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A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test
Li, Xuan1; Wu, Yunqiao1; Wei, Mengting2; Guo, Yiyun3; Yu, Zhenhua4; Wang, Haixian1; Li, Zhanli4; Fan, Hui5
First AuthorLi, Xuan
Correspondent (haixian wang ) ; (zhanli li )
Contribution Rank2

Phase synchronization has been an effective measurement of functional connectivity, detecting similar dynamics over time among distinct brain regions. However, traditional phase synchronization-based functional connectivity indices have been proved to have some drawbacks. For example, the phase locking value (PLV) index is sensitive to volume conduction, while the phase lag index (PLI) and the weighted phase lag index (wPLI) are easily affected by noise perturbations. In addition, thresholds need to be applied to these indices to obtain the binary adjacency matrix that determines the connections. However, the selection of the thresholds is generally arbitrary. To address these issues, in this paper we propose a novel index of functional connectivity, named the phase lag based on the Wilcoxon signed-rank test (PLWT). Specifically, it characterizes the functional connectivity based on the phase lag with a weighting procedure to reduce the influence of volume conduction and noise. Besides, it automatically identifies the important connections without relying on thresholds, by taking advantage of the framework of the Wilcoxon signed-rank test. The performance of the proposed PLWT index is evaluated on simulated electroencephalograph (EEG) datasets, as well as on two resting-state EEG datasets. The experimental results on the simulated EEG data show that the PLWT index is robust to volume conduction and noise. Furthermore, the brain functional networks derived by PLWT on the real EEG data exhibit a reasonable scale-free characteristic and high test-retest (TRT) reliability of graph measures. We believe that the proposed PLWT index provides a useful and reliable tool to identify the underlying neural interactions, while effectively diminishing the influence of volume conduction and noise.

KeywordPhase synchronization Volume conduction Wilcoxon signed-rank test Graph measures Scale-free characteristic Test– retest reliability
Indexed BySCI
Funding ProjectNational Natural Science Foundation of China[61773114] ; Key Research and Development Plan (Industry Foresight and Common Key Technology) of Jiangsu Province[BE2017007-1]
WOS Research AreaNeurosciences & Neurology
WOS SubjectNeurosciences
WOS IDWOS:000585717800001
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Corresponding AuthorWang, Haixian; Li, Zhanli
Affiliation1.Southeast Univ, Sch Biol Sci & Med Engn, Minist Educ, Key Lab Child Dev & Learning Sci, Nanjing 210096, Jiangsu, Peoples R China
2.Chinese Acad Sci, Inst Psychol, Beijing 100101, Peoples R China
3.Qingdao Port Int Co Ltd, Qingdao 266011, Shandong, Peoples R China
4.Xian Univ Sci & Technol, Coll Comp Sci & Technol, Xian 710054, Shaanxi, Peoples R China
5.Shandong Technol & Business Univ, Coinnovat Ctr, Shandong Coll & Univ Future Intelligent Comp, Yantai 264005, Shandong, People's Republ
Recommended Citation
GB/T 7714
Li, Xuan,Wu, Yunqiao,Wei, Mengting,et al. A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test[J]. COGNITIVE NEURODYNAMICS,2020:16.
APA Li, Xuan.,Wu, Yunqiao.,Wei, Mengting.,Guo, Yiyun.,Yu, Zhenhua.,...&Fan, Hui.(2020).A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test.COGNITIVE NEURODYNAMICS,16.
MLA Li, Xuan,et al."A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test".COGNITIVE NEURODYNAMICS (2020):16.
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