Cargando…
Parcellation‐based tractographic modeling of the dorsal attention network
INTRODUCTION: The dorsal attention network (DAN) is an important mediator of goal‐directed attentional processing. Multiple cortical areas, such as the frontal eye fields, intraparietal sulcus, superior parietal lobule, and visual cortex, have been linked in this processing. However, knowledge of ne...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6790316/ https://www.ncbi.nlm.nih.gov/pubmed/31536682 http://dx.doi.org/10.1002/brb3.1365 |
_version_ | 1783458772742569984 |
---|---|
author | Allan, Parker G. Briggs, Robert G. Conner, Andrew K. O'Neal, Christen M. Bonney, Phillip A. Maxwell, Brian D. Baker, Cordell M. Burks, Joshua D. Sali, Goksel Glenn, Chad A. Sughrue, Michael E. |
author_facet | Allan, Parker G. Briggs, Robert G. Conner, Andrew K. O'Neal, Christen M. Bonney, Phillip A. Maxwell, Brian D. Baker, Cordell M. Burks, Joshua D. Sali, Goksel Glenn, Chad A. Sughrue, Michael E. |
author_sort | Allan, Parker G. |
collection | PubMed |
description | INTRODUCTION: The dorsal attention network (DAN) is an important mediator of goal‐directed attentional processing. Multiple cortical areas, such as the frontal eye fields, intraparietal sulcus, superior parietal lobule, and visual cortex, have been linked in this processing. However, knowledge of network connectivity has been devoid of structural specificity. METHODS: Using attention‐related task‐based fMRI studies, an anatomic likelihood estimation (ALE) of the DAN was generated. Regions of interest corresponding to the cortical parcellation scheme previously published under the Human Connectome Project were co‐registered onto the ALE in MNI coordinate space and visually assessed for inclusion in the network. DSI‐based fiber tractography was performed to determine the structural connections between relevant cortical areas comprising the network. RESULTS: Twelve cortical regions were found to be part of the DAN: 6a, 7AM, 7PC, AIP, FEF, LIPd, LIPv, MST, MT, PH, V4t, VIP. All regions demonstrated consistent u‐shaped interconnections between adjacent parcellations. The superior longitudinal fasciculus connects the frontal, parietal, and occipital areas of the network. CONCLUSIONS: We present a tractographic model of the DAN. This model comprises parcellations within the frontal, parietal, and occipital cortices principally linked through the superior longitudinal fasciculus. Future studies may refine this model with the ultimate goal of clinical application. |
format | Online Article Text |
id | pubmed-6790316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-67903162019-10-21 Parcellation‐based tractographic modeling of the dorsal attention network Allan, Parker G. Briggs, Robert G. Conner, Andrew K. O'Neal, Christen M. Bonney, Phillip A. Maxwell, Brian D. Baker, Cordell M. Burks, Joshua D. Sali, Goksel Glenn, Chad A. Sughrue, Michael E. Brain Behav Original Research INTRODUCTION: The dorsal attention network (DAN) is an important mediator of goal‐directed attentional processing. Multiple cortical areas, such as the frontal eye fields, intraparietal sulcus, superior parietal lobule, and visual cortex, have been linked in this processing. However, knowledge of network connectivity has been devoid of structural specificity. METHODS: Using attention‐related task‐based fMRI studies, an anatomic likelihood estimation (ALE) of the DAN was generated. Regions of interest corresponding to the cortical parcellation scheme previously published under the Human Connectome Project were co‐registered onto the ALE in MNI coordinate space and visually assessed for inclusion in the network. DSI‐based fiber tractography was performed to determine the structural connections between relevant cortical areas comprising the network. RESULTS: Twelve cortical regions were found to be part of the DAN: 6a, 7AM, 7PC, AIP, FEF, LIPd, LIPv, MST, MT, PH, V4t, VIP. All regions demonstrated consistent u‐shaped interconnections between adjacent parcellations. The superior longitudinal fasciculus connects the frontal, parietal, and occipital areas of the network. CONCLUSIONS: We present a tractographic model of the DAN. This model comprises parcellations within the frontal, parietal, and occipital cortices principally linked through the superior longitudinal fasciculus. Future studies may refine this model with the ultimate goal of clinical application. John Wiley and Sons Inc. 2019-09-19 /pmc/articles/PMC6790316/ /pubmed/31536682 http://dx.doi.org/10.1002/brb3.1365 Text en © 2019 The Authors. Brain and Behavior published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Allan, Parker G. Briggs, Robert G. Conner, Andrew K. O'Neal, Christen M. Bonney, Phillip A. Maxwell, Brian D. Baker, Cordell M. Burks, Joshua D. Sali, Goksel Glenn, Chad A. Sughrue, Michael E. Parcellation‐based tractographic modeling of the dorsal attention network |
title | Parcellation‐based tractographic modeling of the dorsal attention network |
title_full | Parcellation‐based tractographic modeling of the dorsal attention network |
title_fullStr | Parcellation‐based tractographic modeling of the dorsal attention network |
title_full_unstemmed | Parcellation‐based tractographic modeling of the dorsal attention network |
title_short | Parcellation‐based tractographic modeling of the dorsal attention network |
title_sort | parcellation‐based tractographic modeling of the dorsal attention network |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6790316/ https://www.ncbi.nlm.nih.gov/pubmed/31536682 http://dx.doi.org/10.1002/brb3.1365 |
work_keys_str_mv | AT allanparkerg parcellationbasedtractographicmodelingofthedorsalattentionnetwork AT briggsrobertg parcellationbasedtractographicmodelingofthedorsalattentionnetwork AT connerandrewk parcellationbasedtractographicmodelingofthedorsalattentionnetwork AT onealchristenm parcellationbasedtractographicmodelingofthedorsalattentionnetwork AT bonneyphillipa parcellationbasedtractographicmodelingofthedorsalattentionnetwork AT maxwellbriand parcellationbasedtractographicmodelingofthedorsalattentionnetwork AT bakercordellm parcellationbasedtractographicmodelingofthedorsalattentionnetwork AT burksjoshuad parcellationbasedtractographicmodelingofthedorsalattentionnetwork AT saligoksel parcellationbasedtractographicmodelingofthedorsalattentionnetwork AT glennchada parcellationbasedtractographicmodelingofthedorsalattentionnetwork AT sughruemichaele parcellationbasedtractographicmodelingofthedorsalattentionnetwork |