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Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential
Functional MRI at 3T has become a workhorse for the neurosciences, e.g., neurology, psychology, and psychiatry, enabling non-invasive investigation of brain function and connectivity. However, BOLD-based fMRI is a rather indirect measure of brain function, confounded by physiology related signals, e...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291320/ https://www.ncbi.nlm.nih.gov/pubmed/28164083 http://dx.doi.org/10.3389/fphy.2014.00001 |
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author | Boubela, Roland N. Kalcher, Klaudius Nasel, Christian Moser, Ewald |
author_facet | Boubela, Roland N. Kalcher, Klaudius Nasel, Christian Moser, Ewald |
author_sort | Boubela, Roland N. |
collection | PubMed |
description | Functional MRI at 3T has become a workhorse for the neurosciences, e.g., neurology, psychology, and psychiatry, enabling non-invasive investigation of brain function and connectivity. However, BOLD-based fMRI is a rather indirect measure of brain function, confounded by physiology related signals, e.g., head or brain motion, brain pulsation, blood flow, intermixed with susceptibility differences close or distant to the region of neuronal activity. Even though a plethora of preprocessing strategies have been published to address these confounds, their efficiency is still under discussion. In particular, physiological signal fluctuations closely related to brain supply may mask BOLD signal changes related to “true” neuronal activation. Here we explore recent technical and methodological advancements aimed at disentangling the various components, employing fast multiband vs. standard EPI, in combination with fast temporal ICA. Our preliminary results indicate that fast (TR <0.5 s) scanning may help to identify and eliminate physiologic components, increasing tSNR and functional contrast. In addition, biological variability can be studied and task performance better correlated to other measures. This should increase specificity and reliability in fMRI studies. Furthermore, physiological signal changes during scanning may then be recognized as a source of information rather than a nuisance. As we are currently still undersampling the complexity of the brain, even at a rather coarse macroscopic level, we should be very cautious in the interpretation of neuroscientific findings, in particular when comparing different groups (e.g., age, sex, medication, pathology, etc.). From a technical point of view our goal should be to sample brain activity at layer specific resolution with low TR, covering as much of the brain as possible without violating SAR limits. We hope to stimulate discussion toward a better understanding and a more quantitative use of fMRI. |
format | Online Article Text |
id | pubmed-5291320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
record_format | MEDLINE/PubMed |
spelling | pubmed-52913202017-02-03 Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential Boubela, Roland N. Kalcher, Klaudius Nasel, Christian Moser, Ewald Front Phys Article Functional MRI at 3T has become a workhorse for the neurosciences, e.g., neurology, psychology, and psychiatry, enabling non-invasive investigation of brain function and connectivity. However, BOLD-based fMRI is a rather indirect measure of brain function, confounded by physiology related signals, e.g., head or brain motion, brain pulsation, blood flow, intermixed with susceptibility differences close or distant to the region of neuronal activity. Even though a plethora of preprocessing strategies have been published to address these confounds, their efficiency is still under discussion. In particular, physiological signal fluctuations closely related to brain supply may mask BOLD signal changes related to “true” neuronal activation. Here we explore recent technical and methodological advancements aimed at disentangling the various components, employing fast multiband vs. standard EPI, in combination with fast temporal ICA. Our preliminary results indicate that fast (TR <0.5 s) scanning may help to identify and eliminate physiologic components, increasing tSNR and functional contrast. In addition, biological variability can be studied and task performance better correlated to other measures. This should increase specificity and reliability in fMRI studies. Furthermore, physiological signal changes during scanning may then be recognized as a source of information rather than a nuisance. As we are currently still undersampling the complexity of the brain, even at a rather coarse macroscopic level, we should be very cautious in the interpretation of neuroscientific findings, in particular when comparing different groups (e.g., age, sex, medication, pathology, etc.). From a technical point of view our goal should be to sample brain activity at layer specific resolution with low TR, covering as much of the brain as possible without violating SAR limits. We hope to stimulate discussion toward a better understanding and a more quantitative use of fMRI. 2014-02-11 /pmc/articles/PMC5291320/ /pubmed/28164083 http://dx.doi.org/10.3389/fphy.2014.00001 Text en https://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/3.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Article Boubela, Roland N. Kalcher, Klaudius Nasel, Christian Moser, Ewald Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential |
title | Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential |
title_full | Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential |
title_fullStr | Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential |
title_full_unstemmed | Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential |
title_short | Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential |
title_sort | scanning fast and slow: current limitations of 3 tesla functional mri and future potential |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291320/ https://www.ncbi.nlm.nih.gov/pubmed/28164083 http://dx.doi.org/10.3389/fphy.2014.00001 |
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