Abstract
Recent progress in motor control suggests that in controlling unstable systems humans switch intermittently between the passive and active behavior instead of controlling the system in a continuous manner. Traditionally, the models of intermittent control employ the notion of threshold to mimic control switching mechanisms in humans. The notion of noise-driven control activation developed here provides a richer alternative to the conventional threshold-based models of intermittent motor control. We show that the model implementing noise-driven activation matches the experimental data on human balancing of virtual overdamped stick. Our results suggest that the stochasticity of the control activation mechanism is a fundamental property and may play an important role in the dynamics of human-controlled systems.
