Burst and correlated firing in spiking neural network with global inhibitory feedback

Abstract

Burst and correlated firing activities are observed experimentally in a variety of brain areas, which transmit and communicate information predominantly through spikes. The firing mode of spiking neurons relies on specific network characteristics. The inhibitory feedback is thought to be crucial to the burst firing. However, the effects of inhibitory feedback, and in particular the resulting bursting, on neural correlations need further studies. In order to understand how inhibitory feedback circuit modulates correlations and burst, we carry out numerical simulations of spiking neural network with global inhibitory feedback. Owing to the feedback inhibition, the neurons fire correlated action potentials of a long time scale and exhibit bursting fire pattern. We also found that, with constant output firing rate, the burst firing enhanced network correlations. These results suggest that in the spiking neural network with globally inhibitory feedback the shifts in the feedback strength can induce changes in burst probability, and then effect the correlated firing activities.