Effects of acute exercise fatigue on the spatiotemporal dynamics of resting-state large-scale brain networks - Zhao, Shanguang; Lin, Hao; Chi, Aiping; Gao, Yuanyuan (Frontiers in Neuroscience, 2023)
The 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. Twenty male college students majoring in physical education performed incremental load exercise tests on a running platform until exhaustion, and 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, incidence, and coverage of Microstate C were significantly higher after forceful exercise (p's < 0.01). There was a significantly lower time coverage of Microstate D (p < 0.05), a significant increase in transition probabilities between Microstate A and C (p < 0.05), and a significant decrease in transition probabilities between Microstate B and D (p < 0.05). The power spectrum results showed that the scalp energy was significantly higher in the high-frequency α (p < 0.001) and low-frequency β (p < 0.05) bands. 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 (p < 0.05). The correlation analysis showed that the duration of Microstate C had a significant negative correlation with the high-frequency α band (r = -0.515, p < 0.05). Our results suggest that elevated Microstate C parameters 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 by the neural efficiency hypothesis, which indicates a decrease in neural efficiency.