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Simultaneous EEG-fMRI during a neurofeedback task, a brain imaging dataset for multimodal data integration
Combining EEG and fMRI allows for integration of fine spatial and accurate temporal resolution yet presents numerous challenges, noticeably if performed in real-time to implement a Neurofeedback (NF) loop. Here we describe a multimodal dataset of EEG and fMRI acquired simultaneously during a motor i...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287136/ https://www.ncbi.nlm.nih.gov/pubmed/32523031 http://dx.doi.org/10.1038/s41597-020-0498-3 |
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author | Lioi, Giulia Cury, Claire Perronnet, Lorraine Mano, Marsel Bannier, Elise Lécuyer, Anatole Barillot, Christian |
author_facet | Lioi, Giulia Cury, Claire Perronnet, Lorraine Mano, Marsel Bannier, Elise Lécuyer, Anatole Barillot, Christian |
author_sort | Lioi, Giulia |
collection | PubMed |
description | Combining EEG and fMRI allows for integration of fine spatial and accurate temporal resolution yet presents numerous challenges, noticeably if performed in real-time to implement a Neurofeedback (NF) loop. Here we describe a multimodal dataset of EEG and fMRI acquired simultaneously during a motor imagery NF task, supplemented with MRI structural data. The study involved 30 healthy volunteers undergoing five training sessions. We showed the potential and merit of simultaneous EEG-fMRI NF in previous work. Here we illustrate the type of information that can be extracted from this dataset and show its potential use. This represents one of the first simultaneous recording of EEG and fMRI for NF and here we present the first open access bi-modal NF dataset integrating EEG and fMRI. We believe that it will be a valuable tool to (1) advance and test methodologies for multi-modal data integration, (2) improve the quality of NF provided, (3) improve methodologies for de-noising EEG acquired under MRI and (4) investigate the neuromarkers of motor-imagery using multi-modal information. |
format | Online Article Text |
id | pubmed-7287136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72871362020-06-19 Simultaneous EEG-fMRI during a neurofeedback task, a brain imaging dataset for multimodal data integration Lioi, Giulia Cury, Claire Perronnet, Lorraine Mano, Marsel Bannier, Elise Lécuyer, Anatole Barillot, Christian Sci Data Data Descriptor Combining EEG and fMRI allows for integration of fine spatial and accurate temporal resolution yet presents numerous challenges, noticeably if performed in real-time to implement a Neurofeedback (NF) loop. Here we describe a multimodal dataset of EEG and fMRI acquired simultaneously during a motor imagery NF task, supplemented with MRI structural data. The study involved 30 healthy volunteers undergoing five training sessions. We showed the potential and merit of simultaneous EEG-fMRI NF in previous work. Here we illustrate the type of information that can be extracted from this dataset and show its potential use. This represents one of the first simultaneous recording of EEG and fMRI for NF and here we present the first open access bi-modal NF dataset integrating EEG and fMRI. We believe that it will be a valuable tool to (1) advance and test methodologies for multi-modal data integration, (2) improve the quality of NF provided, (3) improve methodologies for de-noising EEG acquired under MRI and (4) investigate the neuromarkers of motor-imagery using multi-modal information. Nature Publishing Group UK 2020-06-10 /pmc/articles/PMC7287136/ /pubmed/32523031 http://dx.doi.org/10.1038/s41597-020-0498-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Lioi, Giulia Cury, Claire Perronnet, Lorraine Mano, Marsel Bannier, Elise Lécuyer, Anatole Barillot, Christian Simultaneous EEG-fMRI during a neurofeedback task, a brain imaging dataset for multimodal data integration |
title | Simultaneous EEG-fMRI during a neurofeedback task, a brain imaging dataset for multimodal data integration |
title_full | Simultaneous EEG-fMRI during a neurofeedback task, a brain imaging dataset for multimodal data integration |
title_fullStr | Simultaneous EEG-fMRI during a neurofeedback task, a brain imaging dataset for multimodal data integration |
title_full_unstemmed | Simultaneous EEG-fMRI during a neurofeedback task, a brain imaging dataset for multimodal data integration |
title_short | Simultaneous EEG-fMRI during a neurofeedback task, a brain imaging dataset for multimodal data integration |
title_sort | simultaneous eeg-fmri during a neurofeedback task, a brain imaging dataset for multimodal data integration |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287136/ https://www.ncbi.nlm.nih.gov/pubmed/32523031 http://dx.doi.org/10.1038/s41597-020-0498-3 |
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