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The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI)
Measurements of water molecule diffusion along fiber tracts in CNS by diffusion tensor imaging (DTI) provides a static map of neural connections between brain centers, but does not capture the electrical activity along axons for these fiber tracts. Here, a modification of the DTI method is presented...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4241967/ https://www.ncbi.nlm.nih.gov/pubmed/25431757 http://dx.doi.org/10.1016/j.mex.2014.09.004 |
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author | Makris, Nikos Gasic, Gregory P. Garrido, Leoncio |
author_facet | Makris, Nikos Gasic, Gregory P. Garrido, Leoncio |
author_sort | Makris, Nikos |
collection | PubMed |
description | Measurements of water molecule diffusion along fiber tracts in CNS by diffusion tensor imaging (DTI) provides a static map of neural connections between brain centers, but does not capture the electrical activity along axons for these fiber tracts. Here, a modification of the DTI method is presented to enable the mapping of active fibers. It is termed dynamic diffusion tensor imaging (dDTI) and is based on a hypothesized “anisotropy reduction due to axonal excitation” (“AREX”). The potential changes in water mobility accompanying the movement of ions during the propagation of action potentials along axonal tracts are taken into account. Specifically, the proposed model, termed “ionic DTI model”, was formulated as follows. • First, based on theoretical calculations, we calculated the molecular water flow accompanying the ionic flow perpendicular to the principal axis of fiber tracts produced by electrical conduction along excited myelinated and non-myelinated axons. • Based on the changes in molecular water flow we estimated the signal changes as well as the changes in fractional anisotropy of axonal tracts while performing a functional task. • The variation of fractional anisotropy in axonal tracts could allow mapping the active fiber tracts during a functional task. Although technological advances are necessary to enable the robust and routine measurement of this electrical activity-dependent movement of water molecules perpendicular to axons, the proposed model of dDTI defines the vectorial parameters that will need to be measured to bring this much needed technique to fruition. |
format | Online Article Text |
id | pubmed-4241967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-42419672015-01-01 The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI) Makris, Nikos Gasic, Gregory P. Garrido, Leoncio MethodsX Article Measurements of water molecule diffusion along fiber tracts in CNS by diffusion tensor imaging (DTI) provides a static map of neural connections between brain centers, but does not capture the electrical activity along axons for these fiber tracts. Here, a modification of the DTI method is presented to enable the mapping of active fibers. It is termed dynamic diffusion tensor imaging (dDTI) and is based on a hypothesized “anisotropy reduction due to axonal excitation” (“AREX”). The potential changes in water mobility accompanying the movement of ions during the propagation of action potentials along axonal tracts are taken into account. Specifically, the proposed model, termed “ionic DTI model”, was formulated as follows. • First, based on theoretical calculations, we calculated the molecular water flow accompanying the ionic flow perpendicular to the principal axis of fiber tracts produced by electrical conduction along excited myelinated and non-myelinated axons. • Based on the changes in molecular water flow we estimated the signal changes as well as the changes in fractional anisotropy of axonal tracts while performing a functional task. • The variation of fractional anisotropy in axonal tracts could allow mapping the active fiber tracts during a functional task. Although technological advances are necessary to enable the robust and routine measurement of this electrical activity-dependent movement of water molecules perpendicular to axons, the proposed model of dDTI defines the vectorial parameters that will need to be measured to bring this much needed technique to fruition. Elsevier 2014-09-26 /pmc/articles/PMC4241967/ /pubmed/25431757 http://dx.doi.org/10.1016/j.mex.2014.09.004 Text en © 2014 The Authors http://creativecommons.org/licenses/by/3.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Makris, Nikos Gasic, Gregory P. Garrido, Leoncio The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI) |
title | The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI) |
title_full | The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI) |
title_fullStr | The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI) |
title_full_unstemmed | The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI) |
title_short | The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI) |
title_sort | ionic dti model (idti) of dynamic diffusion tensor imaging (ddti) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4241967/ https://www.ncbi.nlm.nih.gov/pubmed/25431757 http://dx.doi.org/10.1016/j.mex.2014.09.004 |
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