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

PURPOSE: Electroencephalography (EEG) microstate analysis provides a marker of the temporal dynamics of large-scale functional brain networks. While exercise is known to influence resting-state brain activity, its relationship with dynamic network organization remains unclear. We therefore investigated associations between physical fitness and EEG microstate dynamics at rest. METHODS: In 30 healthy subjects, VO2max and lower-limb strength was tested using spiroergometric testing on a cycling ergometer and isokinetic strength testing. A 32-channel resting EEG was recorded (2 min eyes open/closed) and temporal parameters for four representative microstate topographies (A - D) were extracted. Associations between physical fitness and temporal parameters of microstate dynamics were examined using partial least squares correlation (PLSC), complemented by FDR-corrected univariate regressions for features showing stable multivariate contributions (Bootstrap ratio ≥ 2.5). RESULTS: = 0.20). No such association was identified for VO2max. CONCLUSION: Our results provide first evidence that interindividual differences in physical fitness are also reflected in the temporal organization of large-scale brain networks. Future studies should determine whether longitudinal exercise interventions can induce such neurobiological adaptations.