Journal article
Johan Nakuci, Matthew McGuire, F. Schweser, D. Poulsen, S. Muldoon
Brain connectivity, 2022
Brain connectivity, 2022
Semantic Scholar
DOI
PubMed
Cite
Cite
APA
Click to copy
Nakuci, J., McGuire, M., Schweser, F., Poulsen, D., & Muldoon, S. (2022). Differential patterns of change in brain connectivity resulting from severe traumatic brain injury. Brain Connectivity.
Chicago/Turabian
Click to copy
Nakuci, Johan, Matthew McGuire, F. Schweser, D. Poulsen, and S. Muldoon. “Differential Patterns of Change in Brain Connectivity Resulting from Severe Traumatic Brain Injury.” Brain connectivity (2022).
MLA
Click to copy
Nakuci, Johan, et al. “Differential Patterns of Change in Brain Connectivity Resulting from Severe Traumatic Brain Injury.” Brain Connectivity, 2022.
BibTeX Click to copy
@article{johan2022a,
title = {Differential patterns of change in brain connectivity resulting from severe traumatic brain injury.},
year = {2022},
journal = {Brain connectivity},
author = {Nakuci, Johan and McGuire, Matthew and Schweser, F. and Poulsen, D. and Muldoon, S.}
}
Abstract
BACKGROUND Traumatic brain injury (TBI) damages white matter tracts, disrupting brain network structure and communication. There exists a wide heterogeneity in the pattern of structural damage associated with injury, as well as a large heterogeneity in behavioral outcomes. However, little is known about the relationship between changes in network connectivity and clinical outcomes.
METHODS We utilize the rat lateral fluid-percussion injury (FPI) model of severe TBI to study differences in brain connectivity in 8 animals that received the insult and 11 animals that received only a craniectomy. Diffusion Tensor Imaging (DTI) is performed 5 weeks after the injury and network theory is used to investigate changes in white matter connectivity.
RESULTS We find that 1) global network measures are not able to distinguish between healthy and injured animals; 2) injury induced alterations predominantly exist in a subset of connections (subnetworks) distributed throughout the brain; and 3) injured animals can be divided into subgroups based on changes in network motifs - measures of local structural connectivity. Additionally, alterations in predicted functional connectivity indicate that the subgroups have different propensities to synchronize brain activity, which could relate to the heterogeneity of clinical outcomes.
DISCUSSION These results suggest that network measures can be used to quantify progressive changes in brain connectivity due to injury and differentiate among subpopulations with similar injuries but different pathological trajectories.