Dynamical Responses of Chaotic Memory Dynamics to Weak Input in a Recurrent Neural Network Model

Abstract

Chaotic dynamics in a recurrent neural network model, in which limit cycle memory attractors are stored, is investigated by means of numerical methods. In particular, we focus on quick and sensitive response characteristics of chaotic memory dynamics to external input, which consists of part of an embedded memory attractor. We have calculated the correlation functions between the firing activities of neurons to understand the dynamical mechanisms of rapid responses. The results of the latter calculation show that quite strong correlations occur very quickly between almost all neurons within 1 ~ 2 updating steps after applying a partial input. They suggest that the existence of dynamical correlations or, in other words, transient correlations in chaos, play a very important role in quick and/or sensitive responses.