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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...

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Detalles Bibliográficos
Autores principales: Boyacioglu, Rasim, Beckmann, Christian F., Barth, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2013
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.
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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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