Multivariate associations between temporal resting-state EEG microstate parameters and physical fitness: An...

Area of Science:

• Neuroscience
• Human Physiology

Background:

• Exercise impacts resting-state brain activity.
• The relationship between physical fitness and dynamic brain network organization is not well understood.
• Electroencephalography (EEG) microstate analysis offers insights into large-scale functional brain network dynamics.

Purpose of the Study:

• To investigate the association between physical fitness and EEG microstate dynamics at rest.
• To explore how parameters like VO2max and lower-limb strength relate to the temporal organization of brain networks.

Main Methods:

• Thirty healthy participants underwent VO2max and lower-limb strength testing.
• Resting EEG data (32-channel) were recorded and analyzed for microstate parameters (A-D).
• Partial least squares correlation (PLSC) and FDR-corrected univariate regressions were used to examine associations between fitness and microstate dynamics.

Main Results:

• A significant multivariate association was found between microstate parameters and lower-limb strength (r=0.71, p=0.028).
• Higher strength correlated with longer durations of microstates B and C, and lower explained variance of microstate C.
• No significant associations were identified between VO2max and EEG microstate dynamics.

Conclusions:

• Interindividual differences in physical fitness, particularly strength, are reflected in the temporal organization of large-scale brain networks.
• This study provides initial evidence linking physical fitness to brain network dynamics.
• Further research is needed to explore if exercise interventions can induce similar neurobiological adaptations.