Antagonism in olfactory receptor neurons and its implications for the perception of odor mixtures

Abstract

Natural environments feature mixtures of odorants of diverse quantities, qualities and complexities. Olfactory receptor neurons (ORNs) are the first layer in the sensory pathway and transmit the olfactory signal to higher regions of the brain. Yet, the response of ORNs to mixtures is strongly non-additive, and exhibits antagonistic interactions among odorants. Here, we model the processing of mixtures by mammalian ORNs, focusing on the role of inhibitory mechanisms. Theoretically predicted response curves capture experimentally determined glomerular responses imaged by a calcium indicator expressed in ORNs of live, breathing mice. Antagonism leads to an effective "normalization" of the ensemble glomerular response, which arises from a novel mechanism involving the distinct statistical properties of receptor binding and activation, without any recurrent neuronal circuitry. Normalization allows our encoding model to outperform noninteracting models in odor discrimination tasks, and to explain several psychophysical experiments in humans.

Antagonistic odor interactions in olfactory sensory neurons are widespread in freely breathing mice

“…This allowed us to ask how OSNs respond to more complex mixtures. We found that the degree of mixture suppression was greater with increasing number of components, which is expected from statistical consideration of antagonistic interactions (Reddy et al, 2018). This feature can be rationalized as increasing normalization of population responses, which we have shown previously to allow greater information transfer about odor identity, when saturation threatens degradation of information (Reddy et al, 2018).…”

“…Some of it could arise at the periphery, including at the receptors themselves. We recently proposed a simple model based on the two-step activation of odorant receptors, and noted that even a modest decorrelation of binding affinity and activation efficacy across odors could lead to antagonistic interactions, which will lead to mixture suppression (Reddy et al, 2018).…”

“…Insect olfactory receptors also exhibit such nonlinear interactions (Silbering and Galizia, 2007;Su et al, 2011). Recently, we offered a principled explanation for all these different effects using a model that decouples the binding affinity of odorants to receptors and their activation efficiency (Reddy et al, 2018). Then, depending on the statistics of these properties in the repertoire of odorants encountered by an animal, the population of odorant receptors could exhibit varying degrees of antagonism or synergy.…”

“…Having normalization occur early in the sensory hierarchy helps avoid saturation early on and preserve more information about the stimulus to be conveyed downstream. Indeed, in our previous work, we demonstrated using information theoretic calculations that a target odorant embedded in a complex mixture can be more easily detected with antagonistic interactions that lead to sparser representation (Reddy et al, 2018). The improved performance with antagonism exists for a wide range of receptor "tuning widths" (i.e., the average number of activated glomeruli per single odorant).…”

“…Recent theoretical work has shown that a variety of non-linear interactions among multiple ligands at the same receptor can readily arise with a simple two-step model of receptor activation (Reddy et al, 2018). Experimental work in vitro in OSNs has suggested the existence of non-linear interactions, especially antagonism (Firestein and Shepherd, 1992;Kurahashi et al, 1994;Mathis et al, 2016;Rospars et al, 2008Rospars et al, , 2000Singh et al, 2019) (also bioRxiv preprints; Inagaki et al, 2019;Pfister et al, 2019;Xu et al, 2019).…”