Evaluating a Novel Method of EEG Evoked Response Potential Analysis in Concussion Assessment

Mild traumatic brain injury (mTBI), also known as concussion, occurs commonly in sport and Motor Vehicle accidents. The Centers for Disease Control and Prevention estimate that as many as 3.8 million sport-related concussions occur annually in the United States. Despite ongoing research, there is no highly sensitive clinical test for cognitive function that can be rapidly applied in a sporting environment. This makes the clinical diagnosis of concussion particularly difficult, as the clinical presentation of concussion is highly variable with symptoms often evolving over time. Furthermore, with less than 10% of concussions resulting in loss of consciousness, self-reported symptom presence may be the only initial evidence of a concussion. These factors make concussion a challenging injury to diagnose. Given the variability in concussion presentations, there is no single test that can diagnose a concussion. ElMindA, the sponsor of this study, has developed a novel method to automatically reveal functional networks of brain activity based on analysis of EEG Event Related Potential (ERP) data. This technological platform is capable of providing new metrics of brain function that can assist in patient evaluation and management. The analysis is done in two separate processes that are entirely separate and are performed independently of one another. Reference Brain Network Models of EEG data were recorded and analyzed from several groups of subjects to establish a set of group patterns that characterized the brain network activity of the group. EEG data from a single subject are processed to enable subject evaluation, as compared to the established group patterns. This individual analysis is the basis of the BNA scores computed for an individual subject. Therefore, this investigation is designed to evaluate the clinical utility of ElMindA's BNA scores in detecting and managing concussive injuries.