{"repo":"AGhaderi/MNE-Preprocessing","free":true,"listed":false,"github":"https://github.com/AGhaderi/MNE-Preprocessing","clone":"git clone https://github.com/AGhaderi/MNE-Preprocessing.git","description":"MNE-preprocessing is a python repository to reduce artifacts based on basic and unanimous approaches step by step from electroencephalographic (EEG) raw data.","language":"Jupyter Notebook","stars":22,"topics":["eeg","preprocessing","python","mne-python","mne","independent-component-analysis","mne-preprocessing","eeg-preprocessing","ica","erp"],"license":null,"category":"dashboards-admin","readme_excerpt":"MNE-Preprocessing EEG preprocessing is required to attenuate artifacts and improve signal quality for downstream analysis. This MNE preprocessing repository is implemented using the MNE-Python package. --- Resting-state EEG preprocessing for PSD analysis The script rs eeg prep for psd analysis is designed for resting-state EEG preprocessing, specifically for power spectrum–based analyses, including 1/f (aperiodic) and oscillatory (periodic) components. - Downsampled to 1000 Hz - Band-pass filtered between 0.1–45 Hz or 0.1–95 Hz using FIR filtering, followed by notch filtering at 50 Hz and its harmonic ( 100 Hz ) - Visually inspected to identify noisy segments (e.g., muscle artifacts affecting multiple channels), which were manually labeled as bad artifact - Bad channels (high-amplitude artifacts consistent across recordings) were removed and spherically interpolated - Data were re-referenced to the average reference - To enhance spatial specificity and reduce volume conduction at the sensor level, a surface Laplacian (current source density, CSD) transform was applied with parameters (Stiffness= 4, Legendre polynomial= 80, Regularization parameter= 10⁻³) - Independent Component Analysis (ICA) using the FastICA algorithm was applied to identify and remove non-brain artifacts (e.g., eye blinks and muscle activity) --- Citations 1. Bertino, S., Ghaderi-Kangavari, A., Meder, D., Vinding, M.C., Raaf, N., Christiansen, L., Thomsen, B.L.C., Løkkegaard, A., Quartarone, A., Beck, M.M.","default_branch":null,"files":null,"tree":[],"storefront":"/r/AGhaderi","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AGhaderi/MNE-Preprocessing/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}