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. The current study 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. 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, we constructed a co-activating neural network as a revised model of facial expression processing that assigns prominent roles to the amygdala, FFA, the occipital gyrus, and the inferior frontal gyrus.

面部表情的感知对于社交互动至关重要。尽管一些竞争模型在绘制大脑区域图方面取得了一些成功，但它们也面临着艰巨的挑战。目前的研究使用更新的激活似然估计 (ALE) 元分析方法来探索大脑区域参与面部表情处理。该样本包含对健康成人的 96 项功能性磁共振成像 (fMRI) 和正电子发射断层扫描 (PET) 研究以及全脑分析结果。主要研究结果表明，腹侧通路，尤其是左侧梭状面部区域 (FFA) 区域，对面部表情的反应更灵敏。当参与者在不被要求判断表情类型或刺激的其他属性的情况下被动地查看情绪面孔时，左后 FFA 表现出强烈的参与。通过对腹侧通路主要大脑区域的元分析连接建模 (MACM)，我们构建了一个协同激活神经网​​络作为面部表情处理的修正模型，该模型赋予杏仁核、FFA、枕回和额下回。