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Network topology changes in chronic mild traumatic brain injury (mTBI)
BACKGROUND: In mild traumatic brain injury (mTBI), diffuse axonal injury results in disruption of functional networks in the brain and is thought to be a major contributor to cognitive dysfunction even years after trauma. OBJECTIVE: Few studies have assessed longitudinal changes in network topology...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163989/ https://www.ncbi.nlm.nih.gov/pubmed/34023667 http://dx.doi.org/10.1016/j.nicl.2021.102691 |
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author | Boroda, Elias Armstrong, Michael Gilmore, Casey S. Gentz, Carrie Fenske, Alicia Fiecas, Mark Hendrickson, Tim Roediger, Donovan Mueller, Bryon Kardon, Randy Lim, Kelvin |
author_facet | Boroda, Elias Armstrong, Michael Gilmore, Casey S. Gentz, Carrie Fenske, Alicia Fiecas, Mark Hendrickson, Tim Roediger, Donovan Mueller, Bryon Kardon, Randy Lim, Kelvin |
author_sort | Boroda, Elias |
collection | PubMed |
description | BACKGROUND: In mild traumatic brain injury (mTBI), diffuse axonal injury results in disruption of functional networks in the brain and is thought to be a major contributor to cognitive dysfunction even years after trauma. OBJECTIVE: Few studies have assessed longitudinal changes in network topology in chronic mTBI. We utilized a graph theoretical approach to investigate alterations in global network topology based on resting-state functional connectivity in veterans with chronic mTBI. METHODS: 50 veterans with chronic mTBI (mean of 20.7 yrs. from trauma) and 40 age-matched controls underwent two functional magnetic resonance imaging scans 18 months apart. Graph theory analysis was used to quantify network topology measures (density, clustering coefficient, global efficiency, and modularity). Hierarchical linear mixed models were used to examine longitudinal change in network topology. RESULTS: With all network measures, we found a significant group × time interaction. At baseline, brain networks of individuals with mTBI were less clustered (p = 0.03) and more modular (p = 0.02) than those of HC. Over time, the mTBI networks became more densely connected (p = 0.002), with increased clustering (p = 0.001) and reduced modularity (p < 0.001). Network topology did not change across time in HC. CONCLUSION: These findings demonstrate that brain networks of individuals with mTBI remain plastic decades after injury and undergo significant changes in network topology even at the later phase of the disease. |
format | Online Article Text |
id | pubmed-8163989 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-81639892021-06-04 Network topology changes in chronic mild traumatic brain injury (mTBI) Boroda, Elias Armstrong, Michael Gilmore, Casey S. Gentz, Carrie Fenske, Alicia Fiecas, Mark Hendrickson, Tim Roediger, Donovan Mueller, Bryon Kardon, Randy Lim, Kelvin Neuroimage Clin Regular Article BACKGROUND: In mild traumatic brain injury (mTBI), diffuse axonal injury results in disruption of functional networks in the brain and is thought to be a major contributor to cognitive dysfunction even years after trauma. OBJECTIVE: Few studies have assessed longitudinal changes in network topology in chronic mTBI. We utilized a graph theoretical approach to investigate alterations in global network topology based on resting-state functional connectivity in veterans with chronic mTBI. METHODS: 50 veterans with chronic mTBI (mean of 20.7 yrs. from trauma) and 40 age-matched controls underwent two functional magnetic resonance imaging scans 18 months apart. Graph theory analysis was used to quantify network topology measures (density, clustering coefficient, global efficiency, and modularity). Hierarchical linear mixed models were used to examine longitudinal change in network topology. RESULTS: With all network measures, we found a significant group × time interaction. At baseline, brain networks of individuals with mTBI were less clustered (p = 0.03) and more modular (p = 0.02) than those of HC. Over time, the mTBI networks became more densely connected (p = 0.002), with increased clustering (p = 0.001) and reduced modularity (p < 0.001). Network topology did not change across time in HC. CONCLUSION: These findings demonstrate that brain networks of individuals with mTBI remain plastic decades after injury and undergo significant changes in network topology even at the later phase of the disease. Elsevier 2021-05-05 /pmc/articles/PMC8163989/ /pubmed/34023667 http://dx.doi.org/10.1016/j.nicl.2021.102691 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Regular Article Boroda, Elias Armstrong, Michael Gilmore, Casey S. Gentz, Carrie Fenske, Alicia Fiecas, Mark Hendrickson, Tim Roediger, Donovan Mueller, Bryon Kardon, Randy Lim, Kelvin Network topology changes in chronic mild traumatic brain injury (mTBI) |
title | Network topology changes in chronic mild traumatic brain injury (mTBI) |
title_full | Network topology changes in chronic mild traumatic brain injury (mTBI) |
title_fullStr | Network topology changes in chronic mild traumatic brain injury (mTBI) |
title_full_unstemmed | Network topology changes in chronic mild traumatic brain injury (mTBI) |
title_short | Network topology changes in chronic mild traumatic brain injury (mTBI) |
title_sort | network topology changes in chronic mild traumatic brain injury (mtbi) |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163989/ https://www.ncbi.nlm.nih.gov/pubmed/34023667 http://dx.doi.org/10.1016/j.nicl.2021.102691 |
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