While the more common neuroimaging method of functional magnetic resonance imaging (fMRI) provides volumetric images defined over voxel grids using a sampling rate of around one image per second, M/EEG captures both slowly and rapidly changing dynamics of brain activations at a millisecond time resolution. Magnetoencephalography (MEG) and electroencephalography (EEG) measure non-invasively the weak electromagnetic signals induced by neural currents. Full documentation, including dozens of examples, is available at. MNE-Python also gives easy access to preprocessed datasets, helping users to get started quickly and facilitating reproducibility of methods by other researchers. Although MNE-Python has only been under heavy development for a couple of years, it has rapidly evolved with expanded analysis capabilities and pedagogical tutorials because multiple labs have collaborated during code development to help share best practices. The code is provided under the new BSD license allowing code reuse, even in commercial products. Moreover, MNE-Python is tightly integrated with the core Python libraries for scientific comptutation (NumPy, SciPy) and visualization (matplotlib and Mayavi), as well as the greater neuroimaging ecosystem in Python via the Nibabel package. All algorithms and utility functions are implemented in a consistent manner with well-documented interfaces, enabling users to create M/EEG data analysis pipelines by writing Python scripts. As part of the MNE software suite, MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions. Using these signals to characterize and locate neural activation in the brain is a challenge that requires expertise in physics, signal processing, statistics, and numerical methods. Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain. Lounasmaa Laboratory, Aalto University School of Science, Espoo, Finland 10Department of Biomedical Engineering and Computational Science, Aalto University School of Science, Espoo, Finland.9Psychological Imaging Laboratory, Psychology, School of Natural Sciences, University of Stirling, Stirling, UK.8Department of Psychology, New York University, New York, NY, USA.7Institute of Biomedical Engineering and Informatics, Ilmenau University of Technology, Ilmenau, Germany.6Brain Imaging Lab, Department of Psychiatry, University Hospital, Cologne, Germany.5Institute of Neuroscience and Medicine - Cognitive Neuroscience (INM-3), Forschungszentrum Juelich, Germany. 4Institute for Learning and Brain Sciences, University of Washington, Seattle WA, USA.3NeuroSpin, CEA Saclay, Gif-sur-Yvette, France.Martinos Center for Biomedical Imaging, Massachusetts General Hospital, and Harvard Medical School, Charlestown MA, USA 1Institut Mines-Telecom, Telecom ParisTech, CNRS LTCI, Paris, France.Engemann 5,6, Daniel Strohmeier 7, Christian Brodbeck 8, Roman Goj 9, Mainak Jas 10,11, Teon Brooks 8, Lauri Parkkonen 10,11 and Matti Hämäläinen 2,11 Alexandre Gramfort 1,2,3 *, Martin Luessi 2, Eric Larson 4, Denis A.
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