Odourant dominance in olfactory mixture processing: what makes a strong odourant?

Schubert, Marco; Sandoz, Jean‐Christophe; Galizia, Giovanni; Giurfa, Martín

doi:10.1098/rspb.2014.2562

Cited by 23 publications

(27 citation statements)

References 51 publications

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“…More general interactions between odorants and receptors can be easily added to our model, at the cost of additional parameters. For example, we showed that the nonlinearities implied by just competitive exclusion and facilitation are sufficient to produce diverse e ects that have been previously reported in the perception of odor mixtures including synergy (17), overshadowing (16), suppression (31) and inhibition (29). These e ects were thought to have a neural origin, but our results suggest that they may be driven partly by the biophysics of receptors.…”

Section: Discussionsupporting

confidence: 68%

“…Our approach is rooted in basic biophysics. For example, the extended models consider consequences of known phenomena like receptors with multiple binding sites, facilitation by already bound odorants, non-competitive inhibition, and heterodimerization of odorant molecules in mixture, and predict e ects such as synergy, antagonism (15) and overshadowing (16) in receptor responses. Such phenomena are reported in studies of human olfactory perception (17), but their origin is unknown.…”

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confidence: 99%

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A competitive binding model predicts nonlinear responses of olfactory receptors to complex mixtures

Singh

Murphy

Balasubramanian

et al. 2018

Preprint

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Summary:In color vision, the quantitative rules for mixing lights to make a target color are well understood. By contrast, the rules for mixing odorants to make a target odor remain elusive. A solution to this problem in vision relied on characterizing the receptor responses to different wavelengths of light and subsequently relating receptor responses to perception. In olfaction, experimentally measuring the receptor response to a representative set of complex mixtures is intractable due to the vast number of possibilities. To meet this challenge, we develop a biophysical model that predicts mammalian receptor responses to complex mixtures using responses to single odorants. The dominant nonlinearity in our model is competitive binding: only one odorant molecule can attach to a receptor binding site at a time. This simple framework predicts receptor responses to mixtures of up to twelve monomolecular odorants to within 10-30% of experimental observations and provides a powerful method for leveraging limited experimental data. Simple extensions of our model describe phenomena such as synergy, overshadowing, and inhibition, suggesting that these perceptual effects can arise partly from receptor binding properties, and may not require either complex neural interactions or feedback from higher brain areas.

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Section: Discussionsupporting

confidence: 68%

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confidence: 99%

A competitive binding model predicts nonlinear responses of olfactory receptors to complex mixtures

Singh

Murphy

Balasubramanian

et al. 2018

Preprint

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“…Third, food sources and the environment constantly undergo changes in odorant concentrations over the course of a day. Moreover, for honeybees, some odorants are more salient and distinct in a mixture than others (Reinhard et al, 2010;Schubert et al, 2015). Thus the question arises, how does a honeybee filter the relevant odor cues from an abundance of an ever-changing environmental odor background?…”

Section: Discussionmentioning

confidence: 99%

Environment‐specific modulation of odorant representations in the honeybee brain

Chakroborty

Menzel

Schubert

2016

Eur J of Neuroscience

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Ca imaging techniques were applied to investigate the neuronal behavior of projection neurons in the honeybee antennal lobe (AL) to examine the effects of long-lasting adaptation on odorant coding. Responses to eight test odorants were measured before, during, and after an odor adaptation phase. Bees were exposed to the adapting odor for 30 min. Test odorant responses were only recorded from a sub-population of accessible glomeruli on the AL surface. Projection neurons, the output neurons of the antennal lobes, are projecting through the lateral, mediolateral, and medial AL tract to higher centers of the olfactory pathway. Due to our staining techniques, we primarily focused our study on projection neurons going through the lateral and medial tract. Test odorants comprised compounds with different functional groups (alcohol, aldehyde, ketone, and ester) representing floral and/or pheromone odorants. Strength and discriminability between combinatorial activity patterns induced by the test odorants were quantified. In two independent experiments, we investigated one group of animals adapted to a colony odor and another adapted to a synthetic odor. Within the experimental groups, we found test odorant responses either decreased or increased in AL projection neurons. Additionally, the discriminability between test odorant patterns became less distinct in the colony odor experiment and more distinct during adaptation in the synthetic mixture experiment. These results are interpreted as odor dependent adaptation effects, increasing or decreasing response strength and discriminability by altered neural coding mechanisms in the AL neuropile.

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“…When two odours are presented simultaneously to honeybees, one of these odours can potentially overshadow or block the other so that the bees only respond to the more salient odour (Smith 1998;Guerrieri et al 2005;Reinhard et al 2010;Schubert et al 2015). This effect could explain the decrease in aggression induced by floral compounds such as PhE or Lol when presented with IAA.…”

Section: Iaa Is Not Masked By Floral Compounds Blocking Aggressionmentioning

confidence: 98%

“…Indeed, IAA seems to mask the plant odour, which is not surprising considering that IAA is present at much higher concentrations in the mixture than the plant odour (10% vs 0.075%, Table 1). Bees conditioned to odour mixtures respond more to a dominant component in the mixture (Reinhard et al 2010;Schubert et al 2015). Based on this finding, bees trained to IAA+PhE or IAA+Pr should respond more to IAA and less to the plant odour given the concentration differences of these odorants.…”

Section: Iaa Is Not Masked By Floral Compounds Blocking Aggressionmentioning

confidence: 99%

Neural and molecular mechanisms underlying the olfactory modulation of aggression in honeybees

Nouvian¹

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Although honeybees were domesticated over 7000 years ago, finding ways to manage their defensive responses against intruders, including humans, is still a current challenge. This is in part due to the complexity of this behaviour, which starts with the detection of the threat by a few specialized individuals and culminates into a generalized, collective attack triggered by the release of an alarm pheromone.Numerous studies have investigated honeybee aggression and stinging behaviour both in the laboratory and field, including the sensory triggers and the potential regulatory mechanisms. However the specific neural and molecular mechanisms regulating this behaviour are still unknown. In my PhD thesis, I investigated the role of olfactory signals and brain biogenic amines in modulating aggression in honeybees, integrating behavioural, physiological, and pharmacological experiments.Using a novel assay to measure the stinging behaviour of individual bees under controlled conditions, I first explored whether a range of plant odours could modulate aggression, in particular by interacting with the alarm pheromone released by aroused bees. I identified two floral compounds, linalool and 2-phenylethanol, that block the recruitment elicited by the alarm pheromone. These odours do not prevent the bees from perceiving the alarm pheromone. Instead, this blocking effect appears to correlate with the appetitive value of these odours. This suggests that a complex sensory integration takes place when honeybees are faced with the decision of engaging or not into defensive tasks. Furthermore, a field test demonstrated that linalool could also be used to manage aggressive colonies, highlighting the practical application of these findings.To gain a better understanding of the neuronal mechanism underlying this effect of floral odours on honeybee aggression, I next investigated how these floral compounds affect the representation of the alarm pheromone in the primary olfactory center of the honeybee brain, the antennal lobe, using in vivo calcium-imaging to monitor the activity of neurons in this area. The antennal lobes are structured into functional units called glomeruli, and an odour identity and concentration is encoded within the pattern and intensity of activated glomeruli. We expected that the representation of the mixture of an appetitive floral odour with the alarm pheromone may not be linearly obtained from the representation of each compound, thus iii revealing the neuronal mechanisms at play during our previous aggression assays.However, analysis of the data suggests no such mechanism, which could be a clue that this processing is happening in higher brain centers.Finally, I investigated the role of brain biogenic amines in honeybee aggression. Biogenic amines are important neuromodulators and have been implicated in the regulation of the aggressive behavior of a number of species.However, their potential role in regulating the honeybee's stinging behavior had not been investigated so far. My experiments showed t...

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Odourant dominance in olfactory mixture processing: what makes a strong odourant?

Cited by 23 publications

References 51 publications

A competitive binding model predicts nonlinear responses of olfactory receptors to complex mixtures

A competitive binding model predicts nonlinear responses of olfactory receptors to complex mixtures

Environment‐specific modulation of odorant representations in the honeybee brain

Neural and molecular mechanisms underlying the olfactory modulation of aggression in honeybees

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