Development of dynamic network-based models of brain plasticity and vulnerability to traumatic brain injury.

By bringing together concepts and ideas that are rooted in temporal network theory, dynamical systems theory, and time-series analysis, we aim to develop a dynamic network-based approach to model brain tissue damage, brain network vulnerability, and plasticity from structural/functional MRI data together with neurophysiological parameters.

Network-based models for dynamic brain connectivity that are capable of modeling pertinent neurological consequences of local tissue damage in the brain is at the core of the project.

In particular, local tissue damage will be studied using in-silico simulations to model local perturbations in brain network connectivity and comparison to empirical data from traumatic brain injury patients.

By developing a platform for network-based models of dynamic functional neuroimaging data, we provide a system-level perspective on the dynamics of human brain function.

The goal of the proposed project is to acquire novel knowledge of the dynamics of the brain’s large-scale networks and build network-based models that can model the complex interplay between the brain’s ability to invoke compensatory mechanisms such as plasticity on one hand, and differences in brain network vulnerability to tissue damage on the other.

The project aims to provide key insights that are of clinical value to accurately diagnose and predict the long-term effects in terms of cognitive impairment and loss of sensory and motor functions after traumatic brain injury.