Compensatory functional connectome changes in a rat model of traumatic brain injury

Abstract

Penetrating cortical impact injuries alter neuronal communication beyond the injury epicenter, across regions involved in affective, sensorimotor, and cognitive processing. Understanding how traumatic brain injury reorganizes local and brain wide nodal interactions may provide valuable quantitative parameters for monitoring pathological progression and recovery. To this end, we investigated spontaneous fluctuations in the functional MRI signal obtained at 11.1 Tesla in rats sustaining controlled cortical impact and imaged at 2- and 30-days post-injury. Graph theory-based calculations were applied to weighted undirected matrices constructed from 12,879 pairwise correlations between functional MRI signals from 162 regions. Our data indicate that on days 2 and 30 post-controlled cortical impact there is a significant increase in connectivity strength in nodes located in contralesional cortical, thalamic, and basal forebrain areas. Rats imaged on day 2 post-injury had significantly greater network modularity than controls, with influential nodes (with high eigenvector centrality) contained within the contralesional module and participating less in cross-modular interactions. By day 30, modularity and cross-modular interactions recover, although a cluster of nodes with low strength and low eigenvector centrality remain in the ipsilateral cortex. Our results suggest that changes in node strength, modularity, eigenvector centrality, and participation coefficient track early and late traumatic brain injury effects on brain functional connectivity. We propose that the observed compensatory functional connectivity reorganization in response to controlled cortical impact may be unfavorable to brain wide communication in the early post-injury period.

Repetitive mild traumatic brain injury impairs resting state fMRI connectivity and alters protein profile signaling networks

“…These results positively reveal that local integration, efficiency, and integrative information processing across distal brain regions were significantly altered following rmTBI. Consistent with previous reports, we did not observe changes in the small-world index and net clustering coefficient after mTBI [25].…”

“…Recent work using rsfMRI identified broad functional connectivity deficits in human subjects; these defects correlated with diminished choice-reaction scores, showing high sensitivity. Our work improves upon pre-clinical and clinical studies because we dissected more granular aspects of functional connectivity in a mouse model of rmTBI and at ultra-high field [25,[39][40][41].…”

“…2D & E) for functional connectivity analysis. We calculated the node clustering coefficient, which is the index of the number of connected neighboring nodes [35]. We found that the clustering coefficient in specific thalamic and visual nodes were the most pronounced and significantly different changes identified (Fig.…”

“…Recent work using rsfMRI identified broad functional connectivity deficits in human subjects; these defects correlated with diminished choice-reaction scores, showing high sensitivity. Our work improves upon pre-clinical and clinical studies because we dissected more granular aspects of functional connectivity in a mouse model of rmTBI and at ultra-high field [25,39–41]. Functional graph metrics such as clustering coefficient, characteristic path length, centrality, and efficiency are quantifiable features that reveal how information flows throughout the network [42], and they were impaired following rmTBI (Fig.…”

“…We also calculated eigenvector and betweenness centrality to assess the highly influential nodes and nodes at the intersection between the shortest path, respectively [25]. We observed high betweenness centrality scores in thalamus dorsal lateral geniculate and high eigenvector centrality scores in modules with nodes located in sub-regions of corpus callosum and thalamus.…”