Geyer, H. | bioRxiv Science

bioRxiv2022

Does Functional Recovery Imply Stable Circuitry in the Spinal Animal?

Spinal animals can regain locomotor function through gait training. However, the neural processes involved in this recovery are poorly understood. Here we use computer simulation to address if the reorganization of spinal circuits associated with the functional recovery leads to meaningful, stable circuitry function. Specifically, we develop a neuromuscular model of a spinalized rat whose circuitry can adapt based on two alternative Hebbian learning strategies, one designed to guide the circuitry back to its normal pre-injury state and the other designed to destabilize it and drive it into saturation. Exposing the model to simulated gait training, we find that both strategies lead to recovery of locomotor function as defined by the outcome measures reported in studies with spinal rats. If anything, the results obtained with the destabilizing learning strategy seem to agree more with animal observations, since it produces similarly excessive amplitudes in muscle activity. Our results suggest that gait training of spinalized animals does not necessarily effect a meaningful recovery of their spinal circuitry function. More experimental work should be directed to clarify this point, as it may have grave implications for the potential of gait rehabilitation in patients with motor complete injuries of the spinal cord.

neuroscience↗

bioRxiv2021

A Neuromuscular Model of Human Locomotion Combines Spinal Reflex Circuits with Voluntary Movements

Existing models of human walking use low-level reflexes or neural oscillators to generate movement. While appropriate to generate the stable, rhythmic movement patterns of steady-state walking, these models lack the ability to change their movement patterns or spontaneously generate new movements in the specific, goal-directed way characteristic of voluntary movements. Here we present a neuromuscular model of human locomotion that bridges this gap and combines the ability to execute goal directed movements with the generation of stable, rhythmic movement patterns that are required for robust locomotion. The model represents goals for voluntary movements of the swing leg on the task level of swing leg joint kinematics. Smooth movements plans towards the goal configuration are generated on the task level and transformed into descending motor commands that execute the planned movements, using internal models. The movement goals and plans are updated in real time based on sensory feedback and task constraints. On the spinal level, the descending commands during the swing phase are integrated with a generic stretch reflex for each muscle. Stance leg control solely relies on dedicated spinal reflex pathways. Spinal reflexes stimulate Hill-type muscles that actuate a biomechanical model with eight internal joints and six free-body degrees of freedom. The model is able to generate voluntary, goal-directed reaching movements with the swing leg and combine multiple movements in a rhythmic sequence. During walking, the swing leg is moved in a goal-directed manner to a target that is updated in real-time based on sensory feedback to maintain upright balance, while the stance leg is stabilized by low-level reflexes and a behavioral organization switching between swing and stance control for each leg. With this combination of reflex-based stance leg and voluntary, goal-directed control of the swing leg, the model controller generates rhythmic, stable walking patterns in which the swing leg movement can be flexibly updated in real-time to step over or around obstacles.

neuroscience↗