ISSN 1671-3710
CN 11-4766/R

心理科学进展 ›› 2022, Vol. 30 ›› Issue (3): 536-555.doi: 10.3724/SP.J.1042.2022.00536

• 元分析 • 上一篇    下一篇


刘俊材1, 冉光明1(), 张琪2   

  1. 1西华师范大学教育学院心理系
    2西华师范大学学前与初等教育学院, 四川 南充 637002
  • 收稿日期:2021-10-06 出版日期:2022-03-15 发布日期:2022-01-25
  • 通讯作者: 冉光明
  • 基金资助:

The neural activities of different emotion carriers and their similarities and differences: A meta-analysis of functional neuroimaging studies

LIU Juncai1, RAN Guangming1(), ZHANG Qi2   

  1. 1Department of Psychology, School of Education, China West Normal University, Nanchong 637002, China
    2College of Preschool and Primary Education, China West Normal University, Nanchong 637002, China
  • Received:2021-10-06 Online:2022-03-15 Published:2022-01-25
  • Contact: RAN Guangming


情绪识别一直是学界关注的热点。虽然已有研究探讨了动态面孔表情、动态身体表情和声音情绪的脑机制, 但对每种情绪载体的整体认识相对不完善, 同时对不同情绪载体之间神经机制的共性和区别知之甚少。因此, 本研究首先通过三项独立的激活似然估计元分析来识别每种情绪模式的大脑激活区域, 然后进行对比分析以评估三种情绪载体之间共同的和独特的神经活动。结果显示, 动态面孔表情的大脑活动包括广泛的额叶、枕叶、颞叶和部分顶叶皮层以及海马、小脑、丘脑、杏仁核等皮层下区域; 动态身体表情的激活集中于颞/枕叶相关脑区以及小脑和海马; 声音情绪则引起了颞叶、额叶、杏仁核、尾状核和脑岛的激活。联合分析表明, 三种情绪载体跨模态激活了左侧颞中回和右侧颞上回。对比分析的结果证明了视觉刺激比听觉刺激更占优势, 动态面孔表情尤为突出, 同时动态身体表情也发挥着重要作用, 但声音情绪有其独特性。总之, 这些发现验证和拓展了三种情绪载体的现有神经模型, 揭示了情绪处理中心的、普遍性的区域, 但每种情绪载体又有自己可靠的特异性神经回路。

关键词: 情绪载体, 动态面孔表情, 动态身体表情, 声音情绪, ALE元分析


Emotion recognition has always been a hot topic in psychology. Although some studies have explored the brain mechanisms of dynamic facial expressions, dynamic bodily expressions and emotional voices, empirical studies have their own inevitable defects, which may lead to low statistical test power and effect size and inconsistent results. In addition, the existing meta-analyses of the three emotion carriers still have some deficiencies. Therefore, at present, the overall understanding of the three emotion carriers is relatively incomplete, and the commonness and differences of neural mechanisms among different emotion carriers were still poorly known. So, based on the background of high ecological validity, this study adopted the meta-analysis technique based on large-scale data synthesis method to overcome the above shortcomings. First, three separated activation likelihood estimation (ALE) meta-analyses were used to identify the brain regions activated by each emotion pattern, and then conjunction and contrast analysis of these activation maps were used to assess common and unique neural activity between the three emotion carriers. It is the first time that meta-analysis is used to explore the brain mechanism of dynamic bodily expressions, and it is also the first time that meta-analysis is used to explore the similarities and differences of neural activity among three emotion carriers: dynamic facial expressions, dynamic bodily expressions and emotional voices, and further improves the overall understanding of the neural mechanisms of dynamic facial expressions and emotional voices by previous meta-analyses. The results of single meta-analysis showed that the brain regions of dynamic facial expressions included superior frontal gyrus (SFG), middle frontal gyrus (MFG), inferior frontal gyrus (IFG), precentral gyrus (PG), inferior parietal lobule (IPL), middle occipital gyrus (MOG), inferior occipital gyrus (IOG), fusiform gyrus (FG), superior temporal gyrus (STG), middle temporal gyrus (MTG), inferior temporal gyrus (ITG), parahippocampal gyrus (PHG), cerebellum, amygdala, lentiform nucleus (LN) and insula. Dynamic bodily expressions caused activation of the middle occipital gyrus, inferior occipital gyrus, fusiform gyrus, superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, cuneus, lingual gyrus (LING), cerebellum, and parahippocampal gyrus. The activation of emotional voices was concentrated in the middle frontal gyrus, inferior frontal gyrus, precentral gyrus, superior temporal gyrus, middle temporal gyrus, heschl’s gyrus (HG), insula, amygdala and caudate nucleus (CN). Conjunction analysis suggested that the left middle temporal gyrus and the right superior temporal gyrus were activated by three emotion carrier across the modalities. The results of the contrast analysis proved that the visual stimuli was more advantaged than the auditory stimuli, especially the dynamic facial expressions, the dynamic bodily expressions also played an important role. However, the emotional voices had their own uniqueness. In sum, these findings validate, support, and extend the existing neural models of the three emotion carriers, revealing a central, universal region of the emotional processing, but with each emotion carrier relying on its own reliable specific neural circuits. This study provides consistent results across studies for researchers of emotional problems, and representative reference coordinate points for future region of interest (ROI) analysis, which is conducive to propose and test hypotheses of future researches, and also is conducive to the identification and neural regulation of patients with emotional disorders. Future researches should further validate and extend these findings to explore the neural mechanisms of emotional processing at different ages and their similarities and differences. In addition, it is necessary to study the brain mechanism of each emotion type and the similarity and difference of neural activity of each emotion in different carriers in the case of sufficient data. Examining the connection of different brain regions, and the different functions of a brain region also is necessary. Meanwhile, it is essential to focus on the neural basis of dynamic bodily expressions.

Key words: emotion carriers, dynamic facial expressions, dynamic bodily expressions, emotional voices, ALE meta-analysis