Olfaction is an evolutionary old sensory system, which provides sophisticated access to information about our surroundings. In particular, detecting the volatile organic compounds (VOCs) emitted during natural and artificial processes can be used as characteristic fingerprints and help to identify their source. Inspired by the biological example, artificial olfaction aims at achieving similar performance and thus digitizing the sense of smell. Here, we present the development of machine learning-enabled graphene-based electronic olfaction sensors and propose an approach to assess their olfactory performance toward VOCs. Eleven transient kinetic features extracted from the sensing response profile are utilized as their fingerprint information. By mimicking the Sniffin' Sticks test, electronic olfaction sensors exhibit high olfactory performance toward four VOC odors (clove, eucalyptus, lemon, and rose scent) in terms of odor detection threshold, odor discrimination, and identification performance. Upon exposure to binary odor mixtures, response features of electronic olfaction sensors behave more similarly to that of an individual odor, with a tendency that correlates with their ratio, resembling the overshadowing effect in human olfactory perception. Molecular dynamics simulations and density functional theory calculations results reveal competing adsorption mechanisms between odorant molecules and sensing materials. This may facilitate electronic olfaction sensor applications in some emerging fields, such as environmental monitoring or public security.

A growing body of research aims at solving what is often referred to as the stimulus-percept problem in olfactory perception. Although computational efforts have made it possible to predict perceptual impressions from the physicochemical space of odors, studies with large psychophysical datasets from non-experts remain scarce. Following previous approaches, we developed a physicochemical odor space using 4094 molecular descriptors of 1389 odor molecules. For 20 of these odors, we examined associations with perceived pleasantness, intensity, odor quality and detection threshold, obtained from a dataset of 2000 naïve participants. Our results show significant differences in perceptual ratings, and we were able to replicate previous findings on the association between perceptual ratings and the first dimensions of the physicochemical odor space. However, the present analyses also revealed striking interindividual variations in perceived pleasantness and intensity. Additionally, interactions between pleasantness, intensity, and olfactory and trigeminal qualitative dimensions were found. To conclude, our results support previous findings on the relation between structure and perception on the group level in our sample of non-expert raters. In the challenging task to relate olfactory stimulus and percept, the physicochemical odor space can serve as a reliable and helpful tool to structure the high-dimensional space of olfactory stimuli. Nevertheless, human olfactory perception in the individual is not an analytic process of molecule detection alone, but is part of a holistic integration of multisensory inputs, context and experience.

The molecular structure of an odor determines whether and how it is perceived by humans. However, the principles of how odorant chemistry links to perceptual patterns remain largely unknown and are primarily studied using odor rating datasets from highly trained olfactory experts, such as perfumers. This limits our knowledge of typical odor perception and its variability over individuals. We provide a dataset featuring free descriptions, evaluative ratings, and qualitative labels for 74 chemically diverse mono-molecular odorants, rated by a large sample of young adults. A total of 1,227 participants described and rated the odors, and completed questionnaires covering their demographic background, personality traits, and the role of olfaction in their daily lives. The dataset offers a valuable foundation for research aimed at understanding the fundamentals of olfactory perception.

The sense of smell is based on sensory detection of the molecule(s), which is then further perceptually interpreted. A possible measure of olfactory perception is an odor-independent olfactory perceptual fingerprint (OPF) defined by Snitz et al. We aimed to investigate whether OPF can distinguish patients with olfactory dysfunction (OD) due to coronavirus disease (COVID-19) from controls and which perceptual descriptors are important for that separation. Our study included 99 healthy controls and 41 patients. They rated 10 odors using 8 descriptors such as “pleasant,” “intense,” “familiar,” “warm,” “cold,” “irritating,” “edible,” and “disgusting.” An unsupervised machine learning method, hierarchical cluster analysis, showed that OPF can distinguish patients from controls with an accuracy of 83%, a sensitivity of 51%, and a specificity of 96%. Furthermore, a supervised machine learning method, random forest classifier, showed that OPF can distinguish patients and controls in the testing dataset with an accuracy of 86%, a sensitivity of 64%, and a specificity of 96%. Principal component analysis and random forest classifier showed that familiarity and intensity were the key qualities to explain the variance of the data. In conclusion, people with COVID-19-related OD have a fundamentally different olfactory perception.

Body odors offer a unique window into the physiological and psychological profile of the emitter. This information, broadcast in nonverbal communication, significantly shapes social interactions. However, effectively digitizing body odors requires a precise framework for perceptual operationalization. Previous research has used a very limited number of verbal terms, such as pleasant, intense, or attractive, which fails to adequately capture qualitative differences. To address this gap, we elicited body odor descriptions from 2,607 participants across 17 countries and 13 languages. All these descriptions are presented here in one dataset, together with a condensed list of 25 body odor words (BOW). Those terms reliably differentiated between body states, and were validated in a separate study with a different group of 155 perceivers. The dataset, available as a web application, provides a novel operationalization of body odor impressions, which is a precondition for studying olfaction in human nonverbal communication, for perception-based digitization of body odors and for comparative studies.

While ample data demonstrate the effectiveness of inpatient psychosomatic treatment, clinical observation and empirical evidence demonstrate that not all patients benefit equally from established therapeutic methods. Especially patients with a comorbid personality disorder often show reduced therapeutic success compared to other patient groups. Due to the heterogeneous and categorical personality assessment, previous studies indicated no uniform direction of this influence. This complicates the derivation of therapeutic recommendations for mental disorders with comorbid personality pathology. Analyzing n = 2094 patients from German university hospitals enrolled in the prospective "MEPP" study, we tested the dynamic interaction between dimensionally assessed personality functioning and psychopathology of anxiety and depression. Longitudinal structural equation modelling replicated the finding that the severity of symptoms at admission predicts symptom improvement within the same symptom domain. In addition, we here report a significant coupling parameter between the baseline level of personality function and the change in general psychopathology - and vice versa. These results imply that personality pathology at admission hinders the therapeutic improvement in anxiety and depression, and that improvement of personality pathology is hindered by general psychopathology. Furthermore, the covariance between both domains supports the assumption that personality functioning and general psychopathology cannot be clearly distinguished and adversely influence each other. A dimensional assessment of the personality pathology is therefore recommendable for psychotherapy research and targeted therapeutic treatment.