This brief introduces a novel bioinspired motor neuron dynamical unit where the neural dynamics, responsible for the generation of the action potentials, is embedded into the actuator dynamics, which here plays the role of, and substitutes, the recovery variable into the classical neuron equations. A recently introduced nullcline-based control strategy, over servomotors embedded into piecewise linearly approximated FitzHugh–Nagumo neuron models, is here applied to the synchronization of two embodied motor-neuron units in the form of either a continuously active proportional gain or an event-driven strategy. In view of the application to such problems as the generation of adaptive control laws for distributed oscillatory networks, at the basis of bioinspired walking machines, the advantages in terms of the reduced-order dynamical equations and ease of synchronization are presented both through simulations and with experiments devoted to control networked Dynamixel MX-28AT servomotors via an microcontroller unit (MCU) board.