Mne Bids Pipeline |best| Now

with open(args.config, 'r') as f: config = yaml.safe_load(f) main(args.subject, config)

For group analysis, save evoked data in BIDS-derivatives: mne bids pipeline

import mne def preprocess_raw(raw, l_freq=0.1, h_freq=40, notch=50): """ Apply standard EEG preprocessing. Adjust parameters for MEG (e.g., high-pass 1 Hz, low-pass 100 Hz). """ # 1. Filter (bandpass) raw.filter(l_freq, h_freq, fir_design='firwin', verbose=True) with open(args

# 4. Set average reference (EEG) if 'eeg' in raw: raw.set_eeg_reference('average', projection=False) config) For group analysis