Nicolet eeg v32

Resting‐state EEG signals were recorded using a 10–20 system with a standard 32‐channel EEG recorder (Nicolet EEG V32, Natus Neurology, USA) equipped with sintered Ag/AgCl needle electrodes. The sampling frequency was 500 Hz and the impedance between the electrodes and the patient's skin was always kept below 5 kΩ to ensure a proper signal‐to‐noise ratio (SNR).
Data preprocessing was performed in MATLAB (version R2016a, MathWorks Inc., Natick, MA, USA) using the eeglab toolbox (version 2021.1). The preprocessing steps were as follows: (1) positioned the electrode spatially; (2) removed obvious noise segments manually, and used the eeglab toolbox to interpolate channels (spherical method) for replacing bad channels; (3) used notch filters to remove 50 Hz power frequency signals, and performed 1–40 Hz bandpass filtering; (4) downsampled the sampling frequency to 250 Hz to reduce computational complexity; (5) used independent component analysis (ICA) to remove oculoelectricity and myoelectricity; (6) regarded signals exceeding ±150 μV as ring segments and eliminated them by the absolute threshold method; and (7) took the average reference for re‐referencing.

We used 32 EEG recorder (Nicolet EEG V32, Natus, United States). EEG recorded at four time points: before the experiment (T0), after a single session of HD-tDCS (T1), after the treatment of 7 days (T2), and 14 days (T3). EEG signals were continuously recorded from 32 channels at positions of the International 10/20 system. The electrodes with the setting of a band-pass filtered at DC to 1000 Hz in the recorder. The EEG signal was digitized at a sampling rate of 2.5 kHz. The skin impedance was maintained below 5 kΩ. EEG recordings were carried out while patients were behaviorally awake.
Off-line analysis was carried out using EEGLAB 12.0.2.5b, running in a MATLAB environment (version 2013b, Math Works Inc., Natick, Massachusetts, United States). The 50-Hz power signal was removed by a notch filter. The independent component analysis function was used to identify and remove the artifact-relevant components. The EEG data were down-sampled to 500 Hz and average referenced. Then, the EEG date were divided into epochs of 10 s with 50% overlap in each patient.

EEG signals were recorded online at the bedside at a sampling rate of 500 Hz using an EEG acquisition device (Nicolet EEG V32, Natus Neurology, USA) with 32 Ag/AgCl electrodes based on the international standard 10–20 system setup. All electrodes were set with FCz as the reference electrode and AFz as the ground electrode. The impedance between the electrodes and the patient's skin was always kept below 5 kΩ. Patients were kept awake during EEG monitoring. 19 electrodes (Fp1, Fp2, F3, Fz, F4, F7, F8, Cz, C3, C4, Pz, P3, P4, O1, O2, T3, T4, T5, T6) were selected for off-line visual EEG, and the EEG display parameters were set to trap 50 Hz, band-pass filtered to 1–40 Hz, reference to average reference, sensitivity to 70 uV/cm, and paper walking speed to 30 mm/s.