1. Network topology changes in chronic mild traumatic brain injury (mTBI)
- Author
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Carrie Gentz, Donovan J. Roediger, Bryon A. Mueller, Michael T. Armstrong, Mark Fiecas, Timothy Hendrickson, Kelvin O. Lim, Alicia Fenske, Casey S. Gilmore, Randy H. Kardon, and Elias Boroda
- Subjects
medicine.medical_specialty ,Traumatic brain injury ,Cognitive Neuroscience ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Network topology ,050105 experimental psychology ,03 medical and health sciences ,0302 clinical medicine ,Physical medicine and rehabilitation ,TBI ,medicine ,Humans ,0501 psychology and cognitive sciences ,Radiology, Nuclear Medicine and imaging ,RC346-429 ,Brain Concussion ,Clustering coefficient ,Modularity (networks) ,Brain Mapping ,medicine.diagnostic_test ,business.industry ,Functional connectivity ,05 social sciences ,Diffuse axonal injury ,fMRI ,Brain ,Infant ,Cognition ,Regular Article ,medicine.disease ,Magnetic Resonance Imaging ,Graph theory ,Neurology ,Brain Injuries ,Neurology (clinical) ,Neurology. Diseases of the nervous system ,business ,Functional magnetic resonance imaging ,030217 neurology & neurosurgery - Abstract
Highlights • 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., 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
- Published
- 2021