title: Dissociable roles of internal feelings and face recognition ability in facial expression decoding.
abstract: The problem of emotion recognition has been tackled by researchers in both affective computing and cognitive neuroscience. While affective computing relies on analyzing visual features from facial expressions, it has been proposed that humans recognize emotions by internally simulating the emotional states conveyed by others' expressions, in addition to perceptual analysis of facial features. Here we investigated whether and how our internal feelings contributed to the ability to decode facial expressions. In two independent large samples of participants, we observed that individuals who generally experienced richer internal feelings exhibited a higher ability to decode facial expressions, and the contribution of internal feelings was independent of face recognition ability. Further, using voxel-based morphometry, we found that the gray matter volume (GMV) of bilateral superior temporal sulcus (STS) and the right inferior parietal lobule was associated with facial expression decoding through the mediating effect of internal feelings, while the GMV of bilateral STS, precuneus, and the right central opercular cortex contributed to facial expression decoding through the mediating effect of face recognition ability. In addition, the clusters in bilateral STS involved in the two components were neighboring yet separate. Our results may provide clues about the mechanism by which internal feelings, in addition to face recognition ability, serve as an important instrument for humans in facial expression decoding.
authors.affiliation: Civil Aviation Medical Center, Civil Aviation Administration of China, Beijing 100123, China; State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
authors.forename: Yiying
authors.initials: Y
authors.lastname: Song
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
authors.forename: Ling
authors.initials: L
authors.lastname: Liu
authors.affiliation: Beijing Key Laboratory of Applied Experimental Psychology, School of Psychology, Beijing Normal University, Beijing 100875, China. Electronic address: liujia@bnu.edu.cn.
authors.forename: Jia
authors.initials: J
authors.lastname: Liu
mesh_terms: D000328:Adult; D000339:Affect / Q000502:physiology; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D004644:Emotions / Q000502:physiology*; D005149:Facial Expression; D000066499:Facial Recognition / Q000502:physiology*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D021641:Recognition, Psychology / Q000502:physiology*; D055815:Young Adult
keywords: Face recognition ability; Facial expression decoding; Individual difference; Internal feelings; Voxel-based morphometry