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

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish
Article number1580808
Number of pages8
JournalFrontiers in Human Neuroscience
Volume19
DOIs
Publication statusPublished - 10 Jul 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

User-Defined Keywords

  • coordinate based meta-analysis
  • GingerALE
  • neurosynth
  • NiMARE
  • SDM

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