An optimal power-law for synchrony and lognormally synaptic weighted hub networks

Details about the structure of a network model are revealed at the spontaneous spike activity level, in which the power-law of synchrony is optimized to that observed in the CA3 hippocampal slice cultures. The network model is subject to spike noise with exponentially distributed interspike intervals. The excitatory (E) and/or inhibitory (I) neurons interact through synapses whose weights show a log-normal distribution. The spike behavior observed in the network model with the appropriate log-normal distributed synaptic weights fits best to that observed in the experiment. The best-fit is then achieved with high activities of I neurons having a hub-like structure, in which the I neurons, subject to optimized spike noise, are intensively projected from low active E neurons.