Spike-train variability of auditory neurons in vivo: dynamic responses follow predictions from constant stimuli
Roland Schaette, Tim Gollisch & Andreas V. M. Herz
Journal of Neurophysiology 93: 3270-3281 (2005)
Abstract
Reliable accounts of the variability observed in neural spike
trains are a prerequisite for the proper interpretation of neural
dynamics and coding principles. Models that accurately describe
neural variability over a wide range of stimulation and response
patterns are therefore highly desirable, especially if they can
explain this variability in terms of basic neural observables and
parameters such as firing rate and refractory period. In this
work, we analyze the response variability recorded in vivo from
locust auditory receptor neurons under acoustic stimulation. In
agreement with results from other systems, our data suggest that
neural refractoriness has a strong influence on spike-train
variability. We therefore explore a stochastic model of spike
generation that includes refractoriness through a recovery
function. Because our experimental data are consistent with a
renewal process, the recovery function can be derived from a
single interspike-interval histogram obtained under constant
stimulation. The resulting description yields quantitatively
accurate predictions of the response variability over the whole
range of firing rates for constant-intensity as well as
amplitude-modulated sound stimuli. Model parameters obtained from
constant stimulation can be used to predict the variability in
response to dynamic stimuli. These results demonstrate that key
ingredients of the stochastic response dynamics of a sensory
neuron are faithfully captured by a simple stochastic model
framework.
Last modified: Fri Nov 28 11:24:16 CET 2008