Opposing cortical forces: Alpha slowing and sensorimotor mu acceleration during motor-related BCI training
Fig 3
(a) Grand-average EEG topographical maps of alpha/mu-band frequency slopes (top row), the percentage of subjects exhibiting a positive slope at each channel (middle row), and task correlations (bottom row), and (b) the corresponding maps for alpha/mu-band magnitude for the Schalk2004, Dreyer2023, Schwarz2020, and Pulferer2022 datasets (left to right; columnwise).
In the slope maps (top rows in (a) and (b)), red hues indicate increasing trends over time (i.e., rising frequency in Hz/hour or magnitude in a.u./hour), while blue hues indicate decreasing trends. The percentage maps (middle rows in (a) and (b)) depict, for each electrode, the fraction of participants exhibiting a statistically significant positive slope (i.e., increasing frequency or magnitude over time), providing a channel-wise measure of how consistently the direction of change is observed across individuals. The task correlation maps (bottom rows in (a) and (b)) show the spatial distribution of the absolute correlation between EKF-estimated alpha/mu-band dynamics and task-related reference signals (e.g., task vs. rest, movement labels, kinematics), averaged across participants. This correlation analysis was used to identify the frequency range most strongly modulated by the task, representing the functionally relevant mu rhythm. Topoplots were generated using the MATLAB toolbox from Víctor Martínez-Cagigal (2025): Topographic EEG/MEG plot (https://www.mathworks.com/matlabcentral/fileexchange/72729-topographic-eeg-meg-plot).