Flexible control of motor units: is the multidimensionality of motor unit manifolds a sufficient condition?

Understanding flexibility in the neural control of movement requires identifying the distribution of common inputs to the motor units. In this study, we identified large samples of motor units from two lower limb muscles: the vastus lateralis (VL; up to 60 motor units per participant) and the gastrocnemius medialis (GM; up to 67 motor units per participant). First, we applied a linear dimensionality reduction method to assess the dimensionality of the manifolds underlying the motor unit activity. We subsequently investigated the flexibility in motor unit control under two conditions: sinusoidal contractions with torque feedback, and online control with visual feedback on motor unit firing rates. Overall, we found that the activity of GM motor units was effectively captured by a single latent factor defining a unidimensional manifold, whereas the VL motor units were better represented by three latent factors defining a multidimensional manifold. Despite this difference in dimensionality, the recruitment of motor units in the two muscles exhibited similarly low levels of flexibility. Using a spiking network model, we tested the hypothesis that dimensionality derived from factorization does not solely represent descending cortical commands but is also influenced by spinal circuitry. We demonstrated that a heterogeneous distribution of inputs to motor units, or specific configurations of recurrent inhibitory circuits, could produce a multidimensional manifold. This study clarifies an important debated issue, demonstrating that while motor unit firings of a non-compartmentalized muscle can lie in a multidimensional manifold, the CNS may still have limited capacity for flexible control of these units. KEY POINTS: To generate movement, the CNS distributes both excitatory and inhibitory inputs to the motor units. The level of flexibility in the neural control of these motor units remains a topic of debate with significant implications for identifying the smallest unit of movement control. By combining experimental data and in silico models, we demonstrated that the activity of a large sample of motor units from a single muscle can be represented by a multidimensional linear manifold; however, these units show very limited flexibility in their recruitment. The dimensionality of the linear manifold may not directly reflect the dimensionality of descending inputs but could instead relate to the organization of local spinal circuits.