Phase Transfer Entropy to Assess Nonlinear Functional Corticokinematic Coupling

被引:0
作者
Peng, Jialin [1 ]
Zha, Fubing [2 ]
Xie, Tianzhe [1 ]
Yuan, Kai [3 ]
Tong, Kai-Yu [3 ]
Bao, Shi-Chun [1 ,4 ]
机构
[1] Natl Innovat Ctr Adv Med Devices, Shenzhen, Peoples R China
[2] Shenzhen Univ, Affiliated Hosp 1, Dept Rehabil, Shenzhen, Peoples R China
[3] Chinese Univ Hong Kong, Dept Biomed Engn, Hong Kong, Peoples R China
[4] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China
来源
2023 11TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING, NER | 2023年
基金
国家重点研发计划;
关键词
corticokinematic coupling; nonlinear neural coupling; phase transfer entropy; PASSIVE FINGER; COHERENCE;
D O I
10.1109/NER52421.2023.10123763
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To understand the mechanism of complex human sensorimotor control system, it is necessary to investigate the functional relationship between the cortex and peripheral movement. Typical cortico-peripheral interaction measures include corticomuscular coupling and corticokinematic coupling (CKC). Functional CKC reflects movement-related proprioceptive inputs, it could be through kinematics and physiological signals. The process consists of both linear and nonlinear properties of the whole neuromotor control system. Previous studies mainly applied linear techniques to assess the functional coupling between the cortex and periphery, but the nonlinear coupling properties were rarely discussed. In this preliminary study, 128 channels of electroencephalography (EEG) and 3-axis acceleration (ACC) signals were acquired for both dominant and non-dominant hand in four healthy participants during passive finger movement stimulus. Corticokinematic coherence and partial directed coherence analysis was performed to investigate linear coupling and directionality between EEG and ACC during movement, special concerns were focused at stimulus frequency (3Hz) and its harmonics. Further, we utilized phase transfer entropy to characterize top-down and bottom-up nonlinear cortico- peripheral information flow, and for the first time, we found typical nonlinear coupling patterns between the cortex and periphery during passive movement tasks. Such results might facilitate our understanding of human sensorimotor control system and imply potential clinical applications.
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页数:4
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