Neurorobotic insights into locomotor control, turning, and recovery after thoracic spinal cord injury

Abstract

Locomotion is produced by the coordination of neural circuits, sensory feedback, and musculoskeletal system, requiring integrated models to uncover how these components interact to generate adaptive movement, steering, and recovery after spinal cord injury. Here, we present complementary quadrupedal neurorobotic models that span different levels of biological detail to investigate both steering control and locomotor recovery after thoracic spinal cord injury. In the first application, we systematically examined how left-right asymmetries in locomotor control parameters shape turning. Simulations showed that asymmetric modulation of intrinsic rhythm frequency destabilizes interlimb coordination, whereas asymmetries in duty factor, limb trajectory, mediolateral foot placement, and spine bending produce stable turning across a range of curvatures. Optimized combinations of control parameter asymmetries further improved stability, with distinct combinations emerging for different turning demands. In the second application the model integrates experimentally derived circuits of rhythm generators, pattern formation networks, commissural and long propriospinal pathways, with Hill-type muscles, and multimodal sensory feedback, providing an embodied platform for studying neural control of locomotion before and after thoracic spinal cord contusion. Simulated recovery after thoracic spinal cord injury required reorganization of sensory feedback and supra- and sublesional spinal connectivity together with biomechanical adaptations that enhanced sensory feedback, stabilized locomotion, and shifted the rhythm generators into a new operating regime. Overall, robotic platforms integrate neural control with biomechanics to understand locomotor function, recovery, and adaptation in health and disease.