  A synfire chain is a network that can generate repeated spike patterns with
millisecond precision. Although synfire chains with only one activity
propagation mode have been intensively analyzed with several neuron models,
those with several stable propagation modes have not been thoroughly
investigated. By using the leaky integrate-and-fire neuron model, we
constructed a layered associative network embedded with memory patterns. We
analyzed the network dynamics with the Fokker-Planck equation. First, we
addressed the stability of one memory pattern as a propagating spike volley. We
showed that memory patterns propagate as pulse packets. Second, we investigated
the activity when we activated two different memory patterns. Simultaneous
activation of two memory patterns with the same strength led the propagating
pattern to a mixed state. In contrast, when the activations had different
strengths, the pulse packet converged to a two-peak state. Finally, we studied
the effect of the preceding pulse packet on the following pulse packet. The
following pulse packet was modified from its original activated memory pattern,
and it converged to a two-peak state, mixed state or non-spike state depending
on the time interval.
