Dataset Information

Dedicated olfactory neurons mediating attraction behavior to ammonia and amines in Drosophila.

ABSTRACT: Animals across various phyla exhibit odor-evoked innate attraction behavior that is developmentally programmed. The mechanism underlying such behavior remains unclear because the odorants that elicit robust attraction responses and the neuronal circuits that mediate this behavior have not been identified. Here, we describe a functionally segregated population of olfactory sensory neurons (OSNs) and projection neurons (PNs) in Drosophila melanogaster that are highly specific to ammonia and amines, which act as potent attractants. The OSNs express IR92a, a member of the chemosensory ionotropic receptor (IR) family and project to a pair of glomeruli in the antennal lobe, termed VM1. In vivo calcium-imaging experiments showed that the OSNs and PNs innervating VM1 were activated by ammonia and amines but not by nonamine odorants. Flies in which the IR92a(+) neurons or IR92a gene was inactivated had impaired amine-evoked physiological and behavioral responses. Tracing neuronal pathways to higher brain centers showed that VM1-PN axonal projections within the lateral horn are topographically segregated from those of V-PN and DC4-PN, which mediate innate avoidance behavior to carbon dioxide and acidity, respectively, suggesting that these sensory stimuli of opposing valence are represented in spatially distinct neuroanatomic loci within the lateral horn. These experiments identified the neurons and their cognate receptor for amine detection, and mapped amine attractive olfactory inputs to higher brain centers. This labeled-line mode of amine coding appears to be hardwired to attraction behavior.

SUBMITTER: Min S

PROVIDER: S-EPMC3619346 | biostudies-other | 2013 Apr

REPOSITORIES: biostudies-other

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Dedicated olfactory neurons mediating attraction behavior to ammonia and amines in Drosophila.

Min Soohong S Ai Minrong M Shin Seul A SA Suh Greg S B GS

Proceedings of the National Academy of Sciences of the United States of America 20130318 14

Animals across various phyla exhibit odor-evoked innate attraction behavior that is developmentally programmed. The mechanism underlying such behavior remains unclear because the odorants that elicit robust attraction responses and the neuronal circuits that mediate this behavior have not been identified. Here, we describe a functionally segregated population of olfactory sensory neurons (OSNs) and projection neurons (PNs) in Drosophila melanogaster that are highly specific to ammonia and amines ...[more]

PMID: 23509267

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Project description:The lack of a deeper understanding of how olfactory sensory neurons (OSNs) encode odors has hindered the progress in understanding the olfactory signal processing in higher brain centers. Here we employ methods of system identification to investigate the encoding of time-varying odor stimuli and their representation for further processing in the spike domain by Drosophila OSNs. In order to apply system identification techniques, we built a novel low-turbulence odor delivery system that allowed us to deliver airborne stimuli in a precise and reproducible fashion. The system provides a 1% tolerance in stimulus reproducibility and an exact control of odor concentration and concentration gradient on a millisecond time scale. Using this novel setup, we recorded and analyzed the in-vivo response of OSNs to a wide range of time-varying odor waveforms. We report for the first time that across trials the response of OR59b OSNs is very precise and reproducible. Further, we empirically show that the response of an OSN depends not only on the concentration, but also on the rate of change of the odor concentration. Moreover, we demonstrate that a two-dimensional (2D) Encoding Manifold in a concentration-concentration gradient space provides a quantitative description of the neuron's response. We then use the white noise system identification methodology to construct one-dimensional (1D) and two-dimensional (2D) Linear-Nonlinear-Poisson (LNP) cascade models of the sensory neuron for a fixed mean odor concentration and fixed contrast. We show that in terms of predicting the intensity rate of the spike train, the 2D LNP model performs on par with the 1D LNP model, with a root mean-square error (RMSE) increase of about 5 to 10%. Surprisingly, we find that for a fixed contrast of the white noise odor waveforms, the nonlinear block of each of the two models changes with the mean input concentration. The shape of the nonlinearities of both the 1D and the 2D LNP model appears to be, for a fixed mean of the odor waveform, independent of the stimulus contrast. This suggests that white noise system identification of Or59b OSNs only depends on the first moment of the odor concentration. Finally, by comparing the 2D Encoding Manifold and the 2D LNP model, we demonstrate that the OSN identification results depend on the particular type of the employed test odor waveforms. This suggests an adaptive neural encoding model for Or59b OSNs that changes its nonlinearity in response to the odor concentration waveforms.

Dataset Information

Dedicated olfactory neurons mediating attraction behavior to ammonia and amines in Drosophila.

Publications

Dedicated olfactory neurons mediating attraction behavior to ammonia and amines in Drosophila.

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