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

The primacy model and the structure of olfactory space

Understanding sensory processing relies on the establishment of a consistent relationship between the stimulus space, its neural representation, and perceptual quality. In olfaction, the difficulty in establishing these links lies partly in the complexity of the underlying odor input space and perceptual responses. Based on the recently proposed primacy model for concentration invariant odor identity representation and a few assumptions, we have developed a theoretical framework for mapping the odor input space to the response properties of olfactory receptors. We analyze a geometrical structure containing odor representations in a multidimensional space of receptor affinities and describe its low-dimensional implementation, the primacy hull. We propose the implications of the primacy hull for the structure of feedforward connectivity in early olfactory networks. We test the predictions of our theory by comparing the existing receptor-ligand affinity and connectivity data obtained in the fruit fly olfactory system. We find that the Kenyon cells of the insect mushroom body integrate inputs from the high-affinity (primacy) sets of olfactory receptors in agreement with the primacy theory.

Object-oriented olfaction: challenges for chemosensation and for chemosensory research

Many animal species use olfaction to extract information about objects in their environment. Yet, the specific molecular signature that any given object emits varies due to various factors. Here, we detail why such variability makes chemosensory-mediated object recognition such a hard problem, and we propose that a major function of the elaborate chemosensory network is to overcome it. We describe previous work addressing different elements of the problem and outline future research directions that we consider essential for a full understanding of object-oriented olfaction. In particular, we call for extensive representation of olfactory object variability in chemical, behavioral, and electrophysiological analyses. While written with an emphasis on macrosmatic mammalian species, our arguments apply to all organisms that employ chemosensation to navigate complex environments.

Distinct information conveyed to the olfactory bulb by feedforward input from the nose and feedback from the cortex

Sensory systems are organized hierarchically, but feedback projections frequently disrupt this order. In the olfactory bulb (OB), cortical feedback projections numerically match sensory inputs. To unravel information carried by these two streams, we imaged the activity of olfactory sensory neurons (OSNs) and cortical axons in the mouse OB using calcium indicators, multiphoton microscopy, and diverse olfactory stimuli. Here, we show that odorant mixtures of increasing complexity evoke progressively denser OSN activity, yet cortical feedback activity is of similar sparsity for all stimuli. Also, representations of complex mixtures are similar in OSNs but are decorrelated in cortical axons. While OSN responses to increasing odorant concentrations exhibit a sigmoidal relationship, cortical axonal responses are complex and nonmonotonic, which can be explained by a model with activity-dependent feedback inhibition in the cortex. Our study indicates that early-stage olfactory circuits have access to local feedforward signals and global, efficiently formatted information about odor scenes through cortical feedback.

Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb

Within a single sniff, the mammalian olfactory system can decode the identity and concentration of odorants wafted on turbulent plumes of air. Yet, it must do so given access only to the noisy, dimensionally-reduced representation of the odor world provided by olfactory receptor neurons. As a result, the olfactory system must solve a compressed sensing problem, relying on the fact that only a handful of the millions of possible odorants are present in a given scene. Inspired by this principle, past works have proposed normative compressed sensing models for olfactory decoding. However, these models have not captured the unique anatomy and physiology of the olfactory bulb, nor have they shown that sensing can be achieved within the 100-millisecond timescale of a single sniff. Here, we propose a rate-based Poisson compressed sensing circuit model for the olfactory bulb. This model maps onto the neuron classes of the olfactory bulb, and recapitulates salient features of their connectivity and physiology. For circuit sizes comparable to the human olfactory bulb, we show that this model can accurately detect tens of odors within the timescale of a single sniff. We also show that this model can perform Bayesian posterior sampling for accurate uncertainty estimation. Fast inference is possible only if the geometry of the neural code is chosen to match receptor properties, yielding a distributed neural code that is not axis-aligned to individual odor identities. Our results illustrate how normative modeling can help us map function onto specific neural circuits to generate new hypotheses.

General Chemical Reaction Network Theory for Olfactory Sensing Based on G-Protein-Coupled Receptors: Elucidation of Odorant Mixture Effects and Agonist-Synergist Threshold

This work presents a general chemical reaction network theory for olfactory sensing processes that employ G-protein-coupled receptors as olfactory receptors (ORs). The theory can be applied to general mixtures of odorants and an arbitrary number of ORs. Reactions of ORs with G-proteins, in both the presence and absence of odorants, are explicitly considered. A unique feature of the theory is the definition of an odor activity vector consisting of strengths of odorant-induced signals from ORs relative to those due to background G-protein activity in the absence of odorants. It is demonstrated that each component of the odor activity defined this way reduces to a Michaelis-Menten form capable of accounting for cooperation or competition effects between different odorants. The main features of the theory are illustrated for a two-odorant mixture. Known and potential mixture effects, such as suppression, shadowing, inhibition, and synergy, are quantitatively described. Effects of relative values of rate constants, basal activity, and G-protein concentration are also demonstrated.

Human Olfactory Receptor Sensor for Odor Reconstitution

Among the five human senses, light, sound, and force perceived by the eye, ear, and skin, respectively are physical phenomena, and therefore can be easily measured and expressed as objective, univocal, and simple digital data with physical quantity. However, as taste and odor molecules perceived by the tongue and nose are chemical phenomena, it has been difficult to express them as objective and univocal digital data, since no reference chemicals can be defined. Therefore, while the recording, saving, transmitting to remote locations, and replaying of human visual, auditory, and tactile information as digital data in digital devices have been realized (this series of data flow is defined as DX (digital transformation) in this review), the DX of human taste and odor information is not yet in the realization stage. Particularly, since there are at least 400,000 types of odor molecules and an infinite number of complex odors that are mixtures of these molecules, it has been considered extremely difficult to realize "human olfactory DX" by converting all odors perceived by human olfaction into digital data. In this review, we discuss the current status and future prospects of the development of "human olfactory DX", which we believe can be realized by utilizing odor sensors that employ the olfactory receptors (ORs) that support human olfaction as sensing molecules (i.e., human OR sensor).

Antagonistic interactions between odorants alter human odor perception

The olfactory system uses hundreds of odorant receptors (ORs), the largest group of the G-protein-coupled receptor (GPCR) superfamily, to detect a vast array of odorants. Each OR is activated by specific odorous ligands, and like other GPCRs, antagonism can block activation of ORs. Recent studies suggest that odorant antagonisms in mixtures influence olfactory neuron activities, but it is unclear how this affects perception of odor mixtures. In this study, we identified a set of human ORs activated by methanethiol and hydrogen sulfide, two potent volatile sulfur malodors, through large-scale heterologous expression. Screening odorants that block OR activation in heterologous cells identified a set of antagonists, including β-ionone. Sensory evaluation in humans revealed that β-ionone reduced the odor intensity and unpleasantness of methanethiol. Additionally, suppression was not observed when methanethiol and β-ionone were introduced simultaneously to different nostrils. Our study supports the hypothesis that odor sensation is altered through antagonistic interactions at the OR level.

Metabolomic NMR analysis and organoleptic perceptions of pomegranate wines: Influence of cultivar and yeast on the product characteristics

Pomegranate (Punica granatum L.) fruits are a historical agricultural product of the Mediterranean basin that became increasingly popular in the latest years for being rich in antioxidants and other micronutrients, and are extensively commercialized as fruits, juice, jams and, in some Eastern countries, as a fermented alcoholic beverage. In this work, four different pomegranate wines specifically designed using combinations of two cultivars (Jolly Red and Smith) and two yeast starters with markedly different characteristics (Saccharomyces cerevisiae Clos and Saccharomyces cerevisiae ex-bayanus EC1118) were analyzed. The chemical characterization of the wines together with the originating unfermented juices was performed by ¹H NMR spectroscopy metabolomic analysis. The full spectra were used for unsupervised and supervised statistical multivariate analysis (MVA), namely Principal Component Analysis (PCA), Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), and sparse PCA (SPCA). The MVA of the wines showed a clear discrimination between the cultivars, and a smaller, yet significant, discrimination between the yeasts used. In particular, a higher content of citrate and gallate was observed for the Smith cv. and, on the contrary, a statistically significant higher content of fructose, malate, glycerol, 2,3 butanediol, trigonelline, aromatic amino acids and 4-hydrophenylacetate was observed in Jolly Red pomegranate wines samples. Significant interaction among the pomegranate cultivar and the fermenting yeast was also observed. Sensorial analysis was performed by a panel of testing experts. MVA of tasting data showed that the cultivar significantly affected the organoleptic parameters considered, while the yeast had a minor impact. Correlation analysis between NMR-detected metabolites and organoleptic descriptors identified several potential sensorially-active molecules as those significantly impacting the characteristics of the pomegranate wines.

Odor deprivation influences human olfactory function

Odor deprivation leads to anatomical and neurochemical changes in the olfactory system, but its effect on human olfaction has not been systematically explored. The present randomized, controlled study aimed to investigate whether odor deprivation by different methods can affect olfactory function in humans. In the present study, sixty-one healthy participants were randomly assigned into three groups: a nasal device group (wearing an intranasal silicone air diversion system for 6-8 h daily), a mask group (wearing a filtering face piece for 6-8 h daily) and a control group (no special instructions in terms of wearing masks). Before and immediately after a 14-day study phase, all participants underwent assessments of olfactory function, nasal patency and well-being. Following the 2-week observation period, the nasal device group exhibited significantly reduced TDI scores (with especially pronounced reductions for odor threshold scores), and the mask group exhibited a minor increase in odor identification scores compared with the control group. The change in well-being scores was positively associated with changes in odor identification and TDI scores. Olfactory deprivation using an intranasal silicone air diversion device is associated with olfactory impairment (especially for odor thresholds). Highlighting the exposure-driven plasticity of the olfactory system, it may serve as a possible model of hyposmia in future studies. In addition, it may also prove useful in patients with parosmia, possibly reducing the burden of unpleasant odorous sensations.

Allosteric modulation of a human odorant receptor

Odor perception is first determined by how the myriad of environmental volatiles are detected at the periphery of the olfactory system. The combinatorial activation of dedicated odorant receptors generates enough encoding power for the discrimination of tens of thousands of odorants. Recent studies have revealed that odorant receptors undergo widespread inhibitory modulation of their activity when presented with mixtures of odorants, a property likely required to maintain discrimination and ensure sparsity of the code for complex mixtures. Here, we establish the role of human OR5AN1 in the detection of musks and identify distinct odorants capable of enhancing its activity in binary mixtures. Chemical and pharmacological characterization indicate that specific α-β unsaturated aliphatic aldehydes act as positive allosteric modulators. Sensory experiments show decreased odor detection threshold in humans, suggesting that allosteric modulation of odorant receptors is perceptually relevant and likely adds another layer of complexity to how odors are encoded in the peripheral olfactory system.

Odor mixtures: A chord with silent notes

The olfactory world is one of complex mixtures and blends containing up to hundreds of molecules. Many of those molecules can act as agonists, antagonists or enhancers at different receptors. This complicates the mechanism by which higher centers construct perceptions of complex mixtures. We propose that along with structural chemistry, psychophysics, the techniques of medicinal chemistry and machine learning can begin to shed light on this difficult neural problem.

Masking effects on iso-valeric acid recognition by sub-threshold odor mixture

Masking unpleasant odors with pleasant-smelling odorants has a long history and is utilized in various industries, including perfumery and consumer products. However, the effectiveness of odor masking is idiosyncratic and temporary. In this study, we employed Sniff olfactometry (SO) to investigate the psychophysics of masking using brief 70 ms stimulations with mixtures of the mal-odorant iso-valeric acid (IVA) and different masking agents. IVA is a component of human sweat that can overpower its smell and is often associated with unpleasant descriptors such as "gym locker," "smelly feet," "dirty clothes," and so on. Traditionally, high concentrations of pleasant-smelling odorants are used to mitigate the unpleasantness of IVA in situations involving clothing or environments contaminated with IVA. To examine the masking effects of sub-threshold levels of various masking agents (neohivernal, geraniol, florhydral, decanal, iso-longifolanone, methyl iso-eugenol, and s-limonene) on IVA, we conducted experiments using SO to measure the probability of recognizing IVA after 70 ms stimulations with headspaces containing mixtures of super-threshold concentrations of IVA and sub-threshold concentrations of IVA suppressors. The study involved nine subjects, and on average, a single masking agent was found to decrease IVA recognition probability by 14-72%. Moreover, a sub-threshold odor mixture consisting of 6 masking agents demonstrated a substantial decrease in IVA recognition, with a reduction of 96%.

Effects of 3-octen-2-one on human olfactory receptor responses to vanilla flavor

Most of the odors that humans perceive daily are complex odors. It is believed that the modulation, enhancement, and suppression of overall complex odors are caused by interactions between odor molecules. In this study, to understand the interaction between odor molecules at the level of human olfactory receptor responses, the effects of 3-octen-2-one, which has been shown to modulate vanilla flavors, were analyzed using a human olfactory receptor sensor that uses all human olfactory receptors (388 types) as sensing molecules. As a result, the response intensity of 1 common receptor (OR1D2) was synergistically enhanced in vanilla flavor with 3-octen-2-one compared with vanilla flavor, and the response of 1 receptor (OR5K1) to vanilla flavor was completely suppressed. These results strongly suggested that the response of human olfactory receptors to complex odors is enhanced or suppressed by relatively few other odor molecules.

Disorder and the Neural Representation of Complex Odors

Animals smelling in the real world use a small number of receptors to sense a vast number of natural molecular mixtures, and proceed to learn arbitrary associations between odors and valences. Here, we propose how the architecture of olfactory circuits leverages disorder, diffuse sensing and redundancy in representation to meet these immense complementary challenges. First, the diffuse and disordered binding of receptors to many molecules compresses a vast but sparsely-structured odor space into a small receptor space, yielding an odor code that preserves similarity in a precise sense. Introducing any order/structure in the sensing degrades similarity preservation. Next, lateral interactions further reduce the correlation present in the low-dimensional receptor code. Finally, expansive disordered projections from the periphery to the central brain reconfigure the densely packed information into a high-dimensional representation, which contains multiple redundant subsets from which downstream neurons can learn flexible associations and valences. Moreover, introducing any order in the expansive projections degrades the ability to recall the learned associations in the presence of noise. We test our theory empirically using data from Drosophila. Our theory suggests that the neural processing of sparse but high-dimensional olfactory information differs from the other senses in its fundamental use of disorder.

Extracellular loop 2 of G protein-coupled olfactory receptors is critical for odorant recognition

G protein–coupled olfactory receptors (ORs) enable us to detect innumerous odorants. They are also ectopically expressed in nonolfactory tissues and emerging as attractive drug targets. ORs can be promiscuous or highly specific, which is part of a larger mechanism for odor discrimination. Here, we demonstrate that the OR extracellular loop 2 (ECL2) plays critical roles in OR promiscuity and specificity. Using site-directed mutagenesis and molecular modeling, we constructed 3D OR models in which ECL2 forms a lid over the orthosteric pocket. We demonstrate using molecular dynamics simulations that ECL2 controls the shape and volume of the odorant-binding pocket, maintains the pocket hydrophobicity, and acts as a gatekeeper of odorant binding. Therefore, we propose the interplay between the specific orthosteric pocket and the variable, less specific ECL2 controls OR specificity and promiscuity. Furthermore, the 3D models created here enabled virtual screening of new OR agonists and antagonists, which exhibited a 70% hit rate in cell assays. Our approach can potentially be generalized to structure-based ligand screening for other G protein–coupled receptors that lack high-resolution 3D structures.

Hyperbolic odorant mixtures as a basis for more efficient signaling between flowering plants and bees

Animals use odors in many natural contexts, for example, for finding mates or food, or signaling danger. Most analyses of natural odors search for either the most meaningful components of a natural odor mixture, or they use linear metrics to analyze the mixture compositions. However, we have recently shown that the physical space for complex mixtures is ‘hyperbolic’, meaning that there are certain combinations of variables that have a disproportionately large impact on perception and that these variables have specific interpretations in terms of metabolic processes taking place inside the flower and fruit that produce the odors. Here we show that the statistics of odorants and odorant mixtures produced by inflorescences (Brassica rapa) are also better described with a hyperbolic rather than a linear metric, and that combinations of odorants in the hyperbolic space are better predictors of the nectar and pollen resources sought by bee pollinators than the standard Euclidian combinations. We also show that honey bee and bumble bee antennae can detect most components of the B. rapa odor space that we tested, and the strength of responses correlates with positions of odorants in the hyperbolic space. In sum, a hyperbolic representation can be used to guide investigation of how information is represented at different levels of processing in the CNS.

Context-dependent reversal of odorant preference is driven by inversion of the response in a single sensory neuron type

The valence and salience of individual odorants are modulated by an animal’s innate preferences, learned associations, and internal state, as well as by the context of odorant presentation. The mechanisms underlying context-dependent flexibility in odor valence are not fully understood. Here, we show that the behavioral response of Caenorhabditis elegans to bacterially produced medium-chain alcohols switches from attraction to avoidance when presented in the background of a subset of additional attractive chemicals. This context-dependent reversal of odorant preference is driven by cell-autonomous inversion of the response to these alcohols in the single AWC olfactory neuron pair. We find that while medium-chain alcohols inhibit the AWC olfactory neurons to drive attraction, these alcohols instead activate AWC to promote avoidance when presented in the background of a second AWC-sensed odorant. We show that these opposing responses are driven via engagement of distinct odorant-directed signal transduction pathways within AWC. Our results indicate that context-dependent recruitment of alternative intracellular signaling pathways within a single sensory neuron type conveys opposite hedonic valences, thereby providing a robust mechanism for odorant encoding and discrimination at the periphery.

State-dependent representations of mixtures by the olfactory bulb

Sensory systems are often tasked to analyse complex signals from the environment, separating relevant from irrelevant parts. This process of decomposing signals is challenging when a mixture of signals does not equal the sum of its parts, leading to an unpredictable corruption of signal patterns. In olfaction, nonlinear summation is prevalent at various stages of sensory processing. Here, we investigate how the olfactory system deals with binary mixtures of odours under different brain states by two-photon imaging of olfactory bulb (OB) output neurons. Unlike previous studies using anaesthetised animals, we found that mixture summation is more linear in the early phase of evoked responses in awake, head-fixed mice performing an odour detection task, due to dampened responses. Despite smaller and more variable responses, decoding analyses indicated that the data from behaving mice was well discriminable. Curiously, the time course of decoding accuracy did not correlate strictly with the linearity of summation. Further, a comparison with naïve mice indicated that learning to accurately perform the mixture detection task is not accompanied by more linear mixture summation. Finally, using a simulation, we demonstrate that, while saturating sublinearity tends to degrade the discriminability, the extent of the impairment may depend on other factors, including pattern decorrelation. Altogether, our results demonstrate that the mixture representation in the primary olfactory area is state-dependent, but the analytical perception may not strictly correlate with linearity in summation.

Understanding responses to chemical mixtures: looking forward from the past

Our goal in this article is to provide a perspective on how to understand the nature of responses to chemical mixtures. In studying responses to mixtures, researchers often identify "mixture interactions"-responses to mixtures that are not accurately predicted from the responses to the mixture's individual components. Critical in these studies is how to predict responses to mixtures and thus to identify a mixture interaction. We explore this issue with a focus on olfaction and on the first level of neural processing-olfactory sensory neurons-although we use examples from taste systems as well and we consider responses beyond sensory neurons, including behavior and psychophysics. We provide a broadly comparative perspective that includes examples from vertebrates and invertebrates, from genetic and nongenetic animal models, and from literature old and new. In the end, we attempt to recommend how to approach these problems, including possible future research directions.

Paradoxical relationship between speed and accuracy in olfactory figure-background segregation

In natural settings, many stimuli impinge on our sensory organs simultaneously. Parsing these sensory stimuli into perceptual objects is a fundamental task faced by all sensory systems. Similar to other sensory modalities, increased odor backgrounds decrease the detectability of target odors by the olfactory system. The mechanisms by which background odors interfere with the detection and identification of target odors are unknown. Here we utilized the framework of the Drift Diffusion Model (DDM) to consider possible interference mechanisms in an odor detection task. We first considered pure effects of background odors on either signal or noise in the decision-making dynamics and showed that these produce different predictions about decision accuracy and speed. To test these predictions, we trained mice to detect target odors that are embedded in random background mixtures in a two-alternative choice task. In this task, the inter-trial interval was independent of behavioral reaction times to avoid motivating rapid responses. We found that increased backgrounds reduce mouse performance but paradoxically also decrease reaction times, suggesting that noise in the decision making process is increased by backgrounds. We further assessed the contributions of background effects on both noise and signal by fitting the DDM to the behavioral data. The models showed that background odors affect both the signal and the noise, but that the paradoxical relationship between trial difficulty and reaction time is caused by the added noise.

Sensory systems are constantly stimulated by signals from many objects in the environment. Segmentation of important signals from the cluttered background is therefore a task that is faced by all sensory systems. For many mammalians, the sense of smell is the primary sense that guides many daily behaviors. As such, the olfactory system must be able to detect and identify odors of interest against varying and dynamic backgrounds. Here we studied how background odors interfere with the detection of target odors. We trained mice on a task in which they are presented with odor mixtures and are required to report whether they include either of two target odors. We analyze the behavioral data using a common model of sensory-guided decision-making—the drift-diffusion-model. In this model, decisions are influenced by two elements: a drift which is the signal produced by the stimulus, and noise. We show that the addition of background odors has a dual effect—a reduction in the drift, as well as an increase in the noise. The increased noise also causes more rapid decisions, thereby producing a paradoxical relationship between trial difficulty and decision speed; mice make faster decisions on more difficult trials.

Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies

When flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, they must solve several challenges, including reliably identifying mixtures of odorants and their intensities, and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and just mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these challenges. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic ("ephaptic") interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla. We find that NSIs improve mixture ratio detection and plume structure sensing and do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. The best performance is achieved when both mechanisms work in synergy. However, we also found that NSIs decrease the dynamic range of co-housed ORNs, especially when they have similar sensitivity to an odorant. These results shed light, from a functional perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Cortical feedback and gating in odor discrimination and generalization

A central question in neuroscience is how context changes perception. In the olfactory system, for example, experiments show that task demands can drive divergence and convergence of cortical odor responses, likely underpinning olfactory discrimination and generalization. Here, we propose a simple statistical mechanism for this effect based on unstructured feedback from the central brain to the olfactory bulb, which represents the context associated with an odor, and sufficiently selective cortical gating of sensory inputs. Strikingly, the model predicts that both convergence and divergence of cortical odor patterns should increase when odors are initially more similar, an effect reported in recent experiments. The theory in turn predicts reversals of these trends following experimental manipulations and in neurological conditions that increase cortical excitability.

Finding the Brain in the Nose

Olfaction is fundamentally distinct from other sensory modalities. Natural odor stimuli are complex mixtures of volatile chemicals that interact in the nose with a receptor array that, in rodents, is built from more than 1,000 unique receptors. These interactions dictate a peripheral olfactory code, which in the brain is transformed and reformatted as it is broadcast across a set of highly interconnected olfactory regions. Here we discuss the problems of characterizing peripheral population codes for olfactory stimuli, of inferring the specific functions of different higher olfactory areas given their extensive recurrence, and of ultimately understanding how odor representations are linked to perception and action. We argue that, despite the differences between olfaction and other sensory modalities, addressing these specific questions will reveal general principles underlying brain function.

What the odor is not: Estimation by elimination

Olfactory systems use a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. We propose a method of decoding such distributed representations by exploiting a statistical fact: Receptors that do not respond to an odor carry more information than receptors that do because they signal the absence of all odorants that bind to them. Thus, it is easier to identify what the odor is not rather than what the odor is. For realistic numbers of receptors, response functions, and odor complexity, this method of elimination turns an underconstrained decoding problem into a solvable one, allowing accurate determination of odorants in a mixture and their concentrations. We construct a neural network realization of our algorithm based on the structure of the olfactory pathway.

Principles of odor coding in vertebrates and artificial chemosensory systems

The biological olfactory system is the sensory system responsible for the detection of the chemical composition of the environment. Several attempts to mimic biological olfactory systems have led to various artificial olfactory systems using different technical approaches. Here we provide a parallel description of biological olfactory systems and their technical counterparts. We start with a presentation of the input to the systems, the stimuli, and treat the interface between the external world and the environment where receptor neurons or artificial chemosensors reside. We then delineate the functions of receptor neurons and chemosensors as well as their overall I-O relationships. Up to this point, our account of the systems goes along similar lines. The next processing steps differ considerably: while in biology the processing step following the receptor neurons is the "integration" and "processing" of receptor neuron outputs in the olfactory bulb, this step has various realizations in electronic noses. For a long period of time, the signal processing stages beyond the olfactory bulb, i.e., the higher olfactory centers were little studied. Only recently there has been a marked growth of studies tackling the information processing in these centers. In electronic noses, a third stage of processing has virtually never been considered. In this review, we provide an up-to-date overview of the current knowledge of both fields and, for the first time, attempt to tie them together. We hope it will be a breeding ground for better information, communication, and data exchange between very related but so far little connected fields.

The influence of stimulus duration on olfactory perception

The duration of a stimulus plays an important role in the coding of sensory information. The role of stimulus duration is extensively studied in the tactile, visual, and auditory system. In the olfactory system, temporal properties of the stimulus are key for obtaining information when an odor is released in the environment. However, how the stimulus duration influences the odor perception is not well understood. To test this, we activated the olfactory bulbs with blue light in mice expressing channelrhodopsin in the olfactory sensory neurons (OSNs) and assessed the relevance of stimulus duration on olfactory perception using foot shock associated active avoidance behavioral task on a "two-arms maze". Our behavior data demonstrate that the stimulus duration plays an important role in olfactory perception and the associated behavioral responses.

A physicochemical model of odor sampling

We present a general physicochemical sampling model for olfaction, based on established pharmacological laws, in which arbitrary combinations of odorant ligands and receptors can be generated and their individual and collective effects on odor representations and olfactory performance measured. Individual odor ligands exhibit receptor-specific affinities and efficacies; that is, they may bind strongly or weakly to a given receptor, and can act as strong agonists, weak agonists, partial agonists, or antagonists. Ligands interacting with common receptors compete with one another for dwell time; these competitive interactions appropriately simulate the degeneracy that fundamentally defines the capacities and limitations of odorant sampling. The outcome of these competing ligand-receptor interactions yields a pattern of receptor activation levels, thereafter mapped to glomerular presynaptic activation levels based on the convergence of sensory neuron axons. The metric of greatest interest is the mean discrimination sensitivity, a measure of how effectively the olfactory system at this level is able to recognize a small change in the physicochemical quality of a stimulus. This model presents several significant outcomes, both expected and surprising. First, adding additional receptors reliably improves the system's discrimination sensitivity. Second, in contrast, adding additional ligands to an odorscene initially can improve discrimination sensitivity, but eventually will reduce it as the number of ligands increases. Third, the presence of antagonistic ligand-receptor interactions produced clear benefits for sensory system performance, generating higher absolute discrimination sensitivities and increasing the numbers of competing ligands that could be present before discrimination sensitivity began to be impaired. Finally, the model correctly reflects and explains the modest reduction in odor discrimination sensitivity exhibited by transgenic mice in which the specificity of glomerular targeting by primary olfactory neurons is partially disrupted.

Position Review: Functional Selectivity in Mammalian Olfactory Receptors

There is increasing appreciation that G-protein-coupled receptors (GPCRs) can initiate diverse cellular responses by activating multiple G proteins, arrestins, and other biochemical effectors. Structurally different ligands targeting the same receptor are thought to stabilize the receptor in multiple distinct active conformations such that specific subsets of signaling effectors are engaged at the exclusion of others, creating a bias toward a particular outcome, which has been referred to as ligand-induced selective signaling, biased agonism, ligand-directed signaling, and functional selectivity, among others. The potential involvement of functional selectivity in mammalian olfactory signal transduction has received little attention, notwithstanding the fact that mammalian olfactory receptors comprise the largest family of mammalian GPCRs. This position review considers the possibility that, although such complexity in G-protein function may have been lost in the specialization of olfactory receptors to serve as sensory receptors, the ability of olfactory receptor neurons (ORNs) to function as signal integrators and growing appreciation that this functionality is widespread in the receptor population suggest otherwise. We pose that functional selectivity driving 2 opponent inputs have the potential to generate an output that reflects the balance of ligand-dependent signaling, the direction of which could be either suppressive or synergistic and, as such, needs to be considered as a mechanistic basis for signal integration in mammalian ORNs.

Widespread Inhibition, Antagonism, and Synergy in Mouse Olfactory Sensory Neurons In Vivo

Sensory information is selectively or non-selectively enhanced and inhibited in the brain, but it remains unclear whether and how this occurs at the most peripheral level. Using in vivo calcium imaging of mouse olfactory bulb and olfactory epithelium in wild-type and mutant animals, we show that odors produce not only excitatory but also inhibitory responses in olfactory sensory neurons (OSNs). Heterologous assays indicate that odorants can act as agonists to some but inverse agonists to other odorant receptors. We also demonstrate that responses to odor mixtures are extensively suppressed or enhanced in OSNs. When high concentrations of odors are mixed, widespread antagonism suppresses the overall response amplitudes and density. In contrast, a mixture of low concentrations of odors often produces synergistic effects and boosts the faint odor inputs. Thus, odor responses are extensively tuned by inhibition, antagonism, and synergy at the most peripheral level, contributing to robust sensory representations.

Individual and Combined Inhalational Sedative Effects in Mice of Low Molecular Weight Aromatic Compounds Found in Agarwood Aroma

Agarwood is known to have a sedative effect and the less studied volatile aromatic constituents it contains may have contribution to the activity. In this study, two Kyara grade (highest-grade agarwood in Japan) samples were extracted using headspace-solid phase microextraction (HS-SPME) and analyzed through gas chromatography-mass spectrometry (GC-MS). Six low molecular weight aromatic compounds (LACs) and one structurally simple compound (diethylene glycol monoethyl ether) present in the aromas were individually evaluated for inhalational sedative activity in mice through open field test. Doses of 0.0001 g/L to 1 g/L were prepared for each compound and administered to mice (n = 6/dose/compound). Results revealed all compounds decreased spontaneous motor activity at almost all doses. Strongest sedative activity of each compound reduced total spontaneous motor activity by more than half against control, demonstrating their contribution to agarwood aroma and potential as independent sedating agents. Mixtures of compounds using their most effective dose were made and evaluated again for inhalational sedative effect. Interestingly, the combination of all compounds showed no significant effect and even caused stimulation in mice movements. This result suggests antagonistic-like interaction between the compounds, which is probably due to structural similarities. Consequently, it implies the other constituents present in agarwood, along with LACs, are also important to the overall sedative activity.

Brief olfactory learning drives perceptive sensitivity in newborn rabbits: New insights in peripheral processing of odor mixtures and induction

Perception of the wide, complex and moving odor world requires that the olfactory system engages processing mechanisms ensuring detection, discrimination and environment adaptation, as early as the peripheral stages. Odor items are mainly elicited by odorant mixtures which give rise to either elemental or configural perceptions. Here, we first explored the contribution of the peripheral olfactory system to configural and elemental perception through odorant interactions at the olfactory receptor (OR) level. This was done in newborn rabbits, which offer the opportunity to pair peripheral electrophysiology and well characterized behavioral responses to two binary mixtures, AB and A'B', which differ in their component ratio (A: ethyl isobutyrate, B: ethyl maltol), and that rabbit pups respectively perceived configurally and elementally. Second, we studied the influence on peripheral reactivity of the brief but powerful learning of one mixture component (odorant B), conditioned by association with the mammary pheromone (MP), which allowed us to assess the possible implication of the phenomenon called induction in neonatal odor learning. Induction is a plasticity mechanism expected to alter both the peripheral electrophysiological responses to, and perceptual detection threshold of, the conditioned stimulus. The results reveal that perceptual modes are partly rooted in differential peripheral processes, the AB configurally perceived mixture mirroring odorant antagonist interactions at OR level to a lesser extent than the A'B' elementally perceived mixture. Further, the results highlight that a single and brief MP-induced odor learning episode is sufficient to alter peripheral responses to the conditioned stimulus and mixtures including it, and shifts the conditioned stimulus detection threshold towards lower concentrations. Thus, MP-induced odor learning relies on induction phenomenon in newborn rabbits.

Computational and Experimental Approaches to Decipher the Binding Mechanism of General Odorant-Binding Protein 2 from Athetis lepigone to Chlorpyrifos and Phoxim

Insect resistance to insecticides is an increasingly serious problem, and the resistant mechanisms are complicated. The resistance research based on the chemosensory pathway is one of the hot problems at present, but the specific binding mechanism of chemosensory genes and insecticides remains elusive. The binding mechanism of AlepGOBP2 (belong to insect chemosensory gene) with two insecticides was investigated by computational and experimental approaches. Our calculation results indicated that four key residues (Phe12, Ile52, Ile94, and Phe118) could steadily interact with these two insecticides and be assigned as hotspot sites responsible for their binding affinities. The significant alkyl-π and hydrophobic interactions involved by these four hotspot residues were found to be the driving forces for their binding affinities, especially for two residues (Phe12 and Ile94) that significantly contribute to the binding of chlorpyrifos, which were also validated by our binding assay results. Furthermore, we also found that the AlepGOBP2-chlorpyrifos/phoxim complexes can be more efficiently converged in the residue-specific force field-(RSFF2C) and its higher accuracy and repeatability in protein dynamics simulation, per-residue free energy decomposition, and computational alanine scanning calculations have also been achieved in this paper. These findings provided useful insights for efficient and reliable calculation of the binding mechanism of relevant AlepGOBPs with other insecticides, facilitating to develop new and efficient insecticides targeting the key sites of AlepGOBP2.

Odor coding in the mammalian olfactory epithelium

Noses are extremely sophisticated chemical detectors allowing animals to use scents to interpret and navigate their environments. Odor detection starts with the activation of odorant receptors (ORs), expressed in mature olfactory sensory neurons (OSNs) populating the olfactory mucosa. Different odorants, or different concentrations of the same odorant, activate unique ensembles of ORs. This mechanism of combinatorial receptor coding provided a possible explanation as to why different odorants are perceived as having distinct odors. Aided by new technologies, several recent studies have found that antagonist interactions also play an important role in the formation of the combinatorial receptor code. These findings mark the start of a new era in the study of odorant-receptor interactions and add a new level of complexity to odor coding in mammals.

Inhibitory signaling in mammalian olfactory transduction potentially mediated by Gαo

Olfactory GPCRs (ORs) in mammalian olfactory receptor neurons (ORNs) mediate excitation through the Gα_s family member Gα_olf. Here we tentatively associate a second G protein, Gα_o, with inhibitory signaling in mammalian olfactory transduction by first showing that odor evoked phosphoinositide 3-kinase (PI3K)-dependent inhibition of signal transduction is absent in the native ORNs of mice carrying a conditional OMP-Cre based knockout of Gα_o. We then identify an OR from native rat ORNs that are activated by octanol through cyclic nucleotide signaling and inhibited by citral in a PI3K-dependent manner. We show that the OR activates cyclic nucleotide signaling and PI3K signaling in a manner that reflects its functionality in native ORNs. Our findings lay the groundwork to explore the interesting possibility that ORs can interact with two different G proteins in a functionally identified, ligand-dependent manner to mediate opponent signaling in mature mammalian ORNs.

Discrimination of Complex Odor Mixtures: A Study Using Wine Aroma Models

There are key unanswered questions when it comes to multicomponent odor discrimination. This study was designed to assess discrimination of odorant mixtures that elicit a singular percept. We collected data to address the following two questions: (1) What odor features do humans notice when attempting to discriminate between subtly different odor mixtures? (2) Are odor mixtures easier to discriminate when an odorant is added, compared with when a component is removed? Using modern aroma chemistry techniques, an odor mixture resembling a generic white wine was constructed. This wine odor mixture was modified using a series of three esters which are commonly found in white wines that vary in chain length and branching. Participants performed a sequence of discrimination tasks for the addition/subtraction of modifiers to the base wine at different concentrations. Only one of the esters (ethyl propanoate) led to a discriminable odor mixture. As concentration of the modifying odorant was increased, discrimination of odor mixtures was first reported because of changes in odor mixture familiarity and then intensity. We found similar sensitivity to changes in odor mixtures regardless whether the modifying compound was added or subtracted, suggesting that perceptual stability of odor mixtures is equally dependent on both imputing missing information (pattern completion) and disregarding extraneous information.

Mixture Coding and Segmentation in the Anterior Piriform Cortex

Coding of odorous stimuli has been mostly studied using single isolated stimuli. However, a single sniff of air in a natural environment is likely to introduce airborne chemicals emitted by multiple objects into the nose. The olfactory system is therefore faced with the task of segmenting odor mixtures to identify objects in the presence of rich and often unpredictable backgrounds. The piriform cortex is thought to be the site of object recognition and scene segmentation, yet the nature of its responses to odorant mixtures is largely unknown. In this study, we asked two related questions. (1) How are mixtures represented in the piriform cortex? And (2) Can the identity of individual mixture components be read out from mixture representations in the piriform cortex? To answer these questions, we recorded single unit activity in the piriform cortex of naïve mice while sequentially presenting single odorants and their mixtures. We find that a normalization model explains mixture responses well, both at the single neuron, and at the population level. Additionally, we show that mixture components can be identified from piriform cortical activity by pooling responses of a small population of neurons-in many cases a single neuron is sufficient. These results indicate that piriform cortical representations are well suited to perform figure-background segmentation without the need for learning.

Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies.. [DOI: 10.1101/2020.07.23.217216]

When flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, they must solve several challenges, including reliably identifying mixtures of odorants and their intensities, and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and just mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these challenges. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic (“ephaptic”) interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla.

We found that NSIs improve mixture ratio detection and plume structure sensing and they do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. However, we also found that NSIs decrease the dynamic range of co-housed ORNs, especially when they have similar sensitivity to an odorant. These results shed light, from a functional perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Author summary

Myelin is important to isolate neurons and avoid disruptive electrical interference between them; it can be found in almost any neural assembly. However, there are a few exceptions to this rule and it remains unclear why. One particularly interesting case is the electrical interaction between olfactory sensory neurons co-housed in the sensilla of insects. Here, we created a computational model of the early stages of the Drosophila olfactory system and observed that the electrical interference between olfactory receptor neurons can be a useful trait that can help flies, and other insects, to navigate the complex plumes of odorants in their natural environment.

With the model we were able to shed new light on the trade-off of adopting this mechanism: We found that the non-synaptic interactions (NSIs) improve both the identification of the concentration ratio in mixtures of odorants and the discrimination of odorant mixtures emanating from a single source from odorants emitted from separate sources – both highly advantageous. However, they also decrease the dynamic range of the olfactory sensory neurons – a clear disadvantage.

Olfaction: Receptor Antagonistes

Odor receptors of the mammalian olfactory system have long been known to be activated in combinatorial fashion by odorants. A large-scale study now reveals that inhibition of receptors by odorants is comparably prevalent and combinatorial.

Odorant Receptor Inhibition Is Fundamental to Odor Encoding

Most natural odors are complex mixtures of volatile components, competing to bind odorant receptors (ORs) expressed in olfactory sensory neurons (OSNs) of the nose. To date, surprisingly little is known about how OR antagonism shapes neuronal representations in the detection layer of the olfactory system. Here, we investigated its prevalence, the degree to which it disrupts OR ensemble activity, and its conservation across phylogenetically related ORs. Calcium imaging microscopy of dissociated OSNs revealed significant inhibition, often complete attenuation, of responses to indole-a commonly occurring volatile associated with both floral and fecal odors-by a set of 36 tested odorants. To confirm an OR mechanism for the observed inhibition, we performed single-cell transcriptomics on OSNs exhibiting specific response profiles to a diagnostic panel of odorants and identified three paralogous receptors-Olfr740, Olfr741, and Olfr743-which, when tested in vitro, recapitulated OSN responses. We screened ten ORs from the Olfr740 gene family with ∼800 perfumery-related odorants spanning a range of chemical scaffolds and functional groups. Over half of these compounds (430) antagonized at least one of the ten ORs. OR activity fitted a mathematical model of competitive receptor binding and suggests normalization of OSN ensemble responses to odorant mixtures is the rule rather than the exception. In summary, we observed OR antagonism occurred frequently and in a combinatorial manner. Thus, extensive receptor-mediated computation of mixture information appears to occur in the olfactory epithelium prior to transmission of odor information to the olfactory bulb.

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

Odor landscapes contain complex blends of molecules that each activate unique, overlapping populations of olfactory sensory neurons (OSNs). Despite the presence of hundreds of OSN subtypes in many animals, the overlapping nature of odor inputs may lead to saturation of neural responses at the early stages of stimulus encoding. Information loss due to saturation could be mitigated by normalizing mechanisms such as antagonism at the level of receptor-ligand interactions, whose existence and prevalence remains uncertain. By imaging OSN axon terminals in olfactory bulb glomeruli as well as OSN cell bodies within the olfactory epithelium in freely breathing mice, we find widespread antagonistic interactions in binary odor mixtures. In complex mixtures of up to 12 odorants, antagonistic interactions are stronger and more prevalent with increasing mixture complexity. Therefore, antagonism is a common feature of odor mixture encoding in OSNs and helps in normalizing activity to reduce saturation and increase information transfer.

Exploring the Characteristics of an Aroma-Blending Mixture by Investigating the Network of Shared Odors and the Molecular Features of Their Related Odorants

The perception of aroma mixtures is based on interactions beginning at the peripheral olfactory system, but the process remains poorly understood. The perception of a mixture of ethyl isobutyrate (Et-iB, strawberry-like odor) and ethyl maltol (Et-M, caramel-like odor) was investigated previously in both human and animal studies. In those studies, the binary mixture of Et-iB and Et-M was found to be configurally processed. In humans, the mixture was judged as more typical of a pineapple odor, similar to allyl hexanoate (Al-H, pineapple-like odor), than the odors of the individual components. To explore the key features of this aroma blend, we developed an in silico approach based on molecules having at least one of the odors—strawberry, caramel or pineapple. A dataset of 293 molecules and their related odors was built. We applied the notion of a “social network” to describe the network of the odors. Additionally, we explored the structural properties of the molecules in this dataset. The network of the odors revealed peculiar links between odors, while the structural study emphasized key characteristics of the molecules. The association between “strawberry” and “caramel” notes, as well as the structural diversity of the “strawberry” molecules, were notable. Such elements would be key to identifying potential odors/odorants to form aroma blends.

Widespread receptor-driven modulation in peripheral olfactory coding

Olfactory responses to single odors have been well characterized but in reality we are continually presented with complex mixtures of odors. We performed high-throughput analysis of single-cell responses to odor blends using Swept Confocally Aligned Planar Excitation (SCAPE) microscopy of intact mouse olfactory epithelium, imaging ~10,000 olfactory sensory neurons in parallel. In large numbers of responding cells, mixtures of odors did not elicit a simple sum of the responses to individual components of the blend. Instead, many neurons exhibited either antagonism or enhancement of their response in the presence of another odor. All eight odors tested acted as both agonists and antagonists at different receptors. We propose that this peripheral modulation of responses increases the capacity of the olfactory system to distinguish complex odor mixtures.

Modulation of the combinatorial code of odorant receptor response patterns in odorant mixtures

The perception of odors relies on combinatorial codes consisting of odorant receptor (OR) response patterns to encode odor identity. Modulation of these patterns by odorant interactions at ORs potentially explains several olfactory phenomena: mixture suppression, unpredictable sensory outcomes, and the perception of odorant mixtures as unique objects. We determined OR response patterns to 4 odorants and 3 binary mixtures in vivo in mice, identifying 30 responsive ORs. These patterns typically had a few strongly responsive ORs and a greater number of weakly responsive ORs. ORs responsive to an odorant were often unrelated sequences distributed across several OR subfamilies. Mixture responses predicted pharmacological interactions between odorants, which were tested in vitro by heterologous expression of ORs in cultured cells, providing independent evidence confirming odorant agonists for 13 ORs and identifying both suppressive and additive effects. This included 11 instances of antagonism of ORs by an odorant, 1 instance of additive responses to a binary mixture, 1 instance of suppression of a strong agonist by a weak agonist, and the discovery of an inverse agonist for an OR. Interactions between odorants at ORs are common even when the odorants are not known to interact perceptually in humans, and in some cases interactions at mouse ORs correlate with the ability of humans to perceive an odorant in a mixture.

Importance of 2,4,6-Trichloroanisole (TCA) as an odorant in the emissions from anaerobically stabilized dewatered biosolids

Odours from stabilized biosolids after anaerobic digestion of wastewater sludge can cause local community impact. Apart from the well-known odorants such as sulfur compounds, contributions from other volatile organic compounds (VOCs) to nuisance odours is limited. The presence of compounds with low odour detection thresholds (ODTs) at low concentrations, can present challenges for analytical identification. Thirty-six biosolids samples were taken after anaerobic stabilisation and dewatering at a wastewater treatment plant, Sydney, Australia. Biosolid cake samples were stored outside in loosely covered trays under aerobic conditions, however without interactions with soil microorganisms as it would be in reality. All biosolids cake samples were analysed over a period of 35 days. Emissions were collected onto Tenax TA sorbent tubes using a U.S. EPA flux hood method at storage days 1, 3, 7, 10, 14, 21 and 35. Gas chromatography (GC) coupled with mass spectrometer detector (MSD) and an olfactory detection port (ODP) was used to identify a musty/moldy/earthy type odorant in the biosolids emissions as 2,4,6-trichloroanisole (TCA). Measured odour intensities, classified on a scale from 1 to 4, and odour characters were specified by three ODP assessors. TCA was identified in all biosolid cake emissions. The measured odour intensities of the TCA did not significantly alter as the biosolids were aged, however varied between biosolids cakes. Due to its odour intensity, 85% frequency of detection and its low ODT, which is orders of magnitudes lower than sulfur compounds, TCA should be considered as a potential odorant of concern in biosolids emissions.

Scaling the interactive effects of attractive and repellent odours for insect search behaviour

Insects searching for resources are exposed to a complexity of mixed odours, often involving both attractant and repellent substances. Understanding how insects respond to this complexity of cues is crucial for understanding consumer-resource interactions, but also to develop novel tools to control harmful pests. To advance our understanding of insect responses to combinations of attractive and repellent odours, we formulated three qualitative hypotheses; the response-ratio hypothesis, the repellent-threshold hypothesis and the odour-modulation hypothesis. The hypotheses were tested by exposing Drosophila melanogaster in a wind tunnel to combinations of vinegar as attractant and four known repellents; benzaldehyde, 1-octen-3-ol, geosmin and phenol. The responses to benzaldehyde, 1-octen-3-ol and geosmin provided support for the response-ratio hypothesis, which assumes that the behavioural response depends on the ratio between attractants and repellents. The response to phenol, rather supported the repellent-threshold hypothesis, where aversion only occurs above a threshold concentration of the repellent due to overshadowing of the attractant. We hypothesize that the different responses may be connected to the localization of receptors, as receptors detecting phenol are located on the maxillary palps whereas receptors detecting the other odorants are located on the antennae.

Optimal compressed sensing strategies for an array of nonlinear olfactory receptor neurons with and without spontaneous activity

There are numerous different odorant molecules in nature but only a relatively small number of olfactory receptor neurons (ORNs) in brains. This "compressed sensing" challenge is compounded by the constraint that ORNs are nonlinear sensors with a finite dynamic range. Here, we investigate possible optimal olfactory coding strategies by maximizing mutual information between odor mixtures and ORNs' responses with respect to the bipartite odor-receptor interaction network (ORIN) characterized by sensitivities between all odorant-ORN pairs. For ORNs without spontaneous (basal) activity, we find that the optimal ORIN is sparse-a finite fraction of sensitives are zero, and the nonzero sensitivities follow a broad distribution that depends on the odor statistics. We show analytically that sparsity in the optimal ORIN originates from a trade-off between the broad tuning of ORNs and possible interference. Furthermore, we show that the optimal ORIN enhances performances of downstream learning tasks (reconstruction and classification). For ORNs with a finite basal activity, we find that having inhibitory odor-receptor interactions increases the coding capacity and the fraction of inhibitory interactions increases with the ORN basal activity. We argue that basal activities in sensory receptors in different organisms are due to the trade-off between the increase in coding capacity and the cost of maintaining the spontaneous basal activity. Our theoretical findings are consistent with existing experiments and predictions are made to further test our theory. The optimal coding model provides a unifying framework to understand the peripheral olfactory systems across different organisms.

Primacy coding facilitates effective odor discrimination when receptor sensitivities are tuned

The olfactory system faces the difficult task of identifying an enormous variety of odors independent of their intensity. Primacy coding, where the odor identity is encoded by the receptor types that respond earliest, might provide a compact and informative representation that can be interpreted efficiently by the brain. In this paper, we analyze the information transmitted by a simple model of primacy coding using numerical simulations and statistical descriptions. We show that the encoded information depends strongly on the number of receptor types included in the primacy representation, but only weakly on the size of the receptor repertoire. The representation is independent of the odor intensity and the transmitted information is useful to perform typical olfactory tasks with close to experimentally measured performance. Interestingly, we find situations in which a smaller receptor repertoire is advantageous for discriminating odors. The model also suggests that overly sensitive receptor types could dominate the entire response and make the whole array useless, which allows us to predict how receptor arrays need to adapt to stay useful during environmental changes. Taken together, we show that primacy coding is more useful than simple binary and normalized coding, essentially because the sparsity of the odor representations is independent of the odor statistics, in contrast to the alternatives. Primacy coding thus provides an efficient odor representation that is independent of the odor intensity and might thus help to identify odors in the olfactory cortex.

Humans can identify odors independent of their intensity. Experimental data suggest that this is accomplished by representing the odor identity by the earliest responding receptor types. Using theoretical modeling, we here show that such a primacy code outperforms alternative encodings and allows discriminating odors with close to experimentally measured performance. This performance depends strongly on the number of receptors considered in the primacy code, but the receptor repertoire size is less important. The model also suggests a strong evolutionary pressure on the receptor sensitivities, which could explain observed receptor copy number adaptations. By predicting psycho-physical experiments, the model will thus contribute to our understanding of the olfactory system.

Front-end Weber-Fechner gain control enhances the fidelity of combinatorial odor coding

We showed previously (Gorur-Shandilya et al., 2017) that Drosophila olfactory receptor neurons (ORNs) expressing the co-receptor Orco scale their gain inversely with mean odor intensity according to Weber-Fechner's law. Here, we show that this front-end adaptation promotes the reconstruction of odor identity from dynamic odor signals, even in the presence of confounding background odors and rapid intensity fluctuations. These enhancements are further aided by known downstream transformations in the antennal lobe and mushroom body. Our results, which are applicable to various odor classification and reconstruction schemes, stem from the fact that this adaptation mechanism is not intrinsic to the identity of the receptor involved. Instead, a feedback mechanism adjusts receptor sensitivity based on the activity of the receptor-Orco complex, according to Weber-Fechner's law. Thus, a common scaling of the gain across Orco-expressing ORNs may be a key feature of ORN adaptation that helps preserve combinatorial odor codes in naturalistic landscapes.

Competitive binding predicts nonlinear responses of olfactory receptors to complex mixtures

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 receptor responses to different wavelengths of light and subsequently relating these responses to perception. In olfaction, experimentally measuring receptor responses 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 (CB): 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 12 monomolecular odorants to within 15% 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. We demonstrate that the presence of such interactions can be identified via systematic deviations from the competitive-binding model.