ArticleeNeuro
Personalized Connectome-Based Modeling in Patients with Semi-Acute Phase TBI: Relationship to Acute Neuroimaging and 6 Month Follow-Up.
Article in eNeuro. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Digital Twin Brain: Generating Multitask Behavior from Connectomes for Personalized Therapy.BME frontiers · 2026Article
- Translational network neuroscience: Nine roadblocks and possible solutions.Network neuroscience (Cambridge, Mass.) · 2025Article
- Prediction of cognitive outcome after mild traumatic brain injury from acute measures of communication within brain networks.Cortex; a journal devoted to the study of the nervous system and behavior · 2024Article
- Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias.Frontiers in aging neuroscience · 2023Article
- Whole-Brain Network Models: From Physics to Bedside.Frontiers in computational neuroscience · 2022Review
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Authors and funding
7 authors.
Funding
Abstract
Following traumatic brain injury (TBI), cognitive impairments manifest through interactions between microscopic and macroscopic changes. On the microscale, a neurometabolic cascade alters neurotransmission, while on the macroscale diffuse axonal injury impacts the integrity of long-range connections. Large-scale brain network modeling allows us to make predictions across these spatial scales by integrating neuroimaging data with biophysically based models to investigate how microscale changes invisible to conventional neuroimaging influence large-scale brain dynamics. To this end, we analyzed structural and functional neuroimaging data from a well characterized sample of 44 adult TBI patients recruited from a regional trauma center, scanned at 1-2 weeks postinjury, and with follow-up behavioral outcome assessed 6 months later. Thirty-six age-matched healthy adults served as comparison participants. Using The Virtual Brain, we fit simulations of whole-brain resting-state functional MRI to the empirical static and dynamic functional connectivity of each participant. Multivariate partial least squares (PLS) analysis showed that patients with acute traumatic intracranial lesions had lower cortical regional inhibitory connection strengths than comparison participants, while patients without acute lesions did not differ from the comparison group. Further multivariate PLS analyses found correlations between lower semiacute regional inhibitory connection strengths and more symptoms and lower cognitive performance at a 6 month follow-up. Critically, patients without acute lesions drove this relationship, suggesting clinical relevance of regional inhibitory connection strengths even when traumatic intracranial lesions were not present. Our results suggest that large-scale connectome-based models may be sensitive to pathophysiological changes in semi-acute phase TBI patients and predictive of their chronic outcomes.
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