In Journal of neurotrauma
Exposure to repetitive head impacts (RHI) has been associated with long-term disturbances in cognition, mood, and neurobehavioral dysregulation, and reflected in neuroimaging. Distinct patterns of changes in quantitative features of the brain electrical activity (qEEG) have been demonstrated to be sensitive to brain changes seen in neurodegenerative disorders and in traumatic brain injuries (TBI). While these qEEG biomarkers are highly sensitive at time of injury, the long-term effects of exposure to RHI on brain electrical activity are relatively unexplored. Ten minutes of eyes closed resting EEG data were collected from a frontal and frontotemporal electrode montage, as well as assessments of neuropsychiatric function and age of first exposure (AFE) to American football. A machine learning (ML) methodology was used to derive a qEEG-based algorithm to discriminate former NFL players (n=87, 55.40±7.98 years old) from same-age men without history of RHI (n=68, 54.94±7.63 years old), and a second algorithm to discriminate former players with AFE<12 years (n=33) from AFE≥12 years (n=54). The algorithm separating NFL retirees from controls had specificity=80%, sensitivity=60%, and area under curve (AUC)=0.75. Within the NFL population, the algorithm separating AFE<12 from AFE≥12 resulted in a sensitivity=76%, specificity=52%, and AUC=0.72. The presence of a profile of EEG abnormalities in the NFL retirees and in those with younger AFE, includes features associated with neurodegeneration and the disruption of neuronal transmission between regions. These results support the long-term consequences of RHI and the potential of EEG as a biomarker of persistent changes in brain function.
Liang Bo, Alosco Michael L, Armañanzas Ruben, Martin Brett, Tripodis Yorghos, Stern Robert A, Prichep Leslie S
2022-Nov-02
BIOMARKERS, EEG, ELECTROPHYSIOLOGY, NEURODEGENERATIVE DISORDERS, TRAUMATIC BRAIN INJURY
