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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
The text was updated successfully, but these errors were encountered:
Hi @agramfort, I’m happy to tell you that we’d like to host your presentation as a lightning talk in the OSR in the Collaborative research session. This will be a talk of 5 minutes + 5 minutes of questions. We can unfortunately not offer you a slot in your preferred session as the ‘new advances’ session had many applicants yet limited availability. We hope this session is ok for you and would like to ask you if in your presentation you could briefly reflect on the session topic: the collaborative nature of your project.
We’ll update the program in the ReadMe.md shortly. We’d much appreciate it if you could submit slides and other presentation material to the presentations folder by means of a Pull Request to this repository, preferably but not necessarily before the presentation.
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
The text was updated successfully, but these errors were encountered: