  This paper addresses the problem of controlling the temporal dynamics of
complex nonlinear network-coupled dynamical systems, specifically in terms of
neurodynamics. Based on the Lyapunov direct method, we derive a control
strategy with theoretical guarantees of controllability. To verify the
performance of the derived control strategy, we perform numerical experiments
on two nonlinear network-coupled dynamical systems that emulate phase
synchronization and neural population dynamics. The results demonstrate the
feasibility and effectiveness of our control strategy.
