surname: White fullname: White, David J. organization: Centre for Human Psychopharmacology, Swinburne University – sequence: 186 givenname: David orcidid: 0000-0003-4793-1171 surname: Wisniewski fullname: Wisniewski, David organization: Department of Experimental Psychology, Ghent University – sequence: 187 givenname: Alba orcidid: 0000-0002-9023-2432 surname: Xifra-Porxas fullname: Xifra-Porxas, Alba organization: Graduate Program in Biological and Biomedical Engineering, McGill University – sequence: 188 givenname: Emily A. surname: Yearling fullname: Yearling, Emily A. organization: Department of Psychological Sciences, University of Connecticut, Brain Imaging Research Center, University of Connecticut, Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut – sequence: 189 givenname: Sangsuk orcidid: 0000-0002-3399-1096 surname: Yoon fullname: Yoon, Sangsuk organization: Department of Management and Marketing, School of Business, University of Dayton – sequence: 190 givenname: Rui orcidid: 0000-0003-4800-3895 surname: Yuan fullname: Yuan, Rui organization: Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine – sequence: 191 givenname: Kenneth S. L. orcidid: 0000-0002-9465-9070 surname: Yuen fullname: Yuen, Kenneth S. L. organization: Leibniz-Institut für Resilienzforschung (LIR), Neuroimaging Center (NIC), Focus Program Translational Neurosciences (FTN), Johannes Gutenberg University Medical Center Mainz – sequence: 192 givenname: Lei orcidid: 0000-0002-9586-595X surname: Zhang fullname: Zhang, Lei organization: Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna – sequence: 193 givenname: Xu orcidid: 0000-0003-1988-7767 surname: Zhang fullname: Zhang, Xu organization: Brain Imaging Research Center, University of Connecticut, Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Biomedical Engineering Department, University of Connecticut – sequence: 194 givenname: Joshua E. orcidid: 0000-0002-1962-3633 surname: Zosky fullname: Zosky, Joshua E. organization: Department of Psychology, University of Nebraska–Lincoln, Center for Brain, Biology and Behavior, University of Nebraska–Lincoln – sequence: 195 givenname: Thomas E. orcidid: 0000-0002-4516-5103 surname: Nichols fullname: Nichols, Thomas E. email: thomas.nichols@bdi.ox.ac.uk organization: Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford – sequence: 196 givenname: Russell A. orcidid: 0000-0001-6755-0259 surname: Poldrack fullname: Poldrack, Russell A. email: poldrack@stanford.edu organization: Department of Psychology, Stanford University – sequence: 197 givenname: Tom orcidid: 0000-0002-4485-816X surname: Schonberg fullname: Schonberg, Tom email: schonberg@tauex.tau.ac.il organization: Sagol School of Neuroscience, Tel Aviv University, Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32483374$$D View this record in MEDLINE/PubMed https://inserm.hal.science/inserm-02914443$$DView record in HAL https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166165$$DView record from Swedish Publication Index (Linköpings universitet) https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-182960$$DView record from Swedish Publication Index (Stockholms universitet) https://research.hhs.se/esploro/outputs/journalArticle/Variability-in-the-analysis-of-a/991001489297706056$$DView record from Swedish Publication Index http://kipublications.ki.se/Default.aspx?queryparsed=id:143718314$$DView record from Swedish Publication Index (Karolinska Institutet) |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 PMCID: PMC7771346 scopus-id:2-s2.0-85085279867 Author contributions NARPS management team: R. Botvinik-Nezer, F. Holzmeister, C.F. Camerer, A. Dreber, J. Huber, M. Johannesson, M. Kirchler, R.A. Poldrack and T. Schonberg.fMRI dataset- experiment design: R. Iwanir, J. Durnez, R.A. Poldrack and T. Schonberg.fMRI dataset- data collection: R. Iwanir and T. Schonberg.fMRI dataset- preprocessing, quality assurance and data sharing: R. Botvinik-Nezer, K. Gorgolewski, R.A. Poldrack and T. Schonberg.Analysis teams- recruitment, point of contact and management: R. Botvinik-Nezer, R.A. Poldrack and T. Schonberg.Analysis teams- analysis of the submitted results and statistical maps: R.A. Poldrack, T.E. Nichols, J.A. Mumford, J-.B. Poline, A. Perez, R. Botvinik-Nezer, and T. Schonberg.Code review: T. Glatard. and K. Dadi.Prediction markets- design and management: F. Holzmeister, C.F. Camerer, A. Dreber, J. Huber, M. Johannesson and M. KirchlerPrediction markets- analysis: F. Holzmeister, R. Botvinik-Nezer, C.F. Camerer, A. Dreber, J. Huber, M. Johannesson, M. Kirchler, S. Kupek, R.A. Poldrack and T. Schonberg.Writing the manuscript: R. Botvinik-Nezer, F. Holzmeister, A. Dreber, J. Huber, M. Johannesson, M. Kirchler, T.E. Nichols, R.A. Poldrack and T. Schonberg.Participated as members of analysis teams and reviewed and edited the manuscript: R.A. Adcock, P. Avesani, B.M. Baczkowski, A. Bajracharya, L. Bakst, S. Ball, M. Barilari, N. Bault, D. Beaton, J. Beitner, R.G. Benoit, R.M.W.J. Berkers, J.P. Bhanji, B.B. Biswal, S. Bobadilla-Suarez, T. Bortolini, K.L. Bottenhorn, A. Bowring, S. Braem, H.R. Brooks, E.G. Brudner, C.B. Calderon, J.A. Camilleri, J.J. Castrellon, L. Cecchetti, E.C. Cieslik, Z.J. Cole, O. Collignon, R.W. Cox, W.A. Cunningham, S. Czoschke, K. Dadi, C.P. Davis, A. De Luca, M.R. Delgado, L. Demetriou, J.B. Dennison, X. Di, E.W. Dickie, E. Dobryakova, C.L. Donnat, J. Dukart, N.W. Duncan, A. Eed, S.B. Eickhoff, A. Erhart, L. Fontanesi, G.M. Fricke, S. Fu, A. Galván, R.i Gau, S. Genon, E. Glerean, J.J. Goeman, S.A.E. Golowin, C. González-García, K. J. Gorgolewski, C.L. Grady, M.A. Green, J.F. Guassi Moreira, O. Guest, S. Hakimi, J.P. Hamilton, R. Hancock, G. Handjaras, B.B. Harry, C. Hawco, P. Herholz, G. Herman, S. Heunis, F. Hoffstaedter, J. Hogeveen, S. Holmes, C.-P. Hu, S.A. Huettel, M.E. Hughes, V. Iacovella, A.D. Iordan, P.M. Isager, A.I. Isik, A. Jahn, M.R. Johnson, T. Johnstone, M.J.E. Joseph, A.C. Juliano, J.W. Kable, M. Kassinopoulos, C. Koba, X.-Z. Kong, T.R. Koscik, N.E. Kucukboyaci, B.A. Kuhl, A.R. Laird, C. Lamm, R. Langner, N. Lauharatanahirun, H. Lee, S. Lee, A. Leemans, A. Leo, E. Lesage, F. Li, M.Y.C. Li, P. Cheng Lim, E.N. Lintz, S.W. Liphardt, A.B. Losecaat Vermeer, B.C. Love, M.L. Mack, N. Malpica, T. Marins, C. Maumet, K. McDonald, J.T. McGuire, H. Melero, A.S. Méndez Leal, B. Meyer, K.N. Meyer, G. Mihai, G.D. Mitsis, J. Moll, D.M. Nielson, G. Nilsonne, M.P. Notter, E. Olivetti, A.I. Onicas, P. Papale, K.R. Patil, J.E. Peelle, D. Pischedda, Y. Prystauka, S. Ray, P.A. Reuter-Lorenz, R. C Reynolds, E. Ricciardi, J.R. Rieck, A.M. Rodriguez-Thompson , A. Romyn, T. Salo, G.R. Samanez-Larkin, E. Sanz-Morales, M.L. Schlichting, D.H. Schultz, Q. Shen, M.A. Sheridan, J.A. Silvers, K. Skagerlund, A. Smith, D.V. Smith, P. Sokol-Hessner, S.R. Steinkamp, S.M. Tashjian, B. Thirion, J.N. Thorp, G. Tinghög, L. Tisdall, S.H. Tompson, C. Toro-Serey, J.J. Torre Tresols, L. Tozzi, V. Truong, L. Turella, A.E. van 't Veer, T. Verguts, J.M. Vettel, S. Vijayarajah, K. Vo, M.B. Wall, W.D. Weeda, S. Weis, D.J. White, D. Wisniewski, A. Xifra-Porxas, E.A. Yearling, S. Yoon, R. Yuan, K.S.L. Yuen, L. Zhang, X. Zhang, J.E. Zosky |
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| OpenAccessLink | https://research.hhs.se/esploro/outputs/journalArticle/Variability-in-the-analysis-of-a/991001489297706056 |
| PMID | 32483374 |
| PQID | 2411176251 |
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| PublicationDate | 2020-06-04 |
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| PublicationPlace | London |
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| PublicationSubtitle | International weekly journal of science |
| PublicationTitle | Nature (London) |
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| PublicationYear | 2020 |
| Publisher | Nature Publishing Group UK Nature Publishing Group |
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| Snippet | Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results... Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional... |
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| SubjectTerms | 59/36 59/57 631/378/2649/1409 631/477/2811 706/648 706/689/2788 Brain - diagnostic imaging Brain - physiology Brain mapping Brain research Cognitive science Correlation analysis Data Analysis Data Science - methods Data Science - standards Datasets Datasets as Topic - statistics & numerical data Electronic data processing Female Flexibility Functional magnetic resonance imaging Functional Neuroimaging Humanities and Social Sciences Humans Image processing Logistic Models Magnetic resonance Magnetic Resonance Imaging Male Mathematical analysis Medical imaging Meta-Analysis as Topic Methods Models, Neurological multidisciplinary Neuroimaging Neuroscience Neurosciences & behavior Neurosciences & comportement Prediction markets Psychology psykologi Reproducibility of Results Research Personnel - organization & administration Research Personnel - standards Researchers Science Science (multidisciplinary) Sciences sociales & comportementales, psychologie Social & behavioral sciences, psychology Software Software packages Teams Technology application Variability |
| Title | Variability in the analysis of a single neuroimaging dataset by many teams |
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