Recurrent network dynamics stabilizes dynamics of embedded synfire chains.

<p>Spiking activity in a synfire chain ( layers, layer width ) receiving background input from an excitatory-inhibitory network (<b>A</b>, cf. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002596#pcbi-1002596-g001" target="_blank">Fig. 1 C</a>) or from a finite pool of excitatory and inhibitory Poisson processes (<b>B</b>, cf. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002596#pcbi-1002596-g001" target="_blank">Fig. 1 D</a>). Average input firing rates, in-degrees and amount of shared input are identical in both cases. Neurons of the first synfire layer (neuron ids ) are stimulated by current pulses at times and . Each neuron in layer receives inputs from all neurons in the preceding layer (synaptic weights , spike transmission delays ), and and excitatory and inhibitory background inputs, respectively, randomly drawn from the presynaptic populations. Neurons in the first layer receive and excitatory and inhibitory background inputs, respectively. Note that there is no feedback from the synfire chain to the embedding network. See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002596#pcbi-1002596-t002" target="_blank">Table 2</a> for network parameters.