A synfire chain in layered coincidence detectors with random synaptic delays

In this paper we analyze a synfire chain in a spiking neuron network. We also employ a coincidence-detector model showing the characteristics of temporal information processing more directly than the integrate-and-fire (I&F) model often discussed in the literature. There are two sources of randomness in a feed-forward network, however, only randomness in input spikes has attracted the attention of researchers and the randomness in synaptic delays has largely been ignored. Theoretical analyses of the synfire chain in I&F neurons without randomness in synaptic delays have shown that the dynamics of pulse packets can be viewed as a shift of the membrane potential distribution made by random noise input spikes. We introduce jittered synaptic delays instead of random noise inputs in a network of coincidence detectors and show that the network has almost the same dynamics as that of the I&F neurons. The distribution of the output spikes can be approximately described by an ordinary differential equation useful in understanding the dynamics of the pulse packets.