ArticleNetwork neuroscience (Cambridge, Mass.)2025
Individualized mouse brain network models produce asymmetric patterns of functional connectivity after simulated traumatic injury.
Article in Network neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Mapping global brain reconfigurations following local targeted manipulations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
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4 authors.
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Abstract
The functional and cognitive effects of traumatic brain injury (TBI) are poorly understood, as even mild injuries (concussion) can lead to long-lasting, untreatable symptoms. Simplified brain dynamics models may help researchers better understand the relationship between brain injury patterns and functional outcomes. Properly developed, these computational models provide an approach to investigate the effects of both computational and in vivo injury on simulated dynamics and cognitive function, respectively, for model organisms. In this study, we apply the Kuramoto model and an existing mesoscale mouse brain structural network to develop a simplified computational model of mouse brain dynamics. We explore how to optimize our initial model to predict existing mouse brain functional connectivity collected from mice under various anesthetic protocols. Finally, to determine how strongly the changes in our optimized models' dynamics can predict the extent of a brain injury, we investigate how our simulations respond to varying levels of structural network damage. Results predict a mixture of hypo- and hyperconnectivity after experimental TBI, similar to results in TBI survivors, and also suggest a compensatory remodeling of connections that may have an impact on functional outcomes after TBI.
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