Spinal cord injury (SCI) causes multifaceted postural and motor impairments that are challenging to quantify. Conventional behavioral tests, such as the Basso mouse scale (BMS), rely on qualitative observations, which do not detect subtle yet significant functional deficits. To perform unbiased and quantitative evaluation of motor function and posture after SCI, we employed high-speed video tracking with machine learning-based whole body pose estimation and weight-bearing analyses using the Blackbox system in freely moving mice. We found enduring alterations in posture induced by SCI not captured by conventional metrics. Postural deficits included reduced hindpaw spacing with concomitant increased forepaw spacing, narrowed femur width, and altered hindpaw angles, which remained evident beyond 42 days post-injury (dpi). Furthermore, sustained deficits in locomotor activity were identified as decreased distance traveled, decreased exploratory behavior, and disrupted fore-to-hindpaw speed ratio. Additionally, we analyzed behavioral motifs using Keypoint MoSeq software and found frequency changes in unique motor syllables correlating with forward acceleration and turning after SCI. Interestingly, while motor deficits persisted, sensory deficits, such as thermal and mechanical sensitivity, returned to baseline levels by 21 days after injury in C57BL/6J mice, with no subsequent hypersensitivity. Lastly, we developed a web-based application to assist in visualization and analyses of Blackbox-based kinematic data. Altogether, our study identifies distinct postural and motor deficits pre- and post-SCI using accurate, unbiased, and quantitative behavioral assessments. By tracking the unique features of motor recovery trajectories, researchers can more accurately assess the effectiveness of SCI therapeutic strategies.
Jobbins et al. (Fri,) studied this question.