Meta all the way down: An overview of neuroimaging meta-analyses
Kendra OudykiD, Jérôme DockèsiD, Julio A. PerazaiD, James Doliver KentiD, Mohammad TorabiiD, Michelle WangiD, Brent Caleb McPhersoniD, Niusha MirhakimiiD, Alejandro I de la VegaiD, Angela R. LairdiD, J.-B. PolineiD
Abstract
Meta-analyses are invaluable tools for navigating the rapidly expanding scientific literature. Given their high value, ensuring the quality of meta-analyses is paramount. We conducted a multifaceted overview, examining each step in a manual neuroimaging meta-analysis on a large scale. We used four novel datasets comprising over 14,000 papers, including fMRI meta-analyses, fMRI studies, studies included in meta-analyses, and studies associated with image data on NeuroVault. Regarding successes, two-thirds of meta-analyses stated that they followed PRISMA guidelines, and 65% included a flowchart describing their inclusion process. We point out several areas for improvement. Pre-registration was fairly rare (20%), and only half listed their exact search strategy. There could be a location bias in which papers are included, and many did not include enough studies to be robust against publication bias (68% of meta analyses have less than 30 studies included). We also offer ideas for future directions. As image based meta-analysis is the gold standard, we have indicated which topics have the most image data available. The potential redundancy of topics can be visualized in our paper, and we recommend future meta-analyses be in conversation with past ones by citing and discussing previous similar work. By addressing these findings, the neuroimaging community can collectively improve the field of neuroimaging meta-analyses.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 2
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Minimal Data Needed for Valid & Accurate Image-Based fMRI Meta-Analysis
Camille Maumet, Thomas E. Nichols·bioRxiv·Apr 20, 2016
- The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis
Daniel Kristanto, Micha Burkhardt, … Andrea Hildebrandt·Neuroscience & Biobehavioral ReviewsPeer-reviewed·Aug 6, 2024
- Advancing image-based meta-analysis for fMRI: A framework for leveraging NeuroVault data
Julio A. Peraza, James Doliver Kent, … Angela R. Laird·bioRxiv·Mar 6, 2025
- The Influence Of Study Characteristics On Coordinate-Based fMRI Meta-Analyses
Han Bossier, Ruth Seurinck, … Beatrijs Moerkerke·bioRxiv·May 30, 2017
- Sharing brain mapping statistical results with the neuroimaging data model
Camille Maumet, Tibor Auer, … Thomas E. Nichols·Scientific DataPeer-reviewed·Dec 6, 2016
- Data management and sharing in neuroimaging: Practices and perceptions of MRI researchers
John Borghi, Ana E. Van Gulick·PLoS ONEPeer-reviewed·Jul 16, 2018