THE IMPACT OF MODERATE AND SEVERE TRAUMATIC BRAIN INJURY IN REDUCING NEURAL NETWORK DYNAMICS
Open Access
- Author:
- Gilbert, Nicholas Lyndon
- Area of Honors:
- Psychology
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Dr. Frank Gerard Hillary, Thesis Supervisor
Dr. Frank Gerard Hillary, Thesis Honors Advisor
Michael Nelson Hallquist, Faculty Reader - Keywords:
- traumatic brain injury
dynamic connectivity
fmri
reliability
graph theory - Abstract:
- Systems-level changes in neurological disorders have increasingly been studied using applications of network science to the cognitive neurosciences. The use of whole-brain fMRI analysis in investigating changes in brain subnetworks following traumatic brain injury (TBI) has mainly focused on static network mapping. Static analyses are capable of providing information regarding large-scale relationships between nodes, but often cannot distinguish subtle changes in network dynamics, which may be important indicators of neural network plasticity. This study focuses on state-level dynamic connectivity differences between TBI-affected individuals and healthy controls over the course of two runs of intermittent task and resting data. The goal of this study was to analyze the dynamic properties of neural networks engaged in periodic task stimulation to determine: (a) the reliability of inter-nodal and network-level characteristics over time and (b) the flexibility of networks states after traumatic brain injury. 23 individuals with moderate and severe TBI at least one-year post injury and 19 age- and education-matched healthy control adults were enrolled. Functional MRI, independent component analysis, dynamic connectivity modeling, and graph theory methods were utilized to reveal six network “states” with reliable frequency between runs and high reproducibility for both samples. Analysis of state transitions showed that the TBI sample had less movement, or transitions, between states than the healthy control sample. Altogether, these findings reveal the reliability of observable dynamic mental states during periods of task performance and contribute to emerging evidence that TBI may result in diminished network dynamics.