Timescales of the posterior parietal cortex during locomotor adaptation

Locomotor adaptation is an error-driven process that allows our motor system to adjust movements and account for new environmental demands. Many behavioral studies have sought to increase our understanding of the neural mechanisms of locomotor adaptation by examining how people adapt to walking on a split-belt treadmill, which usually occurs within minutes. Motor adaptation can be modeled using a double exponential function to characterize the fast and slow adaptation process. Mobile brain imaging with high-density electroencephalography (EEG) now enables quantification of electrocortical dynamics during human locomotion. We recorded high-density EEG and motion capture from 30 healthy, young adults during split-belt treadmill walking. To decrease motion and muscle artifact, we incorporated a dual-electrode EEG system and neck electromyography. We fit single and double exponential models to step length symmetry and EEG spectral power to characterize the time course of split-belt adaptation. We found component clusters near the posterior parietal cortex (PPC) that had significant changes in alpha (8–12 Hz) and beta (13–30 Hz) spectral power from early to late adaptation. We also found that the time constants from the neural models are generally larger than the behavioral models. These results indicate that adaptive locomotor processes in multiple brain regions continue even after behavioral plateau.