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Review
. 2024 Jun 11:17:2331-2345.
doi: 10.2147/PRBM.S453035. eCollection 2024.

Activation Likelihood Estimation Neuroimaging Meta-Analysis: a Powerful Tool for Emotion Research

Tommaso Costa  1   2 , Mario Ferraro  1   2   3 , Jordi Manuello  1   2 , Alessia Camasio  2   3 , Andrea Nani  2 , Lorenzo Mancuso  2 , Franco Cauda  1   2 , Peter T Fox  4   5 , Donato Liloia  1   2
Affiliations
Review

Activation Likelihood Estimation Neuroimaging Meta-Analysis: a Powerful Tool for Emotion Research

Tommaso Costa et al. Psychol Res Behav Manag. .

Abstract

Over the past two decades, functional magnetic resonance imaging (fMRI) has become the primary tool for exploring neural correlates of emotion. To enhance the reliability of results in understanding the complex nature of emotional experiences, researchers combine findings from multiple fMRI studies using coordinate-based meta-analysis (CBMA). As one of the most widely employed CBMA methods worldwide, activation likelihood estimation (ALE) is of great importance in affective neuroscience and neuropsychology. This comprehensive review provides an introductory guide for implementing the ALE method in emotion research, outlining the experimental steps involved. By presenting a case study about the emotion of disgust, with regard to both its core and social processing, we offer insightful commentary as to how ALE can enable researchers to produce consistent results and, consequently, fruitfully investigate the neural mechanisms underpinning emotions, facilitating further progress in this field.

Keywords: BrainMap; affective mapping; affective neuroscience; coordinate-based meta-analysis; fMRI; quantitative synthesis.

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Conflict of interest statement

The authors report no financial interests or potential conflicts of interest in this work. Dr. Donato Liloia, PhD is an Associate Editorial Board Member of this journal but was not involved in the peer-review process nor had access to any information regarding its peer-review.

Figures

Figure 1
Figure 1
Number of published articles per year in PubMed search engine (https://pubmed.ncbi.nlm.nih.gov/) for neuroimaging techniques in the field of emotion research.
Figure 2
Figure 2
Workflow stages of the activation likelihood estimation (ALE) method.
Figure 3
Figure 3
Brain clusters of spatially convergent patterns of activation in the general disgust processing dataset (main ALE analysis of Gan et al (2022); top panel), core disgust processing dataset (subanalysis 1 of Gan et al (2022); bottom left panel), and social disgust processing dataset (subanalysis 2 of Gan et al (2022); bottom right panel). Results were FWE-corrected at 0.05 with cluster-forming value at p <.001 by Gan et al (2022) via GingerALE (v. 3.0.2.; http://www.brainmap.org/ale/). The activation likelihood activation (ALE) maps are visualized as axial slices (2-D cortical and subcortical view). Brain templates are in neurological convention (ie, R is right, L is left).
Figure 4
Figure 4
Conjunction and contrast analyses between core and social disgust processing datasets as performed by Gan et al. Left panel: Convergence of activation between core and social disgust processing datasets (green color represents ALE values). Central panel: Compared to the social disgust dataset, activations are exclusively present in the core disgust dataset (red color represents ALE values). Right panel: Compared to the core disgust dataset, activations are exclusively present in the social disgust dataset (blue color represents ALE values).
See this image and copyright information in PMC

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