Similar brains blend emotion in similar ways: Neural representations of individual difference in emotion profiles

心理学 透视图(图形) 认知心理学 背景(考古学) 情绪分类 构造(python库) 脑电图 情感表达 人工智能 神经科学 计算机科学 生物 古生物学 程序设计语言
作者
Xin Hu,Fei Wang,Dan Zhang
出处
期刊:NeuroImage [Elsevier]
卷期号:247: 118819-118819 被引量:41
标识
DOI:10.1016/j.neuroimage.2021.118819
摘要

Our daily emotional experience is a complex construct that usually involves multiple emotions blended in a context-dependent manner. However, the co-occurring and context-dependent nature of human emotions was understated in previous studies when addressing the individual difference in emotional experiences. The present study proposed a situated and blended 'profile' perspective to characterize individualized emotional experiences. Eighty participants watched a series of emotional videos with their EEG recorded, and the individual differences in their emotion profiles were measured as the vector distances between their multidimensional emotion ratings for these video stimuli. This measure was found to be a reliable descriptor of individualized emotional experiences and could efficiently predict classical emotional complexity indices. More importantly, inter-subject representational analyses revealed that similar emotion profiles were associated with similar delta-band activities over the prefrontal and temporo-parietal regions and similar theta-band activities over the frontal regions. Furthermore, left- and right-lateralized temporo-parietal representations were observed for positive and negative emotion profiles, respectively. Our findings demonstrate the potential of taking a 'profile' perspective for understanding individual differences in human emotions.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
zzx完成签到,获得积分10
1秒前
何何完成签到 ,获得积分10
1秒前
jackhlj完成签到,获得积分10
1秒前
香蕉觅云应助乐小佳采纳,获得10
2秒前
大胆夜绿完成签到,获得积分10
2秒前
青wu完成签到,获得积分10
2秒前
3秒前
竹筏过海应助锦鲤云间月采纳,获得30
3秒前
菠萝吹雪遇见梨花诗完成签到 ,获得积分10
3秒前
杨天水发布了新的文献求助10
4秒前
4秒前
VDC应助梁liang采纳,获得30
4秒前
chen发布了新的文献求助10
4秒前
4秒前
青wu发布了新的文献求助10
5秒前
a龙完成签到,获得积分10
5秒前
眯眯眼的老鼠完成签到,获得积分20
5秒前
无花果应助科研通管家采纳,获得10
5秒前
斯文败类应助科研通管家采纳,获得10
6秒前
wanci应助嗯哼采纳,获得10
6秒前
nanan完成签到,获得积分10
6秒前
6秒前
星辰大海应助科研通管家采纳,获得10
6秒前
Hungrylunch应助科研通管家采纳,获得20
6秒前
Cassie应助科研通管家采纳,获得10
6秒前
爆米花应助科研通管家采纳,获得10
6秒前
酷波er应助科研通管家采纳,获得10
6秒前
科研通AI2S应助科研通管家采纳,获得10
6秒前
暴躁四叔应助科研通管家采纳,获得20
6秒前
Zn应助科研通管家采纳,获得10
6秒前
6秒前
科研通AI5应助科研通管家采纳,获得30
7秒前
Zn应助科研通管家采纳,获得10
7秒前
7秒前
AN应助科研通管家采纳,获得10
7秒前
7秒前
控制小弟应助科研通管家采纳,获得10
7秒前
爆米花应助科研通管家采纳,获得10
7秒前
7秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527304
求助须知:如何正确求助?哪些是违规求助? 3107454
关于积分的说明 9285518
捐赠科研通 2805269
什么是DOI,文献DOI怎么找? 1539827
邀请新用户注册赠送积分活动 716708
科研通“疑难数据库(出版商)”最低求助积分说明 709672