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Predicting the long-term after-effects of rTMS in autism spectrum disorder using temporal variability analysis of scalp EEG

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资源类型：
WOS体系：
Pubmed体系：

收录情况： ◇ SCIE

作者：
Jiang Lin[1,2] * ; He Runyang[1,2] ; Li Yuqin[1,2] ; Yi Chanlin[1,2] ; Peng Yueheng[1,2] ; Yao Dezhong[1,2,3,4] ; Wang Yuping[5,6,7] ; Li Fali[1,2,4] ; Xu Peng[1,2,4,8] ; Yang Yingxue[5,6,7] ;
机构： [1]The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China. [2]School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China. [3]School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, People's Republic of China. [4]Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, People's Republic of China. [5]Department of Neurology, Xuanwu Hospital Capital Medical University, Beijing, People's Republic of China. [6]Beijing Key Laboratory of Neuromodulation, Beijing, People's Republic of China. [7]Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, People's Republic of China. [8]Radiation Oncology Key Laboratory of Sichuan Province, 610041 Chengdu, People's Republic of China.
出处：
DOI： 10.1088/1741-2552/ac999d
ISSN：

关键词： ASD rTMS therapy temporal variability resting-state EEG prediction

摘要：
Objective.Repetitive transcranial magnetic stimulation (rTMS) emerges as a useful therapy for autism spectrum disorder (ASD) clinically. Whereas the mechanisms of action of rTMS on ASD are not fully understood, and no biomarkers until now are available to reliably predict the follow-up rTMS efficacy in clinical practice.Approach.In the current work, the temporal variability was investigated in resting-state electroencephalogram of ASD patients, and the nonlinear complexity of related time-varying networks was accordingly evaluated by fuzzy entropy.Main results.The results showed the hyper-variability in the resting-state networks of ASD patients, while three week rTMS treatment alleviates the hyper fluctuations occurring in the frontal-parietal and frontal-occipital connectivity and further contributes to the ameliorative ASD symptoms. In addition, the changes in variability network properties are closely correlated with clinical scores, which further serve as potential predictors to reliably track the long-term rTMS efficacy for ASD.Significance.The findings consistently demonstrated that the temporal variability of time-varying networks of ASD patients could be modulated by rTMS, and related variability properties also help predict follow-up rTMS efficacy, which provides the potential for formulating individualized treatment strategies for ASD (ChiCTR2000033586).© 2022 IOP Publishing Ltd.

基金：
Project of Science and Technology Department of Sichuan Province (#2021YFSY0040, #2020ZYD013), the National Natural Science Foundation of China (#61961160705, #U19A2082, #62103085, #82102175, #81801124), the Science and Technology Development Fund, Macau SAR (File No. 0045/2019/AFJ), and the Scientific Research Foundation of Sichuan Provincial People’s Hospital (2021LY21).
语种：
外文
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WOS：
PubmedID：
中科院(CAS)分区：
出版当年[2021]版：
大类 | 2 区 工程技术
小类 | 3 区 工程：生物医学 3 区 神经科学
最新[2023]版：
大类 | 3 区 医学
小类 | 3 区 工程：生物医学 3 区 神经科学
JCR分区：
出版当年[2020]版：
Q1 ENGINEERING, BIOMEDICAL Q1 NEUROSCIENCES
最新[2023]版：
Q2 ENGINEERING, BIOMEDICAL Q2 NEUROSCIENCES

影响因子： 最新[2023版] 最新五年平均 出版当年[2020版] 出版当年五年平均 出版前一年[2019版] 出版后一年[2021版]

第一作者：
第一作者机构： [1]The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China. [2]School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China.
通讯作者：
通讯机构： [1]The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China. [2]School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China. [4]Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035 Chengdu, People's Republic of China. [5]Department of Neurology, Xuanwu Hospital Capital Medical University, Beijing, People's Republic of China. [6]Beijing Key Laboratory of Neuromodulation, Beijing, People's Republic of China. [7]Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, People's Republic of China. [8]Radiation Oncology Key Laboratory of Sichuan Province, 610041 Chengdu, People's Republic of China.
推荐引用方式(GB/T 7714)：
Jiang Lin,He Runyang,Li Yuqin,et al.Predicting the long-term after-effects of rTMS in autism spectrum disorder using temporal variability analysis of scalp EEG[J].JOURNAL OF NEURAL ENGINEERING.2022,19(5):doi:10.1088/1741-2552/ac999d.
APA：
Jiang Lin,He Runyang,Li Yuqin,Yi Chanlin,Peng Yueheng...&Yang Yingxue.(2022).Predicting the long-term after-effects of rTMS in autism spectrum disorder using temporal variability analysis of scalp EEG.JOURNAL OF NEURAL ENGINEERING,19,(5)
MLA：
Jiang Lin,et al."Predicting the long-term after-effects of rTMS in autism spectrum disorder using temporal variability analysis of scalp EEG".JOURNAL OF NEURAL ENGINEERING 19..5(2022)

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