Shi Jilong, Nasrallah Fatima A, Mao Xuechen, Huang Qin, Pan Jun, Li Anmin
School of Psychology, Shanghai University of Sport, Shanghai 200438, China.
Center for Exercise and Brain Science, Shanghai University of Sport, Shanghai 200438, China.
Brain Sci. 2024 Feb 27;14(3):222. doi: 10.3390/brainsci14030222.
Table tennis athletes have been extensively studied for their cognitive processing advantages and brain plasticity. However, limited research has focused on the resting-state function of their brains. This study aims to investigate the network characteristics of the resting-state electroencephalogram in table tennis athletes and identify specific brain network biomarkers.
A total of 48 healthy right-handed college students participated in this study, including 24 table tennis athletes and 24 controls with no exercise experience. Electroencephalogram data were collected using a 64-conductive active electrode system during eyes-closed resting conditions. The analysis involved examining the average power spectral density and constructing brain functional networks using the weighted phase-lag index. Network topological characteristics were then calculated.
The results revealed that table tennis athletes exhibited significantly higher average power spectral density in the α band compared to the control group. Moreover, athletes not only demonstrated stronger functional connections, but they also exhibited enhanced transmission efficiency in the brain network, particularly at the local level. Additionally, a lateralization effect was observed, with more potent interconnected hubs identified in the left hemisphere of the athletes' brain.
Our findings imply that the α band may be uniquely associated with table tennis athletes and their motor skills. The brain network characteristics of athletes during the resting state are worth further attention to gain a better understanding of adaptability of and changes in their brains during training and competition.
乒乓球运动员因其认知加工优势和大脑可塑性而受到广泛研究。然而,针对其大脑静息态功能的研究较少。本研究旨在探讨乒乓球运动员静息态脑电图的网络特征,并确定特定的脑网络生物标志物。
共有48名健康的右利手大学生参与本研究,其中包括24名乒乓球运动员和24名无运动经验的对照组。在闭眼静息状态下,使用64导有源电极系统收集脑电图数据。分析包括检查平均功率谱密度,并使用加权相位滞后指数构建脑功能网络。然后计算网络拓扑特征。
结果显示,与对照组相比,乒乓球运动员在α波段的平均功率谱密度显著更高。此外,运动员不仅表现出更强的功能连接,而且在脑网络中,尤其是在局部水平上,表现出更高的传输效率。此外,还观察到一种偏侧化效应,在运动员大脑的左半球发现了更强的相互连接的枢纽。
我们的研究结果表明,α波段可能与乒乓球运动员及其运动技能有着独特的关联。运动员静息状态下的脑网络特征值得进一步关注,以便更好地了解他们在训练和比赛期间大脑的适应性和变化。