cubes

Abstract

High-Throughput Behavioral Phenotyping of Repetitive Mild Traumatic Brain Injury

A. M. CHOO1, A HACKETT1, R ZENOWICH1, A MORENO1, A BARBOZA1, M, OSBORNE1, I MORGANSTERN1, Q CHANG1, T HANANIA1
1PsychoGenics, Inc., Paramus, NJ, USA

Public awareness of the deleterious long-term effects of concussive brain injuries continues to increase due to media attention in professional sports as well as ever increasing diagnoses in military veterans exposed to improvised explosive devices in the battlefield. The vast permutations among injury parameters such as impact severity, interval between repetitive impacts, and total number of cumulative impacts is a barrier to the preclinical modeling of repetitive mild traumatic brain injury (rmTBI) using conventional behavioral assays. We utilize high-throughput computer vision behavioral phenotyping (SmartCube®) to map a spectrum of concussive doses. Bioinformatics analysis of over 2000 behavioral features show that repetitive impacts spaced 1 minute versus 10 minutes apart exhibit distinctive phenotypes. Activity metrics such as stepping and rearing are decreased in both rmTBI groups at 24 hours after injury. The reduction in activity relative to baseline levels is still evident at 2 weeks after rmTBI but the recovery signature is greater when the impacts were spaced 10 minutes apart compared to 1 minute apart. Anxiety metrics indicate that rmTBI increases metrics such as grooming and sniffing at 24 hours. At 2 weeks, the signature of the anxiety metrics is increased in both impact interval groups with the 1 minute impact interval showing a greater increase in anxiety. These data suggest that SmartCube® has the sensitivity and speed to handle the immense combinations of injury parameters for mapping concussive doses.

 

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