The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
Making big data open: data sharing in neuroimaging
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Citations
Cites
Why Most Published Research Findings Are False
Ioannidis, J. P. A. (2005) · PLoS Medicine · doi:10.1371/journal.pmed.0020124 · Cited by 10,505
Power failure: why small sample size undermines the reliability of neuroscience
Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafò, M. R. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3475 · Cited by 7,641
Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011) · Psychological Science · doi:10.1177/0956797611417632 · Cited by 6,567
The WU-Minn Human Connectome Project: An overview
Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E. J., Yacoub, E., & Ugurbil, K. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.041 · Cited by 5,651
Why Most Published Research Findings Are False
Ioannidis, J. P. A. (2005) · CHANCE · doi:10.1080/09332480.2005.10722754 · Cited by 4,702 · cited 1×
“One major source of concern within neuroscience is the low statistical power of many published studies 14 , given that this increases the proportion of published findings that are false 15 and can create unwanted biases 16 .”
BackgroundLarge-scale automated synthesis of human functional neuroimaging data.
Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wager, T. D. (2011) · Nature Methods · doi:10.1038/nmeth.1635 · Cited by 3,686
Self-citationToward discovery science of human brain function
Biswal, B. B., Mennes, M., Zuo, X.-N., Gohel, S., Kelly, C., Smith, S. M., Beckmann, C. F., Adelstein, J. S., Buckner, R. L., Colcombe, S., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0911855107 · Cited by 2,970
Circular analysis in systems neuroscience: the dangers of double dipping
Kriegeskorte, N., Simmons, W. K., Bellgowan, P. S. F., & Baker, C. I. (2009) · Nature Neuroscience · doi:10.1038/nn.2303 · Cited by 2,696
Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python
Gorgolewski, K., Burns, C. D., Madison, C., Clark, D., Halchenko, Y. O., Waskom, M. L., & Ghosh, S. S. (2011) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2011.00013 · Cited by 2,186
Self-citationWhy Most Discovered True Associations Are Inflated
Ioannidis, J. P. A. (2008) · Epidemiology · doi:10.1097/ede.0b013e31818131e7 · Cited by 1,495
Cited by
Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates
Eklund, A., Nichols, T. E., & Knutsson, H. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1602413113 · Cited by 3,487
Bassett, D. S., & Sporns, O. (2017) · Nature Neuroscience · doi:10.1038/nn.4502 · Cited by 2,398
Building better biomarkers: brain models in translational neuroimaging
Woo, C.-W., Chang, L. J., Lindquist, M. A., & Wager, T. D. (2017) · Nature Neuroscience · doi:10.1038/nn.4478 · Cited by 1,056
Cross-validation failure: Small sample sizes lead to large error bars
Varoquaux, G. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.061 · Cited by 897
“Reusing shared data across investigators can increase sample sizes while keeping bounds on data-acquisition costs (Poldrack and Gorgolewski, 2014).”
BackgroundBest practices in data analysis and sharing in neuroimaging using MRI
Nichols, T. E., Das, S., Eickhoff, S. B., Evans, A. C., Glatard, T., Hanke, M., Kriegeskorte, N., Milham, M. P., Poldrack, R. A., Poline, J.-B., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4500 · Cited by 714
Self-citation
Metadata
- Authors
- Poldrack, R. A., & Gorgolewski, K. J.
- Venue
- Nature Neuroscience
- Published
- 2014-10-28
- Volume
- 17
- Issue
- 11
- Pages
- 1510-1517
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W2052341330
- Cited by
- 425
- References
- 64
- FWCI
- 104.48
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- CoChat. (2026). Citation check: Making big data open: data sharing in neuroimaging. https://app.cochat.ai/papers/10.1038/nn.3818
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- Poldrack, R. A., & Gorgolewski, K. J. (2014). Making big data open: data sharing in neuroimaging. Nature Neuroscience. https://doi.org/10.1038/nn.3818
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
