ABSTRACT
This chapter begins with a discussion of what control of chaos involves, including an account of algorithms for effecting control using experimental data. A modular network model for human information processing based on control of chaos is then presented. This model was inspired by ideas originally proposed by Freeman using neural preparations. Throughout this modeling exercise, the relationships between control of chaos and contemporary adaptive models for learning and memory are highlighted. Simulations of the controlled chaotic neural network suggest that such a network might serve as a feasible cognitive model. The control of chaos procedure used by Pyragas involves stimulating the chaotic system with the difference between an external stimulus and the current output of the system. Control of chaos technology has promise as a practical tool for analyzing perplexing psychological problems from both the theoretical and practical points of view.
