Gene expression associated with human brain activations in facial expression recognition

被引:0
|
作者
Zirui Wang
Yuan Ji
Yumeng Fu
Feng Liu
Xin Du
Huaigui Liu
Wenshuang Zhu
Kaizhong Xue
Wen Qin
Quan Zhang
机构
[1] Tianjin Medical University General Hospital,Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging
来源
关键词
Emotion; Facial expression recognition; Magnetic resonance imaging; Gene expression; Allen Human Brain Atlas;
D O I
暂无
中图分类号
学科分类号
摘要
Previous studies identified some genetic loci of emotion, but few focused on human emotion-related gene expression. In this study, the facial expression recognition (FER) task-based high-resolution fMRI data of 203 subjects in the Human Connectome Project (HCP) and expression data of the six healthy human postmortem brain tissues in the Allen Human Brain Atlas (AHBA) were used to conduct a transcriptome-neuroimaging spatial association analysis. Finally, 371 genes were identified to be significantly associated with FER-related brain activations. Enrichment analyses revealed that FER-related genes were mainly expressed in the brain, especially neurons, and might be related to cell junction organization, synaptic functions, and nervous system development regulation, indicating that FER was a complex polygenetic biological process involving multiple pathways. Moreover, these genes exhibited higher enrichment for psychiatric diseases with heavy emotion impairments. This study provided new insight into understanding the FER-related biological mechanisms and might be helpful to explore treatment methods for emotion-related psychiatric disorders.
引用
收藏
页码:1657 / 1670
页数:13
相关论文
共 50 条
  • [41] Facial Expression Recognition Using Facial Graph
    Mohseni, Sina
    Zarei, Niloofar
    Miandji, Ehsan
    FACE AND FACIAL EXPRESSION RECOGNITION FROM REAL WORLD VIDEOS, 2015, 8912 : 58 - 66
  • [42] Facial Expression Recognition on partial facial sections
    Melaugh, Ryan
    Siddique, Nazmul
    Coleman, Sonya
    Yogarajah, Pratheepan
    PROCEEDINGS OF THE 2019 11TH INTERNATIONAL SYMPOSIUM ON IMAGE AND SIGNAL PROCESSING AND ANALYSIS (ISPA 2019), 2019, : 193 - 197
  • [43] Understanding the recognition of facial identity and facial expression
    Andrew J. Calder
    Andrew W. Young
    Nature Reviews Neuroscience, 2005, 6 : 641 - 651
  • [44] Understanding the recognition of facial identity and facial expression
    Calder, AJ
    Young, AW
    NATURE REVIEWS NEUROSCIENCE, 2005, 6 (08) : 641 - 651
  • [45] The Use of Facial Features in Facial Expression Recognition
    Neath, Karly
    Itier, Roxane J.
    CANADIAN JOURNAL OF EXPERIMENTAL PSYCHOLOGY-REVUE CANADIENNE DE PSYCHOLOGIE EXPERIMENTALE, 2012, 66 (04): : 285 - 285
  • [46] Recognition and Analysis of Human Facial Expression: A PSO Optimization Method
    Li, Zhijie
    Duan, Xiaodong
    Wang, Cunrui
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING AND INTELLIGENT SYSTEMS (ICMEIS 2015), 2015, 26 : 419 - 422
  • [47] The Applications of Facial Expression Recognition in Human-computer Interaction
    Wang, Huan-Huan
    Gu, Jing-Wei
    PROCEEDINGS OF THE 2018 IEEE INTERNATIONAL CONFERENCE ON ADVANCED MANUFACTURING (IEEE ICAM), 2018, : 288 - 291
  • [48] Facial expression recognition based upon human cognitive regions
    Zhang, Huiquan
    Luo, Sha
    Yoshie, Osamu
    IEEJ Transactions on Electronics, Information and Systems, 2014, 134 (08) : 1148 - 1156
  • [49] Human facial expression recognition based on learning subspace method
    Chen, XL
    Kwong, S
    Lu, Y
    2000 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, PROCEEDINGS VOLS I-III, 2000, : 403 - 406
  • [50] HUMAN-MACHINE INTERACTION IN FACIAL EXPRESSION RECOGNITION SYSTEM
    Suresh, K.
    Chellappan, C.
    IIOAB JOURNAL, 2016, 7 : 305 - 312