Memory Dynamics in Asynchronous Neural Networks

Abstract

A model which can perform learning, formation of memory without teacher for successive memory recalls is presented. The philosophical background of the study is summarized. The investigated network consists of two sets both composed of asynchronously firing model neurons. One set of neurons is responsible for the field effect, and the other is introduced as an input/output module. The field effect is given in the form of the system's self-response. It is shown that positive and negative global feedbacks by the field effect play an essential role in the successive recall of stored patterns. The possibility that these proposed mechanisms are implemented in the brain is discussed. We obtained a quasi-deterministic law on the level of a macrovariable concerning a random successive recall of memory representations by taking a Lorenz-plot of this macrovariable. We show that this macroscopic order is deterministic chaos steming from collapse of tori and this type of chaos can be an effective gadget for memory traces.