Abstract

Over the past two decades, substantial amount of work has been conducted to characterize different odorant receptors, neuroanatomy and odorant response properties of the early olfactory system of Drosophila melanogaster. Yet many odorant receptors remain only partially characterized, and the odorant transduction process and the axon hillock spiking mechanism of the olfactory sensory neurons (OSNs) have yet to be fully determined. Identity and concentration, two key characteristics of the space of odorants, are encoded by the odorant transduction process. Detailed molecular models of the odorant transduction process are, however, scarce for fruit flies. To address these challenges we advance a comprehensive model of fruit fly OSNs as a cascade consisting of an odorant transduction process (OTP) and a biophysical spike generator (BSG). We model odorant identity and concentration using an odorant-receptor binding rate tensor, modulated by the odorant concentration profile, and an odorant-receptor dissociation rate tensor, and quantitatively describe the mechanics of the molecular ligand binding/dissociation of the OTP. We model the BSG as a Connor-Stevens point neuron. The resulting spatio-temporal encoding model of the Drosophila antenna provides a theoretical foundation for understanding the neural code of both odorant identity and odorant concentration and advances the state-of-the-art in a number of ways. First, it quantifies on the molecular level the spatio-temporal level of complexity of the transformation taking place in the antennae. The concentration-dependent spatio-temporal code at the output of the antenna circuits determines the level of complexity of olfactory processing in the downstream neuropils, such as odorant recognition and olfactory associative learning. Second, the model is biologically validated using multiple electrophysiological recordings. Third, the model demonstrates that the currently available data for odorant-receptor responses only enable the estimation of the affinity of the odorant-receptor pairs. The odorant-dissociation rate is only available for a few odorant-receptor pairs. Finally, our model calls for new experiments for massively identifying the odorant-receptor dissociation rates of relevance to flies.

Highlights

  • The odorant response of olfactory sensory neurons in the Drosophila antennae has been experimentally characterized by multiple research groups [1,2,3], and their results have been combined into a single consensus database, called the DoOR database [4, 5]

  • We evaluate our model with a multitude of odorant waveforms and demonstrate that the model output reproduces the temporal responses of olfactory sensory neurons (OSNs) obtained from in vivo electrophysiology recordings

  • We evaluate the model at the OSN population level and quantify on the molecular level the spatio-temporal level of complexity of the transformation taking place between the odorant space and the OSNs

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Summary

Introduction

The odorant response of olfactory sensory neurons in the Drosophila antennae has been experimentally characterized by multiple research groups [1,2,3], and their results have been combined into a single consensus database, called the DoOR database [4, 5]. A single odorant stimulus usually activates multiple OSN groups that express the same receptor type; likewise different odorants activate different OSN groups [11,12,13]. Such an OSN coding scheme is universal in insects and vertebrates, and has been called a “combinatorial odorant code” in [14]. The identity of an odorant, mono-molecular odorant or mixture alike, is encoded by the combination (i.e., vector) of responding OSN groups [1, 2], and each OSN group serves as one vector component of the code for a set of odorants. The size of the set of the actively spiking OSNs varies as the concentration amplitude changes [2]

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