Relation between stimulus and response in frog olfactory receptor neurons in vivo

Abstract

The spiking activity of receptor neurons was recorded extracellularly in the frog olfactory epithelium in response to four odourants applied at precisely controlled concentrations. A set of criteria was formulated to define the spikes in the response. Four variables - latency, duration, number of interspike intervals and frequency - were determined to quantify the responses. They were studied at the single neuron, neuron population and ciliary membrane levels. The dose-response curves were determined using specific functions and their characteristics were evaluated. The characteristic molar concentrations at threshold or at maximum duration and the characteristics of variables, e.g. minimum latency or maximum frequency, have asymmetric histograms with peaks close to the origin and long tails. Dynamic ranges have even more asymmetric histograms, so that a significant fraction of neurons presents a much wider range than their one-decade peak. From these histograms, response properties of the whole neuron population can be inferred. In general, location along the concentration axis (thresholds), width (dynamic ranges) and heights of dose-response curves are independent, which explains the diversity of curves, prevents their global categorization and supports the qualitative coding of odourants. No evidence for odourant-independent types of neurons was found. Finally, receptor activation and ciliary membrane conductance were reconstructed in the framework of a model based on firing data, known mucus biochemical and neuron morpho-electrical characteristics. It is in agreement with independent determinations of Kd of odourant-receptor interaction and of conductance characteristics, and describes their statistical distributions in the neuron population.

Modelling the signal delivered by a population of first-order neurons in a moth olfactory system

“…Second, the phenomenological nature of the model does not explain the variations observed across ORNs in the population. As noted above, several factors can explain this variability (Rospars et al, 2003;Sandström, 2009) including molecular (receptors, enzymes, ionic channels, pumps), geometrical (areas of various membrane parts) and electrical (membrane resistance etc.) factors that depend on one another (Gu and Rospars, 2011).…”

“…This consistency indicates that the available biophysical models are detailed enough to relate the low-level neuron (and sensillum) characteristics to their high-level (spike train) properties. This opens the way to an interpretation of the observed response variability of ORNs expressing the same olfactory receptor (Grosmaître et al, 2006;Jarriault et al, 2010) or different olfactory receptors (Rospars et al, 2003; that is essential for a proper understanding of cerebral olfactory processes.…”

“…1), especially variables F and L defined above. The dose-response functions F(C) and L(C) of each ORN were characterized by a set of 6 response parameters: F M , C 1/2 , n, L a , L m and as done previously for frog recordings (Rospars et al, 2003).…”

“…This other model was also about an ORN population in which all neurons express the same olfactory receptor but it was built differently and its numerical values come from another system. Each ORN was described by a biophysical model taking into account its biochemical, electrical and geometrical characteristics (Rospars et al, 1996(Rospars et al, , 2003(Rospars et al, , 2008. The series of conversions taking place during transduction (activated receptors, ionic conductances, receptor potential and firing frequency) were summarized as four main equations with 13 parameters.…”

“…The series of conversions taking place during transduction (activated receptors, ionic conductances, receptor potential and firing frequency) were summarized as four main equations with 13 parameters. The values of these parameters and their variability (normal or lognormal) were determined from experimental measurements of frog ORNs (Rospars et al, 2003). A population of ORNs was simulated with 9 of these parameters varying according to the normal (or lognormal) distributions found.…”