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Control of Spatiotemporal Chaos in Neuronal Networks

Different strategies for the control of chaotic neuronal networks and physical systems are presented. The variables of the dynamics span phase-spaces with very high dimensions. Novel control techniques are introduced that handle these high-dimensional cases. Depending on the system, several orbits with different spatiotemporal symmetries may be stabilized out of the chaotic attractor. The role of chaos control in information processing is pointed out.