by Lorenz Esch, Christoph Dinh, Eric Larson, Denis Engemann, Mainak Jas, Sheraz Khan, Alexandre Gramfort, Matti S. Hämäläinen
Abstract:
The methods for acquiring, processing, and visualizing magnetoencephalography (MEG) and electroencephalography (EEG) data are rapidly evolving. Advancements in hardware and software development offer new opportunities for cognitive and clinical neuroscientists but at the same time introduce new challenges as well. In recent years the MEG/EEG community has developed a variety of software tools to overcome these challenges and cater to individual research needs. As part of this endeavor, the MNE software project, which includes MNE-C, MNE-Python, MNE-CPP, and MNE-MATLAB as its subprojects, offers an efficient set of tools addressing certain common needs. Even more importantly, the MNE software family covers diverse use case scenarios. Here, we present the landscape of the MNE project and discuss how it will evolve to address the current and emerging needs of the MEG/EEG community.
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Reference:
MNE: Software for Acquiring, Processing,and Visualizing MEG/EEG Data (Lorenz Esch, Christoph Dinh, Eric Larson, Denis Engemann, Mainak Jas, Sheraz Khan, Alexandre Gramfort, Matti S. Hämäläinen), Chapter in Magnetoencephalography: From Signals to Dynamic Cortical Networks (Selma Supek, Cheryl J. Aine, eds.), Springer International Publishing, 2019.
Bibtex Entry:
@incollection{esch_mne:_2019,
	address = {Cham},
	title = {{MNE}: {Software} for {Acquiring}, {Processing},and {Visualizing} {MEG}/{EEG} {Data}},
	isbn = {978-3-319-62657-4},
	url = {https://doi.org/10.1007/978-3-319-62657-4_59-1},
	abstract = {The methods for acquiring, processing, and visualizing magnetoencephalography (MEG) and electroencephalography (EEG) data are rapidly evolving. Advancements in hardware and software development offer new opportunities for cognitive and clinical neuroscientists but at the same time introduce new challenges as well. In recent years the MEG/EEG community has developed a variety of software tools to overcome these challenges and cater to individual research needs. As part of this endeavor, the MNE software project, which includes MNE-C, MNE-Python, MNE-CPP, and MNE-MATLAB as its subprojects, offers an efficient set of tools addressing certain common needs. Even more importantly, the MNE software family covers diverse use case scenarios. Here, we present the landscape of the MNE project and discuss how it will evolve to address the current and emerging needs of the MEG/EEG community.},
	booktitle = {Magnetoencephalography: {From} {Signals} to {Dynamic} {Cortical} {Networks}},
	publisher = {Springer International Publishing},
	author = {Esch, Lorenz and Dinh, Christoph and Larson, Eric and Engemann, Denis and Jas, Mainak and Khan, Sheraz and Gramfort, Alexandre and Hämäläinen, Matti S.},
	editor = {Supek, Selma and Aine, Cheryl J.},
	year = {2019},
	doi = {10.1007/978-3-319-62657-4_59-1},
	pages = {1--17}
}