ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

Advances in Psychological Science ›› 2021, Vol. 29 ›› Issue (5): 761-772.doi: 10.3724/SP.J.1042.2021.00761

• Conceptual Framework •     Next Articles

Neural mechanism underlying the perception of crowd facial emotions

HE Weiqi(), LI Shuaixia, ZHAO Dongfang   

  1. Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China;Key laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian 116029, China
  • Received:2020-09-01 Online:2021-05-15 Published:2021-03-30
  • Contact: HE Weiqi E-mail:weiqi79920686@sina.com

Abstract:

Human facial expressions convey a wealth of information about individual or group's emotion, motivation, intention or behavioral tendency, and interpreting these cues successfully and efficiently is a fundamental social cognitive process necessary for adaptive social behavior. Exploring how facial expression is processed and its potential cognitive neural mechanism has always been the popular topic for psychology and social neuroscience. The majority of recent studies mainly used single facial expression as stimuli to unravel the neural correlates of emotional processing, which make a great contribution to understandings of face perception and emotion recognition on dyadic interactions. However, much less is known about the emotion perception and recognition when crowds of faces are encountered. Thus, using crowd facial expressions as experimental stimuli, the present project plans to systematically explore the neural correlates of processing crowd emotions from the perspectives of behavioral performance, temporal dynamics and brain activation patterns, through the combined applications of behavioral, ERP, fMRI, and TMS techniques. Firstly, considering that emotional information conveyed by facial expressions differs in valence and intensity, the study 1 intends to investigate the recognition advantage, cerebral temporal and spatial characteristics (i.e. brain regions engaged in the processing of crowd facial expressions) through an emotion discrimination task, in which the valence (positive, neutral, and negative) and intensity (high, medium, and low) of crowd facial expressions will be manipulated well, respectively. Secondly, given that configural and featural information of face can exert an influence on the perception and recognition of emotional facial expressions, the effects of configural and featural cues of crowd faces on emotion perception will be taken into consideration in the study two and three. Specifically, in order to confirm the influence of orientation information on the processing of crowd facial expressions, the study 2 will focus on the orientations (frontal, half profile and profile) and inversions (upright and inverted) of crowd faces of different valences. Additionally, the study 3 will focus on the spatially structural integrity of crowd faces, and two issues below can be to some extent addressed through a masking and exploratory date-driven technology, namely: (1) How does different parts of face influence the processing of crowd facial expressions? (2) What is the diagnostic neural correlates which the perception and recognition of crowd facial expression depends on? Furthermore, it has been well-documented that spatial frequency content has a robust effect on the processing of facial stimuli, and different spatial frequencies transmit different information regarding faces. In general, low spatial frequency (LSF) content conveys information about orientation and contour of a face, which is associated with configural face processing. High spatial frequency (HSF) content conveys information about local details of a face, which is associated with featural face processing. Therefore, in the study 4, the spatial frequencies (broad band, HSF, LSF) and emotional valences (positive and negative) of crowd faces will be manipulated to investigate the temporal and spatial characteristics underlying the influence of spatial frequency on the processing of crowd facial expressions. The implementation of this project, on the one hand, helps to clarify the specific and general brain mechanisms related to individual and crowd facial expressions processing and to extend our understanding of the general rules and characteristics of emotion perception and face processing, which will improve building a universal theoretical model of face recognition. On the other hand, it can provide theoretical guidance for group emotion regulation and intervention, improve group belonging and group cohesion to a large extent, promote prosocial behavior and make a contribution to the construction of a harmonious society.

Key words: facial expression, emotional processing, crowd emotion, ensemble perception

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