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The Rich Get Richer: Brain Injury Elicits Hyperconnectivity in Core Subnetworks
Journal article   Open access   Peer reviewed

The Rich Get Richer: Brain Injury Elicits Hyperconnectivity in Core Subnetworks

Frank G. Hillary, Sarah M. Rajtmajer, Cristina A. Roman, John D. Medaglia, Julia E. Slocomb-Dluzen, Vincent D. Calhoun, David C. Good and Glenn R. Wylie
PloS one, v 9(8), pp e104021-e104021
14 Aug 2014
PMID: 25121760
url
https://doi.org/10.1371/journal.pone.0104021View
Published, Version of Record (VoR)CC BY V4.0 Open

Abstract

Multidisciplinary Sciences Science & Technology Science & Technology - Other Topics
There remains much unknown about how large-scale neural networks accommodate neurological disruption, such as moderate and severe traumatic brain injury (TBI). A primary goal in this study was to examine the alterations in network topology occurring during the first year of recovery following TBI. To do so we examined 21 individuals with moderate and severe TBI at 3 and 6 months after resolution of posttraumatic amnesia and 15 age- and education-matched healthy adults using functional MRI and graph theoretical analyses. There were two central hypotheses in this study: 1) physical disruption results in increased functional connectivity, or hyperconnectivity, and 2) hyperconnectivity occurs in regions typically observed to be the most highly connected cortical hubs, or the "rich club". The current findings generally support the hyperconnectivity hypothesis showing that during the first year of recovery after TBI, neural networks show increased connectivity, and this change is disproportionately represented in brain regions belonging to the brain's core subnetworks. The selective increases in connectivity observed here are consistent with the preferential attachment model underlying scale-free network development. This study is the largest of its kind and provides the unique opportunity to examine how neural systems adapt to significant neurological disruption during the first year after injury.

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Collaboration types
Domestic collaboration
Web of Science research areas
Neurosciences
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