School of Computer Science Intranet
J. Bose, S.B. Furber, J.L. Shapiro.
In this paper we examine issues involving the transmission of information by spike trains through networks made of real time asyn- chronous spiking neurons. For our convenience we use a spiking model that is has an intrinsic delay between an input and output spike. We look at issues involving transmission of a desired average level of stable spiking activity over many layers, and show how feed-back reset inhibition can achieve this aim. We then deal with the coherence of spike trains and show that it is possible for a burst of spikes emitted by a layer to not diverge when passing through different layers of neurons. We present the results of simulations done on a multi layered feed-forward system to illustrate our method.