Connectivity analysis of hypsarrhythmia-EEG for infants with West syndrome

doi:10.1109/TNSRE.2025.3569226

	Connectivity analysis of hypsarrhythmia-EEG for infants with West syndrome
	Lian, Di 1; Guo, Qiongru2 ; Zhao, Zihao2 ; He, Wenyuan 3; Yan, Yumei 1; Hou, Ruolin 1; Wang, Xiaoqiang 6; Li, Yuanning4 ; Bao, Weiqun 1; He, Dake 1; Xu, Lin2,5
	2025
发表期刊	IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING (IF:4.8[JCR-2023],5.4[5-Year])
ISSN	1534-4320
卷号	33 页码:1898-1906
发表状态	已发表
DOI	10.1109/TNSRE.2025.3569226
摘要	Detection of hypsarrhythmia electroencephalography (EEG) in infants with West syndrome (WS) is currently performed by manual inspection of long-term video/EEG recording, producing low inter-rater reliability. Existing studies aiming at exploring digital biomarkers for hypsarrhythmia EEG focus mainly on the temporal and spectral features. The aim of the present study is to explore the spatial distribution and connection of hypsarrhythmia EEG by analysing the brain functional connectivity (BFC) of WS patients and thus to identify possible biomarkers for hypsarrhythmia EEG. To this end, hypsarrhythmia and non-hypsarrhythmia EEG segments were extracted from 107 WS patients, and normal EEG segments were extracted from 155 healthy controls (HCs). Five connectivity metrics, including Pearson correlation coefficient, phase locking value, phase lag index, magnitude-squared coherence (MSC), and time-frequency cross mutual information (TFCMI), were utilized to build the BFC in different EEG sub-bands. Besides, graph theory was employed to estimate the topological parameters of each network, including clustering coefficient, characteristic path length, global efficiency, and local efficiency. Our results show enhanced brain connectivity in WS patients during hypsarrhythmia periods as compared with non-hypsarrhythmia and HCs. The statistical analysis determines significant difference ( ${p}\lt {0}.{05}$ ) in a number of network topological parameters, particularly derived from MSC- and TFCMI-based networks, between hypsarrhythmia EEG and non-hypsarrhythmia EEG or HCs. These findings suggest the BFC topology parameters to be promising biomarkers for hypsarrhythmia detection, possibly leading to the development of automatic tools for efficient and reliable WS diagnosis.
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收录类别	SCIE
语种	英语
来源库	IEEE
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/496940
专题	生物医学工程学院信息科学与技术学院_硕士生信息科学与技术学院_PI研究组_徐林组生物医学工程学院_PI研究组_李远宁
共同第一作者	Guo, Qiongru; Zhao, Zihao
通讯作者	Li, Yuanning; Bao, Weiqun; He, Dake; Xu, Lin
作者单位	1.Shanghai Jiao Tong Univ, Xinhua Hosp, Sch Med, Dept Pediat Neurol, Shanghai 200092, Peoples R China 2.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China 3.Univ Melbourne, Sch Biomed Sci, Parkville, Vic 3010, Australia 4.ShanghaiTech Univ, Sch Biomed Engn, Shanghai 201210, Peoples R China 5.Shanghai Engn Res Ctr Energy Efficient & Custom AI, Shanghai 201210, Peoples R China 6.Shanghai Jiao Tong Univ, Xinhua Hosp, Dept Pediat Neurosurg, Sch Med, Shanghai 200092, Peoples R China
通讯作者单位	生物医学工程学院; 信息科学与技术学院
推荐引用方式 GB/T 7714	Lian, Di,Guo, Qiongru,Zhao, Zihao,et al. Connectivity analysis of hypsarrhythmia-EEG for infants with West syndrome[J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,2025,33:1898-1906.
APA	Lian, Di.,Guo, Qiongru.,Zhao, Zihao.,He, Wenyuan.,Yan, Yumei.,...&Xu, Lin.(2025).Connectivity analysis of hypsarrhythmia-EEG for infants with West syndrome.IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,33,1898-1906.
MLA	Lian, Di,et al."Connectivity analysis of hypsarrhythmia-EEG for infants with West syndrome".IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING 33(2025):1898-1906.