Mild Traumatic Brain Injury Assessment using Functional Connectivity Estimators on Resting State EEG Analysis

In the US, over 2 million people su er from mild traumatic brain injury (mTBI), however in some cases it goes undiagnosed due to lack of symptoms or non-apparent lesion in conventional imaging. In attempts to create an mTBI biomarker, we analyze brain connectivity based on Phase Locking Values (PLV), imaginary PLV, and amplitude envelope correlation (AEC) computed from electroencephalography activity obtained at the resting state in thirteen mTBI and eight normal control subjects during two visits. The study was set up to examine difference groups within visits and groups between visits to observe any signs of deficits or recovery after injury. Functional connectivity graph theory was computed for both intra- and cross-frequency interactions for each subject individually. Finally, classification of the subjects was performed using Support Vector Machines with linear kernel to rank the features and separate the groups effectively.