Abstract：
BACKGROUND: Repetitive mild traumatic brain injury (rmTBI) often occurs in individuals engaged in contact sports, particularly boxing. This study aimed to elucidate the effects of rmTBI on phase-locking value (PLV)-based graph theory and functional network architecture in individuals with boxing-related injuries in five frequency bands by employing resting-state electroencephalography (EEG).
METHODS: Twenty-fore professional boxers and 25 matched healthy controls were recruited to perform a resting-state task, and their noninvasive scalp EEG data were collected simultaneously. Based on the construction of PLV matrices for boxers and controls, phase synchronization and graph-theoretic characteristics were identified in each frequency band. The significance of the calculated functional brain networks between the two populations was analyzed using a network-based statistical (NBS) approach.
RESULTS: Compared to controls, boxers exhibited an increasing trend in PLV synchronization and notable differences in the distribution of functional centers, especially in the gamma frequency band. Additionally, attenuated nodal network parameters and decreased small-world measures were observed in the theta, beta, and gamma bands, suggesting that the functional network efficiency and small-world characteristics were significantly weakened in boxers. NBS analysis revealed that boxers exhibited a significant increase in network connectivity strength compared to controls in the theta, beta, and gamma frequency bands. The functional connectivity of the significance subnetworks exhibited an asymmetric distribution between the bilateral hemispheres, indicating that the optimized organization of information integration and segregation for the resting-state networks was imbalanced and disarranged for boxers.
CONCLUSIONS: This is the first study to investigate the underlying deficits in PLV-based graph-theoretic characteristics and NBS-based functional networks in patients with rmTBI from the perspective of whole-brain resting-state EEG. Joint analyses of distinctive graph-theoretic representations and asymmetrically hyperconnected subnetworks in specific frequency bands may serve as an effective method to assess the underlying deficiencies in resting-state network processing in patients with sports-related rmTBI.
METHODS: Twenty-fore professional boxers and 25 matched healthy controls were recruited to perform a resting-state task, and their noninvasive scalp EEG data were collected simultaneously. Based on the construction of PLV matrices for boxers and controls, phase synchronization and graph-theoretic characteristics were identified in each frequency band. The significance of the calculated functional brain networks between the two populations was analyzed using a network-based statistical (NBS) approach.
RESULTS: Compared to controls, boxers exhibited an increasing trend in PLV synchronization and notable differences in the distribution of functional centers, especially in the gamma frequency band. Additionally, attenuated nodal network parameters and decreased small-world measures were observed in the theta, beta, and gamma bands, suggesting that the functional network efficiency and small-world characteristics were significantly weakened in boxers. NBS analysis revealed that boxers exhibited a significant increase in network connectivity strength compared to controls in the theta, beta, and gamma frequency bands. The functional connectivity of the significance subnetworks exhibited an asymmetric distribution between the bilateral hemispheres, indicating that the optimized organization of information integration and segregation for the resting-state networks was imbalanced and disarranged for boxers.
CONCLUSIONS: This is the first study to investigate the underlying deficits in PLV-based graph-theoretic characteristics and NBS-based functional networks in patients with rmTBI from the perspective of whole-brain resting-state EEG. Joint analyses of distinctive graph-theoretic representations and asymmetrically hyperconnected subnetworks in specific frequency bands may serve as an effective method to assess the underlying deficiencies in resting-state network processing in patients with sports-related rmTBI.
摘要：
背景：重复性轻度创伤性脑损伤（rmTBI）通常发生在从事接触运动的个体中，尤其是拳击。本研究旨在通过采用静息状态脑电图（EEG），阐明rmTBI对五个频带中与拳击相关的损伤个体的基于锁相值（PLV）的图论和功能网络结构的影响。
方法：招募了20名专业拳击手和25名匹配的健康对照来执行静息状态任务，同时收集他们的非侵入性头皮脑电图数据。基于拳击手和控件的PLV矩阵的构建，在每个频带中识别相位同步和图论特性。使用基于网络的统计（NBS）方法分析了两个群体之间计算的功能性脑网络的重要性。
结果：与对照组相比，拳击手在PLV同步和功能中心分布方面表现出增加的趋势，尤其是在伽马频段.此外,在θ中观察到衰减的节点网络参数和减少的小世界度量，beta,和伽马带，这表明拳击手的功能网络效率和小世界特征明显减弱。NBS分析显示，与theta中的对照相比，拳击手的网络连接强度显着增加，beta,和伽马频带。重要子网的功能连通性在双侧半球之间表现出非对称分布，表明静息状态网络的信息集成和隔离的优化组织对于拳击手来说是不平衡和无序的。
结论：这是首次从全脑静息状态脑电图的角度研究rmTBI患者基于PLV的图论特征和基于NBS的功能网络的潜在缺陷的研究。对特定频段中独特的图论表示和不对称超连接子网络的联合分析可能是评估与运动相关的rmTBI患者静息状态网络处理中潜在缺陷的有效方法。
方法：招募了20名专业拳击手和25名匹配的健康对照来执行静息状态任务，同时收集他们的非侵入性头皮脑电图数据。基于拳击手和控件的PLV矩阵的构建，在每个频带中识别相位同步和图论特性。使用基于网络的统计（NBS）方法分析了两个群体之间计算的功能性脑网络的重要性。
结果：与对照组相比，拳击手在PLV同步和功能中心分布方面表现出增加的趋势，尤其是在伽马频段.此外,在θ中观察到衰减的节点网络参数和减少的小世界度量，beta,和伽马带，这表明拳击手的功能网络效率和小世界特征明显减弱。NBS分析显示，与theta中的对照相比，拳击手的网络连接强度显着增加，beta,和伽马频带。重要子网的功能连通性在双侧半球之间表现出非对称分布，表明静息状态网络的信息集成和隔离的优化组织对于拳击手来说是不平衡和无序的。
结论：这是首次从全脑静息状态脑电图的角度研究rmTBI患者基于PLV的图论特征和基于NBS的功能网络的潜在缺陷的研究。对特定频段中独特的图论表示和不对称超连接子网络的联合分析可能是评估与运动相关的rmTBI患者静息状态网络处理中潜在缺陷的有效方法。
