Perception of facial expression is essential for social interactions. Although a few competing models have enjoyed some success to map brain regions, they are also facing difficult challenges.

A research team led by Prof. Xiaolan Fu from the Institute of Psychology of the Chinese Academy of Sciences (CAS) used an updated activation likelihood estimation (ALE) method of meta-analysis to explore the involvement of brain regions in facial expression processing. The sample contained 96 functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) studies of healthy adults with the results of whole-brain analyses.

This meta-analysis provides comprehensive evidence for the role of the ventral stream in facial expression processing and proposes a revised model. The key findings revealed that the ventral pathway, especially the left fusiform face area (FFA) region, was more responsive to facial expression. The left posterior FFA showed strong involvement when participants passively viewing emotional faces without being asked to judge the type of expression or other attributes of the stimuli. Through meta-analytic connectivity modeling (MACM) of the main brain regions in the ventral pathway, a co-activating neural network was constructed as a revised model of facial expression processing that assigns prominent roles to the amygdala, FFA, the occipital gyrus, and the inferior frontal gyrus. This meta-analysis expands people’s understanding of the neural network of facial expression processing.

The study entitled “Reexamining the neural network involved in perception of facial expression: A meta-analysis” has been published in Neuroscience & Biobehavioral Reviews.

LIU Chen
Institute of Psychology
Chinese Academy of Sciences
Beijing 100101, China.
E-mail: liuc@psych.ac.cn