Zhao Shanguang, Lin Hao, Chi Aiping, Gao Yuanyuan
Institute of Physical Education, Shaanxi Normal University, Xi'an, China.
Faculty of Sports and Exercise Science, Universiti Malaya, Kuala Lumpur, Malaysia.
Front Neurosci. 2023 Jan 20;17:986368. doi: 10.3389/fnins.2023.986368. eCollection 2023.
Various approaches have been used to explore different aspects of the regulation of brain activity by acute exercise, but few studies have been conducted on the effects of acute exercise fatigue on large-scale brain functional networks. Therefore, the present study aimed to explore the effects of acute exercise fatigue on resting-state electroencephalogram (EEG) microstates and large-scale brain network rhythm energy.
The Bruce protocol was used as the experimental exercise model with a self-controlled experimental design. Thirty males performed incremental load exercise tests on treadmill until exhaustion. EEG signal acquisition was completed before and after exercise. EEG microstates and resting-state cortical rhythm techniques were used to analyze the EEG signal.
The microstate results showed that the duration, occurrence, and contribution of Microstate C were significantly higher after exhaustive exercise ( < 0.01). There was a significantly lower contribution of Microstate D ( < 0.05), a significant increase in transition probabilities between Microstate A and C ( < 0.05), and a significant decrease in transition probabilities between Microstate B and D ( < 0.05). The results of EEG rhythm energy on the large-scale brain network showed that the energy in the high-frequency β band was significantly higher in the visual network ( < 0.05).
Our results suggest that frequently Microstate C associated with the convexity network are important for the organism to respond to internal and external information stimuli and thus regulate motor behavior in time to protect organism integrity. The decreases in Microstate D parameters, associated with the attentional network, are an important neural mechanism explaining the decrease in attention-related cognitive or behavioral performance due to acute exercise fatigue. The high energy in the high-frequency β band on the visual network can be explained in the sense of the neural efficiency hypothesis, which indicates a decrease in neural efficiency.
人们采用了各种方法来探究急性运动对大脑活动调节的不同方面，但关于急性运动疲劳对大规模脑功能网络影响的研究较少。因此，本研究旨在探讨急性运动疲劳对静息态脑电图（EEG）微状态和大规模脑网络节律能量的影响。
采用布鲁斯方案作为实验运动模型，采用自身对照实验设计。30名男性在跑步机上进行递增负荷运动测试直至 exhaustion。运动前后完成EEG信号采集。使用EEG微状态和静息态皮质节律技术分析EEG信号。
微状态结果显示，力竭运动后微状态C的持续时间、发生率和贡献率显著更高（<0.01）。微状态D的贡献率显著降低（<0.05），微状态A和C之间的转换概率显著增加（<0.05），微状态B和D之间的转换概率显著降低（<0.05）。大规模脑网络上的EEG节律能量结果显示，视觉网络中高频β波段的能量显著更高（<0.05）。
我们的结果表明，与凸面网络相关的微状态C频繁出现，对于机体响应内部和外部信息刺激并及时调节运动行为以保护机体完整性很重要。与注意力网络相关的微状态D参数降低，是解释急性运动疲劳导致注意力相关认知或行为表现下降的重要神经机制。视觉网络上高频β波段的高能量可以从神经效率假说的角度来解释，这表明神经效率降低。
