Poster presentation at MEA Meeting 2014:
9th International Meeting on Substrate-Integrated Microelectrode Arrays, July 1-4, 2014
Dynamical behavior of bursting and reverberation in a cultured network contains important information on its connectivity or topology. Since the structural properties of a network is usually harder to measure directly, it is desirable to recover this information through analysis of the measured dynamics of the network. To understand the relationship between structure and dynamics in a neuronal network, we modify an electrophysiological model of spiking neurons, capable of producing reverberatory bursts that closely resemble what have been observed in cultures, and apply it to networks of different topologies ranging from scale-free to random networks with narrow degree distribution. By varying parameters controlling the excitability of neurons and efficacy of synapses while preserving the time ratio between the bursting and resting states, we show that the two factors compensate each other well only for networks of narrow degree distribution. For these networks, the reverberation remains clearly evident for the entire parameter range considered. For networks of broad degree distribution such as scale-free networks, the mean burst period varies significantly with the parameters, while the reverberation, if exists, is only evident for a limit range of the parameter space.