The effect of the number motor units and their maximum firing rate in a musculoskeletal model of human reaching

Vertebrate muscle has two features which heavily influence its force generation characteristics: rate-coded control and the division of muscles into multiple motor units (MUs). Studying how these features affect functional outcomes is difficult in vivo, but also in silico due to scarcity of modelling frameworks integrating rate-coded MU pool models with musculoskeletal models for functional tasks. We implement a human upper limb reaching model with muscles consisting of multiple rate-coded MUs and demonstrate its ability to generate accurate reaching movements under online control. Using this model, we investigate how reaching performance is influenced by two key features of MU pools, the number of MUs and their maximum firing rates. Our simulations suggest that very small MU pools with low firing rates tend to produce less accurate reaching movements compared to larger pools with higher firing rates. Increasing either the size of the pool or the maximum firing rate generally improves performance, but benefits become negligible beyond about 10-20 MUs and firing rates of 25-50 Hz. This pattern holds for the entire workspace but targets on the distal boundaries appear more sensitive to MU pool properties. Hence, our results indicate that rate coding and MU properties may play a part in determining functional outcomes in a task- and MU pool-dependent manner.