Diminished neural network dynamics after moderate and severe traumatic brain injury

Nicholas Gilbert, Rachel A. Bernier, Vincent D. Calhoun, Einat Brenner, Emily Grossner, Sarah M. Rajtmajer, Frank G. Hillary

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Over the past decade there has been increasing enthusiasm in the cognitive neurosciences around using network science to understand the system-level changes associated with brain disorders. A growing literature has used whole-brain fMRI analysis to examine changes in the brain’s subnetworks following traumatic brain injury (TBI). Much of network modeling in this literature has focused on static network mapping, which provides a window into gross inter-nodal relationships, but is insensitive to more subtle fluctuations in network dynamics, which may be an important predictor of neural network plasticity. In this study, we examine the dynamic connectivity with focus on state-level connectivity (state) and evaluate the reliability of dynamic network states over the course of two runs of intermittent task and resting data. The goal was to examine the dynamic properties of neural networks engaged periodically with task stimulation in order to determine: 1) the reliability of inter-nodal and network-level characteristics over time and 2) the transitions between distinct network states after traumatic brain injury. To do so, we enrolled 23 individuals with moderate and severe TBI at least 1-year post injury and 19 age- and education-matched healthy adults using functional MRI methods, dynamic connectivity modeling, and graph theory. The results reveal several distinct network “states” that were reliably evident when comparing runs; the overall frequency of dynamic network states are highly reproducible (r-values>0.8) for both samples. Analysis of movement between states resulted in fewer state transitions in the TBI sample and, in a few cases, brain injury resulted in the appearance of states not exhibited by the healthy control (HC) sample. Overall, the findings presented here demonstrate the reliability of observable dynamic mental states during periods of on-task performance and support emerging evidence that brain injury may result in diminished network dynamics.

Original languageEnglish (US)
Article numbere0197419
JournalPloS one
Volume13
Issue number6
DOIs
StatePublished - Jun 2018

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neural networks
Brain
Neural networks
brain
Brain Injuries
Magnetic Resonance Imaging
Neuronal Plasticity
Task Performance and Analysis
Brain Diseases
Education
Traumatic Brain Injury
Wounds and Injuries
neurophysiology
Graph theory
sampling
Plasticity
education

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Gilbert, Nicholas ; Bernier, Rachel A. ; Calhoun, Vincent D. ; Brenner, Einat ; Grossner, Emily ; Rajtmajer, Sarah M. ; Hillary, Frank G. / Diminished neural network dynamics after moderate and severe traumatic brain injury. In: PloS one. 2018 ; Vol. 13, No. 6.
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Diminished neural network dynamics after moderate and severe traumatic brain injury. / Gilbert, Nicholas; Bernier, Rachel A.; Calhoun, Vincent D.; Brenner, Einat; Grossner, Emily; Rajtmajer, Sarah M.; Hillary, Frank G.

In: PloS one, Vol. 13, No. 6, e0197419, 06.2018.

Research output: Contribution to journalArticle

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