Auto and crosscorrelograms for the spike response of LIF neurons with slow synapses

TL;DR

This paper provides an analytical framework for understanding the firing variability and synchronization of leaky integrate-and-fire neurons with slow synapses under noisy conditions, advancing the theoretical modeling of neural responses.

Contribution

It introduces a second-order analytical description of spike train correlations for LIF neurons with slow synapses, improving upon previous approximations.

Findings

Derived auto- and cross-correlation functions for neuron pairs

Enhanced understanding of neuron communication mechanisms

Quantitative predictions of firing variability and synchronization

Abstract

An analytical description of the response properties of simple but realistic neuron models in the presence of noise is still lacking. We determine completely up to the second order the firing statistics of a single and a pair of leaky integrate-and-fire neurons (LIFs) receiving some common slowly filtered white noise. In particular, the auto- and cross-correlation functions of the output spike trains of pairs of cells are obtained from an improvement of the adiabatic approximation introduced in \cite{Mor+04}. These two functions define the firing variability and firing synchronization between neurons, and are of much importance for understanding neuron communication.