Beyond consensus: Embracing heterogeneity in curated neuroimaging meta-analysis

Neuroimage. 2019 Oct 15;200:142-158. doi: 10.1016/j.neuroimage.2019.06.037. Epub 2019 Jun 20.

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).

Keywords: Attentional control; Autobiographical memory; Executive function; Inhibition; Mental disorder subtypes; Theory of mind.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Attention / physiology
  • Cerebral Cortex / diagnostic imaging
  • Cerebral Cortex / physiology*
  • Executive Function / physiology
  • Functional Neuroimaging / methods*
  • Humans
  • Inhibition, Psychological
  • Likelihood Functions
  • Memory, Episodic
  • Meta-Analysis as Topic*
  • Models, Theoretical*
  • Nerve Net / diagnostic imaging
  • Nerve Net / physiology*
  • Theory of Mind / physiology
  • Thinking / physiology