STRUCTURE AND DYNAMICS OF PRECISE FIRING SEQUENCES DETECTED IN COUPLED NEURAL NETWORKS

We simulated a large scale spiking neural network
characterized by an initial developmental phase featuring cell death
driven by excessive firing rate, followed by the spike timing dependent
synaptic plasticity (STDP) in presence of Poissonian noise. The analysis
of the effective spike trains recorded throughout the whole network
reveled appearance of precise firing sequences that suggests a self
organization of initially randomly connected networks. The firing
dynamic of initially identical network topologies was analyzed and
compared in three cases: in presence of temporally structured stimuli,
in absence of any stimulation and for coupled networks, where the output
spike trains of selected (efferent) neurons of a neuronal network
correspond to the the input to selected (afferent) neurons of another
similar network. The analysis of recurrent precise firing sequences
detected in these three cases showed differences in their structure and
dynamics; in particular, the precise firing sequences detected on the
downstream network are characterized by a more complex distribution of
their internal time structure.