Abstract
Neurons and neural networks in the brain, which also interest many people in the field of engineering, are nonlinear systems. Neurons fire not only regularly but also irregularly depending on the membrane potential, stimulus intensity, and stimulus frequency. This irregular firing is nonperiodic oscillation, which is subject to a dynamical law referred to as chaos. In neural networks, the field potential, which reflects the mass activity of neurons, causes phase locking and chaotic responses to periodic stimulation. That is, the degree of synchronization and the number of synchronous neurons fluctuate owing to periodic stimulation. Here, the nonlinear dynamical features of neurons and neural networks are first reviewd. It is then demonstrated that stochastic resonance (SR) occurs in the hippocampal CA3-CA1 network model, and memory patterns embedded in Schaffer collateral synapses in CA1 can be recalled via SR, as an example of research on information-processing mechanisms in the brain.
