Beyond consensus: Embracing heterogeneity in curated neuroimaging meta-analysis

Gia H. Ngo, Simon B. Eickhoff, Minh Nguyen, Gunes Sevinc, Peter T. Fox, R. Nathan Spreng, B. T.Thomas Yeo

Research output: Contribution to journalArticle

2 Scopus citations

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).

Original languageEnglish (US)
Pages (from-to)142-158
Number of pages17
JournalNeuroImage
Volume200
DOIs
StatePublished - Oct 15 2019

Keywords

  • Attentional control
  • Autobiographical memory
  • Executive function
  • Inhibition
  • Mental disorder subtypes
  • Theory of mind

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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    Ngo, G. H., Eickhoff, S. B., Nguyen, M., Sevinc, G., Fox, P. T., Spreng, R. N., & Yeo, B. T. T. (2019). Beyond consensus: Embracing heterogeneity in curated neuroimaging meta-analysis. NeuroImage, 200, 142-158. https://doi.org/10.1016/j.neuroimage.2019.06.037