Network-based statistic and connectome-based predictive modeling for structural alterations in military service members with mild TBI

Motivation: Mild traumatic brain injury (mTBI) presents with a wide array of clinical features due to the great heterogeneity of underlying pathological features. Goal(s): To identify aberrant structural connectivity in mTBI service members (SMs) and to evaluate the usefulness of predictive models of brain-behavior relationships from structural connectivity data. Approach: Employ Network-Based Statistic (NBS) and Connectome-based Predictive Modeling (CPM) to evaluate the structural connectome of SMs who had a remote mTBI, as mapped by advanced diffusion MRI. Results: NBS identified sub-networks involving the default mode networks with decreased connectivity density; CPM revealed an association between the predicted post-concussive symptom scores and the self-report scores. Impact: Structure connectome-based analysis using advanced diffusion MRI techniques has the potential for the objective evaluation of white matter properties, which can become biomarkers in monitoring clinical symptoms in SMs after a remote brain injury