  When facing a task of balancing a dynamic system near an unstable
equilibrium, humans often adopt intermittent control strategy: instead of
continuously controlling the system, they repeatedly switch the control on and
off. Paradigmatic example of such a task is stick balancing. Despite the
simplicity of the task itself, the complexity of human intermittent control
dynamics in stick balancing still puzzles researchers in motor control. Here we
attempt to model one of the key mechanisms of human intermittent control,
control activation, using as an example the task of overdamped stick balancing.
In so doing, we focus on the concept of noise-driven activation, a more general
alternative to the conventional threshold-driven activation. We describe
control activation as a random walk in an energy potential, which changes in
response to the state of the controlled system. By way of numerical
simulations, we show that the developed model captures the core properties of
human control activation observed previously in the experiments on overdamped
stick balancing. Our results demonstrate that the double-well potential model
provides tractable mathematical description of human control activation at
least in the considered task, and suggest that the adopted approach can
potentially aid in understanding human intermittent control in more complex
processes.
