Fast global oscillations in networks of integrate-and-fire neurons with low firing rates

Fast global oscillations in networks of integrate-and-fire neurons with low firing rates

February 1, 2008 | Nicolas Brunel and Vincent Hakim
This paper investigates the dynamics of a network of sparsely connected inhibitory integrate-and-fire neurons, focusing on the regime where individual neurons fire irregularly and at low rates. The authors analytically study the transition from a stationary to an oscillatory global activity regime, where neurons exhibit weak synchronization. The oscillations become more pronounced when the inhibitory feedback is strong enough, and the period of these oscillations is primarily controlled by synaptic times, with some dependence on external input characteristics. In large but finite networks, global oscillations with finite coherence time are found to exist both above and below the critical inhibition threshold. The characteristics of these oscillations are determined by the system parameters in both regimes. The results are supported by numerical simulations, showing good agreement with the analytical findings. The study also explores the effects of synaptic time variability, connection number variability, and more detailed models of postsynaptic currents, providing insights into the robustness and generality of the observed phenomena.This paper investigates the dynamics of a network of sparsely connected inhibitory integrate-and-fire neurons, focusing on the regime where individual neurons fire irregularly and at low rates. The authors analytically study the transition from a stationary to an oscillatory global activity regime, where neurons exhibit weak synchronization. The oscillations become more pronounced when the inhibitory feedback is strong enough, and the period of these oscillations is primarily controlled by synaptic times, with some dependence on external input characteristics. In large but finite networks, global oscillations with finite coherence time are found to exist both above and below the critical inhibition threshold. The characteristics of these oscillations are determined by the system parameters in both regimes. The results are supported by numerical simulations, showing good agreement with the analytical findings. The study also explores the effects of synaptic time variability, connection number variability, and more detailed models of postsynaptic currents, providing insights into the robustness and generality of the observed phenomena.
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