Toward open sharing of task-based fMRI data: the OpenfMRI project

By Russell A. Poldrack, Deanna M. Barch, Jason P. Mitchell, Tor D. Wager, Anthony D. Wagner, Joseph T. Devlin, Chad Cumba, Oluwasanmi Koyejo, Michael P. Milham. Front. Neuroinform., 2013

361 citations recorded by the source corpus.

The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper describes the OpenFMRI project (accessible online at http://www.openfmri.org), which aims to provide the neuroimaging community with a resource to support open sharing of task-based fMRI studies. We describe the motivation behind the project, focusing particularly on how this project addresses some of the well-known challenges to sharing of task-based fMRI data. Results from a preliminary analysis of the current database are presented, which demonstrate the ability to classify between task contrasts with high generalization accuracy across subjects, and the ability to identify individual subjects from their activation maps with moderately high accuracy. Clustering analyses show that the similarity relations between statistical maps have a somewhat orderly relation to the mental functions engaged by the relevant tasks. These results highlight the potential of the project to support large-scale multivariate analyses of the relation between mental processes and brain function.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/04776d1dd4252e7588186684a6c961443da34e2c

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In Cognitive Neuroscience

Citations in the corpus

Precision functional mapping of individual human brains (2017, neutral): “The completeMSC dataset is freely available from openfmri.org (Poldrack et al., 2013) and neurovault.org (Gorgolewski et al., 2015) as a resource for neuroscientists.”
Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates (2015, positive): “We also thank Russ Poldrack and his colleagues for starting the OpenfMRI Project (supported by National Science Foundation Grant OCI-1131441) and all of the researchers who have shared their task-based data.”
MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites (2016, methodology): “A second potential application is the use of automated QC predictions as data descriptors to support the recently born “data papers” track of many journals and public databases like OpenfMRI [46].”
Interpretable LSTMs For Whole-Brain Neuroimaging Analyses (2018, neutral): “Neuroimaging research has recently started collecting large corpora of experimental data, often comprising many hundred individuals [1, 2].”
Making big data open: data sharing in neuroimaging (2014, methodology): “For example, previous work has shown that cognitive processes can be effectively decoded across individuals using fMRI data collected on different MRI scanners using very different parameters by using statistical maps as the decoding basis 37 .”
Cross‐validation failure: Small sample sizes lead to large error bars (2017, background): “Platforms to share neuroimaging data are rapidly growing, as with OpenfMRI (Poldrack et al., 2013) that now hosts 63 studies comprising 2200 subjects, or Neurovault (Gorgolewski et al.”
Scientific Utopia: II. Restructuring Incentives and Practices to Promote Truth Over Publishability (2012, methodology): “, 2011; Stock & Kulhavy, 1989), increased ability to aggregate data across multiple investigations for improved confidence in research findings (Hrynaszkiewicz, 2010; Rothstein, Sutton, & Borenstein, 2006; Yarkoni, Poldrack, Van Essen, & Wager, 2010), the opportunity for novel methodologies and insi”
Comparing spatial null models for brain maps (2021, neutral): “…advances in imaging, tracing, and recording technologies ( Insel et al., 2013 ), together with global data sharing initiatives ( Casey et al., 2018; Poldrack et al., 2013; Sudlow et al., 2015; Van Essen et al., 2013 ), have resulted in the generation of high-resolution maps of many of these…”
Analyzing Neuroimaging Data Through Recurrent Deep Learning Models (2018, neutral): “Neuroimaging research has recently started collecting large corpora of experimental functional Magnetic Resonance Imaging (fMRI) data, often comprising many hundred individuals [Van Essen et al., 2013, Poldrack et al., 2013].”
The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments (2016, methodology): “Despite its relatively young age BIDS has been already adopted by the OpenfMRI repository 16 .”
Teaching Computational Reproducibility for Neuroimaging (2018, background): “All teams chose a paper and accompanying dataset from OpenFMRI,19 a publicly-available depository of MRI and EEG datasets (Poldrack et al., 2013; Poldrack and Gorgolewski, 2015).”
Assessing and tuning brain decoders: Cross‐validation, caveats, and guidelines (2016, methodology): “We also use a nonpublished dataset, ds009 from openfMRI (Poldrack et al., 2013).”
From brain maps to cognitive ontologies: informatics and the search for mental structure (2015, methodology): “F or p er so na l u se o nl y. PS67CH24-Poldrack ARI 13 November 2015 20:41 Model; http://www.nidm.nidash.org/); creating reproducible, shareable, open-source analysis pipelines (e.g., the Nipype framework; Gorgolewski et al. 2011); and the establishment of open resources for the sharing of both raw”
Single Subject Prediction of Brain Disorders in Neuroimaging: Promises and Pitfalls (2016, background): “The field is currently in the state of establishing central repositories of anonymized raw data (Bockholt et al., 2009; Buccigrossi et al., 2007; Di Martino et al., 2014; Jack et al., 2008; Keator et al., 2008; Landis et al., 2016; Marcus et al., 2007; Poldrack et al., 2013; Scott et al., 2011; Turn”
The BRAIN Initiative data-sharing ecosystem: Characteristics, challenges, benefits, and opportunities (2024, unknown): “Devel-oped initially out of the OpenfMRI archive, OpenNeuro is part of a long line of efforts—which reach back at least to the establishment of the fMRI Data Center in 1999—to support data sharing in neuro-imaging communities ( Poldrack et al., 2013 ; Van Horn and Gazzaniga, 2002 ).”