Computer Simulation of the Neural Control of Locomotion in the Cat

Locomotion is one of the most important behaviours and requires interaction between sensors at various levels of the nervous system and the limb muscles of an animal. The basic neural rhythm for locomotion in mammals has been shown to arise from local neural networks residing in the spinal cord and these networks are known as central pattern generators (CPGs). However, during the locomotion, these centres are constantly interacting with the sensory feedback signals coming from muscles, joints and peripheral skin receptors in order to adapt the stepping to varying environmental conditions. Conceptual models of mammalian locomotion have been constructed using mathematical models of locomotor subsystems based on the abundance of neurophysiological evidence obtained primarily in the cat. Several aspects of locomotor control using the cat as an animal model have been investigated employing computer simulations and here we use the same approach to address number of questions or/and hypotheses related to rhythmic locomotion in quadrupeds. Some of the involve questions are, role of mechanical linkage during deafferented walking, finding inherent stabilities/instabilities of muscle-joint interactions during normal walking, estimating phase dependent controlability of muscle action over joints. This thesis presents the basics of a biologically realistic model of mammalian locomotion and summarises methodological approaches in modelling quadruped locomotor subsystems such as CPGs, limb muscles and sensory pathways. In the first appended article, we extensively discuss the construction details of the three-dimensional computer simulator for the study of the hind leg neuro-musculo-skeletal-control system and its interactions during normal walking of the cat. The simulator with the walking model is programmed in Python scripting language with other supported open source libraries such as Open Dynamics Engine (ODE) for simulating body dynamics and OpenGL for three dimensional graphical representation. We have examined the functionality of the simulator and the walking model by simulating deafferented walking. It was possible to obtain a realistic stepping in the hind legs even without sensory feedback to the two controllers (CPGs) for each leg. We conclude that the mechanical linkages between the legs also play a major role in producing alternating gait. The use of simulations of walking in the cat for gaining insights into more complex interactions between the environment and the neuro-muscular-skeletal system is important especially for questions where a direct neurophysiological experiment can not be performed on a real walking animal. For instance, it is experimentally hard to isolate individual mechanisms without disrupting the natural walking pattern. In the second article, we introduce a different approach where we use the walking model to identify what control is necessary to maintain stability in the musculo-skeletal system. We show that the actions of most of the hindlimb muscles over the joints have an inherent stability during stepping, even without the involvement of proprioceptive feedback mechanisms. In addition, we observe that muscles generating movements in the ankle joint of the hind leg must be controlled by neural mechanisms, which may involve supraspinal structures, over the whole step cycle.QC 2010111