Cargando…

Disconnection of network hubs and cognitive impairment after traumatic brain injury

Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes...

Descripción completa

Detalles Bibliográficos
Autores principales: Fagerholm, Erik D., Hellyer, Peter J., Scott, Gregory, Leech, Robert, Sharp, David J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4614120/
https://www.ncbi.nlm.nih.gov/pubmed/25808370
http://dx.doi.org/10.1093/brain/awv075
_version_ 1782396358828752896
author Fagerholm, Erik D.
Hellyer, Peter J.
Scott, Gregory
Leech, Robert
Sharp, David J.
author_facet Fagerholm, Erik D.
Hellyer, Peter J.
Scott, Gregory
Leech, Robert
Sharp, David J.
author_sort Fagerholm, Erik D.
collection PubMed
description Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury.
format Online
Article
Text
id pubmed-4614120
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-46141202015-10-26 Disconnection of network hubs and cognitive impairment after traumatic brain injury Fagerholm, Erik D. Hellyer, Peter J. Scott, Gregory Leech, Robert Sharp, David J. Brain Original Articles Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury. Oxford University Press 2015-06 2015-03-22 /pmc/articles/PMC4614120/ /pubmed/25808370 http://dx.doi.org/10.1093/brain/awv075 Text en © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Articles
Fagerholm, Erik D.
Hellyer, Peter J.
Scott, Gregory
Leech, Robert
Sharp, David J.
Disconnection of network hubs and cognitive impairment after traumatic brain injury
title Disconnection of network hubs and cognitive impairment after traumatic brain injury
title_full Disconnection of network hubs and cognitive impairment after traumatic brain injury
title_fullStr Disconnection of network hubs and cognitive impairment after traumatic brain injury
title_full_unstemmed Disconnection of network hubs and cognitive impairment after traumatic brain injury
title_short Disconnection of network hubs and cognitive impairment after traumatic brain injury
title_sort disconnection of network hubs and cognitive impairment after traumatic brain injury
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4614120/
https://www.ncbi.nlm.nih.gov/pubmed/25808370
http://dx.doi.org/10.1093/brain/awv075
work_keys_str_mv AT fagerholmerikd disconnectionofnetworkhubsandcognitiveimpairmentaftertraumaticbraininjury
AT hellyerpeterj disconnectionofnetworkhubsandcognitiveimpairmentaftertraumaticbraininjury
AT scottgregory disconnectionofnetworkhubsandcognitiveimpairmentaftertraumaticbraininjury
AT leechrobert disconnectionofnetworkhubsandcognitiveimpairmentaftertraumaticbraininjury
AT sharpdavidj disconnectionofnetworkhubsandcognitiveimpairmentaftertraumaticbraininjury