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Atomic Dynamic Functional Interaction Patterns for Characterization of ADHD
Ou, Jinli1; Lian, Zhichao2; Xie, Li1; Li, Xiang3,4; Wang, Peng5; Hao, Yun6; Zhu, Dajiang3,4; Jiang, Rongxin1; Wang, Yufeng5; Chen, Yaowu1; Zhang, Jing2; Liu, Tianming3,4
关键词brain networks functional interaction temporal dynamics nonnegative matrix factorization ADHD
刊名HUMAN BRAIN MAPPING
2014-10-01
DOI10.1002/hbm.22548
35期:10页:5262-5278
收录类别SCI
文章类型Article
WOS标题词Science & Technology
类目[WOS]Neurosciences ; Neuroimaging ; Radiology, Nuclear Medicine & Medical Imaging
研究领域[WOS]Neurosciences & Neurology ; Radiology, Nuclear Medicine & Medical Imaging
关键词[WOS]NONNEGATIVE MATRIX FACTORIZATION ; BRAIN NETWORKS ; CONNECTIVITY ; MODEL ; SCHIZOPHRENIA ; FLUCTUATIONS ; LOCALIZATION ; PROFILES ; CLUSTERS ; NUMBER
英文摘要

Modeling abnormal temporal dynamics of functional interactions in psychiatric disorders has been of great interest in the neuroimaging field, and thus a variety of methods have been proposed so far. However, the temporal dynamics and disease-related abnormalities of functional interactions within specific data-driven discovered subnetworks have been rarely explored yet. In this work, we propose a novel computational framework composed of an effective Bayesian connectivity change point model for modeling functional brain interactions and their dynamics simultaneously and an effective variant of nonnegative matrix factorization for assessing the functional interaction abnormalities within subnetworks. This framework has been applied on the resting state fmagnetic resonance imaging (fMRI) datasets of 23 children with attention-deficit/hyperactivity disorder (ADHD) and 45 normal control (NC) children, and has revealed two atomic functional interaction patterns (AFIPs) discovered for ADHD and another two AFIPs derived for NC. Together, these four AFIPs could be grouped into two pairs, one common pair representing the common AFIPs in ADHD and NC, and the other abnormal pair representing the abnormal AFIPs in ADHD. Interestingly, by comparing the abnormal AFIP pair, two data-driven abnormal functional subnetworks are derived. Strikingly, by evaluating the approximation based on the four AFIPs, all of the ADHD children were successfully differentiated from NCs without any false positive. Hum Brain Mapp 35:5262-5278, 2014. (c) 2014 Wiley Periodicals, Inc.

语种英语
WOS记录号WOS:000342667400023
项目编号R01 DA-033393 ; R01 AG-042599 ; IIS-1149260 ; CBET-1302089
资助机构NIH ; NSF ; Yale University
引用统计
被引频次:12[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.bjmu.edu.cn/handle/400002259/65060
专题北京大学精神卫生研究所
作者单位1.Zhejiang Univ, Sch Biomed Engn & Instrument Sci, Hangzhou 310003, Zhejiang, Peoples R China
2.Univ Georgia, Dept Comp Sci, Cort Architecture Imaging & Discovery Lab, Athens, GA 30602 USA
3.Univ Georgia, Bioimaging Res Ctr, Athens, GA 30602 USA
4.Yale Univ, Dept Stat, New Haven, CT 06520 USA
5.Peking Univ, Inst Mental Hlth, Beijing 100871, Peoples R China
6.Fudan Univ, Sch Life Sci, Shanghai 200433, Peoples R China
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GB/T 7714
Ou, Jinli,Lian, Zhichao,Xie, Li,et al. Atomic Dynamic Functional Interaction Patterns for Characterization of ADHD[J]. HUMAN BRAIN MAPPING,2014,35(10):5262-5278.
APA Ou, Jinli.,Lian, Zhichao.,Xie, Li.,Li, Xiang.,Wang, Peng.,...&Liu, Tianming.(2014).Atomic Dynamic Functional Interaction Patterns for Characterization of ADHD.HUMAN BRAIN MAPPING,35(10),5262-5278.
MLA Ou, Jinli,et al."Atomic Dynamic Functional Interaction Patterns for Characterization of ADHD".HUMAN BRAIN MAPPING 35.10(2014):5262-5278.
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