How Spike Generation Mechanisms Determine the Neuronal Response to Fluctuating Inputs

1. J Neurosci. 2003 Dec 17;23(37):11628-40. doi:
10.1523/JNEUROSCI.23-37-11628.2003.

How spike generation mechanisms determine the neuronal response to fluctuating
inputs.

Fourcaud-Trocmé N(1), Hansel D, van Vreeswijk C, Brunel N.

Author information:
(1)Centre National de la Recherche Scientifique Unité Mixte de Recherche 8119,
Neurophysique et Physiologie du Système Moteur, Unité de Formation et de
Recherche Biomédicale, Université Paris 5 René Descartes, 75270 Paris Cedex 06,
France.

This study examines the ability of neurons to track temporally varying inputs,
namely by investigating how the instantaneous firing rate of a neuron is
modulated by a noisy input with a small sinusoidal component with frequency (f).
Using numerical simulations of conductance-based neurons and analytical
calculations of one-variable nonlinear integrate-and-fire neurons, we
characterized the dependence of this modulation on f. For sufficiently high
noise, the neuron acts as a low-pass filter. The modulation amplitude is
approximately constant for frequencies up to a cutoff frequency, fc, after which
it decays. The cutoff frequency increases almost linearly with the firing rate.
For higher frequencies, the modulation amplitude decays as C/falpha, where the
power alpha depends on the spike initiation mechanism. For conductance-based
models, alpha = 1, and the prefactor C depends solely on the average firing rate
and a spike « slope factor, » which determines the sharpness of the spike
initiation. These results are attributable to the fact that near threshold, the
sodium activation variable can be approximated by an exponential function. Using
this feature, we propose a simplified one-variable model, the « exponential
integrate-and-fire neuron, » as an approximation of a conductance-based model. We
show that this model reproduces the dynamics of a simple conductance-based model
extremely well. Our study shows how an intrinsic neuronal property (the
characteristics of fast sodium channels) determines the speed with which neurons
can track changes in input.

DOI: 10.1523/JNEUROSCI.23-37-11628.2003
PMCID: PMC6740955
PMID: 14684865 [Indexed for MEDLINE]

Auteurs Bordeaux Neurocampus