The paper provides a comprehensive overview of the MNE (Magnetoencephalography and Electroencephalography) software package, which is designed for processing and analyzing M/EEG data. MNE offers a range of tools for preprocessing, source estimation, time-frequency analysis, statistical analysis, and functional connectivity estimation. The software is developed collaboratively by multiple institutions and is available under the simplified BSD license, allowing both free and commercial use. MNE consists of three core subpackages: MNE-C, MNE-Matlab, and MNE-Python, all of which use the same FIF file format and consistent analysis steps. The paper details the steps involved in using MNE for M/EEG data analysis, including data inspection, noise reduction, source localization, statistical analysis, and functional connectivity estimation. It also highlights the importance of proper artifact rejection, the use of distributed source models, and the integration of anatomical information from MRI data. The MNE software is designed to facilitate reproducibility and standardization in M/EEG research.The paper provides a comprehensive overview of the MNE (Magnetoencephalography and Electroencephalography) software package, which is designed for processing and analyzing M/EEG data. MNE offers a range of tools for preprocessing, source estimation, time-frequency analysis, statistical analysis, and functional connectivity estimation. The software is developed collaboratively by multiple institutions and is available under the simplified BSD license, allowing both free and commercial use. MNE consists of three core subpackages: MNE-C, MNE-Matlab, and MNE-Python, all of which use the same FIF file format and consistent analysis steps. The paper details the steps involved in using MNE for M/EEG data analysis, including data inspection, noise reduction, source localization, statistical analysis, and functional connectivity estimation. It also highlights the importance of proper artifact rejection, the use of distributed source models, and the integration of anatomical information from MRI data. The MNE software is designed to facilitate reproducibility and standardization in M/EEG research.