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This lecture explores computational models of spinal locomotor circuitry, focusing on the integration of supraspinal commands and afferent feedback signals to produce coordinated muscle activations for stable locomotion. The instructor presents models investigating central neuronal interactions and a neuromechanical model integrating neuronal circuits with the musculoskeletal system. These models accurately reproduce speed-dependent gait expressions and changes observed following manipulation of genetically-identified neuronal populations, offering experimentally testable predictions for future studies.