Andreas Herz, Zhaoping Li, J. van Hemmen
We study the representation of static patterns and temporal associa(cid:173) tions in neural networks with a broad distribution of signal delays. For a certain class of such systems, a simple intuitive understanding of the spatia-temporal computation becomes possible with the help of a novel Lyapunov functional. It allows a quantitative study of the asymptotic network behavior through a statistical mechanical analysis. We present analytic calculations of both retrieval quality and storage capacity and compare them with simulation results.