Learning functional brain networks with heterogeneous connectivities for brain disease identification

被引:1
|
作者
Zhang, Chaojun [1 ,2 ]
Ma, Yunling [1 ]
Qiao, Lishan [1 ]
Zhang, Limei [1 ]
Liu, Mingxia [3 ,4 ]
机构
[1] Shandong Jianzhu Univ, Sch Comp Sci & Technol, Jinan 250101, Shandong, Peoples R China
[2] Hainan Univ, Sch Comp Sci & Technol, Haikou 570228, Hainan, Peoples R China
[3] Univ North Carolina Chapel Hill, Dept Radiol, Chapel Hill, NC 27599 USA
[4] Univ North Carolina Chapel Hill, BRIC, Chapel Hill, NC 27599 USA
基金
中国国家自然科学基金;
关键词
Functional brain network; Neurological disorder; Mental disorder; Improved orthogonal matching pursuit; Heterogeneous connectivity;
D O I
10.1016/j.neunet.2024.106660
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Functional brain networks (FBNs), which are used to portray interactions between different brain regions, have been widely used to identify potential biomarkers of neurological and mental disorders. The FBNs estimated using current methods tend to be homogeneous, indicating that different brain regions exhibit the same type of correlation. This homogeneity limits our ability to accurately encode complex interactions within the brain. Therefore, to the best of our knowledge, in the present study, for the first time, we propose the existence of heterogeneous FBNs and introduce a novel FBN estimation model that adaptively assigns heterogeneous connections to different pairs of brain regions, thereby effectively encoding the complex interaction patterns in the brain. Specifically, we first construct multiple types of candidate correlations from different views or based on different methods and then develop an improved orthogonal matching pursuit algorithm to select at most one correlation for each brain region pair under the guidance of label information. These adaptively estimated heterogeneous FBNs were then used to distinguish subjects with neurological/mental disorders from healthy controls and identify potential biomarkers related to these disorders. Experimental results on real datasets show that the proposed scheme improves classification performance by 7.07% and 7.58% at the two sites, respectively, compared with the baseline approaches. This emphasizes the plausibility of the heterogeneity hypothesis and effectiveness of the heterogeneous connection assignment algorithm.
引用
收藏
页数:12
相关论文
共 50 条
  • [21] The Brain's Heterogeneous Functional Landscape
    McCaffrey, Joseph B.
    PHILOSOPHY OF SCIENCE, 2015, 82 (05) : 1010 - 1022
  • [22] Functional Connectivities in the Brain That Mediate the Association Between Depressive Problems and Sleep Quality
    Cheng, Wei
    Rolls, Edmund T.
    Ruan, Hongtao
    Feng, Jianfeng
    JAMA PSYCHIATRY, 2018, 75 (10) : 1052 - 1061
  • [23] Fetal functional imaging portrays heterogeneous development of emerging human brain networks
    Jakab, Andras
    Schwartz, Ernst
    Kasprian, Gregor
    Gruber, Gerlinde M.
    Prayer, Daniela
    Schoepf, Veronika
    Langs, Georg
    FRONTIERS IN HUMAN NEUROSCIENCE, 2014, 8
  • [24] Brain anomaly networks uncover heterogeneous functional reorganization patterns after stroke
    Zou, Yong
    Zhao, Zhiyong
    Yin, Dazhi
    Fan, Mingxia
    Small, Michael
    Liu, Zonghua
    Hilgetag, Claus C.
    Kurths, Juergen
    NEUROIMAGE-CLINICAL, 2018, 20 : 523 - 530
  • [25] Disrupted structural and functional brain networks in Alzheimer's disease
    Dai, Zhengjia
    Lin, Qixiang
    Li, Tao
    Wang, Xiao
    Yuan, Huishu
    Yu, Xin
    He, Yong
    Wang, Huali
    NEUROBIOLOGY OF AGING, 2019, 75 : 71 - 82
  • [26] Functional Brain Networks and Cognitive Deficits in Parkinson's Disease
    Baggio, Hugo-Cesar
    Sala-Llonch, Roser
    Segura, Barbara
    Marti, Maria-Jose
    Valldeoriola, Francesc
    Compta, Yaroslau
    Tolosa, Eduardo
    Junque, Carme
    HUMAN BRAIN MAPPING, 2014, 35 (09) : 4620 - 4634
  • [27] Hyper-connectivity of functional networks for brain disease diagnosis
    Jie, Biao
    Wee, Chong-Yaw
    Shen, Dinggang
    Zhang, Daoqiang
    MEDICAL IMAGE ANALYSIS, 2016, 32 : 84 - 100
  • [28] Negative functional brain networks
    Fabrizio Parente
    Marianna Frascarelli
    Alessia Mirigliani
    Fabio Di Fabio
    Massimo Biondi
    Alfredo Colosimo
    Brain Imaging and Behavior, 2018, 12 : 467 - 476
  • [29] Describing functional diversity of brain regions and brain networks
    Anderson, Michael L.
    Kinnison, Josh
    Pessoa, Luiz
    NEUROIMAGE, 2013, 73 : 50 - 58
  • [30] Structure of Brain Functional Networks
    Kuchaiev, Oleksii
    Wang, Po T.
    Nenadic, Zoran
    Przulj, Natasa
    2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20, 2009, : 4166 - +