EEG data preprocessing

Figure ​Figure22 shows the processing procedure for EEG data. First, the raw EEG signals from the 32-channel electrode array were notch filtered at 50 Hz to reduce line noise. Our previous study showed that cortical activity in rats was concentrated in the 3- to 50-Hz frequency band when encountering unexpected terrain [19], so the signal was filtered at 3 to 50 Hz. Next, The EEG data were re-referenced to the common average and down-sampled to 500 Hz. Subsequently, the EEG data were decomposed into independent component (IC) sources by an independent component analysis algorithm. We removed those non-brain IC sources by visually inspecting each IC scalp projection and power spectrum to obtain clean EEG data. After the above processing, we extracted epoch from the EEG data of each rat according to the mean hind limb kinematics data of all rats (each epoch started 1 s before the event RC and the total duration was 2.5 s, including 2 complete preparation phases and 1 complete walking phase). After that, epochs from all rats were divided into 3 groups according to different task conditions (FF: 685 epochs, FU: 586 epochs, and UF: 575 epochs). Each rat contributed a similar number of epochs under each condition). The above EEG data analysis was performed using custom scripts written in MATLAB v2018b (The MathWorks, Inc., Nedick, MA, USA) containing functions from EEGLAB [20].

EEG data processing procedure. CAR, common average; ICA, independent component analysis; VIS, visual area; RSS, right somatosensory area.