This workstream will use and develop mathematical modelling and computational analysis to examine the data collected in other workstreams to help identify markers that can be used to better diagnose and predict the outcomes in TBI.
In recent years our understanding of the causes of neurological disorders has changed. Simplistic concepts of single brain regions being responsible for disease are being updated with the concept that the connectivity between different brain areas (known as called connectomics) is increasingly implicated in neurological disorders. This workstream will use computer models that describe both the neural activity within brain regions, as well as the connections between them and the fMRI, MEG and EEG data collected in other workstreams.
Using algorithms that we have developed in previous work, we will construct large scale brain networks and take two approaches to interrogating these networks. In the first approach, we are not seeking an answer to a preconceived question, but we will use a range of techniques to reveal potential markers of severity of TBI and the likelihood of developing specific outcomes.
The second approach is to define network markers based on specific assumptions made from previously published studies and define mathematical models to address these questions and learn more and help predict outcomes.
Lead Researchers