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Han S, Gao J, Xing W, Zhou X, Luo Y. Facial attractiveness in the eyes of men with high arousal. Brain Behav 2023; 13:e3132. [PMID: 37367435 PMCID: PMC10498057 DOI: 10.1002/brb3.3132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 05/04/2023] [Accepted: 06/08/2023] [Indexed: 06/28/2023] Open
Abstract
INTRODUCTION Individuals differ in how they judge facial attractiveness. However, little is known about the role of arousal level and gender differences in individuals' facial attractiveness judgments. METHODS We used resting-state electroencephalogram (EEG) to investigate this issue. A total of 48 men (aged 22.5 ± 3.03 years [mean ± SD], range: 18-30 years) and 27 women (aged 20.3 ± 2.03 years [mean ± SD], range: 18-25 years) participated in the experiment. After the EEG was collected, participants were instructed to complete a facial attractiveness judgment task. Connectome-based predictive modeling was used to predict individual judgment of facial attractiveness. RESULTS Men with high arousal judged female faces as more attractive (M = 3.85, SE = 0.81) than did men with low arousal (M = 3.33, SE = 0.81) and women (M = 3.24, SE = 1.02). Functional connectivity of the alpha band predicted judgment of female facial attractiveness in men but not in women. After controlling for the age and variability, the prediction effect was still significant. CONCLUSION Our results provide neural evidence for the enhancement of the judgment of facial attractiveness in men with high arousal levels, which supports the hypothesis that individuals' spontaneous arousal contributes to variations in facial attractiveness preferences.
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Affiliation(s)
- Shangfeng Han
- Department of Psychology and Center for Brain and Cognitive Sciences, School of EducationGuangzhou UniversityGuangzhouChina
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Center for Brain Disorders and Cognitive Sciences, School of PsychologyShenzhen UniversityShenzhenChina
| | - Jie Gao
- School of Psychology, Sichuan Center of Applied PsychologyChengdu Medical CollegeChengduChina
| | - Wenjuan Xing
- College of Economics and ManagementQilu Normal UniversityJiningChina
| | - Xinyi Zhou
- Institute for Neuropsychological RehabilitationUniversity of Health and Rehabilitation SciencesQingdaoChina
| | - Yuejia Luo
- School of Psychology, Sichuan Center of Applied PsychologyChengdu Medical CollegeChengduChina
- Institute for Neuropsychological RehabilitationUniversity of Health and Rehabilitation SciencesQingdaoChina
- The State Key Lab of Cognitive and Learning, State Key Laboratory of Cognitive Neuroscience and Learning, Faculty of PsychologyBeijing Normal UniversityBeijingChina
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Zhao J, Wu M, Zhou L, Wang X, Jia J. Cognitive psychology-based artificial intelligence review. Front Neurosci 2022; 16:1024316. [PMID: 36278021 PMCID: PMC9582153 DOI: 10.3389/fnins.2022.1024316] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 09/13/2022] [Indexed: 12/02/2022] Open
Abstract
Most of the current development of artificial intelligence is based on brain cognition, however, this replication of biology cannot simulate the subjective emotional and mental state changes of human beings. Due to the imperfections of existing artificial intelligence, this manuscript summarizes and clarifies that artificial intelligence system combined with cognitive psychology is the research direction of artificial intelligence. It aims to promote the development of artificial intelligence and give computers human advanced cognitive abilities, so that computers can recognize emotions, understand human feelings, and eventually achieve dialog and empathy with humans and other artificial intelligence. This paper emphasizes the development potential and importance of artificial intelligence to understand, possess and discriminate human mental states, and argues its application value with three typical application examples of human–computer interaction: face attraction, affective computing, and music emotion, which is conducive to the further and higher level of artificial intelligence research.
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Affiliation(s)
- Jian Zhao
- School of Information Science and Technology, Northwest University, Xi’an, China
| | - Mengqing Wu
- School of Information Science and Technology, Northwest University, Xi’an, China
| | - Liyun Zhou
- School of Information Science and Technology, Northwest University, Xi’an, China
| | - Xuezhu Wang
- School of Information Science and Technology, Northwest University, Xi’an, China
| | - Jian Jia
- Medical Big Data Research Center, Northwest University, Xi’an, China
- School of Mathematics, Northwest University, Xi’an, China
- *Correspondence: Jian Jia,
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Han S, Shen J, Wang X, Guo Z, Liu S, Gan Y, Xu Q, Zhang L. The impact of repeated exposure on facial attractiveness: The role of cognition and emotion. CURRENT PSYCHOLOGY 2022. [DOI: 10.1007/s12144-022-03653-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Li X, Lei X, Xie R, Xu C, Chen S, Han C, Deng S. Good video game players look better: exploring the relationship between game skills, sexual dimorphism, and facial attractiveness. CURRENT PSYCHOLOGY 2022. [DOI: 10.1007/s12144-022-03454-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Han S, Hu J, Gao J, Fan J, Xu X, Xu P, Luo Y. Comparisons make faces more attractive: An ERP study. Brain Behav 2022; 12:e2561. [PMID: 35546305 PMCID: PMC9226814 DOI: 10.1002/brb3.2561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 01/25/2022] [Accepted: 02/27/2022] [Indexed: 11/12/2022] Open
Abstract
Facial attractiveness judgment largely depends on the characteristics of the facial structure and the personality of the observer. However, little is known about the influence of contextual variations on facial attractiveness. In this electroencephalogram study, participants judged the attractiveness of faces presented individually or in pairs with either a higher-attractive face (HAF) or lower-attractive face (LAF). The attractiveness judgment rating of the target face was significantly higher when presented in pairs with HAFs or LAFs than when presented individually and was accompanied by a larger late positive complex. These results suggest that contextual faces enhance the attractiveness judgment of target faces. Microstate analyses revealed that the global field power (GFP) of state 3 was significantly correlated with the attractiveness judgment in the HAF condition whereas the GFP of state 2 was significantly correlated with the attractiveness judgment in the LAF condition. Interestingly, the GFP of state 2 mediated the relationship between narcissism and facial attractiveness judgment in the context of LAFs. Source location analyses showed that states 3 and 2 activated the superior and middle frontal gyrus, which are involved in emotion processing. Our findings suggest that facial attractiveness can be enhanced by contextual comparison with other faces, subject to personality of the observer.
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Affiliation(s)
- Shangfeng Han
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen, China
| | - Jie Hu
- School of Psychology, Sichuan Center of Applied Psychology, Chengdu Medical College, Chengdu, China
| | - Jie Gao
- School of Psychology, Sichuan Center of Applied Psychology, Chengdu Medical College, Chengdu, China
| | - Jiayu Fan
- School of Psychology, Sichuan Center of Applied Psychology, Chengdu Medical College, Chengdu, China
| | - Xinyun Xu
- School of Psychology, Sichuan Center of Applied Psychology, Chengdu Medical College, Chengdu, China
| | - Pengfei Xu
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing, China.,Center for Emotion and Brain, Shenzhen Institute of Neuroscience, Shenzhen, 518057, China
| | - Yuejia Luo
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen, China.,School of Psychology, Sichuan Center of Applied Psychology, Chengdu Medical College, Chengdu, China.,Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing, China.,College of Teacher Education, Qilu Normal University, Jining, China.,The Center of Brain Science and Visual Cognition, Kunming University of Science and Technology, Kunming, China
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