ArticleNeuroImage2019
Beyond consensus: Embracing heterogeneity in curated neuroimaging meta-analysis.
Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Accurate localization and coactivation profiles of the frontal eye field and inferior frontal junction: an ALE and MACM fMRI meta-analysis.Brain structure & function · 2023Pooled it
- Tasks activating the default mode network map multiple functional systems.Brain structure & function · 2022Pooled it
- Parsing variability in borderline personality disorder: a meta-analysis of neuroimaging studies.Translational psychiatry · 2021Pooled it
- Brain decoding of spontaneous thought: Predictive modeling of self-relevance and valence using personal narratives.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Obliviate! Reviewing Neural Fundamentals of Intentional Forgetting from a Meta-Analytic Perspective.Biomedicines · 2022Review
- To learn or to gain: neural signatures of exploration in human decision-making.Brain structure & function · 2022Article
- Structure, function and connectivity fingerprints of the frontal eye field versus the inferior frontal junction: A comprehensive comparison.The European journal of neuroscience · 2021Review
- The Functional Foundations of Episodic Memory Remain Stable Throughout the Lifespan.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Towards a Universal Taxonomy of Macro-scale Functional Human Brain Networks.Brain topography · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Coordinate-based meta-analysis can provide important insights into mind-brain relationships. A popular approach for curated small-scale meta-analysis is activation likelihood estimation (ALE), which identifies brain regions consistently activated across a selected set of experiments, such as within a functional domain or mental disorder. ALE can also be utilized in meta-analytic co-activation modeling (MACM) to identify brain regions consistently co-activated with a seed region. Therefore, ALE aims to find consensus across experiments, treating heterogeneity across experiments as noise. However, heterogeneity within an ALE analysis of a functional domain might indicate the presence of functional sub-domains. Similarly, heterogeneity within a MACM analysis might indicate the involvement of a seed region in multiple co-activation patterns that are dependent on task contexts. Here, we demonstrate the use of the author-topic model to automatically determine if heterogeneities within ALE-type meta-analyses can be robustly explained by a small number of latent patterns. In the first application, the author-topic modeling of experiments involving self-generated thought (N = 179) revealed cognitive components fractionating the default network. In the second application, the author-topic model revealed that the left inferior frontal junction (IFJ) participated in multiple task-dependent co-activation patterns (N = 323). Furthermore, the author-topic model estimates compared favorably with spatial independent component analysis in both simulation and real data. Overall, the results suggest that the author-topic model is a flexible tool for exploring heterogeneity in ALE-type meta-analyses that might arise from functional sub-domains, mental disorder subtypes or task-dependent co-activation patterns. Code for this study is publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/meta-analysis/Ngo2019_AuthorTopic).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.