Altered large-scale functional brain networks in neurological Wilson’s disease

被引:0
|
作者
Rixing Jing
Yongsheng Han
Hewei Cheng
Yongzhu Han
Kai Wang
Daniel Weintraub
Yong Fan
机构
[1] Chinese Academy of Sciences,National Laboratory of Pattern Recognition, Institute of Automation
[2] University of Chinese Academy of Sciences,Institute of Neurology
[3] Anhui University of Chinese Medicine,Department of Biomedical Engineering, School of Bioinformatics
[4] Chongqing University of Posts and Telecommunications,Department of Neurology
[5] The First Affiliated Hospital of Anhui Medical University,Section of Geriatric Psychiatry, Perelman School of Medicine
[6] University of Pennsylvania,Department of Radiology, Perelman School of Medicine
[7] University of Pennsylvania,undefined
来源
关键词
Wilson’s disease; Large-scale functional brain networks; Functional magnetic resonance images; Machine learning; Biomarkers;
D O I
暂无
中图分类号
学科分类号
摘要
Wilson’s disease patients with neurological symptoms have motor symptoms and cognitive deficits, including frontal executive, visuospatial processing, and memory impairments. Although the brain structural abnormalities associated with Wilson’s disease have been documented, it remains largely unknown how Wilson’s disease affects large-scale functional brain networks. In this study, we investigated functional brain networks in Wilson’s disease. Particularly, we analyzed resting state functional magnetic resonance images of 30 Wilson’s disease patients and 26 healthy controls. First, functional brain networks for each participant were extracted using an independent component analysis method. Then, a computationally efficient pattern classification method was developed to identify discriminative brain functional networks associated with Wilson’s disease. Experimental results indicated that Wilson’s disease patients, compared with healthy controls, had altered large-scale functional brain networks, including the dorsal anterior cingulate cortex and basal ganglia network, the middle frontal gyrus, the dorsal striatum, the inferior parietal lobule, the precuneus, the temporal pole, and the posterior lobe of cerebellum. Classification models built upon these networks distinguished between neurological WD patients and HCs with accuracy up to 86.9% (specificity: 86.7%, sensitivity: 89.7%). The classification scores were correlated with the United Wilson’s Disease Rating Scale measures and durations of disease of the patients. These results suggest that Wilson’s disease patients have multiple aberrant brain functional networks, and classification scores derived from these networks are associated with severity of clinical symptoms.
引用
收藏
页码:1445 / 1455
页数:10
相关论文
共 50 条
  • [41] Unified Wilson's Disease Rating Scale - a proposal for the neurological scoring of Wilson's disease patients
    Cztonkowska, Anna
    Tarnacka, Beata
    Moeller, Jens Carsten
    Leinweber, Barbara
    Bandmann, Oliver
    Woimant, France
    Oertel, Wolfgang H.
    NEUROLOGIA I NEUROCHIRURGIA POLSKA, 2007, 41 (01) : 1 - 12
  • [42] Altered topological patterns of brain functional networks in Crohn’s disease
    Peng Liu
    Ru Li
    Chunhui Bao
    Ying Wei
    Yingying Fan
    Yanfei Liu
    Geliang Wang
    Huangan Wu
    Wei Qin
    Brain Imaging and Behavior, 2018, 12 : 1466 - 1478
  • [43] Competitive and cooperative dynamics of large-scale brain functional networks supporting recollection
    Fornito, Alex
    Harrison, Ben J.
    Zalesky, Andrew
    Simons, Jon S.
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2012, 109 (31) : 12788 - 12793
  • [44] Topological variations of large-scale brain functional networks based on mutual information
    Zhang, Jian
    Cai, Shi-Min
    Fu, Zhong-Qian
    Zhou, Pei-Ling
    2010 4TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING (ICBBE 2010), 2010,
  • [45] Stress-induced alterations in large-scale functional networks of the rodent brain
    Henckens, Marloes J. A. G.
    van der Marel, Kajo
    van der Toorn, Annette
    Pillai, Anup G.
    Fernandez, Guillen
    Dijkhuizen, Rick M.
    Joels, Marian
    NEUROIMAGE, 2015, 105 : 312 - 322
  • [46] Developmental differences of large-scale functional brain networks for spoken word processing
    Liu, Xin
    He, Yin
    Gao, Yue
    Booth, James R.
    Zhang, Lihuan
    Zhang, Shudong
    Lu, Chunming
    Liu, Li
    BRAIN AND LANGUAGE, 2022, 231
  • [47] Electrophysiological correlates of the brain's intrinsic large-scale functional architecture
    He, Biyu J.
    Snyder, Abraham Z.
    Zempel, John M.
    Smyth, Matthew D.
    Raichle, Marcus E.
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2008, 105 (41) : 16039 - 16044
  • [48] Structural instability of large-scale functional networks
    Mizutaka, Shogo
    Yakubo, Kousuke
    PLOS ONE, 2017, 12 (07):
  • [49] Altered interplay among large-scale brain functional networks underpins multi-domain anosognosia in early-AD
    Bermejo, Jose Manuel Valera
    De Marco, Matteo
    Venneri, Annalena
    JOURNAL OF THE NEUROLOGICAL SCIENCES, 2021, 429
  • [50] Large-scale brain networks in affective and social neuroscience: towards an integrative functional architecture of the brain
    Barrett, Lisa Feldman
    Satpute, Ajay Bhaskar
    CURRENT OPINION IN NEUROBIOLOGY, 2013, 23 (03) : 361 - 372