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Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging
Diffusion tensor imaging (DTI) provides us an insight into the micro-architecture of white-matter tracts in the brain. This method has proved promising in understanding and investigating the neuronal tracts and structural connectivity between the brain regions in primates as well as rodents. The clo...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5122865/ https://www.ncbi.nlm.nih.gov/pubmed/27886204 http://dx.doi.org/10.1038/srep36851 |
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author | Robinson, Jennifer L. Baxi, Madhura Katz, Jeffrey S. Waggoner, Paul Beyers, Ronald Morrison, Edward Salibi, Nouha Denney, Thomas S. Vodyanoy, Vitaly Deshpande, Gopikrishna |
author_facet | Robinson, Jennifer L. Baxi, Madhura Katz, Jeffrey S. Waggoner, Paul Beyers, Ronald Morrison, Edward Salibi, Nouha Denney, Thomas S. Vodyanoy, Vitaly Deshpande, Gopikrishna |
author_sort | Robinson, Jennifer L. |
collection | PubMed |
description | Diffusion tensor imaging (DTI) provides us an insight into the micro-architecture of white-matter tracts in the brain. This method has proved promising in understanding and investigating the neuronal tracts and structural connectivity between the brain regions in primates as well as rodents. The close evolutionary relationship between canines and humans may have spawned a unique bond in regard to social cognition rendering them useful as an animal model in translational research. In this study, we acquired diffusion data from anaesthetized dogs and created a DTI-based atlas for a canine model which could be used to investigate various white matter diseases. We illustrate the application of this atlas by calculating DTI tractography based structural connectivity between the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) regions of the default mode network (DMN) in dogs. White matter connectivity was investigated to provide structural basis for the functional dissociation observed between the anterior and posterior parts of DMN. A comparison of the integrity of long range structural connections (such as in the DMN) between dogs and humans is likely to provide us with new perspectives on the neural basis of the evolution of cognitive functions. |
format | Online Article Text |
id | pubmed-5122865 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-51228652016-11-28 Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging Robinson, Jennifer L. Baxi, Madhura Katz, Jeffrey S. Waggoner, Paul Beyers, Ronald Morrison, Edward Salibi, Nouha Denney, Thomas S. Vodyanoy, Vitaly Deshpande, Gopikrishna Sci Rep Article Diffusion tensor imaging (DTI) provides us an insight into the micro-architecture of white-matter tracts in the brain. This method has proved promising in understanding and investigating the neuronal tracts and structural connectivity between the brain regions in primates as well as rodents. The close evolutionary relationship between canines and humans may have spawned a unique bond in regard to social cognition rendering them useful as an animal model in translational research. In this study, we acquired diffusion data from anaesthetized dogs and created a DTI-based atlas for a canine model which could be used to investigate various white matter diseases. We illustrate the application of this atlas by calculating DTI tractography based structural connectivity between the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) regions of the default mode network (DMN) in dogs. White matter connectivity was investigated to provide structural basis for the functional dissociation observed between the anterior and posterior parts of DMN. A comparison of the integrity of long range structural connections (such as in the DMN) between dogs and humans is likely to provide us with new perspectives on the neural basis of the evolution of cognitive functions. Nature Publishing Group 2016-11-25 /pmc/articles/PMC5122865/ /pubmed/27886204 http://dx.doi.org/10.1038/srep36851 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Robinson, Jennifer L. Baxi, Madhura Katz, Jeffrey S. Waggoner, Paul Beyers, Ronald Morrison, Edward Salibi, Nouha Denney, Thomas S. Vodyanoy, Vitaly Deshpande, Gopikrishna Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging |
title | Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging |
title_full | Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging |
title_fullStr | Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging |
title_full_unstemmed | Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging |
title_short | Characterization of Structural Connectivity of the Default Mode Network in Dogs using Diffusion Tensor Imaging |
title_sort | characterization of structural connectivity of the default mode network in dogs using diffusion tensor imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5122865/ https://www.ncbi.nlm.nih.gov/pubmed/27886204 http://dx.doi.org/10.1038/srep36851 |
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