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Description
Title
MEG and EEG data processing using MNE: News from the trenches
Presentor and Affiliation
A. Gramfort, Inria
Collaborators
MNE-Python is developped by a growing international community from the MNE ecosystem: https://github.com/mne-tools/mne-python/graphs/contributors.
Github Link (if applicable)
https://github.com/mne-tools/mne-python
Abstract (max. 200 words):
MNE-Python is a software package for processing electrophysiological signals primarily from magnetoencephalographic (MEG) and electroencephalographic (EEG) recordings. It provides a comprehensive solution for data preprocessing, forward modeling (with boundary element models), distributed source imaging, time–frequency analysis, non-parametric multivariate statistics, multivariate pattern analysis, and connectivity estimation. MNE is developed by an international team, with particular care for computational efficiency, code quality, and readability, as well as the common goal of facilitating reproducibility in neuroscience.
This talk will contain an interactive overview of the basics of MEG/EEG data processing with MNE-Python, as well as highlight some recent new features.
Preferred Session
3. Demo: New advances in open neuroimaging methods
Additional Context