SynthesisNeuroinformatics2023
A Minimum Bayes Factor Based Threshold for Activation Likelihood Estimation.
Synthesis in Neuroinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Neurofunctional Correlates of Emotional Dysregulation: Systematic Review and ALE Meta-Analysis.Brain and behavior · 2026Pooled it
- Meta-analytic connectivity perturbation analysis (MACPA): a new method for enhanced precision in fMRI connectivity analysis.Brain structure & function · 2024Pooled it
- Extracting Weight of Evidence fromBrain sciences · 2026Article
- Activation Likelihood Estimation Neuroimaging Meta-Analysis: a Powerful Tool for Emotion Research.Psychology research and behavior management · 2024Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Activation likelihood estimation (ALE) is among the most used algorithms to perform neuroimaging meta-analysis. Since its first implementation, several thresholding procedures had been proposed, all referred to the frequentist framework, returning a rejection criterion for the null hypothesis according to the critical p-value selected. However, this is not informative in terms of probabilities of the validity of the hypotheses. Here, we describe an innovative thresholding procedure based on the concept of minimum Bayes factor (mBF). The use of the Bayesian framework allows to consider different levels of probability, each of these being equally significant. In order to simplify the translation between the common ALE practice and the proposed approach, we analised six task-fMRI/VBM datasets and determined the mBF values equivalent to the currently recommended frequentist thresholds based on Family Wise Error (FWE). Sensitivity and robustness toward spurious findings were also analyzed. Results showed that the cutoff log
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Registered trials
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