EVALUATING MAGNETIC SOURCE IMAGING FUNCTIONAL CONNECTIVITY NETWORKS OF SEVERE TRAUMATIC BRAIN INJURY TO ESTABLISH BIOMARKERS OF RECOVERY

Abstract

Traumatic brain injuries (TBI) are a leading cause of disability and death globally. As TBI severity increases, recovery becomes more complex and survival rates decline. Despite this, resources for tracking and assessing severe TBI (sTBI) recovery remain limited. Magnetoencephalography (MEG) holds promise for evaluating patients with sTBI and identifying post-injury biomarkers of recovery. This longitudinal study investigated brain functional connectivity networks in patients, (n=6, ages 26-71; acute Glasgow Coma Scale scores of 3-8) at three time points. Scans were conducted approximately 7 days, 1.5 months, and 8 months post-injury. Synthetic aperture magnetometry (SAM) maps were utilized to select one representative voxel, or source, per region of interest (ROI) corresponding to the AAL Atlas. Weighted phase-lag index (wPLI) was applied to virtual electrode data to generate functional connectivity networks. Connectome analysis revealed a decrease in delta connectivity between scans 1 and 2, indicative of transition from coma to wakefulness. Subsets of nodes within the ascending reticular activating system (ARAS), default mode network (DMN), and central executive network (CEN) were pulled from the connectome for additional analysis. These results identified clustering coefficient and nodal strength as indicators of reorganization and recovery. Overall, this study illustrates MEG’s utility in tracking functional connectivity network changes over time, offering insights into connectivity during sTBI recovery, representing valuable implications for clinical interventions.