ArticleNeuroImage2009
Is it time to re-prioritize neuroimaging databases and digital repositories?
Article in NeuroImage, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
49 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Do brain image databanks support understanding of normal ageing brain structure? A systematic review.European radiology · 2012Pooled it
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- Scalable, reproducible, and cost-effective processing of large-scale medical imaging datasets.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Challenging the status quo: A guide to open and reproducible neuroimaging for early career researchers.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- The BRAIN Initiative data-sharing ecosystem: Characteristics, challenges, benefits, and opportunities.eLife · 2024Article
- Optimizing neuroscience data management by combining REDCap, BIDS and SQLite: a case study in Deep Brain Stimulation.Frontiers in neuroinformatics · 2024Article
- Editorial: What the New White House Rules on Equitable Access Mean for the Neurosciences.Neuroinformatics · 2023Article
- Common Data Elements, Scalable Data Management Infrastructure, and Analytics Workflows for Large-Scale Neuroimaging Studies.Frontiers in psychiatry · 2021Article
- Dimensional connectomics of anxious misery, a human connectome study related to human disease: Overview of protocol and data quality.NeuroImage. Clinical · 2020Review
- Big data sharing and analysis to advance research in post-traumatic epilepsy.Neurobiology of disease · 2019Review
- From the Wet Lab to the Web Lab: A Paradigm Shift in Brain Imaging Research.Frontiers in neuroinformatics · 2019Review
- Integration ofFrontiers in neuroinformatics · 2018Article
- Envisioning the future of 'big data' biomedicine.Journal of biomedical informatics · 2017Article
- Can data repositories help find effective treatments for complex diseases?Progress in neurobiology · 2017Review
- Science in the cloud (SIC): A use case in MRI connectomics.GigaScience · 2017Article
- Article
- Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework.Frontiers in neuroinformatics · 2017Article
- The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments.Scientific data · 2016Article
- The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke.NeuroImage · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The development of in vivo brain imaging has lead to the collection of large quantities of digital information. In any individual research article, several tens of gigabytes-worth of data may be represented-collected across normal and patient samples. With the ease of collecting such data, there is increased desire for brain imaging datasets to be openly shared through sophisticated databases. However, very often the raw and pre-processed versions of these data are not available to researchers outside of the team that collected them. A range of neuroimaging databasing approaches has streamlined the transmission, storage, and dissemination of data from such brain imaging studies. Though early sociological and technical concerns have been addressed, they have not been ameliorated altogether for many in the field. In this article, we review the progress made in neuroimaging databases, their role in data sharing, data management, potential for the construction of brain atlases, recording data provenance, and value for re-analysis, new publication, and training. We feature the LONI IDA as an example of an archive being used as a source for brain atlas workflow construction, list several instances of other successful uses of image databases, and comment on archive sustainability. Finally, we suggest that, given these developments, now is the time for the neuroimaging community to re-prioritize large-scale databases as a valuable component of brain imaging science.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.