Advancing image-based meta-analysis through systematic use of crowdsourced NeuroVault data.

ABSTRACT: Image-based meta-analysis (IBMA) is a powerful method for synthesizing results from various fMRI studies. However, challenges related to data accessibility and the lack of available tools and methods have limited its widespread use. This study examined the current state of the NeuroVault repository and developed a comprehensive framework for selecting and analyzing neuroimaging statistical maps within it. By systematically assessing the quality of NeuroVault's data and implementing novel selection and meta-analysis techniques, we demonstrated the repository's potential for IBMA. We created a multi-stage selection framework that includes preliminary, heuristic, and manual image selection. We conducted meta-analyses for three distinct domains: working memory, motor, and emotion processing. T

SUBMITTER: Peraza JA 

PROVIDER: S-EPMC12540767 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature