Journal article
Network topology changes in chronic mild traumatic brain injury (mTBI)
NeuroImage clinical, Vol.31, pp.102691-102691
2021
DOI: 10.1016/j.nicl.2021.102691
PMCID: PMC8163989
PMID: 34023667
Abstract
•Brain networks in mTBI remain plastic decades after injury.•Global integration increased over time in mTBI group to the level of Controls.•mTBI networks became more clustered and less segregated into modules over time.
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.
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.
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.
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.
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.
Details
- Title: Subtitle
- Network topology changes in chronic mild traumatic brain injury (mTBI)
- Creators
- Elias Boroda - Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USAMichael Armstrong - Minneapolis VA Health Care System, Minneapolis, MN, USACasey S Gilmore - Minneapolis VA Health Care System, Minneapolis, MN, USACarrie Gentz - Minneapolis VA Health Care System, Minneapolis, MN, USAAlicia Fenske - Minneapolis VA Health Care System, Minneapolis, MN, USAMark Fiecas - Center for the Prevention and Treatment of Visual Loss, Iowa City VA Healthcare System, Iowa City, IA, USATim Hendrickson - University of Minnesota Informatics Institute, University of Minnesota, Minneapolis, MN, USADonovan Roediger - Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USABryon Mueller - Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USARandy Kardon - University of Minnesota Informatics Institute, University of Minnesota, Minneapolis, MN, USAKelvin Lim - Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Resource Type
- Journal article
- Publication Details
- NeuroImage clinical, Vol.31, pp.102691-102691
- DOI
- 10.1016/j.nicl.2021.102691
- PMID
- 34023667
- PMCID
- PMC8163989
- NLM abbreviation
- Neuroimage Clin
- ISSN
- 2213-1582
- eISSN
- 2213-1582
- Publisher
- Elsevier Inc
- Grant note
- DOI: 10.13039/100000005, name: US Department of Defense
- Language
- English
- Date published
- 2021
- Academic Unit
- Iowa Neuroscience Institute; Ophthalmology and Visual Sciences
- Record Identifier
- 9984101223202771
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