ArticleBiostatistics (Oxford, England)2024
Neuroimaging meta regression for coordinate based meta analysis data with a spatial model.
Article in Biostatistics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- CBMR: Coordinate-based meta-regression for group and covariate inference.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Consistent activation differences versus differences in consistent activation: Evaluating meta-analytic contrasts.Imaging neuroscience (Cambridge, Mass.) · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
Coordinate-based meta-analysis combines evidence from a collection of neuroimaging studies to estimate brain activation. In such analyses, a key practical challenge is to find a computationally efficient approach with good statistical interpretability to model the locations of activation foci. In this article, we propose a generative coordinate-based meta-regression (CBMR) framework to approximate a smooth activation intensity function and investigate the effect of study-level covariates (e.g. year of publication, sample size). We employ a spline parameterization to model the spatial structure of brain activation and consider four stochastic models for modeling the random variation in foci. To examine the validity of CBMR, we estimate brain activation on 20 meta-analytic datasets, conduct spatial homogeneity tests at the voxel level, and compare the results to those generated by existing kernel-based and model-based approaches. Keywords: generalized linear models; meta-analysis; spatial statistics; statistical modeling.
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Registered trials
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