The perception of odor objects in everyday life: a review on the processing of odor mixtures

Pred-O3, a web server to predict molecules, olfactory receptors and odor relationships

The sense of smell is a biological process involving volatile molecules that interact with proteins called olfactory receptors to transmit a nervous message that allows the recognition of a perceived odor. However, the relationships between odorant molecules, olfactory receptors and odors (O3) are far from being well understood due to the combinatorial olfactory codes and large family of olfactory receptors. This is the reason why, based on 5802 odorant molecules and their annotations to 863 olfactory receptors (human) and 7029 odors and flavors annotations, a web server called Pred-O3 has been designed to provide insights into olfaction. Predictive models based on Artificial Intelligence have been developed allowing to suggest olfactory receptors and odors associated with a new molecule. In addition, based on the encoding of the odorant molecule's structure, physicochemical features related to odors and/or olfactory receptors are proposed. Finally, based on the structural models of the 98 olfactory receptors a systematic docking protocol can be applied and suggest if a molecule can bind or not to an olfactory receptor. Therefore, Pred-O3 is well suited to aid in the design of new odorant molecules and assist in fragrance research and sensory neuroscience. Pred-O3 is accessible at ' https://odor.rpbs.univ-paris-diderot.fr/'.

Impact of a minimally processing route for the production of infant formulas on their sensory properties

Infant formulas (IFs), the sole adequate substitute to human milk, undergo several thermal treatments during production that can damage milk proteins and promote the formation of Maillard reaction products, modifying nutritional and sensory properties. The aim of this study was to determine the impact of a minimally processing route based on membrane filtration associated with different levels of heat treatment, on the odor, taste, texture and color attributes of IFs, then to compare with those of commercial milks. Three experimental IFs (produced with membrane filtration associated with low - T-, medium - T+, or high thermal treatments - T+++) were evaluated. Triangular tests conducted with a panel of 50 adults highlighted clear disparities between all the IFs. The same panel applied the Check-All-That-Apply method to evaluate the IFs: the range of variability between T- and T+++ was similar to that between the 2 commercial IFs, and the sensory characteristics of the experimental IFs were not far from the commercial brands for flavor and texture attributes. Analysis performed on the citation frequencies for each descriptor differentiated T-/T+ from T+++, but all the experimental IFs were described with positive sensory characteristics, unlike one commercial IF. Volatile organic compounds (VOCs) content of IFs with low and high thermal treatments were analyzed. Forty VOCs were identified by gas chromatography-mass spectrometry. T- contained a higher quantity of VOCs than T+++, except for benzaldehyde (Maillard reaction product), and aldehydes (oxidation-related products) were the most represented compounds. In conclusion, the processing was associated with sensory differences among IFs, but no marked difference in flavors was found according to CATA and physicochemical analysis. Additionally, no unpleasant sensory descriptors were noted. This shows that the minimally processed route leads to IFs that could fit well within the market from a sensory point of view.

Brain waves spectral analysis of human responses to odorous and non-odorous substances: a preliminary study

OBJECTIVE

The aim of this study was to identify the potential electrophysiological biomarkers of human responses by comparing the electroencephalogram brain wave changes towards lavender versus normal saline in a healthy human population.

METHOD

This study included a total of 44 participants without subjective olfactory disturbances. Lavender and normal saline were used as the olfactory stimulant and control. Electroencephalogram was recorded and power spectra were analysed by the spectral analysis for each alpha, beta, delta, theta and gamma bandwidth frequency upon exposure to lavender and normal saline independently.

RESULTS

The oscillatory brain activities in response to the olfactory stimulant indicated that the lavender smell decreased the beta activity in the left frontal (F7 electrode) and central region (C3 electrode) with a reduction in the gamma activity in the right parietal region (P4 electrode) (p < 0.05).

CONCLUSION

Olfactory stimulants result in changes of electrical brain activities in different brain regions, as evidenced by the topographical brain map and spectra analysis of each brain wave.

Exploring the effects of mixture composition factors and perceptual interactions on the perception of icewine odor: An olfactometer-based study

The perception of food odor, derived from complex mixtures of odorants, remains poorly understood. This study investigated how key odorants of icewine influence odor mixture perception and mixture-induced perceptual interactions. A multichannel olfactometer was used to deliver 90 mixtures to 36 trained participants who used a Rate-All-That-Apply method to rate the odor samples. Results showed that adding odorants to a mixture affected both the characteristic odor of the individual component and other odor characteristics, revealing specific perceptual interactions. Combining up to six odorants with icewine odor influenced a maximum of two odor characteristics in the mixture, regardless of the specific combination. Interestingly, adding odorants had a stronger impact on the overall mixture odor profile than omitting them, particularly when manipulating fewer than three odorants. These findings emphasize the complexity of odor mixture perception and provide new insights into the influence of key odorants on the aroma of wine.

Predicting odor profile of food from its chemical composition: Towards an approach based on artificial intelligence and flavorists expertise

Odor is central to food quality. Still, a major challenge is to understand how the odorants present in a given food contribute to its specific odor profile, and how to predict this olfactory outcome from the chemical composition. In this proof-of-concept study, we seek to develop an integrative model that combines expert knowledge, fuzzy logic, and machine learning to predict the quantitative odor description of complex mixtures of odorants. The model output is the intensity of relevant odor sensory attributes calculated on the basis of the content in odor-active comounds. The core of the model is the mathematically formalized knowledge of four senior flavorists, which provided a set of optimized rules describing the sensory-relevant combinations of odor qualities the experts have in mind to elaborate the target odor sensory attributes. The model first queries analytical and sensory databases in order to standardize, homogenize, and quantitatively code the odor descriptors of the odorants. Then the standardized odor descriptors are translated into a limited number of odor qualities used by the experts thanks to an ontology. A third step consists of aggregating all the information in terms of odor qualities across all the odorants found in a given product. The final step is a set of knowledge-based fuzzy membership functions representing the flavorist expertise and ensuring the prediction of the intensity of the target odor sensory descriptors on the basis of the products' aggregated odor qualities; several methods of optimization of the fuzzy membership functions have been tested. Finally, the model was applied to predict the odor profile of 16 red wines from two grape varieties for which the content in odorants was available. The results showed that the model can predict the perceptual outcome of food odor with a certain level of accuracy, and may also provide insights into combinations of odorants not mentioned by the experts.

Enhancement effect of odor and multi-sensory superposition on sweetness

The impact of sugary foods on public health has contributed to the development of low-sugar and sugar-substituted products, and sugar reduction has become a major challenge for the food industry. There is growing empirical evidence that odor can enhance the perception of sweetness without increasing the caloric load. This current review summarizes the researches on odor-induced sweetness enhancement published in recent years and discusses the mechanisms and influencing factors of odor-sweetness interactions. In addition, by combing existing studies, this paper also summarizes the research methods and strategies to investigate odor-induced sweetness enhancement. Finally, the feasibility of synergistic enhancement of sweetness through the superposition of odor with other senses (texture, visual, etc.) is also discussed and analyzed. In conclusion, odor-induced sweetness enhancement may present an alternative or complementary approach for developing foods with less sugar.

Predicting minty compounds binary mixtures' pleasantness by odor intensity in aqueous solutions

The aroma of mint is well-liked by the public, and key flavor odorants in mint aroma had been found, but how these molecules interact and form a satisfying odor remains a challenge. Quality, intensity, and pleasantness are our most basic perceptions of aromas; both intensity and pleasantness can be quantified. However, compared to intensity, research on pleasantness was lacking. Pleasantness was one of the most important indicators for formulating a satisfying mint flavor, and the study of binary mixtures was fundamental to our understanding of more complex mixtures. Therefore, the purpose of this study was to explore the characteristics of pleasantness as a function of concentration and, at the same time, to investigate the relationship between intensity and pleasantness in binary mixtures. Thirty sensory evaluation volunteers participated in the evaluation of the intensity and pleasantness of six key flavor odorants of mint and five binary mixtures. The results showed that the pleasantness increased first and then decreased or stabilized with the rising of concentration; even though the interactions in binary mixtures were not the same, their pleasantness could be predicted using the intensities of the components by Response Surface Design of Experiments, and the goodness of fit was greater than 0.92, indicating that the models had the great predictive ability. PRACTICAL APPLICATION: Whether blending flavors or evaluating them, a great deal of experience is required, yet the acquisition of this experience is a long process. Performing these tasks is difficult for the novice, and it helps to quantify the feeling for the flavor and build some mathematical models.

A critical review on odor measurement and prediction

Odor pollution has become a global environmental issue of increasing concern in recent years. Odor measurements are the basis of assessing and solving odor problems. Olfactory and chemical analysis can be used for odor and odorant measurements. Olfactory analysis reflects the subjective perception of human, and chemical analysis reveals the chemical composition of odors. As an alternative to olfactory analysis, odor prediction methods have been developed based on chemical and olfactory analysis results. The combination of olfactory and chemical analysis is the best way to control odor pollution, evaluate the performances of the technologies, and predict odor. However, there are still some limitations and obstacles for each method, their combination, and the prediction. Here, we present an overview of odor measurement and prediction. Different olfactory analysis methods (namely, the dynamic olfactometry method and the triangle odor bag method) are compared in detail, the latest revisions of the standard olfactometry methods are summarized, and the uncertainties of olfactory measurement results (i.e., the odor thresholds) are analyzed. The researches, applications, and limitations of chemical analysis and odor prediction are introduced and discussed. Finally, the development and application of odor databases and algorithms for optimizing odor measurement and prediction methods are prospected, and a preliminary framework for an odor database is proposed. This review is expected to provide insights into odor measurement and prediction.

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.

Research on odor characteristics of typical odorants of railway vehicle products

Odor annoyance was a kind of environmental air pollution. Compared to other indoor environments, vehicle interior materials were not well studied. Especially, there had been little research on odor character of the railway vehicles. This study applied the OAV method to identify the key odorants of railway vehicle materials and discussed the characteristics of these odorants through Weber Fechner law and a dual variable method. The result showed that for single odorant, Weber Fechner law can be used to estimate the perceived intensity of an odor gas sample at different concentration levels. The odorant with smaller slope had significant tolerance to human. For the mixtures of odorants, the overall intensity of the mixture is generally dominated by the strongest odor intensity of the individual substance in the mixture, and positive interaction effect can be observed in mixtures whose intensities had little difference. But there was a kind of odorants, such as methacrylate, in which a very small variation in the concentration of mixtures can affect its odor intensity largely. Meanwhile, the odor intensity modification coefficient was an effective way to identify and evaluate odor interaction effect. The interaction potential of the studied odorants from strong to weak was methacrylate, dibutyl-amine, nonanal, 2-ethyl hexanol. The odor interaction potential and odor nature should be paying much attention in the improvement of odor in railway vehicle product.

Flare exhaust: An underestimated pollution source in municipal solid waste landfills

Flares are commonly used in municipal solid waste landfills, and the pollution from flare exhaust is usually underestimated. This study aimed to reveal the odorants, hazardous pollutants, and greenhouse gas emission characteristics of the flare exhaust. Odorants, hazardous pollutants, and greenhouse gases emitted from air-assisted flares and a diffusion flare were analyzed, the priority monitoring pollutants were identified, and the combustion and odorant removal efficiencies of the flares were estimated. The concentrations of most odorants and the sum of odor activity values decreased significantly after combustion, but the odor concentration could still exceed 2,000. The odorants in the flare exhaust were dominated by oxygenated volatile organic compounds (OVOCs), while the major odor contributors were OVOCs and sulfur compounds. Hazardous pollutants, including carcinogens, acute toxic pollutants, endocrine disrupting chemicals, and ozone precursors with the total ozone formation potential up to 75 ppm_v, as well as greenhouse gases (methane and nitrous oxide with maximum concentrations of 4,000 and 1.9 ppm_v, respectively) were emitted from the flares. Additionally, secondary pollutants, such as acetaldehyde and benzene, were formed during combustion. The combustion performance of the flares varied with landfill gas composition and flare design. The combustion and pollutant removal efficiencies could be lower than 90%, especially for the diffusion flare. Acetaldehyde, benzene, toluene, p-cymene, limonene, hydrogen sulfide, and methane could be priority monitoring pollutants for flare emissions in landfills. Flares are useful for odor and greenhouse gas control in landfills, but they are also potential sources of odor, hazardous pollutants, and greenhouse gases.

Soft, miniaturized, wireless olfactory interface for virtual reality

Recent advances in virtual reality (VR) technologies accelerate the creation of a flawless 3D virtual world to provide frontier social platform for human. Equally important to traditional visual, auditory and tactile sensations, olfaction exerts both physiological and psychological influences on humans. Here, we report a concept of skin-interfaced olfactory feedback systems with wirelessly, programmable capabilities based on arrays of flexible and miniaturized odor generators (OGs) for olfactory VR applications. By optimizing the materials selection, design layout, and power management, the OGs exhibit outstanding device performance in various aspects, from response rate, to odor concentration control, to long-term continuous operation, to high mechanical/electrical stability and to low power consumption. Representative demonstrations in 4D movie watching, smell message delivery, medical treatment, human emotion control and VR/AR based online teaching prove the great potential of the soft olfaction interface in various practical applications, including entertainment, education, human machine interfaces and so on.

Does atrazine induce changes in predator recognition, growth, morphology, and metamorphic traits of larval skipper frogs (Euphlyctis cyanophlyctis)?

Atrazine, an info disruptor, interferes with the olfaction of aquatic organisms by impairing the chemosensory system. Consequently, it affects behavior, physiology, and growth increases mortality and infections, and suppresses the immune system of aquatic animals. In this study, we wanted to determine the sensitivity of larval Euphlyctis cyanophlyctis to different concentrations of atrazine by assessing their antipredator behavior, growth, morphology, and metamorphic traits. The results indicate that exposure to atrazine did not affect the survival of tadpoles. However, it caused retarded growth at higher concentrations. Interestingly, the antipredator behavior of tadpoles toward conspecific alarm cues decreased in a dose-dependent manner with an increase in the concentration of atrazine. Tadpoles exposed to low concentrations of atrazine had deeper, wider bodies and tails while those exposed to higher concentrations had shallower and narrower bodies with shallower tail muscles. However, at low and moderate concentrations atrazine did not affect size at metamorphosis, it extended the larval duration at higher concentrations.

Expansive linguistic representations to predict interpretable odor mixture discriminability

Language is often thought as being poorly adapted to precisely describe or quantify smell and olfactory attributes. In this work, we show that semantic descriptors of odors can be implemented in a model to successfully predict odor mixture discriminability, an olfactory attribute. We achieved this by taking advantage of the structure-to-percept model we previously developed for monomolecular odorants, using chemical descriptors to predict pleasantness, intensity and 19 semantic descriptors such as "fish," "cold," "burnt," "garlic," "grass," and "sweet" for odor mixtures, followed by a metric learning to obtain odor mixture discriminability. Through this expansion of the representation of olfactory mixtures, our Semantic model outperforms state of the art methods by taking advantage of the intermediary semantic representations learned from human perception data to enhance and generalize the odor discriminability/similarity predictions. As 10 of the semantic descriptors were selected to predict discriminability/similarity, our approach meets the need of rapidly obtaining interpretable attributes of odor mixtures as illustrated by the difficulty of finding olfactory metamers. More fundamentally, it also shows that language can be used to establish a metric of discriminability in the everyday olfactory space.

Volatile Compound Abundance Correlations Provide a New Insight into Odor Balances in Sauce-Aroma Baijiu

Sauce-aroma Baijiu (SAB) is one of the most famous Baijius in China; SAB has more than 500 aroma compounds in it. However, the key aroma compound in SAB flavor remains unclear. Volatiles play an important role in SAB aroma and are highly correlated to SAB quality. In the present study, 63 volatile compounds were quantified among 66 SAB samples using gas chromatography with flame ionization detector (GC-FID). The authors analyzed odor contributions and volatile compound correlations in two quality groups of SAB samples. Moreover, an odor activity value (OAV) ratio-based random forest classifier was used to explain the volatile compound relationship differentiations between the two quality groups. Our results proved higher quality SABs had richer aromas and indicated a set of fruity-like ethyl valerate, green- and malt-like isobutyraldehyde and malt-like 3-methylbutyraldehyde and sweet-like furfural, had closer co-abundance correlations in higher quality SABs. These results indicated that the aroma and contributions of volatile compounds in SABs should be analyzed not only with compound odor activity values, but also the correlations between different aroma compounds.

Mania associated olfactory dysfunction: A comparison between bipolar subjects in mania and remission

OBJECTIVES

The aim of this study was to assess the olfactory functions of patients with bipolar disorder in manic phase and to compare them to those of bipolar subjects in remission and healthy controls.

METHODS

We recruited 96 participants divided in 3 groups: bipolar mania (MB), euthymic bipolar in remission (EB) and healthy controls (HC). All participants underwent an assessment of their olfactory functions using the Sniffin' sticks threshold and identification tests. Odors' pleasantness, intensity, familiarity and emotion were assessed. All participants were screened for the presence of psychiatric disorder through the MINI questionnaire. Clinical evaluation explored dimensions of mania, depression, anxiety respectively through YMRS, MADRS and STAI scales. Anhedonia was explored through the Chapman physical and social anhedonia questionnaire.

RESULTS

Patients in mania had deficits in identifying positive smells compared to bipolar subjects in remission and to healthy controls (MB < EB < HC; p < 0.001). Hedonic (MB < EB = HC; p < 0.001) and emotional (MB < EB = HC; p < 0.001) ratings of positive smells were lower in patients in manic phase compared to remitted subjects or controls. Mania was associated to higher emotion rating of negative smells compared to remitted subjects and controls (MB > EB = HC; p < 0.001). There was no difference between the 3 groups in the ratings of intensity and familiarity of smells, as well as in the olfactory threshold testing. The 3 groups showed no difference in the identification of negative smells.

CONCLUSIONS

Patients in manic episodes showed deficits in identifying positive odors. They evaluated these smells as less pleasant and less emotional compared to remitted bipolar subjects and healthy controls. These olfactory dysfunctions may constitute potential indicators of manic state. The persistence of olfactory dysfunction in remission phase (deficit in the olfactory identification of positive odors compared to healthy controls) may constitute a potential trait indicator of bipolarity.

OOPS, the Ontology for Odor Perceptual Space: From Molecular Composition to Sensory Attributes of Odor Objects

When creating a flavor to elicit a specific odor object characterized by odor sensory attributes (OSA), expert perfumers or flavorists use mental combinations of odor qualities (OQ) such as Fruity, Green, and Smoky. However, OSA and OQ are not directly related to the molecular composition in terms of odorants that constitute the chemical stimuli supporting odor object perception because of the complex non-linear integration of odor mixtures within the olfactory system. Indeed, single odorants are described with odor descriptors (OD), which can be found in various databases. Although classifications and aroma wheels studied the relationships between OD and OQ, the results were highly dependent on the studied products. Nevertheless, ontologies have proven to be very useful in sharing concepts across applications in a generic way and to allow experts' knowledge integration, implying non-linear cognitive processes. In this paper, we constructed the Ontology for Odor Perceptual Space (OOPS) to merge OD into a set of OQ best characterizing the odor, further translated into a set of OSA thanks to expert knowledge integration. Results showed that OOPS can help bridge molecular composition to odor perception and description, as demonstrated in the case of wines.

Characterization of odour emissions in a wastewater treatment plant using a drone-based chemical sensor system

Conventionally, odours emitted by different sources present in wastewater treatment plants (WWTPs) are measured by dynamic olfactometry, where a human panel sniffs and analyzes air bags collected from the plant. Although the method is considered the gold standard, the process is costly, slow, and infrequent, which does not allow operators to quickly identify and respond to problems. To better monitor and map WWTP odour emissions, here we propose a small rotary-wing drone equipped with a lightweight (1.3-kg) electronic nose. The "sniffing drone" sucks in air via a ten-meter (33-foot) tube and delivers it to a sensor chamber where it is analyzed in real-time by an array of 21 gas sensors. From the sensor signals, machine learning (ML) algorithms predict the odour concentration that a human panel using the EN13725 methodology would report. To calibrate and validate the predictive models, the drone also carries a remotely controlled sampling device (compliant with EN13725:2022) to collect sample air in bags for post-flight dynamic olfactometry. The feasibility of the proposed system is assessed in a WWTP in Spain through several measurement campaigns covering diverse operating regimes of the plant and meteorological conditions. We demonstrate that training the ML algorithms with dynamic (transient) sensor signals measured in flight conditions leads to better performance than the traditional approach of using steady-state signals measured in the lab via controlled exposures to odour bags. The comparison of the electronic nose predictions with dynamic olfactometry measurements indicates a negligible bias between the two measurement techniques and 95 % limits of agreement within a factor of four. This apparently large disagreement, partly caused by the high uncertainty of olfactometric measurements (typically a factor of two), is more than offset by the immediacy of the predictions and the practical advantages of using a drone-based system.

Application of artificial intelligence to decode the relationships between smell, olfactory receptors and small molecules

Deciphering the relationship between molecules, olfactory receptors (ORs) and corresponding odors remains a challenging task. It requires a comprehensive identification of ORs responding to a given odorant. With the recent advances in artificial intelligence and the growing research in decoding the human olfactory perception from chemical features of odorant molecules, the applications of advanced machine learning have been revived. In this study, Convolutional Neural Network (CNN) and Graphical Convolutional Network (GCN) models have been developed on odorant molecules-odors and odorant molecules-olfactory receptors using a large set of 5955 molecules, 160 odors and 106 olfactory receptors. The performance of such models is promising with a Precision/Recall Area Under Curve of 0.66 for the odorant-odor and 0.91 for the odorant-olfactory receptor GCN models respectively. Furthermore, based on the correspondence of odors and ORs associated for a set of 389 compounds, an odor-olfactory receptor pairwise score was computed for each odor-OR combination allowing to suggest a combinatorial relationship between olfactory receptors and odors. Overall, this analysis demonstrate that artificial intelligence may pave the way in the identification of the smell perception and the full repertoire of receptors for a given odorant molecule.

You Eat How You Think: A Review on the Impact of Cognitive Styles on Food Perception and Behavior

Sensory perception is understood to be a complex area of research that requires investigations from a variety of different perspectives. Although researchers have tried to better understand consumers’ perception of food, one area that has been minimally explored is how psychological cognitive theories can help them explain consumer perceptions, behaviors, and decisions in food-related experiences. The concept of cognitive styles has existed for nearly a century, with the majority of cognitive style theories existing along a continuum with two bookends. Some of the more common theories such as individualist-collectivist, left-brain-right-brain, and convergent-divergent theories each offered their own unique insight into better understanding consumer behavior. However, these theories often focused only on niche applications or on specific aspects of cognition. More recently, the analytic-holistic cognitive style theory was developed to encompass many of these prior theoretical components and apply them to more general cognitive tendencies of individuals. Through applying the analytic-holistic theory and focusing on modern cultural psychology work, this review may allow researchers to be able to answer one of the paramount questions of sensory and consumer sciences: how and why do consumers perceive and respond to food stimuli the way that they do?

Shedding Light on Inter-Individual Variability of Olfactory Circuits in Drosophila

Inter-individual differences in behavioral responses, anatomy or functional properties of neuronal populations of animals having the same genotype were for a long time disregarded. The majority of behavioral studies were conducted at a group level, and usually the mean behavior of all individuals was considered. Similarly, in neurophysiological studies, data were pooled and normalized from several individuals. This approach is mostly suited to map and characterize stereotyped neuronal properties between individuals, but lacks the ability to depict inter-individual variability regarding neuronal wiring or physiological characteristics. Recent studies have shown that behavioral biases and preferences to olfactory stimuli can vary significantly among individuals of the same genotype. The origin and the benefit of these diverse “personalities” is still unclear and needs to be further investigated. A perspective taken into account the inter-individual differences is needed to explore the cellular mechanisms underlying this phenomenon. This review focuses on olfaction in the vinegar fly Drosophila melanogaster and summarizes previous and recent studies on odor-guided behavior and the underlying olfactory circuits in the light of inter-individual variability. We address the morphological and physiological variabilities present at each layer of the olfactory circuitry and attempt to link them to individual olfactory behavior. Additionally, we discuss the factors that might influence individuality with regard to olfactory perception.

Assessing the contribution of odor-active compounds in icewine considering odor mixture-induced interactions through gas chromatography-olfactometry and Olfactoscan

The sensory impact of odor-active compounds on icewine aroma could be influenced by perceptual interactions with other odor-active compounds. The aim of this study was to establish an approach to evaluate the contribution of odor-active compounds found in icewine considering mixture-induced perceptual interactions. By comparing the impact of key odorants detected in icewine following a gas chromatography-olfactometry approach with an Olfactoscan-based methodology using a background odor of icewine, 69 odor zones were detected, and their related compounds were further identified. The results revealed that icewine background odor could exert odor masking or enhancement on key odorants when they are considered in the complex wine aroma buffer. Several compounds can induce qualitative changes in the overall wine aroma. This study underlined the efficiency of Olfactoscan-like approaches to screen for the real impact of key odorants and to pinpoint specific compounds that could be highly influential once embedded in the aroma buffer.

Biological constraints on configural odour mixture perception

Animals, including humans, detect odours and use this information to behave efficiently in the environment. Frequently, odours consist of complex mixtures of odorants rather than single odorants, and mixtures are often perceived as configural wholes, i.e. as odour objects (e.g. food, partners). The biological rules governing this 'configural perception' (as opposed to the elemental perception of mixtures through their components) remain weakly understood. Here, we first review examples of configural mixture processing in diverse species involving species-specific biological signals. Then, we present the original hypothesis that at least certain mixtures can be processed configurally across species. Indeed, experiments conducted in human adults, newborn rabbits and, more recently, in rodents and honeybees show that these species process some mixtures in a remarkably similar fashion. Strikingly, a mixture AB (A, ethyl isobutyrate; B, ethyl maltol) induces configural processing in humans, who perceive a mixture odour quality (pineapple) distinct from the component qualities (A, strawberry; B, caramel). The same mixture is weakly configurally processed in rabbit neonates, which perceive a particular odour for the mixture in addition to the component odours. Mice and honeybees also perceive the AB mixture configurally, as they respond differently to the mixture compared with its components. Based on these results and others, including neurophysiological approaches, we propose that certain mixtures are convergently perceived across various species of vertebrates/invertebrates, possibly as a result of a similar anatomical organization of their olfactory systems and the common necessity to simplify the environment's chemical complexity in order to display adaptive behaviours.

Canine olfactory detection of trained explosive and narcotic odors in mixtures using a Mixed Odor Delivery Device

Like using a substandard calibrant to test and calibrate an instrumental detector, when detection canines are regularly exposed to less than optimal training material, their detection proficiency is diminished, risking the lives of their handlers and civilians they are intended to protect. This research examined canine detection proficiency to odor mixtures and the use of mixture training to improve said proficiency. Trained detection canines were tested on their ability to correctly locate their trained target odors, explosives or narcotics, in various mixtures from a series of blanks and distractor odors. After making base measurements, canines were trained on the target odor in mixtures using the Mixed Odor Delivery Device (MODD), which was previously developed to safely contain separated explosive components and deliver the mixed odor to a canine detector for training purposes. Headspace measurements, made using solid phase microextraction with gas chromatography/mass spectrometry (SPME-GC/MS), were also taken of mixture components in and out of the MODD to confirm that odor mixtures were accurately portrayed to the canines during MODD training. Following mixture training, canines were retested on the same mixtures. Results of the headspace analysis showed that the MODD did not alter the delivery of the odorants from the mixture components. As such, canines showed an improved proficiency in detection of target mixtures following mixture training, increasing the detection rate from 63% to 72% for pseudo cocaine mixtures and from 19% to 100% for explosive mixtures.

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.

Strategies for the identification and sensory evaluation of volatile constituents in wine

Wine aroma, which stems from complex perceptual and cognitive processes, is initially driven by a multitude of naturally occurring volatile constituents. Its interpretation depends on the characterization of relevant volatile constituents. With large numbers of volatile constituents already identified, the search for unknown volatiles in wine has become increasingly challenging. However, the opportunities to discover unknown volatile compounds contributing to the wine volatilome are still of great interest, as demonstrated by the recent identification of highly odorous trace (µg/L) to ultra-trace (ng/L) volatile compounds in wine. This review provides an overview of both existing strategies and future directions on identifying unknown volatile constituents in wine. Chemical identification, including sample extraction, fractionation, gas chromatography, olfactometry, and mass spectrometry, is comprehensively covered. In addition, this review also focuses on aspects related to sensory-guided wine selection, authentic reference standards, artifacts and interferences, and the evaluation of the sensory significance of discovered wine volatiles. Powerful key volatile odorants present at ultra-trace levels, for which these analytical approaches have been successfully applied, are discussed. Research areas where novel wine volatiles are likely to be identified are pointed out. The importance of perceptual interaction phenomena is emphasized. Finally, future avenues for the exploration of yet unknown wine volatiles by coupling analytical approaches and sensory evaluation are suggested.

A New Classification of Perceptual Interactions between Odorants to Interpret Complex Aroma Systems. Application to Model Wine Aroma

Although perceptual interactions are usually mentioned and blamed for the difficulties in understanding the relationship between odorant composition and aromatic sensory properties, they are poorly defined and categorised. Furthermore, old classifications refer mainly to effects on the odour intensity of the mixture of dissimilar non-blending odours and do not consider odour blending, which is one of the most relevant and influential perceptual interactions. Beginning with the results from classical studies about odour interaction, a new and simple systematic is proposed in which odour interactions are classified into four categories: competitive, cooperative, destructive and creative. The first categories are most frequent and display a mild level of interaction, being characterised mostly by analytical processing. The last two are less frequent and activate (or deactivate) configurational processes of object recognition with deep effects on the quality and intensity of the perception. These interactions can be systematically applied to interpret the formation of sensory descriptors from the odorant composition, suggesting that qualitatively the system works. However, there is a lack of quantitative data to work with odour intensities reliably, and a pressing need to systematise the effects of creative interactions.

Resolving different presynaptic activity patterns within single olfactory glomeruli of Xenopus laevis larvae

Olfactory sensing is generally organized into groups of similarly sensing olfactory receptor neurons converging into their corresponding glomerulus, which is thought to behave as a uniform functional unit. It is however unclear to which degree axons within a glomerulus show identical activity, how many converge into a glomerulus, and to answer these questions, how it is possible to visually separate them in live imaging. Here we investigate activity of olfactory receptor neurons and their axon terminals throughout olfactory glomeruli using electrophysiological recordings and rapid 4D calcium imaging. While single olfactory receptor neurons responsive to the same odor stimulus show a diversity of responses in terms of sensitivity and spontaneous firing rate on the level of the somata, their pre-synaptic calcium activity in the glomerulus is homogeneous. In addition, we could not observe the correlated spontaneous calcium activity that is found on the post-synaptic side throughout mitral cell dendrites and has been used in activity correlation imaging. However, it is possible to induce spatio-temporal presynaptic response inhomogeneities by applying trains of olfactory stimuli with varying amino acid concentrations. Automated region-of-interest detection and correlation analysis then visually distinguishes at least two axon subgroups per glomerulus that differ in odor sensitivity.

Decoding Odor Mixtures in the Dog Brain: An Awake fMRI Study

In working and practical contexts, dogs rely upon their ability to discriminate a target odor from distracting odors and other sensory stimuli. Using awake functional magnetic resonance imaging (fMRI) in 18 dogs, we examined the neural mechanisms underlying odor discrimination between 2 odors and a mixture of the odors. Neural activation was measured during the presentation of a target odor (A) associated with a food reward, a distractor odor (B) associated with nothing, and a mixture of the two odors (A+B). Changes in neural activation during the presentations of the odor stimuli in individual dogs were measured over time within three regions known to be involved with odor processing: the caudate nucleus, the amygdala, and the olfactory bulbs. Average activation within the amygdala showed that dogs maximally differentiated between odor stimuli based on the stimulus-reward associations by the first run, while activation to the mixture (A+B) was most similar to the no-reward (B) stimulus. To clarify the neural representation of odor mixtures in the dog brain, we used a random forest classifier to compare multilabel (elemental) versus multiclass (configural) models. The multiclass model performed much better than the multilabel (weighted-F1 0.44 vs. 0.14), suggesting the odor mixture was processed configurally. Analysis of the subset of high-performing dogs' brain classification metrics revealed a network of olfactory information-carrying brain regions that included the amygdala, piriform cortex, and posterior cingulate. These results add further evidence for the configural processing of odor mixtures in dogs and suggest a novel way to identify high-performers based on brain classification metrics.

Pleasantness of Binary Odor Mixtures: Rules and Prediction

Pleasantness is a major dimension of odor percepts. While naturally encountered odors rely on mixtures of odorants, few studies have investigated the rules underlying the perceived pleasantness of odor mixtures. To address this issue, a set of 222 binary mixtures based on a set of 72 odorants were rated by a panel of 30 participants for odor intensity and pleasantness. In most cases, the pleasantness of the binary mixtures was driven by the pleasantness and intensity of its components. Nevertheless, a significant pleasantness partial addition was observed in 6 binary mixtures consisting of 2 components with similar pleasantness ratings. A mathematical model, involving the pleasantness of the components as well as τ-values reflecting components' odor intensity, was applied to predict mixture pleasantness. Using this model, the pleasantness of mixtures including 2 components with contrasted intensity and pleasantness could be efficiently predicted at the panel level (R2 > 0.80, Root Mean Squared Error < 0.67).

Exploring the Kairomone-Based Foraging Behaviour of Natural Enemies to Enhance Biological Control: A Review

Kairomones are chemical signals that mediate interspecific interactions beneficial to organisms that detect the cues. These attractants can be individual compounds or mixtures of herbivore-induced plant volatiles (HIPVs) or herbivore chemicals such as pheromones, i.e., chemicals mediating intraspecific communication between herbivores. Natural enemies eavesdrop on kairomones during their foraging behaviour, i.e., location of oviposition sites and feeding resources in nature. Kairomone mixtures are likely to elicit stronger olfactory responses in natural enemies than single kairomones. Kairomone-based lures are used to enhance biological control strategies via the attraction and retention of natural enemies to reduce insect pest populations and crop damage in an environmentally friendly way. In this review, we focus on ways to improve the efficiency of kairomone use in crop fields. First, we highlight kairomone sources in tri-trophic systems and discuss how these attractants are used by natural enemies searching for hosts or prey. Then we summarise examples of field application of kairomones (pheromones vs. HIPVs) in recruiting natural enemies. We highlight the need for future field studies to focus on the application of kairomone blends rather than single kairomones which currently dominate the literature on field attractants for natural enemies. We further discuss ways for improving kairomone use through attract and reward technique, olfactory associative learning, and optimisation of kairomone lure formulations. Finally, we discuss why the effectiveness of kairomone use for enhancing biological control strategies should move from demonstration of increase in the number of attracted natural enemies, to reducing pest populations and crop damage below economic threshold levels and increasing crop yield.

Perceptual interactions among food odors: Major influences on odor intensity evidenced with a set of 222 binary mixtures of key odorants

This study explored the impact of perceptual interactions on the odor intensity of 222 binary mixtures designed from 72 odorants found in food products. Odor intensity was rated by 30 trained subjects. The results showed that in most cases, the components' odor was perceived within the mixture and their intensity remained the same as in the unmixed situation in 54.3% of cases. Masking was the second major effect (44.8%) and occurred more frequently when components' pleasantness was significantly different. Synergy occurred in a small number of cases (0.9%) and only for four compounds. The overall odor intensity of the mixture was determined to be equal to the strongest component in most cases (73.9%), while partial addition was observed as the second most frequent effect (21.7%), especially when the components had equal intensity. Overall, this work provides general rules about the outcome to expect when mixing key components of food aromas.

A chemometric approach to characterize the aroma of selected brown and red edible seaweeds / extracts

BACKGROUND

Information pertaining to the aromatic profile of seaweeds and seaweed extracts can provide evidence regarding their potential suitability as ingredients in processed foods. To date only limited material has been available on the volatile profiles of some seaweed species. Others in this study have not previously been described. The volatile profiles of dried brown (Himanthalia elongata, Undaria pinnatifida, Alaria esculenta) and red (Porphyra umbilicalis, Palmaria palmata) seaweeds, and a brown seaweed extract (fucoxanthin) from Laminaria japonica were investigated using a chemometric approach to collate data from volatile gas chromatography - mass spectrometry (GC-MS), direct sensory aroma evaluation, and gas-chromatography - olfactometry (GC-O) to obtain a better understanding of their volatile profile and sensory perception.

RESULTS

More than 100 volatile compounds were identified by static headspace solid phase micro-extraction (HS-SPME) and thermal desorption gas chromatography - mass spectrometry (TD GC-MS). Brown seaweeds were characterized by 'grassy/herbal/floral', 'fruity', and 'fatty' aromas, red seaweeds by 'green/vegetable', 'mushroom/earthy' and 'sweet/buttery' aromas, and the fucoxanthin extract by 'rancid' and 'nutty' aromas with an overall lower intensity. Heptanal appeared to be a major odor-active compound in all samples. Other volatiles were more characteristic of each individual seaweed: hexanal, (E,Z)-2,6-nonadienal and 2-pentylfuran for H. elongata; ethyl butanoate and 2,3-butanedione for U. pinnatifida; 6-dimethylpyrazine, (E,Z)-2,6-nonadienal and sulactone for P. palmata; 1-octen-3-ol for P. umbilicalis, heptanone for A. esculenta, and 2-furanmethanol for fucoxanthin.

CONCLUSION

Brown and red seaweeds had distinct sensory properties with individual seaweeds having differing volatiles and odorants. This study provides additional information that can contribute to the development of products incorporating dried seaweeds / extracts that are more acceptable to the consumer. © 2020 Society of Chemical Industry.

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.

The Role of Trialeurodes vaporariorum-Infested Tomato Plant Volatiles in the Attraction of Encarsia formosa (Hymenoptera: Aphelinidae)

Natural enemies locate their herbivorous host and prey through kairomones emitted by host plants and herbivores. These kairomones could be exploited to attract and retain natural enemies in crop fields for insect pest control. The parasitoid Encarsia formosa preferentially parasitises its whitefly host, Trialeurodes vaporariorum, a major pest of tomato Solanum lycopersicum, thus offering an effective way to improve whitefly control. However, little is known about the chemical interactions that occur in E. formosa-T. vaporariorum-S. lycopersicum tritrophic system. Using behavioural assays and chemical analyses, we investigated the kairomones mediating attraction of the parasitoid to host-infested tomato plants. In Y-tube olfactometer bioassays, unlike volatiles of healthy tomato plants, those of T. vaporariorum-infested tomato plants attracted E. formosa, and this response varied with host infestation density. Coupled gas chromatography/mass spectrometric analyses revealed that host infestation densities induced varying qualitative and quantitative differences in volatile compositions between healthy and T. vaporariorum adult-infested tomato plants. Bioassays using synthetic chemicals revealed the attractiveness of 3-carene, β-ocimene, β-myrcene and α-phellandrene to the parasitoid, and the blend of the four compounds elicited the greatest attraction. Our results suggest that these terpenes could be used as an attractant lure to recruit the parasitoid E. formosa for the control of whiteflies in tomato crop fields.

Configural memory of a blending aromatic mixture reflected in activation of the left orbital part of the inferior frontal gyrus

Blending aromatic mixtures components naturally fuse to form a unique odor - a configuration- qualitatively different from each component's odor. Repeated exposure to the components either in the mixture or separately, favors respectively, configural and elemental processings. The neural bases of such processes are still unknown. We examined the brain correlates of the experienced-induced configural processing of a well-known model of binary blending odor mixture, the aromatic pineapple blending (AB, ethyl maltol + ethyl isobutyrate). Before fMRI recording, half of the participants were repeatedly exposed to the mixture (AB, group Gmix), with the other half exposed to its separate components (A and B; Gcomp). During the fMRI recording, all participants were stimulated with the mixture (AB) and the components (A and B). Finally, participants rated the number of odors perceived for each stimulus. Gmix perceived the AB mixture as less complex than did Gcomp. While Gcomp perceived the mixture as more complex than its components, Gmix did not. These results show the presence of experience-induced configural or elemental processing of the AB mixture in each group. Contrasting the brain activity of Gcomp and Gmix, when stimulated with AB, revealed higher activation in the left orbital part of the inferior frontal gyrus. This result sheds light on this area's function, commonly found activated in olfactory studies, and closely connected with the lateral orbitofrontal cortex. We discuss the role of this area as a mediator of configural percepts between temporal and orbitofrontal areas involved in configural memory processes.

Odor hedonics coding in the vertebrate olfactory bulb

Whether an odorant is perceived as pleasant or unpleasant (hedonic value) governs a range of crucial behaviors: foraging, escaping danger, and social interaction. Despite its importance in olfactory perception, little is known regarding how odor hedonics is represented and encoded in the brain. Here, we review recent findings describing how odorant hedonic value is represented in the first olfaction processing center, the olfactory bulb. We discuss how olfactory bulb circuits might contribute to the coding of innate and learned odorant hedonics in addition to the odorant's physicochemical properties.

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.

Assessment of odor hedonic perception: the Sniffin' sticks parosmia test (SSParoT)

Qualitative olfactory dysfunction is characterized as distorted odor perception and can have a profound effect on quality of life of affected individuals. Parosmia and phantosmia represent the two main subgroups of qualitative impairment and are currently diagnosed based on patient history only. We have developed a test method which measures qualitative olfactory function based on the odors of the Sniffin’ Sticks Identification subtest. The newly developed test is called Sniffin’ Sticks Parosmia Test (SSParoT). SSParoT uses hedonic estimates of two oppositely valenced odors (pleasant and unpleasant) to assess hedonic range (HR) and hedonic direction (HD), which represent qualitative olfactory perception. HR is defined as the perceivable hedonic distance between two oppositely valenced odors, while HD serves as an indicator for overall hedonic perception of odors. This multicenter study enrolled a total of 162 normosmic subjects in four consecutive experiments. Cluster analysis was used to group odors from the 16-item Sniffin’ Sticks Identification test and 24-additional odors into clusters with distinct hedonic properties. Eleven odor pairs were found to be suitable for estimation of HR and HD. Analysis showed agreement between test–retest sessions for all odor pairs. SSparoT might emerge as a valuable tool to assess qualitative olfactory function in health and disease.

A Systematic Framework for Olfactory Bulb Signal Transformations

We describe an integrated theory of olfactory systems operation that incorporates experimental findings across scales, stages, and methods of analysis into a common framework. In particular, we consider the multiple stages of olfactory signal processing as a collective system, in which each stage samples selectively from its antecedents. We propose that, following the signal conditioning operations of the nasal epithelium and glomerular-layer circuitry, the plastic external plexiform layer of the olfactory bulb effects a process of category learning-the basis for extracting meaningful, quasi-discrete odor representations from the metric space of undifferentiated olfactory quality. Moreover, this early categorization process also resolves the foundational problem of how odors of interest can be recognized in the presence of strong competitive interference from simultaneously encountered background odorants. This problem is fundamentally constraining on early-stage olfactory encoding strategies and must be resolved if these strategies and their underlying mechanisms are to be understood. Multiscale general theories of olfactory systems operation are essential in order to leverage the analytical advantages of engineered approaches together with our expanding capacity to interrogate biological systems.

Encoding the Odor of Cigarette Smoke

The encoding of odors is believed to begin as a combinatorial code consisting of distinct patterns of responses from odorant receptors (ORs), trace-amine associated receptors (TAARs), or both. To determine how specific response patterns arise requires detecting patterns in vivo and understanding how the components of an odor, which are nearly always mixtures of odorants, give rise to parts of the pattern. Cigarette smoke, a common and clinically relevant odor consisting of >400 odorants, evokes responses from 144 ORs and 3 TAARs in freely behaving male and female mice, the first example of in vivo responses of both ORs and TAARs to an odor. As expected, a simplified artificial mimic of cigarette smoke odor tested at low concentration to identify highly sensitive receptors evokes responses from four ORs, all also responsive to cigarette smoke. Human subjects of either sex identify 1-pentanethiol as the odorant most critical for perception of the artificial mimic; and in mice the OR response patterns to these two odors are significantly similar. Fifty-eight ORs respond to the headspace above 25% 1-pentanethiol, including 9 ORs responsive to cigarette smoke. The response patterns to both cigarette smoke and 1-pentanethiol have strongly responsive ORs spread widely across OR sequence diversity, consistent with most other combinatorial codes previously measured in vivo The encoding of cigarette smoke is accomplished by a broad receptor response pattern, and 1-pentanethiol is responsible for a small subset of the responsive ORs in this combinatorial code.SIGNIFICANCE STATEMENT Complex odors are usually perceived as distinct odor objects. Cigarette smoke is the first complex odor whose in vivo receptor response pattern has been measured. It is also the first pattern shown to include responses from both odorant receptors and trace-amine associated receptors, confirming that the encoding of complex odors can be enriched by signals coming through both families of receptors. Measures of human perception and mouse receptor physiology agree that 1-pentanethiol is a critical component of a simplified odorant mixture designed to mimic cigarette smoke odor. Its receptor response pattern helps to link those of the artificial mimic and real cigarette smoke, consistent with expectations about perceptual similarity arising from shared elements in receptor response patterns.

Encoding the Odor of Cigarette Smoke

The encoding of odors is believed to begin as a combinatorial code consisting of distinct patterns of responses from odorant receptors (ORs), trace-amine associated receptors (TAARs), or both. To determine how specific response patterns arise requires detecting patterns in vivo and understanding how the components of an odor, which are nearly always mixtures of odorants, give rise to parts of the pattern. Cigarette smoke, a common and clinically relevant odor consisting of >400 odorants, evokes responses from 144 ORs and 3 TAARs in freely behaving male and female mice, the first example of in vivo responses of both ORs and TAARs to an odor. As expected, a simplified artificial mimic of cigarette smoke odor tested at low concentration to identify highly sensitive receptors evokes responses from four ORs, all also responsive to cigarette smoke. Human subjects of either sex identify 1-pentanethiol as the odorant most critical for perception of the artificial mimic; and in mice the OR response patterns to these two odors are significantly similar. Fifty-eight ORs respond to the headspace above 25% 1-pentanethiol, including 9 ORs responsive to cigarette smoke. The response patterns to both cigarette smoke and 1-pentanethiol have strongly responsive ORs spread widely across OR sequence diversity, consistent with most other combinatorial codes previously measured in vivo The encoding of cigarette smoke is accomplished by a broad receptor response pattern, and 1-pentanethiol is responsible for a small subset of the responsive ORs in this combinatorial code.SIGNIFICANCE STATEMENT Complex odors are usually perceived as distinct odor objects. Cigarette smoke is the first complex odor whose in vivo receptor response pattern has been measured. It is also the first pattern shown to include responses from both odorant receptors and trace-amine associated receptors, confirming that the encoding of complex odors can be enriched by signals coming through both families of receptors. Measures of human perception and mouse receptor physiology agree that 1-pentanethiol is a critical component of a simplified odorant mixture designed to mimic cigarette smoke odor. Its receptor response pattern helps to link those of the artificial mimic and real cigarette smoke, consistent with expectations about perceptual similarity arising from shared elements in receptor response patterns.

Subpopulations of Projection Neurons in the Olfactory Bulb

Generation of neuronal diversity is a biological strategy widely used in the brain to process complex information. The olfactory bulb is the first relay station of olfactory information in the vertebrate central nervous system. In the olfactory bulb, axons of the olfactory sensory neurons form synapses with dendrites of projection neurons that transmit the olfactory information to the olfactory cortex. Historically, the olfactory bulb projection neurons have been classified into two populations, mitral cells and tufted cells. The somata of these cells are distinctly segregated within the layers of the olfactory bulb; the mitral cells are located in the mitral cell layer while the tufted cells are found in the external plexiform layer. Although mitral and tufted cells share many morphological, biophysical, and molecular characteristics, they differ in soma size, projection patterns of their dendrites and axons, and odor responses. In addition, tufted cells are further subclassified based on the relative depth of their somata location in the external plexiform layer. Evidence suggests that different types of tufted cells have distinct cellular properties and play different roles in olfactory information processing. Therefore, mitral and different types of tufted cells are considered as starting points for parallel pathways of olfactory information processing in the brain. Moreover, recent studies suggest that mitral cells also consist of heterogeneous subpopulations with different cellular properties despite the fact that the mitral cell layer is a single-cell layer. In this review, we first compare the morphology of projection neurons in the olfactory bulb of different vertebrate species. Next, we explore the similarities and differences among subpopulations of projection neurons in the rodent olfactory bulb. We also discuss the timing of neurogenesis as a factor for the generation of projection neuron heterogeneity in the olfactory bulb. Knowledge about the subpopulations of olfactory bulb projection neurons will contribute to a better understanding of the complex olfactory information processing in higher brain regions.

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.