Controlling Nonchaotic Neuronal Noise Using Chaos Control Techniques

Abstract

Chaos control techniques have been used to control a wide variety of experimental systems, including physiological systems. Here chaos control, periodic pacing, and anticontrol were applied to a noise-driven, nonchaotic neuronal model, and results similar to those recently reported for apparently chaotic, in vitro neuronal networks were obtained. Similar results were produced when chaos control was applied to a simple stochastic system. These suggest that the neuronal networks may not have been chaotic and that chaos control techniques can be applied to a wider range of experimental systems (e.g., stochastic systems) than previously thought.