The distribution of time intervals between successive spikes generated by a neuronal cell --the inter spike intervals (ISI)-- may reveal interesting features of the underlying dynamics. In the present study we analyze the ISI sequence --the spike train-- generated by a neuron whose output activity is modelled by a jump-diffusion process. We show that, with specific ranges of the involved parameters, it is possible to observe multimodal ISI distributions, thus revealing ``characteristic firing times''. The activity of this neuron is studied in the framework of a small network and its dynamics exhibited resonant-like behavior, with modulation of the spike timings by the noise intensity. We show also that the strong inhibitory inputs might play a role beyond the maintenance of the excitatory/inhibitory balance and could facilitate the signal transmission through the small network.
Multimodal inter-spike intervals distributions in a jump-diffusion neuronal model
SIROVICH, ROBERTA;SACERDOTE, Laura Lea;
2006-01-01
Abstract
The distribution of time intervals between successive spikes generated by a neuronal cell --the inter spike intervals (ISI)-- may reveal interesting features of the underlying dynamics. In the present study we analyze the ISI sequence --the spike train-- generated by a neuron whose output activity is modelled by a jump-diffusion process. We show that, with specific ranges of the involved parameters, it is possible to observe multimodal ISI distributions, thus revealing ``characteristic firing times''. The activity of this neuron is studied in the framework of a small network and its dynamics exhibited resonant-like behavior, with modulation of the spike timings by the noise intensity. We show also that the strong inhibitory inputs might play a role beyond the maintenance of the excitatory/inhibitory balance and could facilitate the signal transmission through the small network.
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