ISSN 0439-755X
CN 11-1911/B

Acta Psychologica Sinica ›› 2025, Vol. 57 ›› Issue (9): 1553-1571.doi: 10.3724/SP.J.1041.2025.1553

• Reports of Empirical Studies • Previous Articles     Next Articles

Automatic processing of variability in multiple facial expressions: Evidence from visual mismatch responses

CHEN Zilong, JI Luyan()   

  1. School of Education, Guangzhou University, Guangzhou 510006, China
  • Published:2025-09-25 Online:2025-06-26
  • Contact: JI Luyan E-mail:luyanji@gzhu.edu.cn

Abstract:

This study examined whether individuals can automatically process emotional variability from multiple facial expressions and whether this process is affected by emotion type using the passive oddball paradigm and visual mismatch negativity (vMMN). A central fixation discrimination task was used, and four emotional faces were presented simultaneously in the peripheral visual field, independent of the task. Emotional variability was manipulated by varying the emotional intensity of the faces. In Experiment 1, faces with low emotional variability did not induce vMMN when the mean emotion was neutral, whereas faces with high emotional variability induced both early and late vMMN. Experiment 2 further differentiated between angry and happy emotions, and found that when the mean emotion was happy, neither high nor low emotional variability elicited significant vMMN. In contrast, when the mean emotion was anger, low variability induced a significant vMMN, while high variability induced a vMMP (visual mismatch positivity). Experiment 3, which controlled for emotional ranges and distributions, found that low-variability faces did not induce vMMN, whereas high-variability faces induced vMMP at a later stage. Moreover, the whole brain was able to decode standard and deviant stimuli at an early stage in all conditions of the three experiments. Experiment 2 additionally revealed that faces with low emotional variability were decoded later than those with high emotional variability. In conclusion, the brain can automatically process emotional variability from multiple faces, and there is an advantage for the automatic processing of relatively higher variability, which is influenced by the type of emotion.

Key words: emotional variability, ensemble perception, facial expressions, visual mismatch negativity (vMMN), event-related potentials (ERPs)