Quantitative evaluation of 3D mouse behaviors and motor function in the open-field after spinal cord injury using...

Thousands of scientists strive to identify cellular mechanisms that could lead to breakthroughs in developing ameliorative treatments for debilitating neural and muscular conditions such as spinal cord injury (SCI). Most studies use rodent models to test hypotheses, and these are all limited by the methods available to evaluate animal motor function. This study's goal was to develop a behavioral and locomotor assessment system in a murine model of SCI that enables quantitative kinematic measurements to be made automatically in the open-field by applying markerless motion tracking approaches. Three-dimensional movements of eight naïve, five mild, five moderate, and four severe SCI mice were recorded using 10 cameras (100 Hz). Background subtraction was used in each video frame to identify the animal's silhouette, and the 3D shape at each time was reconstructed using shape-from-silhouette. The reconstructed volume was divided into front and back halves using k-means clustering. The animal's front Center of Volume (CoV) height and whole-body CoV speed were calculated and used to automatically classify animal behaviors including directed locomotion, exploratory locomotion, meandering, standing, and rearing. More detailed analyses of CoV height, speed, and lateral deviation during directed locomotion revealed behavioral differences and functional impairments in animals with mild, moderate, and severe SCI when compared with naïve animals. Naïve animals displayed the widest variety of behaviors including rearing and crossing the center of the open-field, the fastest speeds, and tallest rear CoV heights. SCI reduced the range of behaviors, and decreased speed (r = .70 p<.005) and rear CoV height (r = .65 p<.01) were significantly correlated with greater lesion size. This markerless tracking approach is a first step toward fundamentally changing how rodent movement studies are conducted. By providing scientists with sensitive, quantitative measurement methods, subjectivity and human error is reduced, potentially providing insights leading to breakthroughs in treating human disease.