Key result
Acute exhaustive exercise significantly increased the duration, occurrence, and contribution of EEG Microstate C (p<0.01) and increased high-frequency beta band energy in the visual network (p<0.05).
Why the study?
Few studies have examined the effects of acute exercise fatigue on large-scale brain functional networks.
Does acute exercise fatigue alter resting-state EEG microstates and large-scale brain network rhythm energy in healthy male college students?
Does acute exercise fatigue alter resting-state EEG microstates and large-scale brain network rhythm energy in healthy male college students?
Acute exhaustive exercise alters resting-state EEG microstates and increases high-frequency beta band energy in the visual network, providing a potential neural mechanism for fatigue-induced decreases in attention and cognitive performance.
Answers are grounded in this paper and cite their sources.
May indicate exercise effects on visual networks; hypothesis-generating and requires larger trials before clinical or research implications.
Introduction 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. Methods 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. Results The microstate results showed that the duration, occurrence, and contribution of Microstate C were significantly higher after exhaustive exercise ( p’s < 0.01). There was a significantly lower contribution 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 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). Discussion 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.
No takes yet. Share an insight, caveat, or question.
Zhao et al. (2023) studied Healthy (n=30). Acute exhaustive exercise (Bruce protocol) vs. Pre-exercise resting state was evaluated on Resting-state EEG microstates (duration, occurrence, contribution) and large-scale brain network rhythm energy (p=<0.01). Acute exhaustive exercise significantly increased the duration, occurrence, and contribution of EEG Microstate C (p<0.01) and increased high-frequency beta band energy in the visual network (p<0.05).
Synapse has enriched 10 related papers. Consider them for comparative context: