Making big data open: data sharing in neuroimaging

In the last decade, major advances have been made in the availability of shared neuroimaging data, such that there are more than 8,000 shared MRI (magnetic resonance imaging) data sets available online. Here we outline the state of data sharing for task-based functional MRI (fMRI) data, with a focus on various forms of data and their relative utility for subsequent analyses. We also discuss challenges to the future success of data sharing and highlight the ethical argument that data sharing may be necessary to maximize the contribution of human subjects.

[1]  P. Meehl Theory-Testing in Psychology and Physics: A Methodological Paradox , 1967, Philosophy of Science.

[2]  M. Posner,et al.  Localization of cognitive operations in the human brain. , 1988, Science.

[3]  E. Marshall Bermuda Rules: Community Spirit, With Teeth , 2001, Science.

[4]  J B Woodward,et al.  The Functional Magnetic Resonance Imaging Data Center (fMRIDC): the challenges and rewards of large-scale databasing of neuroimaging studies. , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[5]  Dan Lloyd,et al.  Functional MRI and the Study of Human Consciousness , 2002, Journal of Cognitive Neuroscience.

[6]  Arthur W Toga,et al.  The LONI Pipeline Processing Environment , 2003, NeuroImage.

[7]  Steve R. Gunn,et al.  Result Analysis of the NIPS 2003 Feature Selection Challenge , 2004, NIPS.

[8]  Angela R. Laird,et al.  BrainMap , 2007, Neuroinformatics.

[9]  Daniel S. Marcus,et al.  The extensible neuroimaging archive toolkit , 2007, Neuroinformatics.

[10]  Timothy R. Olsen,et al.  The Extensible Neuroimaging Archive Toolkit: an informatics platform for managing, exploring, and sharing neuroimaging data. , 2007, Neuroinformatics.

[11]  J. Ioannidis Why Most Discovered True Associations Are Inflated , 2008, Epidemiology.

[12]  Perry L. Miller,et al.  The NIF LinkOut Broker: A Web Resource to Facilitate Federated Data Integration using NCBI Identifiers , 2008, Neuroinformatics.

[13]  Hans-Michael Müller,et al.  The Neuroscience Information Framework: A Data and Knowledge Environment for Neuroscience , 2008, Neuroinformatics.

[14]  Arthur W. Toga,et al.  Provenance in neuroimaging , 2008, NeuroImage.

[15]  J. Brooks Why most published research findings are false: Ioannidis JP, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece , 2008 .

[16]  W. K. Simmons,et al.  Circular analysis in systems neuroscience: the dangers of double dipping , 2009, Nature Neuroscience.

[17]  Arthur W. Toga,et al.  Is it time to re-prioritize neuroimaging databases and digital repositories? , 2009, NeuroImage.

[18]  Stephen M. Smith,et al.  Meta-analysis of neuroimaging data: A comparison of image-based and coordinate-based pooling of studies , 2009, NeuroImage.

[19]  Stephen José Hanson,et al.  Decoding the Large-Scale Structure of Brain Function by Classifying Mental States Across Individuals , 2009, Psychological science.

[20]  H. Pashler,et al.  Puzzlingly High Correlations in fMRI Studies of Emotion, Personality, and Social Cognition 1 , 2009, Perspectives on psychological science : a journal of the Association for Psychological Science.

[21]  Russell A Poldrack,et al.  Science Perspectives on Psychological Mapping Mental Function to Brain Structure: How Can Cognitive Neuroimaging Succeed? on Behalf Of: Association for Psychological Science , 2022 .

[22]  Jonathan A. Eisen,et al.  BioTorrents: A File Sharing Service for Scientific Data , 2010, PloS one.

[23]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[24]  Thomas E. Nichols,et al.  Everything You Never Wanted to Know about Circular Analysis, but Were Afraid to Ask , 2010, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[25]  D. Stott Parker,et al.  Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline , 2010, PloS one.

[26]  Tobias Kober,et al.  MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field , 2010, NeuroImage.

[27]  N. Volkow,et al.  Functional connectivity density mapping , 2010, Proceedings of the National Academy of Sciences.

[28]  Olaf Sporns,et al.  Weight-conserving characterization of complex functional brain networks , 2011, NeuroImage.

[29]  Russell A. Poldrack,et al.  Large-scale automated synthesis of human functional neuroimaging data , 2011, Nature Methods.

[30]  David B. Keator,et al.  XCEDE: An Extensible Schema for Biomedical Data , 2011, Neuroinformatics.

[31]  Jessica A. Turner,et al.  The Cognitive Paradigm Ontology: Design and Application , 2011, Neuroinformatics.

[32]  Leif D. Nelson,et al.  False-Positive Psychology , 2011, Psychological science.

[33]  Satrajit S. Ghosh,et al.  Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python , 2011, Front. Neuroinform..

[34]  Jessica A. Turner,et al.  COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets , 2011, Front. Neuroinform..

[35]  Aniket Kittur,et al.  The Cognitive Atlas: Toward a Knowledge Foundation for Cognitive Neuroscience , 2011, Front. Neuroinform..

[36]  Joshua Carp,et al.  On the Plurality of (Methodological) Worlds: Estimating the Analytic Flexibility of fMRI Experiments , 2012, Front. Neurosci..

[37]  Alan C. Evans,et al.  LORIS: a web-based data management system for multi-center studies , 2012, Front. Neuroinform..

[38]  Alan C. Evans,et al.  The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for scientific workflows , 2012, Front. Neuroinform..

[39]  O. Sporns,et al.  Network centrality in the human functional connectome. , 2012, Cerebral cortex.

[40]  Michael W. Weiner,et al.  The ADNI Publication Policy: Commensurate recognition of critical contributors who are not authors , 2012, NeuroImage.

[41]  Richard D. Hoge,et al.  Calibrated fMRI , 2012, NeuroImage.

[42]  Russell A. Poldrack,et al.  Discovering Relations Between Mind, Brain, and Mental Disorders Using Topic Mapping , 2012, PLoS Comput. Biol..

[43]  Carlos H. Acuña The ADHD-200 Consortium: a model to advance the translational potential of neuroimaging in clinical neuroscience , 2012 .

[44]  Torsten Rohlfing,et al.  Why shared data should not be acknowledged on the author byline , 2012, NeuroImage.

[45]  Claudine Joëlle Gauthier,et al.  Absolute quantification of resting oxygen metabolism and metabolic reactivity during functional activation using QUO2 MRI , 2012, NeuroImage.

[46]  Satrajit S. Ghosh,et al.  Data sharing in neuroimaging research , 2012, Front. Neuroinform..

[47]  Oluwasanmi Koyejo,et al.  Toward open sharing of task-based fMRI data: the OpenfMRI project , 2013, Front. Neuroinform..

[48]  Abraham Z. Snyder,et al.  Human Connectome Project informatics: Quality control, database services, and data visualization , 2013, NeuroImage.

[49]  Bharat B. Biswal,et al.  Making data sharing work: The FCP/INDI experience , 2013, NeuroImage.

[50]  David B. Keator,et al.  Towards structured sharing of raw and derived neuroimaging data across existing resources , 2012, NeuroImage.

[51]  Jeffrey S. Anderson,et al.  BOLD Granger Causality Reflects Vascular Anatomy , 2013, PloS one.

[52]  Essa Yacoub,et al.  The WU-Minn Human Connectome Project: An overview , 2013, NeuroImage.

[53]  Gaël Varoquaux,et al.  Mapping paradigm ontologies to and from the brain , 2013, NIPS.

[54]  Russell A. Poldrack,et al.  The ethics of secondary data analysis: Considering the application of Belmont principles to the sharing of neuroimaging data , 2013, NeuroImage.

[55]  Michael S. Gazzaniga,et al.  Why share data? Lessons learned from the fMRIDC , 2013, NeuroImage.

[56]  James E. Monogan A Case for Registering Studies of Political Outcomes: An Application in the 2010 House Elections , 2013, Political Analysis.

[57]  J. Ioannidis,et al.  Potential Reporting Bias in fMRI Studies of the Brain , 2013, PloS one.

[58]  Yufeng Zang,et al.  Standardizing the intrinsic brain: Towards robust measurement of inter-individual variation in 1000 functional connectomes , 2013, NeuroImage.

[59]  Brian A. Nosek,et al.  Power failure: why small sample size undermines the reliability of neuroscience , 2013, Nature Reviews Neuroscience.

[60]  Amos Storkey,et al.  A test-retest fMRI dataset for motor, language and spatial attention functions , 2013, GigaScience.

[61]  Krzysztof J. Gorgolewski,et al.  Making Data Sharing Count: A Publication-Based Solution , 2012, Front. Neurosci..

[62]  Neda Jahanshad,et al.  Whole-genome analyses of whole-brain data: working within an expanded search space , 2014, Nature Neuroscience.

[63]  Oliver Speck,et al.  A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie , 2014, Scientific Data.

[64]  Link,et al.  Willingness to share research data is related to the strength of the evidence and the quality of reporting of statistical results , 2014 .

[65]  Leonardo L. Gollo,et al.  Time-resolved resting-state brain networks , 2014, Proceedings of the National Academy of Sciences.

[66]  B. T. Thomas Yeo,et al.  Estimates of segregation and overlap of functional connectivity networks in the human cerebral cortex , 2014, NeuroImage.

[67]  J. Ioannidis Why Most Published Research Findings Are False , 2019, CHANCE.