Information processing using stable and unstable oscillations: a tutorial

We review some principles for information storage and processing, based on oscillations in dynamical systems. Oscillations and chaos are present in both biological and artificial neurons. A single biological neuron has an oscillatory dynamics, and can generate chaos. At a macroscopic level however, chaos is not created by the dynamics of individual neurons, but by the interaction of large groups of neurons. These macroscopic oscillations are measured by EEG recordings that indicate the presence of chaotic attractors in the brain. Also in the visual cortex, neurons have been found to oscillate in a coherent way depending on the global stimulus. On the other hand, as recurrent artificial neural networks are non linear dynamical systems, it is possible to get different behaviours by adjusting their parameters: convergence toward equilibrium points, toward periodic solutions or chaotic trajectories. In this case, the study of oscillations is more a scientific activity than a goal for storing and processing information. In this paper, however, we explore the possibilities to make use of chaos for information storage