Estimation of functional connectivity of neuronal network from spike data

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I estimated a functional connectivity of neuronal network from burst like neuronal spike data recorded from cultured neurons. With using a dynamic Bayesian estimation algorithm, I obtained a network model the distribution of synaptic weights of which has a long tail. The obtained model could reproduce the burst like neuronal activities, which disappeared when the synaptic weights were shuffled. These results suggest that both the weight distribution and the network structure are important to induce the burst like neuronal activities.