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Testing covariance models for MEG source reconstruction of hippocampal activity
Beamforming is one of the most commonly used source reconstruction methods for magneto- and electroencephalography (M/EEG). One underlying assumption, however, is that distant sources are uncorrelated and here we tested whether this is an appropriate model for the human hippocampal data. We revised...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413350/ https://www.ncbi.nlm.nih.gov/pubmed/34475476 http://dx.doi.org/10.1038/s41598-021-96933-0 |
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author | O’Neill, George C. Barry, Daniel N. Tierney, Tim M. Mellor, Stephanie Maguire, Eleanor A. Barnes, Gareth R. |
author_facet | O’Neill, George C. Barry, Daniel N. Tierney, Tim M. Mellor, Stephanie Maguire, Eleanor A. Barnes, Gareth R. |
author_sort | O’Neill, George C. |
collection | PubMed |
description | Beamforming is one of the most commonly used source reconstruction methods for magneto- and electroencephalography (M/EEG). One underlying assumption, however, is that distant sources are uncorrelated and here we tested whether this is an appropriate model for the human hippocampal data. We revised the Empirical Bayesian Beamfomer (EBB) to accommodate specific a-priori correlated source models. We showed in simulation that we could use model evidence (as approximated by Free Energy) to distinguish between different correlated and uncorrelated source scenarios. Using group MEG data in which the participants performed a hippocampal-dependent task, we explored the possibility that the hippocampus or the cortex or both were correlated in their activity across hemispheres. We found that incorporating a correlated hippocampal source model significantly improved model evidence. Our findings help to explain why, up until now, the majority of MEG-reported hippocampal activity (typically making use of beamformers) has been estimated as unilateral. |
format | Online Article Text |
id | pubmed-8413350 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-84133502021-09-07 Testing covariance models for MEG source reconstruction of hippocampal activity O’Neill, George C. Barry, Daniel N. Tierney, Tim M. Mellor, Stephanie Maguire, Eleanor A. Barnes, Gareth R. Sci Rep Article Beamforming is one of the most commonly used source reconstruction methods for magneto- and electroencephalography (M/EEG). One underlying assumption, however, is that distant sources are uncorrelated and here we tested whether this is an appropriate model for the human hippocampal data. We revised the Empirical Bayesian Beamfomer (EBB) to accommodate specific a-priori correlated source models. We showed in simulation that we could use model evidence (as approximated by Free Energy) to distinguish between different correlated and uncorrelated source scenarios. Using group MEG data in which the participants performed a hippocampal-dependent task, we explored the possibility that the hippocampus or the cortex or both were correlated in their activity across hemispheres. We found that incorporating a correlated hippocampal source model significantly improved model evidence. Our findings help to explain why, up until now, the majority of MEG-reported hippocampal activity (typically making use of beamformers) has been estimated as unilateral. Nature Publishing Group UK 2021-09-02 /pmc/articles/PMC8413350/ /pubmed/34475476 http://dx.doi.org/10.1038/s41598-021-96933-0 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/) . |
spellingShingle | Article O’Neill, George C. Barry, Daniel N. Tierney, Tim M. Mellor, Stephanie Maguire, Eleanor A. Barnes, Gareth R. Testing covariance models for MEG source reconstruction of hippocampal activity |
title | Testing covariance models for MEG source reconstruction of hippocampal activity |
title_full | Testing covariance models for MEG source reconstruction of hippocampal activity |
title_fullStr | Testing covariance models for MEG source reconstruction of hippocampal activity |
title_full_unstemmed | Testing covariance models for MEG source reconstruction of hippocampal activity |
title_short | Testing covariance models for MEG source reconstruction of hippocampal activity |
title_sort | testing covariance models for meg source reconstruction of hippocampal activity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413350/ https://www.ncbi.nlm.nih.gov/pubmed/34475476 http://dx.doi.org/10.1038/s41598-021-96933-0 |
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