Relationships among motor unit discharge parameters used to estimate synaptic inputs to motoneurons

The motor unit, consisting of a single α-motoneuron and the muscle fibers it innervates, is a neuromechanical transducer that transforms neural inputs from afferent, spinal, and descending sources into motoneuron discharge patterns and resulting muscle forces. The neural inputs that converge on the motoneuron constitute the motor command and are classified into three types: excitatory, inhibitory, and neuromodulatory. Motoneurons have complex and malleable input/output functions that depend on the mixture of excitatory, inhibitory, and neuromodulatory input. Recently, a reverse engineering paradigm was developed to identify temporal features of motoneuron discharge that can estimate aspects of excitatory, inhibitory, and neuromodulatory input. However, the common parameters used are sensitive to more than one type of input. The purpose of this study was to explore relationships among the reverse engineering parameters and to determine if the parameter set can be reduced to a smaller number of dimensions that summarize patterns in the data. We performed principal component (PC) analysis on seven reverse engineering parameters and found PCs corresponding to the amplification aspect of neuromodulation, the prolongation aspect of neuromodulation, and the pattern of inhibition.