Date of Award

Spring 2019

Degree Name

Bachelor of Science



First Advisor

Dan Lloyd

Second Advisor

Sarah Raskin


The ability of electroencephalogram (EEG) to be used as a diagnostic device for acquired brain injuries (ABI) has been conceptualized previously. Averaged event-related potentials (ERP) derived from an EEG are suitable as markers of dysfunction however, distinctive properties in the frequency domain have not been established previously. In the present study, we examined pre- existing EEG signal data of healthy adults (HA), mild ABI (mABI), and severe ABI (sABI) human groups. Through Fourier analysis performed in MATLAB, we found that individuals in our sample population (n=80) were able to be categorized into their respective group based on common neuronal activity detected at specific electrode locations. The characteristic activity patterns of individuals with ABI were found to be related to the amplitude of their theta waves. This novel way of interpreting EEG with respect to ABI, could significantly inform the diagnostic criteria for ABIs; it may also offer a pragmatic way for non-professionals to quickly detect concussions or similar injuries in competing athletes. Further efforts to sonify such neural activity of interest may elucidate more characteristic trends of ABI.


For Background Information See: "Relationship between physiological and clinical measures of prospective memory in individuals with mild acquired brain injury, severe acquired brain injury and healthy adults" - Consuelo Pedro (2015)

Senior thesis completed at Trinity College, Hartford, CT for the degree of Bachelor of Science in Neuroscience.