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Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging
Functional magnetic resonance imaging (fMRI) has become an indispensable tool for investigating the human brain. However, the inherently poor signal-to-noise-ratio (SNR) of the fMRI measurement represents a major barrier to expanding its spatiotemporal scale as well as its utility and ultimate impac...
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/PMC8405721/ https://www.ncbi.nlm.nih.gov/pubmed/34462435 http://dx.doi.org/10.1038/s41467-021-25431-8 |
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author | Vizioli, Luca Moeller, Steen Dowdle, Logan Akçakaya, Mehmet De Martino, Federico Yacoub, Essa Uğurbil, Kamil |
author_facet | Vizioli, Luca Moeller, Steen Dowdle, Logan Akçakaya, Mehmet De Martino, Federico Yacoub, Essa Uğurbil, Kamil |
author_sort | Vizioli, Luca |
collection | PubMed |
description | Functional magnetic resonance imaging (fMRI) has become an indispensable tool for investigating the human brain. However, the inherently poor signal-to-noise-ratio (SNR) of the fMRI measurement represents a major barrier to expanding its spatiotemporal scale as well as its utility and ultimate impact. Here we introduce a denoising technique that selectively suppresses the thermal noise contribution to the fMRI experiment. Using 7-Tesla, high-resolution human brain data, we demonstrate improvements in key metrics of functional mapping (temporal-SNR, the detection and reproducibility of stimulus-induced signal changes, and accuracy of functional maps) while leaving the amplitude of the stimulus-induced signal changes, spatial precision, and functional point-spread-function unaltered. We demonstrate that the method enables the acquisition of ultrahigh resolution (0.5 mm isotropic) functional maps but is also equally beneficial for a large variety of fMRI applications, including supra-millimeter resolution 3- and 7-Tesla data obtained over different cortical regions with different stimulation/task paradigms and acquisition strategies. |
format | Online Article Text |
id | pubmed-8405721 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-84057212021-09-22 Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging Vizioli, Luca Moeller, Steen Dowdle, Logan Akçakaya, Mehmet De Martino, Federico Yacoub, Essa Uğurbil, Kamil Nat Commun Article Functional magnetic resonance imaging (fMRI) has become an indispensable tool for investigating the human brain. However, the inherently poor signal-to-noise-ratio (SNR) of the fMRI measurement represents a major barrier to expanding its spatiotemporal scale as well as its utility and ultimate impact. Here we introduce a denoising technique that selectively suppresses the thermal noise contribution to the fMRI experiment. Using 7-Tesla, high-resolution human brain data, we demonstrate improvements in key metrics of functional mapping (temporal-SNR, the detection and reproducibility of stimulus-induced signal changes, and accuracy of functional maps) while leaving the amplitude of the stimulus-induced signal changes, spatial precision, and functional point-spread-function unaltered. We demonstrate that the method enables the acquisition of ultrahigh resolution (0.5 mm isotropic) functional maps but is also equally beneficial for a large variety of fMRI applications, including supra-millimeter resolution 3- and 7-Tesla data obtained over different cortical regions with different stimulation/task paradigms and acquisition strategies. Nature Publishing Group UK 2021-08-30 /pmc/articles/PMC8405721/ /pubmed/34462435 http://dx.doi.org/10.1038/s41467-021-25431-8 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 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Vizioli, Luca Moeller, Steen Dowdle, Logan Akçakaya, Mehmet De Martino, Federico Yacoub, Essa Uğurbil, Kamil Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging |
title | Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging |
title_full | Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging |
title_fullStr | Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging |
title_full_unstemmed | Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging |
title_short | Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging |
title_sort | lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8405721/ https://www.ncbi.nlm.nih.gov/pubmed/34462435 http://dx.doi.org/10.1038/s41467-021-25431-8 |
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