Categorical dimensions of human odor descriptor space revealed by non-negative matrix factorization

The poetry of senses: exploring semantic mediation in timbre-aroma correspondences

Cross-modal correspondences between audition and olfaction have received relatively less attention compared to other modality pairs. This study expands on previous work regarding timbre-aroma correspondences by examining the semantic mediation hypothesis, according to which cross-modal correspondences may be partly explained by the existence of common semantic qualities. In a behavioral experiment, 26 musically trained participants rated 26 complex synthetic tones and 12 aromatic stimuli across two separate blocks using a common set of semantic scales. The analysis of semantic variables identified a largely consistent organization for both modalities, condensing into three prominent clusters: [bright, fresh, sweet], [sharp, metallic], and [full, rich, warm]. Furthermore, distances between stimuli derived from semantic ratings and optimized through a genetic algorithm exhibited a strong correlation with previously estimated ground-truth distances of direct cross-modal associations. Additionally, the stimulus configuration within the semantic space generated through Multidimensional Scaling analysis exhibited notable commonalities with the organization of stimuli derived from direct timbre-aroma correspondences. Overall, this study provides compelling evidence that semantic mediation plays a significant role in shaping cross-modal correspondences between auditory and olfactory stimuli, paving the way for further exploration of the underlying semantic dimensions that connect these two modalities.

Automatic scent creation by cheminformatics method

The sense of smell is fundamental for various aspects of human existence including the flavor perception, environmental awareness, and emotional impact. However, unlike other senses, it has not been digitized. Its digitalization faces challenges such as the lack of reliable odor sensing technology or the precise scent delivery through olfactory displays. Its subjective nature and context dependence add complexity to the process. Moreover, the method of converting odors to digital information remains unclear. This work focuses on one of the most challenging aspects of digital olfaction: automatic scent creation. We propose a method that automatically creates a desired odor profile with the addition of one specific odor descriptor. It is based on a deep neural network that predicts odor descriptors from the multidimensional sensing data, such as mass spectra and an odor reproduction technique using odor components. The results demonstrate that the proposed method can successfully create a scent with the desired odor profile and that its performance depends on the accuracy of the underlying odor predicting method. This opens up the possibility of automatic scent creation, allowing for the presentation of scents with specific odor profiles with an olfactory display.

Food odour perception and affective response in Virtual spacecraft and microgravity body posture (1-G) - Potential ground-based simulations

This study investigates food odour perception and affective response within a virtually simulated spacecraft environment, with links to the volatile composition of odours. Healthy participants (n = 44) between the ages of 18-39 years rated the intensity of eight food odours in two simulated space environments for comparison, a 'microgravity' posture (MicroG Posture; physical) and Virtual Reality (VR; visual-spatial cues) simulation of a spacecraft. Results indicate that these methods yield different outcomes. Particularly, odour intensity perception was significantly higher in VR compared to the MicroG Posture for all odours (p < 0.05), except lemongrass. Moreover, individual differences in odour sensitivity were observed, with low-sensitive individuals (n = 14) perceiving stronger almond odour (p < 0.001) and highly sensitive individuals (n = 29) perceiving stronger vinegar odour (p = 0.003) in VR. Emotional dimensions of valence and arousal were also significantly higher (p < 0.001) in VR, while stress response remained low across contexts (all p > 0.05). While emotional and stress responses did not generally affect odour intensity perception, valence was positively correlated with almond and vinegar odour perception, while stress was negatively correlated with vinegar odour perception. These findings suggest that odour perception and affective response may vary in virtual space contexts, with certain individuals exhibiting sensitivity to specific odours due to their unique flavour profiles. This highlights how confined, cluttered environments, reminiscent of space conditions, affect sensory responses to food, with implications for personalised dietary interventions and improved well-being in similar populations.

Olfactory training with four and eight odors: comparison with clinical testing and olfactory bulb volumetrics

PURPOSE

Post-infectious olfactory dysfunction (PIOD) is one of the most common causes of olfactory impairment but has limited treatment options. Recently, olfactory training (OT) has been considered an effective treatment method; however, several questions have arisen regarding its optimal scheme. The aim of this study was to assess whether an OT scheme with 8 odors is more effective than the classic OT scheme with 4 odors by comparing psychophysical test results and olfactory bulb (OB) volumetrics.

METHODS

In this prospective cohort study, 72 patients with PIOD were included. The patients followed either the classic 4-odor OT scheme (COT; n = 34 patients) or an extended 8-odor scheme (EOT; n = 38 patients) for 16 weeks. All patients underwent olfactory testing with a Sniffin'Sticks battery test at 0, 8, and 16 weeks. Of the patients, 38 underwent brain magnetic resonance imaging for OB volumetric assessment before and after treatment.

RESULTS

The comparison of the olfactory test results did not show any significant difference between the two study groups, in agreement with the OB volumetrics. The convex OB showed better test results than the non-convex OB, with significantly better improvement after treatment regardless of OT type. The EOT group presented significantly better adherence than the COT group.

CONCLUSION

The number of odors did not appear to play a significant role in the effect of the OT. However, the training scheme with more than four odors showed better adherence among the patients in a long-term treatment plan. The shape of the OB may have prognostic value in clinical assessment and warrants further investigation.

Conceptual Spaces for Conceptual Engineering? Feminism as a Case Study

Recently, there has been much research into conceptual engineering in connection with feminist inquiry and activism, most notably involving gender issues, but also sexism and misogyny. Our paper contributes to this research by explicating, in a principled manner, a series of other concepts important for feminist research and activism, to wit, feminist political identity terms. More specifically, we show how the popular Conceptual Spaces Framework (CSF) can be used to identify and regiment concepts that are central to feminist research, focusing especially on feminism in France. According to the CSF, concepts can be represented geometrically, as regions in similarity spaces. A particular strength of the CSF framework is its empirically-focused methodology, which allows researchers to infer the boundaries of concepts from empirical data, thus eliminating the need to strongly rely on intuitions about meanings. This is shown to be especially valuable for the explication of concepts relating to feminist political identity, given that the intuitions of feminist scholars and activists about what would appear to be core concepts in the area tend to be poorly aligned or even conflicting. We report the results from an empirical categorization study conducted among French feminists and show how they support the view that the CSF can contribute to both the conceptual engineering project and our understanding of the structure of social reality.

Orthonasal olfactory influences on consumer food behaviour

It is often suggested in the popular press that food chains deliberately introduce enticing product aromas into (and in the immediate vicinity of) their premises in order to attract customers. However, despite the widespread use of odours in the field of sensory marketing, laboratory research suggests that their effectiveness in modulating people's food behaviours depends on a range of contextual factors. Given the evidence that has been published to date, only under a subset of conditions is there likely to be a measurable effect of the presence of ambient odours on people's food attitudes and choices. This narrative historical review summarizes the various ways in which food odours appear to bias people's food preferences (appetite) and food choices (food consumption and purchase). Emphasis is placed on those experimental studies that have been designed to investigate how the characteristics of the olfactory stimuli (e.g., the congruency between the olfactory cues and the foods, intensity and duration of exposure to odours, and taste properties of odours) modulate the effects of olfactory cues on food behaviour. The review also explores the moderating roles of individual differences, such as dietary restraint, Body Mass Index (BMI), genetic and cultural differences in odour sensitivity and perception. Ultimately, following a review of empirical studies on food-related olfaction, current approaches in scent marketing are discussed and a research agenda is proposed to help encourage further studies on the effective application of scents in promoting healthy foods.

Developing human olfactory network and exploring olfactory receptor-odorant interaction

The Olfactory receptor (OR)-odorant interactions are perplexed. ORs can bind to structurally diverse odorants associated with one or more odor percepts. Various attempts have been made to understand the intricacies of OR-odorant interaction. In this study, experimentally documented OR-odorant interactions are investigated comprehensively to; (a) suggest potential odor percepts for ORs based on the OR-OR network; (b) determine how odorants interacting with specific ORs differ in terms of inherent pharmacophoric features and molecular properties, (c) identify molecular interactions that explained OR-odorant interactions of selective ORs; and (d) predict the probable role of ORs other than olfaction. Human olfactory receptor network (hORnet) is developed to study possible odor percepts for ORs. We identified six molecular properties which showed variation and significant patterns to differentiate odorants binding with five ORs. The pharmacophore analysis revealed that odorants subset of five ORs follow similar pharmacophore hypothesis, (one hydrogen acceptor and two hydrophobic regions) but differ in terms of distance and orientation of pharmacophoric features. To ascertain the binding site residues and key interactions between the selected ORs and their interacting odorants, 3D-structure modelling, docking and molecular dynamics studies were carried out. Lastly, the potential role of ORs beyond olfaction is explored. A human OR-OR network was developed to suggest possible odor percepts for ORs using empirically proven OR-odorant interactions. We sought to find out significant characteristics, molecular properties, and molecular interactions that could explain OR-odorant interactions and add to the understanding of the complex issue of odor perception.Communicated by Ramaswamy H. Sarma.

Similarity-based reasoning in conceptual spaces

Whereas the validity of deductive inferences can be characterized in terms of their logical form, this is not true for all inferences that appear pre-theoretically valid. Nonetheless, philosophers have argued that at least some of those inferences-sometimes called "similarity-based inferences" -can be given a formal treatment with the help of similarity spaces, which are mathematical spaces purporting to represent human similarity judgments. In these inferences, we conclude that a given property pertains to a category of items on the grounds that the same property pertains to a similar category of items. We look at a specific proposal according to which the strength of such inferences is a function of the distance, as measured in the appropriate similarity space, between the category referenced in the premise and the category referenced in the conclusion. We report the outcomes of three studies that all support the said proposal.

High-precision mapping reveals the structure of odor coding in the human brain

Odor perception is inherently subjective. Previous work has shown that odorous molecules evoke distributed activity patterns in olfactory cortices, but how these patterns map on to subjective odor percepts remains unclear. In the present study, we collected neuroimaging responses to 160 odors from 3 individual subjects (18 h per subject) to probe the neural coding scheme underlying idiosyncratic odor perception. We found that activity in the orbitofrontal cortex (OFC) represents the fine-grained perceptual identity of odors over and above coarsely defined percepts, whereas this difference is less pronounced in the piriform cortex (PirC) and amygdala. Furthermore, the implementation of perceptual encoding models enabled us to predict olfactory functional magnetic resonance imaging responses to new odors, revealing that the dimensionality of the encoded perceptual spaces increases from the PirC to the OFC. Whereas encoding of lower-order dimensions generalizes across subjects, encoding of higher-order dimensions is idiosyncratic. These results provide new insights into cortical mechanisms of odor coding and suggest that subjective olfactory percepts reside in the OFC.

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).

Physicochemical features partially explain olfactory crossmodal correspondences

During the olfactory perception process, our olfactory receptors are thought to recognize specific chemical features. These features may contribute towards explaining our crossmodal perception. The physicochemical features of odors can be extracted using an array of gas sensors, also known as an electronic nose. The present study investigates the role that the physicochemical features of olfactory stimuli play in explaining the nature and origin of olfactory crossmodal correspondences, which is a consistently overlooked aspect of prior work. Here, we answer the question of whether the physicochemical features of odors contribute towards explaining olfactory crossmodal correspondences and by how much. We found a similarity of 49% between the perceptual and the physicochemical spaces of our odors. All of our explored crossmodal correspondences namely, the angularity of shapes, smoothness of textures, perceived pleasantness, pitch, and colors have significant predictors for various physicochemical features, including aspects of intensity and odor quality. While it is generally recognized that olfactory perception is strongly shaped by context, experience, and learning, our findings show that a link, albeit small (6-23%), exists between olfactory crossmodal correspondences and their underlying physicochemical features.

Metabolic activity organizes olfactory representations

Hearing and vision sensory systems are tuned to the natural statistics of acoustic and electromagnetic energy on earth and are evolved to be sensitive in ethologically relevant ranges. But what are the natural statistics of odors, and how do olfactory systems exploit them? Dissecting an accurate machine learning model (Lee et al., 2022) for human odor perception, we find a computable representation for odor at the molecular level that can predict the odor-evoked receptor, neural, and behavioral responses of nearly all terrestrial organisms studied in olfactory neuroscience. Using this olfactory representation (principal odor map [POM]), we find that odorous compounds with similar POM representations are more likely to co-occur within a substance and be metabolically closely related; metabolic reaction sequences (Caspi et al., 2014) also follow smooth paths in POM despite large jumps in molecular structure. Just as the brain's visual representations have evolved around the natural statistics of light and shapes, the natural statistics of metabolism appear to shape the brain's representation of the olfactory world.

Efficacy of Combined Visual-Olfactory Training With Patient-Preferred Scents as Treatment for Patients With COVID-19 Resultant Olfactory Loss: A Randomized Clinical Trial

Importance

The number of olfactory dysfunction cases has increased dramatically because of the COVID-19 pandemic. Identifying therapies that aid and accelerate recovery is essential.

Objective

To determine the efficacy of bimodal visual-olfactory training and patient-preferred scents vs unimodal olfactory training and physician-assigned scents in COVID-19 olfactory loss.

Design, Setting, and Participants

This was a randomized, single-blinded trial with a 2-by-2 factorial design (bimodal, patient preferred; unimodal, physician assigned; bimodal, physician assigned; unimodal, patient preferred) and an independent control group. Enrollment occurred from February 1 to May 27, 2021. Participants were adults 18 to 71 years old with current olfactory loss defined as University of Pennsylvania Smell Identification Test (UPSIT) score less than 34 for men and less than 35 for women and duration of 3 months or longer. Olfactory loss was initially diagnosed within 2 weeks of COVID-19 infection.

Interventions

Participants sniffed 4 essential oils for 15 seconds with a 30-second rest in between odors for 3 months. Participants in the physician-assigned odor arms trained with rose, lemon, eucalyptus, and clove. Participants randomized to the patient-preferred arms chose 4 of 24 available scents. If assigned to the bimodal arm, participants were shown digital images of the essential oil they were smelling.

Main Outcomes and Measures

The primary end point was postintervention change in UPSIT score from baseline; measures used were the UPSIT (validated, objective psychometric test of olfaction), Clinical Global Impressions Impression-Improvement (CGI-I; self-report improvement scale), and Olfactory Dysfunction Outcomes Rating (ODOR; olfaction-related quality-of-life questionnaire).

Results

Among the 275 enrolled participants, the mean (SD) age was 41 (12) years, and 236 (86%) were female. The change in UPSIT scores preintervention to postintervention was similar between the study arms. The marginal mean difference for change in UPSIT scores preintervention to postintervention between participants randomized to patient-preferred vs physician-assigned olfactory training was 0.73 (95% CI, -1.10 to 2.56), and between participants randomized to bimodal vs unimodal olfactory training was 1.10 (95% CI, -2.92 to 0.74). Five (24%) participants in the control arm had clinically important improvement on UPSIT compared with 18 (53%) in the bimodal, patient-preferred arm for a difference of 29% (95% CI, 4%-54%). Four (19%) participants in the control group self-reported improvement on CGI-I compared with 12 (35%) in the bimodal, patient-preferred arm for a difference of 16% (95% CI, -7% to 39%). The mean change in ODOR score preintervention to postintervention was 11.6 points (95% CI, 9.2-13.9), which was not deemed clinically important nor significantly different between arms.

Conclusions and Relevance

Based on the change in UPSIT scores, this randomized clinical trial did not show any difference between intervention arms, but when exploring within-patient change in UPSIT as well as self-reported impression of improvement, active interventions were associated with larger improvement than controls with a potential advantage of bimodal intervention. While not definitive, these results suggest that patients with COVID-19 olfactory loss may benefit from bimodal visual-olfactory training with patient-preferred scents.

Trial Registration

ClinicalTrials.gov Identifier: NCT04710394.

The Semantic Organization of the English Odor Vocabulary

The vocabulary for describing odors in English natural language is not well understood, as prior studies of odor descriptions have often relied on preselected descriptors and odor ratings. Here, we present a data-driven approach that automatically identifies English odor descriptors based on their degree of olfactory association, and derive their semantic organization from their distributions in natural texts, using a distributional-semantic language model. We identify 243 descriptors that are much more strongly associated with olfaction than English words in general. We then derive the semantic organization of these olfactory descriptors, and find that it is captured by four clusters that we name Offensive, Malodorous, Fragrant, and Edible. The semantic space derived from our model primarily differentiates descriptors in terms of pleasantness and edibility along which our four clusters are positioned, and is similar to a space derived from perceptual data. The semantic organization of odor vocabulary can thus be mapped using natural language data (e.g., online text), without the limitations of odor-perceptual data and preselected descriptors. Our method may thus facilitate research on olfaction, a sensory system known to often elude verbal description.

Extraction of sensing data for desired scent impressions using mass spectra of odorant molecules

Most of the olfactory perception works focused on forward prediction of odor impression, for example, given an odorant’s molecular structure parameters or the sensing data predict its odor impression. So far, mapping of mass spectrum of odorant molecules into the odor perception space (binary or continuous sensory space) has been successfully performed. However, it is difficult to predict odorant’s sensing data associated with binary odor descriptors (e.g., minty, peach, vanilla etc.). In this study, we have proposed a method to extract the corresponding sensing data (mass spectrum as sensing data) for a desired scent impression although one-to-one relationships are not usually guaranteed. Our target is to extract the sensing data for a given odor descriptor that will help perfumers to create scent. This study is first report for predicting sensing data for a given binary odor descriptor.

Searching for perceptual similarity within, and between, the (chemical) senses

In this narrative historical review, I want to take a closer look at the concept of perceptual similarity both as it applies within, and between, the chemical senses (specifically taste and smell). The discussion is linked to issues of affective similarity and connotative meaning. The relation between intramodal and crossmodal judgments of perceptual similarity, and the putatively special status of those odorants that happen to take on taste qualities will also be discussed. An important distinction is drawn between the interrelated, though sometimes distinct, notions of perceptual similarity and crossmodal congruency, specifically as they relate to the comparison of chemosensory stimuli. Such phenomena are often referred to as crossmodal correspondences, or by others (incorrectly in my view), as a kind of ubiquitous synesthesia.

COVID-19 Induced Taste Dysfunction and Recovery: Association with Smell Dysfunction and Oral Health Behaviour

Background and Objectives: Disruption to taste and smell are common symptoms of COVID-19 infection. The current literature overlooks taste symptoms and tends to focus on the sense of smell. Persisting cases (>28 days) of taste dysfunction are increasingly recognised as a major future healthcare challenge. This study focuses on the severity and recovery of COVID-19 induced taste loss and association with olfactory symptoms, lifestyle and oral health factors. Materials and Methods: This study was a cross-sectional survey comparing 182 rapid taste recovery participants (≤28 days) with 47 participants with prolonged taste recovery >28 days. Analyses of taste loss in association with smell loss, age, sex, illness severity, diet, BMI, vitamin-D supplementation, antidepressants, alcohol use, smoking, brushing frequency, flossing, missing teeth, appliances and number of dental restorations were conducted. Differences in the severity of the loss of sour, sweet, salt, bitter and umami tastes were explored. Results: Both the severity and the duration of taste and smell loss were closely correlated (p < 0.001). Salt taste was significantly less affected than all other taste qualities (p < 0.001). Persisting taste loss was associated with older age (mean ± 95% CI = 31.73 ± 1.23 years vs. 36.66 ± 3.59 years, p < 0.001) and reduced likelihood of using floss (odds ratio ± 95% CI = 2.22 (1.15−4.25), p = 0.047). Conclusions: Smell and taste loss in COVID-19 are closely related, although a minority of individuals can experience taste or smell dysfunction in the absence of the other. The taste of salt may be less severely affected than other taste qualities and future work exploring this finding objectively is indicated. The association of flossing with rapid taste recovery adds to the growing evidence of a link between good periodontal health and favourable COVID-19 outcomes.

Spatiotemporal dynamics of odor representations in the human brain revealed by EEG decoding

To elucidate when and where in the brain different aspects of odor perception emerge, we decoded odors from an electroencephalogram and associated the results with perception and source activities. The odor information was decoded 100 ms after odor onset at the earliest, with its signal sources estimated in and around the olfactory areas. The neural representation of odor unpleasantness emerged 300 ms after odor onset, followed by pleasantness and perceived quality at 500 ms. During this time, brain regions representing odor information spread rapidly from the olfactory areas to regions associated with emotional, semantic, and memory processing. The results suggested that odor perception emerges through computations in these areas, with different perceptual aspects having different spatiotemporal dynamics.

How the human brain translates olfactory inputs into diverse perceptions, from pleasurable floral smells to sickening smells of decay, is one of the fundamental questions in olfaction. To examine how different aspects of olfactory perception emerge in space and time in the human brain, we performed time-resolved multivariate pattern analysis of scalp-recorded electroencephalogram responses to 10 perceptually diverse odors and associated the resulting decoding accuracies with perception and source activities. Mean decoding accuracies of odors exceeded the chance level 100 ms after odor onset and reached maxima at 350 ms. The result suggests that the neural representations of individual odors were maximally separated at 350 ms. Perceptual representations emerged following the decoding peak: unipolar unpleasantness (neutral to unpleasant) from 300 ms, and pleasantness (neutral to pleasant) and perceptual quality (applicability to verbal descriptors such as “fruity” or “flowery”) from 500 ms after odor onset, with all these perceptual representations reaching their maxima after 600 ms. A source estimation showed that the areas representing the odor information, estimated based on the decoding accuracies, were localized in and around the primary and secondary olfactory areas at 100 to 350 ms after odor onset. Odor representations then expanded into larger areas associated with emotional, semantic, and memory processing, with the activities of these later areas being significantly associated with perception. These results suggest that initial odor information coded in the olfactory areas (<350 ms) evolves into their perceptual realizations (300 to >600 ms) through computations in widely distributed cortical regions, with different perceptual aspects having different spatiotemporal dynamics.

Long-Lasting Olfactory Dysfunction in Hospital Workers Due to COVID-19: Prevalence, Clinical Characteristics, and Most Affected Odorants

Hospital workers have increased exposure risk of healthcare-associated infections due to the frontline nature of their work. Olfactory dysfunction is highly prevalent. The objectives for this investigation are to study the prevalence of long-lasting olfactory dysfunction associated with COVID-19 infection in hospital workers during the first pandemic wave, to identify clinical characteristics and associated symptomatology, and to analyze how many patients with COVID-19 infection had developed olfactory dysfunction during infection and maintained a reduced olfactory function for approximately 10 weeks after diagnosis. Between June and July of 2020, a cross-sectional study was carried out at the Hospital Central de la Cruz Roja San José and Santa Adela in Madrid, Spain. One hundred sixty-four participants were included, of which 110 were patient-facing healthcare staff and 54 were non-patient-facing healthcare staff. Participants were split into three groups, according to COVID-19 diagnosis and presence of COVID-19 related olfactory symptomatology. Participants were asked to complete a structured online questionnaire along with Sniffin' Stick Olfactory Test measurements. In this study, 88 participants were confirmed for COVID-19 infection, 59 of those participants also reported olfactory symptomatology. The prevalence of COVID-19 infection was 11.35%, and the prevalence for olfactory dysfunction was 67.05%. Olfactory dysfunction associated with COVID-19 infection leads to long-lasting olfactory loss. Objective assessment with Sniffin' Stick Olfactory Test points to odor identification as the most affected process. Lemon, liquorice, solvent, and rose are the odors that are worst recognized. Mint, banana, solvent, garlic, coffee, and pineapple, although they are identified, are perceived with less intensity. The findings of this study confirmed a high prevalence of SARS-CoV-2 infection among the hospital workers.

Development and Validation of a Novel At-home Smell Assessment

IMPORTANCE

Current tools for diagnosis of olfactory dysfunction (OD) are costly, time-consuming, and often require clinician administration.

OBJECTIVE

To develop and validate a simple screening assessment for OD using common household items.

DESIGN, SETTING, AND PARTICIPANTS

This fully virtual diagnostic study included adults with self-reported OD from any cause throughout the US. Data were collected from December 2020 to April 2021 and analyzed from May 2021 to July 2021.

MAIN OUTCOMES AND MEASURES

Participants with self-reported olfactory dysfunction took a survey assessing smell perception of 45 household items and completed the Clinical Global Impression-Severity (CGI-S) smell questionnaire, the University of Pennsylvania Smell Identification Test (UPSIT), and the 36-item Short Form Survey (SF-36). Psychometric and clinimetric analyses were used to consolidate 45 household items into 2 short Novel Anosmia Screening at Leisure (NASAL) assessments, NASAL-7 (range, 0-14; lower score indicating greater anosmia) and NASAL-3 (range, 0-6; lower score indicating greater anosmia).

RESULTS

A total of 115 participants were included in the study, with a median (range) age of 42 (19-70) years, 92 (80%) women, and 97 (84%) White individuals. There was a moderate correlation between the UPSIT and NASAL-7 scores and NASAL-3 scores (NASAL-7: ρ = 0.484; NASAL-3: ρ = 0.404). Both NASAL-7 and NASAL-3 had moderate accuracy in identifying participants with anosmia as defined by UPSIT (NASAL-7 area under the receiver operating curve [AUC], 0.706; 95% CI, 0.551-0.862; NASAL-3 AUC, 0.658; 95% CI, 0.503-0.814). Scoring 7 or less on the NASAL-7 had 70% (95% CI, 48%-86%) sensitivity and 53% (95% CI, 43%-63%) specificity in discriminating participants with anosmia from participants without. Scoring 2 or less on the NASAL-3 had 57% (95% CI, 36%-76%) sensitivity and 78% (95% CI, 69%-85%) specificity in discriminating participants with anosmia from participants without. There was moderate agreement between UPSIT-defined OD categories and those defined by NASAL-7 (weighted κ = 0.496; 95% CI, 0.343-0.649) and those defined by NASAL-3 (weighted κ = 0.365; 95% CI, 0.187-0.543). The agreement with self-reported severity of olfactory dysfunction as measured by CGI-S and the NASAL-7 and NASAL-3 was moderate, with a weighted κ of 0.590 (95% CI, 0.474-0.707) for the NASAL-7 and 0.597 (95% CI, 0.481-0.712) for the NASAL-3.

CONCLUSION AND RELEVANCE

The findings of this diagnostic study suggest that NASAL-7 and NASAL-3, inexpensive and brief patient-reported assessments, can be used to identify individuals with OD. As the burden of COVID-19-associated OD increases, these assessments may prove beneficial as screening and diagnostic tools. Future work will explore whether the NASAL assessments are sensitive to change and how much of a change is clinically important.

Effects of High Hydrostatic Pressure Combined with Vacuum-Freeze Drying on the Aroma-Active Compounds in Blended Pumpkin, Mango, and Jujube Juice

A combination process of completely non-thermal processing methods involving high hydrostatic pressure (HHP) and vacuum-freeze drying (VFD) for producing a new snack from fruit and vegetable blends was developed, and the effect of the process on flavor quality was investigated. The HHP-VFD treatment did not significantly reduce volatile compound contents compared to single HHP or VFD. Gas chromatography-olfactometry showed that HHP-VFD raised the contents of floral-like volatile compounds (e.g., β-ionone) compared to the untreated sample. Sensory evaluation analysis confirmed that the overall liking was unchanged after the HHP-VFD treatment. The HHP-VFD combined treatment is effective in maintaining the flavor and extending shelf life, and is convenient for the portability and transportation of ready-to-drink juice.

Odour detection in children and young people with profound intellectual and multiple disabilities

BACKGROUND

Olfaction provides information on very important dimensions of the environment; however the olfactory abilities of children and young people with profound intellectual and multiple disabilities (PIMD) remain largely unknown. This within-subjects study explores olfactory detection abilities in children with PIMD.

METHOD

Twenty-two children and young people with PIMD (7-18 years) were presented with 18 medium intensity odours and an odourless control stimulus. Odorants were presented one by one in a randomised order. The neutral stimulus was presented prior to each odorant. Participants' responses were measured using 21 behavioural indicators.

RESULTS

Results show that participants make a clear distinction between odorous and neutral conditions, between food and non-food, and between pleasant and unpleasant odours. The detection abilities are manifested by several behaviours, in particular by the duration of the head alignment on the odorant.

CONCLUSIONS

This study shows that participants detect the stimuli and act differently depending on the category.

OlfactionBase: a repository to explore odors, odorants, olfactory receptors and odorant-receptor interactions

Olfaction is a multi-stage process that initiates with the odorants entering the nose and terminates with the brain recognizing the odor associated with the odorant. In a very intricate way, the process incorporates various components functioning together and in synchronization. OlfactionBase is a free, open-access web server that aims to bring together knowledge about many aspects of the olfaction mechanism in one place. OlfactionBase contains detailed information of components like odors, odorants, and odorless compounds with physicochemical and ADMET properties, olfactory receptors (ORs), odorant- and pheromone binding proteins, OR-odorant interactions in Human and Mus musculus. The dynamic, user-friendly interface of the resource facilitates exploration of different entities: finding chemical compounds having desired odor, finding odorants associated with OR, associating chemical features with odor and OR, finding sequence information of ORs and related proteins. Finally, the data in OlfactionBase on odors, odorants, olfactory receptors, human and mouse OR-odorant pairs, and other associated proteins could aid in the inference and improved understanding of odor perception, which might provide new insights into the mechanism underlying olfaction. The OlfactionBase is available at https://bioserver.iiita.ac.in/olfactionbase/.

Evaluation of the Impact of Different Natural Zeolite Treatments on the Capacity of Eliminating/Reducing Odors and Toxic Compounds

Unlike odorants that mask odors, natural zeolite acts as a molecular sieve that captures and eliminates odors. Different treatment methods can be applied to influence the properties of the natural zeolites. To enhance the odor adsorption capacities of the natural zeolite two types of treatment methods were applied: chemical (acid, basic) and thermal. The initial natural zeolites and the activated one were characterized using X-ray diffraction (XRD) and scanning electron microscope (SEM-EDX). Two experiments were performed to establish the odor adsorption capacity of the activated natural zeolites. The best zeolite for the adsorption of humidity, ammonia and hydrogen sulfide was the 1-3 mm zeolite activated through thermal treatment. For the adsorption of PAHs, the best zeolite was the one activated through basic treatment, with an adsorption capacity of 89.6 ng/g.

Deconstructing the mouse olfactory percept through an ethological atlas

Odor perception in non-humans is poorly understood. Here, we generated the most comprehensive mouse olfactory ethological atlas to date, consisting of behavioral responses to a diverse panel of 73 odorants, including 12 at multiple concentrations. These data revealed that mouse behavior is incredibly diverse and changes in response to odorant identity and concentration. Using only behavioral responses observed in other mice, we could predict which of two odorants was presented to a held-out mouse 82% of the time. Considering all 73 possible odorants, we could uniquely identify the target odorant from behavior on the first try 20% of the time and 46% within five attempts. Although mouse behavior is difficult to predict from human perception, they share three fundamental properties: first, odor valence parameters explained the highest variance of olfactory perception. Second, physicochemical properties of odorants can be used to predict the olfactory percept. Third, odorant concentration quantitatively and qualitatively impacts olfactory perception. These results increase our understanding of mouse olfactory behavior and how it compares to human odor perception and provide a template for future comparative studies of olfactory percepts among species.

Parsing Sage and Rosemary in Time: The Machine Learning Race to Crack Olfactory Perception

Color and pitch perception are largely understandable from characteristics of physical stimuli: the wavelengths of light and sound waves, respectively. By contrast, understanding olfactory percepts from odorous stimuli (volatile molecules) is much more challenging. No intuitive set of molecular features is up to the task. Here in Chemical Senses, the Ray lab reports using a predictive modeling framework-first breaking molecular structure into thousands of features and then using this to train a predictive statistical model on a wide range of perceptual descriptors-to create a tool for predicting the odor character of hundreds of thousands of available but previously uncharacterized molecules (Kowalewski et al. 2021). This will allow future investigators to representatively sample the space of odorous molecules as well as identify previously unknown odorants with a target odor character. Here, I put this work into the context of other modeling efforts and highlight the urgent need for large new datasets and transparent benchmarks for the field to make and evaluate modeling breakthroughs, respectively.

A System-Wide Understanding of the Human Olfactory Percept Chemical Space

The fundamental units of olfactory perception are discrete 3D structures of volatile chemicals that each interact with specific subsets of a very large family of hundreds of odorant receptor proteins, in turn activating complex neural circuitry and posing a challenge to understand. We have applied computational approaches to analyze olfactory perceptual space from the perspective of odorant chemical features. We identify physicochemical features associated with ~150 different perceptual descriptors and develop machine-learning models. Validation of predictions shows a high success rate for test set chemicals within a study, as well as across studies more than 30 years apart in time. Due to the high success rates, we are able to map ~150 percepts onto a chemical space of nearly 0.5 million compounds, predicting numerous percept-structure combinations. The chemical structure-to-percept prediction provides a system-level view of human olfaction and opens the door for comprehensive computational discovery of fragrances and flavors.

Categorizing Smells: A Localist Approach

Humans are poorer at identifying smells and communicating about them, compared to other sensory domains. They also cannot easily organize odor sensations in a general conceptual space, where geometric distance could represent how similar or different all odors are. These two generalities are more or less accepted by psychologists, and they are often seen as connected: If there is no conceptual space for odors, then olfactory identification should indeed be poor. We propose here an important revision to this conclusion: We believe that the claim that there is no odor space is true only if by odor space, one means a conceptual space representing all possible odor sensations, in the paradigmatic sense used for instance for color. However, in a less paradigmatic sense, local conceptual spaces representing a given subset of odors do exist. Thus the absence of a global odor space does not warrant the conclusion that there is no olfactory conceptual map at all. Here we show how a localist account provides a new interpretation of experts and cross-cultural categorization studies: Rather than being exceptions to the poor olfactory identification and communication usually seen elsewhere, experts and cross-cultural categorization are here taken to corroborate the existence of local conceptual spaces.

Odor quality profile is partially influenced by verbal cues

Characterizing an odor quality is difficult for humans. Ever-increasing physiological and behavioral studies have characterized odor quality and demonstrated high performance of human odor categorization. However, there are no precise methods for measuring the multidimensional axis of an odor quality. Furthermore, it can be altered by individual experience, even when using existing measurement methods for the multidimensional axis of odor such as odor profiling. It is, therefore, necessary to characterize patterns of odor quality with odor profiling and observe alterations in odor profiles under the influence of subjective rating conditions such as verbal cues. Considering the high performance of human odor categorization, we hypothesized that odor may have specific odor quality that is scarcely altered by verbal cues. We assessed odor responses to isovaleric acid with and without verbal cues and compared the results in each stimulation condition. We found that verbal cues influenced the rating of odor quality descriptors. Verbal cues weakly influenced the odor quality descriptors of high-rated value (upper 25%) compared to odor quality descriptors of low-rated value (lower 75%) by the survey test. Even under different verbal cue conditions, the same odor was classified in the same class when using high-rated odor quality descriptors. Our study suggests that people extract essential odor quality descriptors that represent the odor itself in order to efficiently quantify odor quality.

Development of a Piezoelectric-Based Odor Reproduction System

Odor reproduction, a branch of machine olfaction, is a technology through which a machine represents various odors by blending several odor sources in different proportions and releases them. In this paper, an odor reproduction system is proposed. The system includes an atomization-based odor dispenser using 16 micro-porous piezoelectric transducers. The authors propose the use of an electronic nose combined with a Principal Component Analysis–Linear Discriminant Analysis (PCA–LDA) model to evaluate the effectiveness of the system. The results indicate that the model can be used to evaluate the system.

A Mathematical Approach to Correlating Objective Spectro-Temporal Features of Non-linguistic Sounds With Their Subjective Perceptions in Humans

Non-linguistic sounds (NLSs) are a core feature of our everyday life and many evoke powerful cognitive and emotional outcomes. The subjective perception of NLSs by humans has occasionally been defined for single percepts, e.g., their pleasantness, whereas many NLSs evoke multiple perceptions. There has also been very limited attempt to determine if NLS perceptions are predicted from objective spectro-temporal features. We therefore examined three human perceptions well-established in previous NLS studies ("Complexity," "Pleasantness," and "Familiarity"), and the accuracy of identification, for a large NLS database and related these four measures to objective spectro-temporal NLS features, defined using rigorous mathematical descriptors including stimulus entropic and algorithmic complexity measures, peaks-related measures, fractal dimension estimates, and various spectral measures (mean spectral centroid, power in discrete frequency ranges, harmonicity, spectral flatness, and spectral structure). We mapped the perceptions to the spectro-temporal measures individually and in combinations, using complex multivariate analyses including principal component analyses and agglomerative hierarchical clustering.

Putting prototypes in place

It has recently been proposed that natural concepts are those represented by the cells of an optimally partitioned similarity space. In this proposal, optimal partitioning has been defined in terms of rational design criteria, criteria that a good engineer would adopt if asked to develop a conceptual system. It has been argued, for instance, that convexity should rank high among such criteria. Other criteria concern the possibility of placing prototypes such that they are both similar to the items they represent-each prototype ought to be representative-and dissimilar to each other: the prototypes ought to be contrastive. Parts of this design proposal are already supported by evidence. This paper reports results of a new study meant to address parts still lacking in empirical support. In particular, it presents data concerning color similarity space which indicate that color prototypes are indeed located such that they trade off optimally between being representative and being contrastive.

Neural correlates of sparse coding and dimensionality reduction

Supported by recent computational studies, there is increasing evidence that a wide range of neuronal responses can be understood as an emergent property of nonnegative sparse coding (NSC), an efficient population coding scheme based on dimensionality reduction and sparsity constraints. We review evidence that NSC might be employed by sensory areas to efficiently encode external stimulus spaces, by some associative areas to conjunctively represent multiple behaviorally relevant variables, and possibly by the basal ganglia to coordinate movement. In addition, NSC might provide a useful theoretical framework under which to understand the often complex and nonintuitive response properties of neurons in other brain areas. Although NSC might not apply to all brain areas (for example, motor or executive function areas) the success of NSC-based models, especially in sensory areas, warrants further investigation for neural correlates in other regions.

Accurate prediction of personalized olfactory perception from large-scale chemoinformatic features

Background

The olfactory stimulus-percept problem has been studied for more than a century, yet it is still hard to precisely predict the odor given the large-scale chemoinformatic features of an odorant molecule. A major challenge is that the perceived qualities vary greatly among individuals due to different genetic and cultural backgrounds. Moreover, the combinatorial interactions between multiple odorant receptors and diverse molecules significantly complicate the olfaction prediction. Many attempts have been made to establish structure-odor relationships for intensity and pleasantness, but no models are available to predict the personalized multi-odor attributes of molecules. In this study, we describe our winning algorithm for predicting individual and population perceptual responses to various odorants in the DREAM Olfaction Prediction Challenge.

Results

We find that random forest model consisting of multiple decision trees is well suited to this prediction problem, given the large feature spaces and high variability of perceptual ratings among individuals. Integrating both population and individual perceptions into our model effectively reduces the influence of noise and outliers. By analyzing the importance of each chemical feature, we find that a small set of low- and nondegenerative features is sufficient for accurate prediction.

Conclusions

Our random forest model successfully predicts personalized odor attributes of structurally diverse molecules. This model together with the top discriminative features has the potential to extend our understanding of olfactory perception mechanisms and provide an alternative for rational odorant design.

Cognitive Metaphysics

In recent years philosophers have been interested in the methodology of metaphysics. Most of these developments are related to formal work in logic or physics, often against the backdrop of the Carnap-Quine debate on ontology. Drawing on Quine’s later work, I argue that a psychological or cognitive perspective on metaphysical topics may be a valuable addition to contemporary metametaphysics. The method is illustrated by means of cognitive studies of the notions “identity,” “vagueness,” and “object” and is compared to other extant metametaphysical positions.

Information Olfactation: Harnessing Scent to Convey Data

Olfactory feedback for analytical tasks is a virtually unexplored area in spite of the advantages it offers for information recall, feature identification, and location detection. Here we introduce the concept of information olfactation as the fragrant sibling of information visualization, and discuss how scent can be used to convey data. Building on a review of the human olfactory system and mirroring common visualization practice, we propose olfactory marks, the substrate in which they exist, and their olfactory channels that are available to designers. To exemplify this idea, we present VISCENT: A six-scent stereo olfactory display capable of conveying olfactory glyphs of varying temperature and direction, as well as a corresponding software system that integrates the display with a traditional visualization display. Finally, we present three applications that make use of the viScent system: A 2D graph visualization, a 2D line and point chart, and an immersive analytics graph visualization in 3D virtual reality. We close the paper with a review of possible extensions of viScent and applications of information olfactation for general visualization beyond the examples in this paper.

Pleasantness and trigeminal sensations as salient dimensions in organizing the semantic and physiological spaces of odors

A major issue in human olfaction research is to characterize the main dimensions that organize the space of odors. The present study examines this question and shows that, beside pleasantness, trigeminal sensations, and particularly irritation, play an important role. These results were consistent along two different spaces constructed using semantic description and physiological responses to 105 odorants, smelled and described by human participants. Taken together, these findings suggest that salient trigeminal features, in conjunction with pleasantness, are involved in detecting relevant emotional stimuli, and modify the way organisms categorize smells. These results shed light on the importance of trigeminal sensitivity in the well-established defensive function of olfaction.

Immunomodulatory Properties of Carvone Inhalation and Its Effects on Contextual Fear Memory in Mice

A complex network of interactions exists between the immune, the olfactory, and the central nervous system (CNS). Inhalation of different fragrances can affect immunological reactions in response to an antigen but also may have effects on the CNS and cognitive activity. We performed an exploratory study of the immunomodulatory ability of a series of compounds representing each of the 10 odor categories or clusters described previously. We evaluated the impact of each particular odor on the immune response after immunization with the model antigen ovalbumin in combination with the TLR3 agonist poly I:C. We found that some odors behave as immunostimulatory agents, whereas others might be considered as potential immunosuppressant odors. Interestingly, the immunomodulatory capacity was, in some cases, strain-specific. In particular, one of the fragrances, carvone, was found to be immunostimulatory in BALB/c mice and immunosuppressive in C57BL/6J mice, facilitating or impairing viral clearance, respectively, in a model of a viral infection with a recombinant adenovirus. Importantly, inhalation of the odor improved the memory capacity in BALB/c mice in a fear-conditioning test, while it impaired this same capacity in C57BL/6J mice. The improvement in memory capacity in BALB/c was associated with higher CD3⁺ T cell infiltration into the hippocampus and increased local expression of mRNA coding for IL-1β, TNF-α, and IL-6 cytokines. In contrast, the memory impairment in C57BL/6 was associated with a reduction in CD3 numbers and an increase in IFN-γ. These data suggest an association between the immunomodulatory capacity of smells and their impact on the cognitive functions of the animals. These results highlight the potential of studying odors as therapeutic agents for CNS-related diseases.

Predicting human olfactory perception from chemical features of odor molecules

It is still not possible to predict whether a given molecule will have a perceived odor or what olfactory percept it will produce. We therefore organized the crowd-sourced DREAM Olfaction Prediction Challenge. Using a large olfactory psychophysical data set, teams developed machine-learning algorithms to predict sensory attributes of molecules based on their chemoinformatic features. The resulting models accurately predicted odor intensity and pleasantness and also successfully predicted 8 among 19 rated semantic descriptors ("garlic," "fish," "sweet," "fruit," "burnt," "spices," "flower," and "sour"). Regularized linear models performed nearly as well as random forest-based ones, with a predictive accuracy that closely approaches a key theoretical limit. These models help to predict the perceptual qualities of virtually any molecule with high accuracy and also reverse-engineer the smell of a molecule.

Pattern of Smell Identification Impairment in Alzheimer's Disease

Olfactory dysfunction in general, and impaired odor identification in particular, have been reported in Alzheimer's disease (AD). Olfactory testing may be a useful diagnostic aid for AD, but the types of odor most commonly affected need to be identified. This study aimed to determine pattern and types of odor affected in AD with the goal of improving clinical applicability. 54 outpatients with mild to moderate AD and 40 age and gender-matched non-demented controls (NDC) were tested using British version of University of Pennsylvania Smell Identification Test (UPSIT; Sensonics, Inc., Haddon Heights, NJ) and data analyzed to identify an optimal subset of UPSIT to best differentiate AD patients from controls. AD subjects had significantly lower UPSIT total scores than NDC. Random Forest with backward elimination identified 12 UPSIT items which accurately differentiated AD patients compared to controls (sensitivity, 0.89 and specificity, 0.83, positive predictive value of 0.889, and negative predictive value of 0.833). The 12 smell items found to be most affected in AD subjects reflects important attributes such as safety and food, known to be affected in people with AD and that has the potential to impair activities of daily living. The 12 items of British UPSIT most affected in AD subjects provides a potential brief scale for early detection of AD in clinical settings. Independent replication is needed to validate these findings.

Odor Impression Prediction from Mass Spectra

The sense of smell arises from the perception of odors from chemicals. However, the relationship between the impression of odor and the numerous physicochemical parameters has yet to be understood owing to its complexity. As such, there is no established general method for predicting the impression of odor of a chemical only from its physicochemical properties. In this study, we designed a novel predictive model based on an artificial neural network with a deep structure for predicting odor impression utilizing the mass spectra of chemicals, and we conducted a series of computational analyses to evaluate its performance. Feature vectors extracted from the original high-dimensional space using two autoencoders equipped with both input and output layers in the model are used to build a mapping function from the feature space of mass spectra to the feature space of sensory data. The results of predictions obtained by the proposed new method have notable accuracy (R≅0.76) in comparison with a conventional method (R≅0.61).

Predicting the response of olfactory sensory neurons to odor mixtures from single odor response

The response of olfactory receptor neurons to odor mixtures is not well understood. Here, using experimental constraints, we investigate the mathematical structure of the odor response space and its consequences. The analysis suggests that the odor response space is 3-dimensional, and predicts that the dose-response curve of an odor receptor can be obtained, in most cases, from three primary components with specific properties. This opens the way to an objective procedure to obtain specific olfactory receptor responses by manipulating mixtures in a mathematically predictable manner. This result is general and applies, independently of the number of odor components, to any olfactory sensory neuron type with a response curve that can be represented as a sigmoidal function of the odor concentration.

Measuring Graded Membership: The Case of Color

This paper considers Kamp and Partee's account of graded membership within a conceptual spaces framework and puts the account to the test in the domain of colors. Three experiments are reported that are meant to determine, on the one hand, the regions in color space where the typical instances of blue and green are located and, on the other hand, the degrees of blueness/greenness of various shades in the blue-green region as judged by human observers. From the locations of the typical blue and typical green regions in conjunction with Kamp and Partee's account follow degrees of blueness/greenness for the color shades we are interested in. These predicted degrees are compared with the judged degrees, as obtained in the experiments. The results of the comparison support the account of graded membership at issue.

Understanding the Odour Spaces: A Step towards Solving Olfactory Stimulus-Percept Problem

Odours are highly complex, relying on hundreds of receptors, and people are known to disagree in their linguistic descriptions of smells. It is partly due to these facts that, it is very hard to map the domain of odour molecules or their structure to that of perceptual representations, a problem that has been referred to as the Structure-Odour-Relationship. We collected a number of diverse open domain databases of odour molecules having unorganised perceptual descriptors, and developed a graphical method to find the similarity between perceptual descriptors; which is intuitive and can be used to identify perceptual classes. We then separately projected the physico-chemical and perceptual features of these molecules in a non-linear dimension and clustered the similar molecules. We found a significant overlap between the spatial positioning of the clustered molecules in the physico-chemical and perceptual spaces. We also developed a statistical method of predicting the perceptual qualities of a novel molecule using its physico-chemical properties with high receiver operating characteristics(ROC).