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MNE-ICALabel: Automatically annotating ICA components with ICLabel in Python

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 27 Oct 2023Publisher:Zenodo
Authors: Li, Adam; Höchenberger, Richard; Donoghue, Thomas; Scheltienne, Mathieu; Feitelberg, Jacob; Saini, Anand;
Code repository: https://github.com/mne-tools/mne-icalabel/tree/v0.5.1

doi: 10.5281/zenodo.10054181 , 10.5281/zenodo.10048084 , 10.5281/zenodo.10519370 , 10.5281/zenodo.10048085 , 10.5281/zenodo.17187403 , 10.5281/zenodo.12914470 , 10.5281/zenodo.17380955

MNE-ICALabel: Automatically annotating ICA components with ICLabel in Python

Abstract

MNE-ICALabel is a Python library to facilitate the automatic annotation of ICA components for MEG, EEG, and iEEG data with MNE-Python. More information about MNE-Python can be found at mne.tools.

Please cite this software using the metadata from 'preferred-citation' in the CITATION.cff file.

Related Organizations
Keywords

neuroscience, python, magnetoencephalography, neuroimaging, meg, ieeg, eeg, ica, mne, electroencephalography

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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!
0
Average
Average
Average
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Neuroscience