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An Investigation of RSN Frequency Spectra Using Ultra-Fast Generalized Inverse Imaging
With the advancements in MRI hardware, pulse sequences and reconstruction techniques, many low TR sequences are becoming more and more popular within the functional MRI (fMRI) community. In this study, we have investigated the spectral characteristics of resting state networks (RSNs) with a newly in...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3632876/ https://www.ncbi.nlm.nih.gov/pubmed/23630487 http://dx.doi.org/10.3389/fnhum.2013.00156 |
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author | Boyacioglu, Rasim Beckmann, Christian F. Barth, Markus |
author_facet | Boyacioglu, Rasim Beckmann, Christian F. Barth, Markus |
author_sort | Boyacioglu, Rasim |
collection | PubMed |
description | With the advancements in MRI hardware, pulse sequences and reconstruction techniques, many low TR sequences are becoming more and more popular within the functional MRI (fMRI) community. In this study, we have investigated the spectral characteristics of resting state networks (RSNs) with a newly introduced ultra fast fMRI technique, called generalized inverse imaging (GIN). The high temporal resolution of GIN (TR = 50 ms) enables to sample cardiac signals without aliasing into a separate frequency band from the BOLD fluctuations. Respiration related signal changes are, on the other hand, removed from the data without the need for external physiological recordings. We have observed that the variance over the subjects is higher than the variance over RSNs. |
format | Online Article Text |
id | pubmed-3632876 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-36328762013-04-29 An Investigation of RSN Frequency Spectra Using Ultra-Fast Generalized Inverse Imaging Boyacioglu, Rasim Beckmann, Christian F. Barth, Markus Front Hum Neurosci Neuroscience With the advancements in MRI hardware, pulse sequences and reconstruction techniques, many low TR sequences are becoming more and more popular within the functional MRI (fMRI) community. In this study, we have investigated the spectral characteristics of resting state networks (RSNs) with a newly introduced ultra fast fMRI technique, called generalized inverse imaging (GIN). The high temporal resolution of GIN (TR = 50 ms) enables to sample cardiac signals without aliasing into a separate frequency band from the BOLD fluctuations. Respiration related signal changes are, on the other hand, removed from the data without the need for external physiological recordings. We have observed that the variance over the subjects is higher than the variance over RSNs. Frontiers Media S.A. 2013-04-23 /pmc/articles/PMC3632876/ /pubmed/23630487 http://dx.doi.org/10.3389/fnhum.2013.00156 Text en Copyright © 2013 Boyacioglu, Beckmann and Barth. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc. |
spellingShingle | Neuroscience Boyacioglu, Rasim Beckmann, Christian F. Barth, Markus An Investigation of RSN Frequency Spectra Using Ultra-Fast Generalized Inverse Imaging |
title | An Investigation of RSN Frequency Spectra Using Ultra-Fast Generalized Inverse Imaging |
title_full | An Investigation of RSN Frequency Spectra Using Ultra-Fast Generalized Inverse Imaging |
title_fullStr | An Investigation of RSN Frequency Spectra Using Ultra-Fast Generalized Inverse Imaging |
title_full_unstemmed | An Investigation of RSN Frequency Spectra Using Ultra-Fast Generalized Inverse Imaging |
title_short | An Investigation of RSN Frequency Spectra Using Ultra-Fast Generalized Inverse Imaging |
title_sort | investigation of rsn frequency spectra using ultra-fast generalized inverse imaging |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3632876/ https://www.ncbi.nlm.nih.gov/pubmed/23630487 http://dx.doi.org/10.3389/fnhum.2013.00156 |
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