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PracticalMEEG2022: MNE-python hands-on tutorial

appsOther research productkeyboard_double_arrow_right InteractiveResource 10 Jan 2023Publisher:Zenodo
Authors: Westner, Britta;

doi: 10.5281/zenodo.7602381 , 10.5281/zenodo.7516145 , 10.5281/zenodo.7516144

PracticalMEEG2022: MNE-python hands-on tutorial

Abstract

This tutorial was held at PracticalMEEG2022. The hands-on part of this workshop is based on the Frontiers Research Topic From raw MEG/EEG to publication: a collection of articles processing the same multimodal dataset using different software environments. It presents the processing of one subject (sub-01) of this dataset (pruned version of the dataset available here), following the processing pipeline described in the article MEG/EEG Group Analysis With Brainstorm, but using MNE-python toolbox. The original tutorial (version 2019) was made by A.Gramfort and D. Engeeman, remastered for 2022 by Britta Westner. This version uses MNE-python v1.30.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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23