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FLUX: A pipeline for MEG analysis

Magnetoencephalography (MEG) allows for quantifying modulations of human neuronal activity on a millisecond time scale while also making it possible to estimate the location of the underlying neuronal sources. The technique relies heavily on signal processing and source modelling. To this end, there...

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Autores principales: Ferrante, Oscar, Liu, Ling, Minarik, Tamas, Gorska, Urszula, Ghafari, Tara, Luo, Huan, Jensen, Ole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127391/
https://www.ncbi.nlm.nih.gov/pubmed/35276363
http://dx.doi.org/10.1016/j.neuroimage.2022.119047
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author Ferrante, Oscar
Liu, Ling
Minarik, Tamas
Gorska, Urszula
Ghafari, Tara
Luo, Huan
Jensen, Ole
author_facet Ferrante, Oscar
Liu, Ling
Minarik, Tamas
Gorska, Urszula
Ghafari, Tara
Luo, Huan
Jensen, Ole
author_sort Ferrante, Oscar
collection PubMed
description Magnetoencephalography (MEG) allows for quantifying modulations of human neuronal activity on a millisecond time scale while also making it possible to estimate the location of the underlying neuronal sources. The technique relies heavily on signal processing and source modelling. To this end, there are several open-source toolboxes developed by the community. While these toolboxes are powerful as they provide a wealth of options for analyses, the many options also pose a challenge for reproducible research as well as for researchers new to the field. The FLUX pipeline aims to make the analyses steps and setting explicit for standard analysis done in cognitive neuroscience. It focuses on quantifying and source localization of oscillatory brain activity, but it can also be used for event-related fields and multivariate pattern analysis. The pipeline is derived from the Cogitate consortium addressing a set of concrete cognitive neuroscience questions. Specifically, the pipeline including documented code is defined for MNE Python (a Python toolbox) and FieldTrip (a Matlab toolbox), and a data set on visuospatial attention is used to illustrate the steps. The scripts are provided as notebooks implemented in Jupyter Notebook and MATLAB Live Editor providing explanations, justifications and graphical outputs for the essential steps. Furthermore, we also provide suggestions for text and parameter settings to be used in registrations and publications to improve replicability and facilitate pre-registrations. The FLUX can be used for education either in self-studies or guided workshops. We expect that the FLUX pipeline will strengthen the field of MEG by providing some standardization on the basic analysis steps and by aligning approaches across toolboxes. Furthermore, we also aim to support new researchers entering the field by providing education and training. The FLUX pipeline is not meant to be static; it will evolve with the development of the toolboxes and with new insights. Furthermore, with the anticipated increase in MEG systems based on the Optically Pumped Magnetometers, the pipeline will also evolve to embrace these developments.
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spelling pubmed-91273912022-06-14 FLUX: A pipeline for MEG analysis Ferrante, Oscar Liu, Ling Minarik, Tamas Gorska, Urszula Ghafari, Tara Luo, Huan Jensen, Ole Neuroimage Article Magnetoencephalography (MEG) allows for quantifying modulations of human neuronal activity on a millisecond time scale while also making it possible to estimate the location of the underlying neuronal sources. The technique relies heavily on signal processing and source modelling. To this end, there are several open-source toolboxes developed by the community. While these toolboxes are powerful as they provide a wealth of options for analyses, the many options also pose a challenge for reproducible research as well as for researchers new to the field. The FLUX pipeline aims to make the analyses steps and setting explicit for standard analysis done in cognitive neuroscience. It focuses on quantifying and source localization of oscillatory brain activity, but it can also be used for event-related fields and multivariate pattern analysis. The pipeline is derived from the Cogitate consortium addressing a set of concrete cognitive neuroscience questions. Specifically, the pipeline including documented code is defined for MNE Python (a Python toolbox) and FieldTrip (a Matlab toolbox), and a data set on visuospatial attention is used to illustrate the steps. The scripts are provided as notebooks implemented in Jupyter Notebook and MATLAB Live Editor providing explanations, justifications and graphical outputs for the essential steps. Furthermore, we also provide suggestions for text and parameter settings to be used in registrations and publications to improve replicability and facilitate pre-registrations. The FLUX can be used for education either in self-studies or guided workshops. We expect that the FLUX pipeline will strengthen the field of MEG by providing some standardization on the basic analysis steps and by aligning approaches across toolboxes. Furthermore, we also aim to support new researchers entering the field by providing education and training. The FLUX pipeline is not meant to be static; it will evolve with the development of the toolboxes and with new insights. Furthermore, with the anticipated increase in MEG systems based on the Optically Pumped Magnetometers, the pipeline will also evolve to embrace these developments. Academic Press 2022-06 /pmc/articles/PMC9127391/ /pubmed/35276363 http://dx.doi.org/10.1016/j.neuroimage.2022.119047 Text en © 2022 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ferrante, Oscar
Liu, Ling
Minarik, Tamas
Gorska, Urszula
Ghafari, Tara
Luo, Huan
Jensen, Ole
FLUX: A pipeline for MEG analysis
title FLUX: A pipeline for MEG analysis
title_full FLUX: A pipeline for MEG analysis
title_fullStr FLUX: A pipeline for MEG analysis
title_full_unstemmed FLUX: A pipeline for MEG analysis
title_short FLUX: A pipeline for MEG analysis
title_sort flux: a pipeline for meg analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127391/
https://www.ncbi.nlm.nih.gov/pubmed/35276363
http://dx.doi.org/10.1016/j.neuroimage.2022.119047
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