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Practical real-time MEG-based neural interfacing with optically pumped magnetometers

BACKGROUND: Brain-computer interfaces decode intentions directly from the human brain with the aim to restore lost functionality, control external devices or augment daily experiences. To combine optimal performance with wide applicability, high-quality brain signals should be captured non-invasivel...

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Autores principales: Wittevrongel, Benjamin, Holmes, Niall, Boto, Elena, Hill, Ryan, Rea, Molly, Libert, Arno, Khachatryan, Elvira, Van Hulle, Marc M., Bowtell, Richard, Brookes, Matthew J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356471/
https://www.ncbi.nlm.nih.gov/pubmed/34376215
http://dx.doi.org/10.1186/s12915-021-01073-6
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author Wittevrongel, Benjamin
Holmes, Niall
Boto, Elena
Hill, Ryan
Rea, Molly
Libert, Arno
Khachatryan, Elvira
Van Hulle, Marc M.
Bowtell, Richard
Brookes, Matthew J.
author_facet Wittevrongel, Benjamin
Holmes, Niall
Boto, Elena
Hill, Ryan
Rea, Molly
Libert, Arno
Khachatryan, Elvira
Van Hulle, Marc M.
Bowtell, Richard
Brookes, Matthew J.
author_sort Wittevrongel, Benjamin
collection PubMed
description BACKGROUND: Brain-computer interfaces decode intentions directly from the human brain with the aim to restore lost functionality, control external devices or augment daily experiences. To combine optimal performance with wide applicability, high-quality brain signals should be captured non-invasively. Magnetoencephalography (MEG) is a potent candidate but currently requires costly and confining recording hardware. The recently developed optically pumped magnetometers (OPMs) promise to overcome this limitation, but are currently untested in the context of neural interfacing. RESULTS: In this work, we show that OPM-MEG allows robust single-trial analysis which we exploited in a real-time ‘mind-spelling’ application yielding an average accuracy of 97.7%. CONCLUSIONS: This shows that OPM-MEG can be used to exploit neuro-magnetic brain responses in a practical and flexible manner, and opens up new avenues for a wide range of new neural interface applications in the future. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12915-021-01073-6).
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spelling pubmed-83564712021-08-16 Practical real-time MEG-based neural interfacing with optically pumped magnetometers Wittevrongel, Benjamin Holmes, Niall Boto, Elena Hill, Ryan Rea, Molly Libert, Arno Khachatryan, Elvira Van Hulle, Marc M. Bowtell, Richard Brookes, Matthew J. BMC Biol Methodology Article BACKGROUND: Brain-computer interfaces decode intentions directly from the human brain with the aim to restore lost functionality, control external devices or augment daily experiences. To combine optimal performance with wide applicability, high-quality brain signals should be captured non-invasively. Magnetoencephalography (MEG) is a potent candidate but currently requires costly and confining recording hardware. The recently developed optically pumped magnetometers (OPMs) promise to overcome this limitation, but are currently untested in the context of neural interfacing. RESULTS: In this work, we show that OPM-MEG allows robust single-trial analysis which we exploited in a real-time ‘mind-spelling’ application yielding an average accuracy of 97.7%. CONCLUSIONS: This shows that OPM-MEG can be used to exploit neuro-magnetic brain responses in a practical and flexible manner, and opens up new avenues for a wide range of new neural interface applications in the future. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12915-021-01073-6). BioMed Central 2021-08-10 /pmc/articles/PMC8356471/ /pubmed/34376215 http://dx.doi.org/10.1186/s12915-021-01073-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology Article
Wittevrongel, Benjamin
Holmes, Niall
Boto, Elena
Hill, Ryan
Rea, Molly
Libert, Arno
Khachatryan, Elvira
Van Hulle, Marc M.
Bowtell, Richard
Brookes, Matthew J.
Practical real-time MEG-based neural interfacing with optically pumped magnetometers
title Practical real-time MEG-based neural interfacing with optically pumped magnetometers
title_full Practical real-time MEG-based neural interfacing with optically pumped magnetometers
title_fullStr Practical real-time MEG-based neural interfacing with optically pumped magnetometers
title_full_unstemmed Practical real-time MEG-based neural interfacing with optically pumped magnetometers
title_short Practical real-time MEG-based neural interfacing with optically pumped magnetometers
title_sort practical real-time meg-based neural interfacing with optically pumped magnetometers
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356471/
https://www.ncbi.nlm.nih.gov/pubmed/34376215
http://dx.doi.org/10.1186/s12915-021-01073-6
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