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In the absence of sensory stimuli, continuous neuronal firings are observed in cortical networks. Such self-sustained ongoing activity is referred to as “spontaneous activity,” the dynamics of which is characterized by (1) low firing frequency, (2) irregularity, and (3) asynchronous firings among neurons. Despite numerous theoretical attempts, the mechanism that underlies the spontaneous firing activity has remained unclear. Recently, Teramae et al. proposed a neuronal network model with excitatory postsynaptic potentials (EPSPs) obeying a lognormal distribution, as observed in physiological experiments. The model successfully reproduced the key features of the spontaneous activity. Their model, however, focused mainly on the lognormal distribution of the network connectivity, where the correlation of EPSPs observed between bidirectionally coupled neurons was disregarded. The present paper introduces the correlated EPSPs to the lognormal network model and shows that a physiologically plausible level of such correlation causes (i) synchronous firings among neurons, (ii) extremely high firing frequencies observed in a group of neurons, and (iii) intermittent switching between asynchronous and synchronous firing states.

Synchronized Firing Induced by Correlated Bidirectional Couplings in a Neural Network Model for Spontaneous Activity