ABSTRACT Spinal cord injury (SCI) disrupts motor function, with recovery involving complex adaptive motor behaviors that cannot be fully assessed with traditional manual recovery assessments and their predefined recovery criteria. To move beyond these constraints, we employed motion sequencing (MoSeq), a machine learning-driven framework that automatically segments freely moving mouse behavior into discrete, repeated behavioral “syllables”, effectively capturing entire behavioral repertoires and dynamic behavioral…