Exploring intensity-dependent modulations in EEG resting-state network efficiency induced by exercise

Abstract

Purpose Exhaustive cardiovascular load can affect neural processing and is associated with decreases in sensorimotor performance. The purpose of this study was to explore intensity-dependent modulations in brain network efficiency in response to treadmill running assessed from resting-state electroencephalography (EEG) measures.

Methods Sixteen trained participants were tested for individual peak oxygen uptake (VO2 peak) and performed an incremental treadmill exercise at 50% (10 min), 70% (10 min) and 90% speed VO2 peak (all-out) followed by cool-down running and active recovery. Before the experiment and after each stage, borg scale (BS), blood lactate concentration (BLa), resting heartrate (HRrest) and 64-channel EEG resting state were assessed. To analyze network efficiency, graph theory was applied to derive small world index (SWI) from EEG data in theta, alpha-1 and alpha-2 frequency bands.

Results Analysis of variance for repeated measures revealed significant main effects for intensity on BS, BLa, HRrest and SWI. While BS, BLa and HRrest indicated maxima after all-out, SWI showed a reduction in the theta network after all-out.

Conclusion Our explorative approach suggests intensity-dependent modulations of resting-state brain networks, since exhaustive exercise temporarily reduces brain network efficiency. Resting-state network assessment may prospectively play a role in training monitoring by displaying the readiness and efficiency of the central nervous system in different training situations.