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Directed network analysis reveals changes in cortical and muscular connectivity caused by different standing balance tasks

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机构: [1]Hebei Univ, Key Lab Digital Med Engn Hebei Prov, Baoding 071002, Peoples R China [2]Yanshan Univ, Inst Elect Engn, Qinhuangdao 066004, Hebei, Peoples R China [3]Hebei Univ, Dev Planning Off, Affiliated Hosp, Baoding 071002, Peoples R China
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关键词: standing balance EEG network EMG corticomuscular coupling

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Objective. Standing balance forms the basis of daily activities that require the integration of multi-sensory information and coordination of multi-muscle activation. Previous studies have confirmed that the cortex is directly involved in balance control, but little is known about the neural mechanisms of cortical integration and muscle coordination in maintaining standing balance. Approach. We used a direct directed transfer function (dDTF) to analyze the changes in the cortex and muscle connections of healthy subjects (15 subjects: 13 male and 2 female) corresponding to different standing balance tasks. Main results. The results show that the topology of the EEG brain network and muscle network changes significantly as the difficulty of the balancing tasks increases. For muscle networks, the connection analysis shows that the connection of antagonistic muscle pairs plays a major role in the task. For EEG brain networks, graph theory-based analysis shows that the clustering coefficient increases significantly, and the characteristic path length decreases significantly with increasing task difficulty. We also found that cortex-to-muscle connections increased with the difficulty of the task and were significantly stronger than the muscle-to-cortex connections. Significance. These results show that changes in the difficulty of balancing tasks alter EEG brain networks and muscle networks, and an analysis based on the directed network can provide rich information for exploring the neural mechanisms of balance control.

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出版当年[2023]版:
大类 | 3 区 医学
小类 | 3 区 工程:生物医学 3 区 神经科学
最新[2025]版:
大类 | 3 区 医学
小类 | 3 区 工程:生物医学 3 区 神经科学
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出版当年[2022]版:
Q2 ENGINEERING, BIOMEDICAL Q2 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[2022版] 出版当年五年平均 出版前一年[2021版] 出版后一年[2023版]

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第一作者机构: [1]Hebei Univ, Key Lab Digital Med Engn Hebei Prov, Baoding 071002, Peoples R China [2]Yanshan Univ, Inst Elect Engn, Qinhuangdao 066004, Hebei, Peoples R China
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通讯机构: [1]Hebei Univ, Key Lab Digital Med Engn Hebei Prov, Baoding 071002, Peoples R China [3]Hebei Univ, Dev Planning Off, Affiliated Hosp, Baoding 071002, Peoples R China
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