Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jul 10:19:1580808.
doi: 10.3389/fnhum.2025.1580808. eCollection 2025.

Which software packages did researchers use to meta-analyze fMRI data? A literature survey from 2019 to 2024

Andy Wai Kan Yeung  1 , Natalie Sui Miu Wong  2
Affiliations

Which software packages did researchers use to meta-analyze fMRI data? A literature survey from 2019 to 2024

Andy Wai Kan Yeung et al. Front Hum Neurosci. .

Abstract

Introduction: There are various methods available for conducting meta-analyses of fMRI data, with coordinate-based meta-analysis (CBMA) being a frequently used approach due to the limited availability of effect size and statistical maps. Since the literature has accumulated many fMRI meta-analyses, several reports have been published to reveal the prevalence of numerous meta-analytic software packages without investigating into the recency of their versions used. To address this gap, a literature survey was conducted to identify the software packages and version numbers used for fMRI meta-analyses published between 2019 and 2024.

Methods: The online databases of Web of Science Core Collection (WOSCC) and Scopus were queried to identify relevant papers. After screening, the analysis consisted of data manually extracted from 820 papers.

Results: The most frequently used software was GingerALE (407 out of 820 papers, 49.6%), followed by SDM-PSI (27.4%) and Neurosynth (11.0%). Overall, 540 papers (65.9%) fully disclosed the names and version numbers of the software packages used in their analyses, whereas 19 papers (2.3%) reported neither the names nor the version numbers. For GingerALE, the most frequently used versions were 2.3.6 and 3.0.2, but it should be noted that versions prior to 2.3.6 have an issue of inflated false positive rates. For SDM-PSI, the most frequently used versions were 5.141, 5.15, 6.21, and 6.22, but the meta-analytic method adopted for version 6 differs from those used in prior versions.

Discussion: To ensure transparency and reproducibility in research, researchers should clearly report the name and version number of software package used.

Keywords: GingerALE; NiMARE; SDM; coordinate based meta-analysis; neurosynth.

PubMed Disclaimer

Conflict of interest statement

AY is an editorial board member of Frontiers at the time of submission. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Flowchart of a systematic review process. The identification phase shows records identified from Web of Science (n = 1065) and Scopus (n = 1512), with 959 duplicates removed. Screening has 1618 records screened and sought for retrieval, assessed for eligibility. Exclusions include no meta-analysis on fMRI data (n = 792), no full-text access (n = 5), and article retraction (n = 1). The inclusion phase has 820 studies in the review.
FIGURE 1
Screening process of the fMRI meta-analysis literature.
Bar chart showing the number of papers using different software tools. GingerALE leads with 407 papers, followed by SDM-PSI with 225 and Neurosynth with 90. Other tools like MKDA, Matlab, and R have 20 or fewer papers each.
FIGURE 2
Frequency count of different software packages used to perform fMRI meta-analysis. Out of the 820 papers that performed fMRI meta-analysis, some used more than one software. Therefore, the total frequency count amounted to 853.
Line graph showing the publication share among GingerALE papers from 2019 to 2024 for three versions. Version 2.3.6 (orange) dominates initially but declines sharply to near zero by 2021. Version 3.0.2 (gray) begins at zero in 2019, rises steeply to nearly 80% by 2021, and then stabilizes. An unidentified version (blue) remains consistently low throughout the period.
FIGURE 3
Change in the annual publication share of commonly used versions of GingerALE. “? Version” refers to papers that did not report the exact version number. The publication share is computed from GingerALE papers, not all meta-analysis papers.
Line graph showing publication share among SDM-PSI papers from 2019 to 2024. Five lines represent different versions: ? Version (blue), 5.141 (orange), 5.15 (gray), 6.21 (yellow), and 6.22 (green). The percentage ranges from 0% to 50%. Notable changes include a decrease in ? Version and an increase in versions 6.21 and 6.22 over time.
FIGURE 4
Change in the annual publication share of commonly used versions of SDM-PSI. “? Version” refers to papers that did not report the exact version number. The publication share is computed from SDM-PSI papers, not all meta-analysis papers.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Acar F., Maumet C., Heuten T., Vervoort M., Bossier H., Seurinck R., et al. (2024). Improving the eligibility of task-based fMRI studies for meta-analysis: A review and reporting recommendations. Neuroinformatics 22 5–22. 10.1007/s12021-023-09643-5 - DOI - PubMed
    1. Albajes-Eizagirre A., Radua J. (2018). What do results from coordinate-based meta-analyses tell us? Neuroimage 176 550–553. 10.1016/j.neuroimage.2018.04.065 - DOI - PubMed
    1. Albajes-Eizagirre A., Solanes A., Vieta E., Radua J. (2019). Voxel-based meta-analysis via permutation of subject images (PSI): Theory and implementation for SDM. Neuroimage 186 174–184. 10.1016/j.neuroimage.2018.10.077 - DOI - PubMed
    1. Belyk M., Kraft S., Brown S. (2015). Stuttering as a trait or state – an ALE meta-analysis of neuroimaging studies. Eur. J. Neurosci. 41 275–284. 10.1111/ejn.12765 - DOI - PubMed
    1. Belyk M., Kraft S., Brown S. (2017). Stuttering as a trait or a state revisited: Motor system involvement in persistent developmental stuttering. Eur. J. Neurosci. 45 622–624. 10.1111/ejn.13512 - DOI - PubMed

Publication types

LinkOut - more resources