Double Inverse Stochastic Resonance with Dynamic Synapses

TL;DR

This paper explores how static and dynamic synapses influence inverse stochastic resonance in neuron models, revealing the emergence of double inverse stochastic resonance with dynamic synapses featuring short-term plasticity.

Contribution

It demonstrates the occurrence of double inverse stochastic resonance in neuron models with dynamic synapses, extending understanding of noise effects in neural systems.

Findings

Static synapses produce inverse stochastic resonance at certain firing rates.

Dynamic synapses can extend or diminish the ISR interval.

Double ISR can occur with short-term synaptic plasticity.

Abstract

We investigate the behavior of a model neuron that receives a biophysically-realistic noisy post-synaptic current based on uncorrelated spiking activity from a large number of afferents. We show that, with static synapses, such noise can give rise to inverse stochastic resonance (ISR) as a function of the presynaptic firing rate. We compare this to the case with dynamic synapses that feature short-term synaptic plasticity, and show that the interval of presynaptic firing rate over which ISR exists can be extended or diminished. We consider both short-term depression and facilitation. Interestingly, we find that a double inverse stochastic resonance (DISR), with two distinct wells centered at different presynaptic firing rates, can appear.