Channel noise from both slow adaptation currents and fast currents is required to explain spike-response variability in a sensory neuron

Fisch, Karin; Schwalger, Tilo; Lindner, Benjamin; Herz, Andreas V. M. und Benda, Jan (28. November 2012): Channel noise from both slow adaptation currents and fast currents is required to explain spike-response variability in a sensory neuron. In: Journal of Neuroscience, Bd. 32, Nr. 48: S. 17332-17344

Abstract

Spike-timing variability has a large effect on neural information processing. However, for many systems little is known about the noise sources causing the spike-response variability. Here we investigate potential sources of spike-response variability in auditory receptor neurons of locusts, a classic insect model system. At low-spike frequencies, our data show negative interspike-interval (ISI) correlations and ISI distributions that match the inverse Gaussian distribution. These findings can be explained by a white-noise source that interacts with an adaptation current. At higher spike frequencies, more strongly peaked distributions and positive ISI correlations appear, as expected from a canonical model of suprathreshold firing driven by temporally correlated (i.e., colored) noise. Simulations of a minimal conductance-based model of the auditory receptor neuron with stochastic ion channels exclude the delayed rectifier as a possible noise source. Our analysis suggests channel noise from an adaptation current and the receptor or sodium current as main sources for the colored and white noise, respectively. By comparing the ISI statistics with generic models, we find strong evidence for two distinct noise sources. Our approach does not involve any dendritic or somatic recordings that may harm the delicate workings of many sensory systems. It could be applied to various other types of neurons, in which channel noise dominates the fluctuations that shape the neuron's spike statistics.

• Dokumententyp: Zeitschriftenartikel
• Publikationsform: Publisher's Version
• Fakultät: Biologie > Department Biologie II > Neurobiologie
• Themengebiete: 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften; Biologie
• ISSN: 0270-6474
• Sprache: Englisch