Automatic rule-based generation of spinal cord connectome model for a neuro-musculoskeletal limb in-silico

Studying spinal interactions with muscles has been of great importance for over a century. However, with surging spinal-related movement pathologies, the need for computational models to study spinal pathways is increasing. Although spinal cord connectome models have been developed, anatomically relevant spinal neuromotor models are rare. However, building and maintaining such models is time-consuming. In this study, the concept of the rule-based generation of a spinal connectome was introduced and lumbosacral connectome generation was demonstrated as an example. Furthermore, the rule-based autogenerated connectome models were synchronized with lower-limb musculoskeletal models to create an in-silico testbed. Using this setup, the role of the autogenic Ia-excitatory pathway in controlling the ankle angle was tested.