Opposing cortical forces: Alpha slowing and sensorimotor mu acceleration during motor-related BCI training.

Abstract

Brain-computer interfaces (BCIs) depend on the reliable decoding of brain activity, yet key rhythms like alpha and mu are not spectrally static and can shift with cognitive and motor demands. Here, we investigated within-session changes in instantaneous alpha/mu frequency and magnitude during motor-related BCI calibration using an oscillator-tracking framework based on an extended Kalman filter (EKF). We applied this method to four public EEG datasets spanning motor execution and imagery tasks. Across all datasets, we observed consistent increases in mu instantaneous frequency and magnitude over central sensorimotor regions, indicative of motor engagement and possible training-related neuroplasticity. In contrast, posterior and surrounding cortical areas often showed alpha slowing, suggestive of declining vigilance or cognitive fatigue, or alternatively, resource reallocation via inhibition of task-irrelevant regions. These opposing spatial trends underscore the functional heterogeneity of alpha-band activity across the cortex. Our results highlight the potential of real-time frequency tracking not only to improve decoding accuracy but also to monitor neurophysiological state changes and guide adaptive adjustments in BCI calibration paradigms.