The spinal cord facilitates cerebellar upper limb motor learning and control; inputs from neuromusculoskeletal simulation
Authors: Bruel Alice , Abadía Ignacio , Collin Thibault , Sakr Icare , Lorach Henri , Luque Niceto R. , Ros Eduardo , Ijspeert Auke 
Published: March 2023

Complex interactions between brain regions and the spinal cord (SC) govern body motion, which is ultimately driven by muscle activation. Motor planning or learning are mainly conducted at higher brain regions, whilst the SC acts as a brain-muscle gateway and as a motor control centre providing fast reflexes and muscle activity regulation. Thus, higher brain areas need to cope with the SC as an inherent and evolutionary older part of the body dynamics. Here, we address the question of how SC dynamics affects motor learning within the cerebellum; in particular, does the SC facilitate cerebellar motor learning or constitute a biological constraint? We provide an exploratory framework by integrating biologically plausible cerebellar and SC computational models in a musculoskeletal upper limb control loop. The cerebellar model, equipped with the main form of cerebellar plasticity, provides motor adaptation; whilst the SC model implements stretch reflex and reciprocal inhibition between antagonist muscles. The resulting spino-cerebellar model is tested performing a set of upper limb motor tasks, including external perturbation studies. A cerebellar model, lacking the implemented SC model and directly controlling the simulated muscles, was also tested in the same benchmark. The performances of the spino-cerebellar and cerebellar models were then compared, thus allowing directly addressing the SC influence on cerebellar motor adaptation and learning, and on handling external motor perturbations. Performance was assessed in both joint and muscle space, and compared with kinematic and EMG recordings from healthy participants. The differences in cerebellar synaptic adaptation between both models were also studied. We conclude that the SC facilitates cerebellar motor learning; when the SC circuits are in the loop, faster convergence in motor learning is achieved with simpler cerebellar synaptic weight distributions. The SC is also found to improve robustness against external perturbations, by better reproducing and modulating muscle cocontraction patterns.

Accurate motor control emerges from complex interactions between different brain areas, the spinal cord (SC), and the musculoskeletal system. These different actors contribute with distributed, integrative and complementary roles yet to be fully elucidated. To further study and hypothesise about such interactions, neuromechanical modelling and computational simulation constitute powerful tools. Here, we focus on the SC influence on motor learning in the cerebellum, an issue that has drawn little attention so far; does the SC facilitate or hinder cerebellar motor learning? To address this question, we integrate biologically plausible computational models of the cerebellum and SC, equipped with motor learning capability and fast reflex responses respectively. The resulting spino-cerebellar model is used to control a simulated musculoskeletal upper limb performing a set of motor tasks involving two degrees of freedom. Moreover, we use kinematic and EMG recordings from healthy participants to validate the model performance. The SC fast control primitives operating in muscle space are shown to facilitate cerebellar motor learning, both in terms of kinematics and synaptic adaptation. This, to the best of our knowledge, is the first time to be shown. The SC also modulates muscle cocontraction, improving the robustness against external motor perturbations.