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BACKGROUND: There is a prevailing view that humans' capacity to use language to characterize sensations like odors or tastes is poor, providing an unreliable source of information. METHODS: Here, we developed a machine learning method based on Natural Language Processing (NLP) using Large Language Models (LLM) to predict COVID-19 diagnosis solely based on text descriptions of acute changes in chemosensation, i.e., smell, taste and chemesthesis, caused by the disease. The dataset of more than 1500 subjects was obtained from survey responses early in the COVID-19 pandemic, in Spring 2020. RESULTS: When predicting COVID-19 diagnosis, our NLP model performs comparably (AUC ROC ~ 0.65) to models based on self-reported changes in function collected via quantitative rating scales. Further, our NLP model could attribute importance of words when performing the prediction; sentiment and descriptive words such as "smell", "taste", "sense", had strong contributions to the predictions. In addition, adjectives describing specific tastes or smells such as "salty", "sweet", "spicy", and "sour" also contributed considerably to predictions. CONCLUSIONS: Our results show that the description of perceptual symptoms caused by a viral infection can be used to fine-tune an LLM model to correctly predict and interpret the diagnostic status of a subject. In the future, similar models may have utility for patient verbatims from online health portals or electronic health records.

Early in the COVID-19 pandemic, people who were infected with SARS-CoV-2 reported changes in smell and taste. To better study these symptoms of SARS-CoV-2 infections and potentially use them to identify infected patients, a survey was undertaken in various countries asking people about their COVID-19 symptoms. One part of the questionnaire asked people to describe the changes in smell and taste they were experiencing. We developed a computational program that could use these responses to correctly distinguish people that had tested positive for SARS-CoV-2 infection from people without SARS-CoV-2 infection. This approach could allow rapid identification of people infected with SARS-CoV-2 from descriptions of their sensory symptoms and be adapted to identify people infected with other viruses in the future.

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People often confuse smell loss with taste loss, so it is unclear how much gustatory function is reduced in patients self-reporting taste loss. Our pre-registered cross-sectional study design included an online survey in 12 languages with instructions for self-administering chemosensory tests with 10 household items. Between June 2020 and March 2021, 10,953 individuals participated. Of these, 5,225 self-reported a respiratory illness and were grouped based on their reported COVID test results: COVID-positive (COVID+, N = 3,356), COVID-negative (COVID-, N = 602), and COVID unknown for those waiting for a test result (COVID?, N = 1,267). The participants who reported no respiratory illness were grouped by symptoms: sudden smell/taste changes (STC, N = 4,445), other symptoms excluding smell or taste changes (OthS, N = 832), and no symptoms (NoS, N = 416). Taste, smell, and oral irritation intensities and self-assessed abilities were rated on visual analog scales. Compared to the NoS group, COVID+ was associated with a 21% reduction in taste (95% confidence interval (CI): 15-28%), 47% in smell (95% CI: 37-56%), and 17% in oral irritation (95% CI: 10-25%) intensity. There were medium to strong correlations between perceived intensities and self-reported abilities (r = 0.84 for smell, r = 0.68 for taste, and r = 0.37 for oral irritation). Our study demonstrates that COVID-19-positive individuals report taste dysfunction when self-tested with stimuli that have little to none olfactory components. Assessing the smell and taste intensity of household items is a promising, cost-effective screening tool that complements self-reports and may help to disentangle taste loss from smell loss. However, it does not replace standardized validated psychophysical tests.

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People often confuse smell loss with taste loss, so it is unclear how much gustatory function is reduced in patients self-reporting taste loss. Our pre-registered cross-sectional study design included an online survey in 12 languages with instructions for self-administering chemosensory tests with ten household items. Between June 2020 and March 2021, 10,953 individuals participated. Of these, 3,356 self-reported a positive and 602 a negative COVID-19 diagnosis (COVID+ and COVID-, respectively); 1,267 were awaiting test results (COVID?). The rest reported no respiratory illness and were grouped by symptoms: sudden smell/taste changes (STC, N=4,445), other symptoms excluding smell or taste loss (OthS, N=832), and no symptoms (NoS, N=416). Taste, smell, and oral irritation intensities and self-assessed abilities were rated on visual analog scales. Compared to the NoS group, COVID+ was associated with a 21% reduction in taste (95% Confidence Interval (CI): 15-28%), 47% in smell (95%-CI: 37-56%), and 17% in oral irritation (95%-CI: 10-25%) intensity. In all groups, perceived intensity of smell (r=0.84), taste (r=0.68), and oral irritation (r=0.37) was correlated. Our findings suggest most reports of taste dysfunction with COVID-19 were genuine and not due to misinterpreting smell loss as taste loss (i.e., a classical taste-flavor confusion). Assessing smell and taste intensity of household items is a promising, cost-effective screening tool that complements self-reports and helps to disentangle taste loss from smell loss. However, it does not replace standardized validated psychophysical tests.

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INTRODUCTION: Nutrition claims are one of the most common tools used to improve food decisions. Previous research has shown that nutrition claims impact expectations; however, their effects on perceived pleasantness, valuation, and their neural correlates are not well understood. These claims may have both intended and unintended effects on food perception and valuation, which may compromise their effect on food decisions. METHODS: We investigated the effects of nutrition claims on expectations, perceptions, and valuation of milk-mix drinks in a behavioral (n = 110) and an fMRI (n = 39) study. In the behavioral study, we assessed the effects of a "fat-reduced" and a "protein-rich" nutrition claim on expected and perceived food attributes of otherwise equal food products. In the fMRI study, we investigated the effect of a "protein-rich" claim on taste pleasantness perception and valuation, and on their neural correlates during tasting and swallowing. RESULTS: We found that both nutrition claims increased expected and perceived healthiness and decreased expected but not perceived taste pleasantness. The "protein-rich" claim increased expected but not perceived satiating quality ratings, while the "fat-reduced" claim decreased both expected and perceived satiating quality ratings. In the absence vs. presence of the "protein-rich" claim, we observed an increased activity in a cluster extending to the left nucleus accumbens during tasting and an increased functional connectivity between this cluster and a cluster in right middle frontal gyrus during swallowing. CONCLUSION: Altogether, we found that nutrition claims impacted expectations and attenuated reward-related responses during tasting but did not negatively affect perceived pleasantness. Our findings support highlighting the presence of nutrients with positive associations and exposure to foods with nutrition claims to increase their acceptance. Our study offers insights that may be valuable in designing and optimizing the use of nutrition claims.

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Remembering a particular taste is crucial in food intake and associative learning. We investigated whether taste can be dynamically encoded, maintained, and retrieved on short time scales consistent with working memory (WM). We use novel single and multi-item taste recognition tasks to show that a single taste can be reliably recognized despite repeated oro-sensory interference suggesting active and resilient maintenance (Experiment 1, N = 21). When multiple tastes were presented (Experiment 2, N = 20), the resolution with which these were maintained depended on their serial position, and recognition was reliable for up to three tastes suggesting a limited capacity of gustatory WM. Lastly, stimulus similarity impaired recognition with increasing set size, which seemed to mask the awareness of capacity limitations. Together, the results advocate a hybrid model of gustatory WM with a limited number of slots where items are stored with varying precision.

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Taste and smell function decline with age, with robust impairment in the very old. Much less is known about taste and smell function in young and middle aged. We investigated taste and smell sensitivity via thresholds in a sub-sample of the NutriAct Family Study (NFS), the NFS Examinations cohort (NFSE; N = 251, age M = 62.5 years). We examined different aspects relating to taste and smell function: the degree to which taste and smell sensitivity relate to another and to taste and smell preferences, the role of gender and age, as well as effects on Quality of Life (QoL). Taste thresholds were highly correlated, but no correlation was observed between taste and smell thresholds and between thresholds and preference. Women were more sensitive for both taste and smell than men. We found no effect of age on sensitivity and no effect of sensitivity on QoL. All null findings were complemented by Bayesian statistics. Together our results indicate the independence of taste and smell despite their overlap during sensorial experiences. We found no evidence for age-related sensory decline, which could be due to our sample's characteristics of non-clinical volunteers with good dental health and 93% non-smokers.

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Chemosensory impairments have been established as a specific indicator of COVID-19. They affect most patients and may persist long past the resolution of respiratory symptoms, representing an unprecedented medical challenge. Since the SARS-CoV-2 pandemic started, we now know much more about smell, taste, and chemesthesis loss associated with COVID-19. However, the temporal dynamics and characteristics of recovery are still unknown. Here, capitalizing on data from the Global Consortium for Chemosensory Research (GCCR) crowdsourced survey, we assessed chemosensory abilities after the resolution of respiratory symptoms in participants diagnosed with COVID-19 during the first wave of the pandemic in Italy. This analysis led to the identification of two patterns of chemosensory recovery, partial and substantial, which were found to be associated with differential age, degrees of chemosensory loss, and regional patterns. Uncovering the self-reported phenomenology of recovery from smell, taste, and chemesthetic disorders is the first, yet essential step, to provide healthcare professionals with the tools to take purposeful and targeted action to address chemosensory disorders and their severe discomfort.

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Chemosensory impairments have been established as a specific indicator of COVID-19. They affect most patients and may persist long past the resolution of respiratory symptoms, representing an unprecedented medical challenge. Since the SARS-CoV-2 pandemic started, we now know much more about smell, taste, and chemesthesis loss associated with COVID-19. However, the temporal dynamics and characteristics of recovery are still unknown. Here, capitalizing on data from the Global Consortium for Chemosensory Research (GCCR) crowdsourced survey, we assessed chemosensory abilities after the resolution of respiratory symptoms in participants diagnosed with COVID-19 during the first wave of the pandemic in Italy. This analysis led to the identification of two patterns of chemosensory recovery, limited (partial) and substantial, which were found to be associated with differential age, degrees of chemosensory loss, and regional patterns. Uncovering the self-reported phenomenology of recovery from smell, taste, and chemesthetic disorders is the first, yet essential step, to provide healthcare professionals with the tools to take purposeful and targeted action to address chemosensory disorders and its severe discomfort.

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RATIONAL: At all times humans have made attempts to improve their cognitive abilities by different means, among others, with the use of stimulants. Widely available stimulants such as caffeine, but also prescription substances such as methylphenidate and modafinil, are being used by healthy individuals to enhance cognitive performance. OBJECTIVES: There is a lack of knowledge on the effects of prescription stimulants when taken by healthy individuals (as compared with patients) and especially on the effects of different substances across different cognitive domains. METHODS: We conducted a pilot study with three arms in which male participants received placebo and one of three stimulants (caffeine, methylphenidate, modafinil) and assessed cognitive performance with a test battery that captures various cognitive domains. RESULTS: Our study showed some moderate effects of the three stimulants tested. Methylphenidate had positive effects on self-reported fatigue as well as on declarative memory 24 hours after learning; caffeine had a positive effect on sustained attention; there was no significant effect of modafinil in any of the instruments of our test battery. All stimulants were well tolerated, and no trade-off negative effects on other cognitive domains were found. CONCLUSIONS: The few observed significant positive effects of the tested stimulants were domain-specific and of rather low magnitude. The results can inform the use of stimulants for cognitive enhancement purposes as well as direct further research to investigate the effects of stimulants on specific cognitive domains that seem most promising, possibly by using tasks that are more demanding.

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In a preregistered, cross-sectional study, we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n = 4148) or negative (C19-; n = 546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean ± SD, C19+: -82.5 ± 27.2 points; C19-: -59.8 ± 37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC = 0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g., fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0-10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4 < OR < 10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable.

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BACKGROUND: COVID-19 has heterogeneous manifestations, though one of the most common symptoms is a sudden loss of smell (anosmia or hyposmia). We investigated whether olfactory loss is a reliable predictor of COVID-19. METHODS: This preregistered, cross-sectional study used a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified singular and cumulative predictors of COVID-19 status and post-COVID-19 olfactory recovery. RESULTS: Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean±SD, C19+: -82.5±27.2 points; C19-: -59.8±37.7). Smell loss during illness was the best predictor of COVID-19 in both single and cumulative feature models (ROC AUC=0.72), with additional features providing no significant model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms, such as fever or cough. Olfactory recovery within 40 days was reported for ~50% of participants and was best predicted by time since illness onset. CONCLUSIONS: As smell loss is the best predictor of COVID-19, we developed the ODoR-19 tool, a 0-10 scale to screen for recent olfactory loss. Numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (10

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Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments, such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, and generally lacked quantitative measurements. Here, we report the development, implementation, and initial results of a multilingual, international questionnaire to assess self-reported quantity and quality of perception in 3 distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, and 8 others, aged 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste, and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change ±100) revealed a mean reduction of smell (-79.7 ± 28.7, mean ± standard deviation), taste (-69.0 ± 32.6), and chemesthetic (-37.3 ± 36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell but also affects taste and chemesthesis. The multimodal impact of COVID-19 and the lack of perceived nasal obstruction suggest that severe acute respiratory syndrome coronavirus strain 2 (SARS-CoV-2) infection may disrupt sensory-neural mechanisms.

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Current non-invasive neuroimaging methods can assess neural activity in all areas of the human brain but the olfactory bulb (OB). The OB has been suggested to fulfill a role comparable to that of V1 and the thalamus in the visual system and have been closely linked to a wide range of olfactory tasks and neuropathologies. Here we present a method for non-invasive recording of signals from the human OB with millisecond precision. We demonstrate that signals obtained via recordings from EEG electrodes at the nasal bridge represent responses from the human olfactory bulb - recordings we term Electrobulbogram (EBG). The EBG will aid future olfactory-related translational work but can also potentially be implemented as an everyday clinical tool to detect pathology-related changes in human central olfactory processing in neurodegenerative diseases. In conclusion, the EBG is localized to the OB, is reliable, and follows response patterns demonstrated in non-human animal models.

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Taste perception, although vital for nutrient sensing, has long been overlooked in sensory assessments. This can, at least in part, be attributed to challenges associated with the handling of liquid, perishable stimuli, but also with scarce efforts to optimize testing procedures to be more time-efficient. We have previously introduced an adaptive, QUEST-based procedure to measure taste sensitivity thresholds that was quicker than other existing approaches, yet similarly reliable. Despite its advantages, the QUEST procedure lacks experimental control of false alarms (i.e., response bias) and psychometric function slope. Variations of these parameters, however, may also influence the threshold estimate. This raises the question as to whether a procedure that simultaneously assesses threshold, false-alarm rate, and slope might be able to produce threshold estimates with higher repeatability, i.e., smaller variation between repeated measurements. Here, we compared the performance of QUEST with a method that allows measurement of false-alarm rates and slopes, quick Yes-No (qYN), in a test-retest design for citric acid, sodium chloride, quinine hydrochloride, and sucrose recognition thresholds. We used complementary measures of repeatability, namely test-retest correlations and coefficients of repeatability. Both threshold procedures yielded largely overlapping thresholds with good repeatability between measurements. Together the data suggest that participants used a conservative response criterion. Furthermore, we explored the link between taste sensitivity and taste liking or which we found, however, no clear association.

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The ability to smell is crucial for most species as it enables the detection of environmental threats like smoke, fosters social interactions, and contributes to the sensory evaluation of food and eating behavior. The high prevalence of smell disturbances throughout the life span calls for a continuous effort to improve tools for quick and reliable assessment of olfactory function. Odor-dispensing pens, called Sniffin' Sticks, are an established method to deliver olfactory stimuli during diagnostic evaluation. We tested the suitability of a Bayesian adaptive algorithm (QUEST) to estimate olfactory sensitivity using Sniffin' Sticks by comparing QUEST sensitivity thresholds with those obtained using a procedure based on an established standard staircase protocol. Thresholds were measured twice with both procedures in two sessions (Test and Retest). Overall, both procedures exhibited considerable overlap, with QUEST displaying slightly higher test-retest correlations, less variability between measurements, and reduced testing duration. Notably, participants were more frequently presented with the highest concentration during QUEST, which may foster adaptation and habituation effects. We conclude that further research is required to better understand and optimize the procedure for assessment of olfactory performance.

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Our current environment is characterized by the omnipresence of food cues. The taste and smell of real foods-but also graphical depictions of appetizing foods-can guide our eating behavior, for example, by eliciting food craving and anticipatory cephalic phase responses. To facilitate research into this so-called cue reactivity, several groups have compiled standardized food image sets. Yet, selecting the best subset of images for a specific research question can be difficult as images and image sets vary along several dimensions. In the present report, we review the strengths and weaknesses of popular food image sets to guide researchers during stimulus selection. Furthermore, we present a recent extension of our previously published database food-pics, which comprises an additional 328 food images from different countries to increase cross-cultural applicability. This food-pics_extended stimulus database, thus, encompasses and replaces food-pics. Normative data from a predominantly German-speaking sample are again presented as well as updated calculations of image characteristics.

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The gustatory system encodes information about chemical identity, nutritional value, and concentration of sensory stimuli before transmitting the signal from taste buds to central neurons that process and transform the signal. Deciphering the coding logic for taste quality requires examining responses at each level along the neural axis-from peripheral sensory organs to gustatory cortex. From the earliest single-fiber recordings, it was clear that some afferent neurons respond uniquely and others to stimuli of multiple qualities. There is frequently a "best stimulus" for a given neuron, leading to the suggestion that taste exhibits "labeled line coding." In the extreme, a strict "labeled line" requires neurons and pathways dedicated to single qualities (e.g., sweet, bitter, etc.). At the other end of the spectrum, "across-fiber," "combinatorial," or "ensemble" coding requires minimal specific information to be imparted by a single neuron. Instead, taste quality information is encoded by simultaneous activity in ensembles of afferent fibers. Further, "temporal coding" models have proposed that certain features of taste quality may be embedded in the cadence of impulse activity. Taste receptor proteins are often expressed in nonoverlapping sets of cells in taste buds apparently supporting "labeled lines." Yet, taste buds include both narrowly and broadly tuned cells. As gustatory signals proceed to the hindbrain and on to higher centers, coding becomes more distributed and temporal patterns of activity become important. Here, we present the conundrum of taste coding in the light of current electrophysiological and imaging techniques at several levels of the gustatory processing pathway.

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In an increasingly complex information society, demands for cognitive functioning are growing steadily. In recent years, numerous strategies to augment brain function have been proposed. Evidence for their efficacy (or lack thereof) and side effects has prompted discussions about ethical, societal, and medical implications. In the public debate, cognitive enhancement is often seen as a monolithic phenomenon. On a closer look, however, cognitive enhancement turns out to be a multifaceted concept: There is not one cognitive enhancer that augments brain function per se, but a great variety of interventions that can be clustered into biochemical, physical, and behavioral enhancement strategies. These cognitive enhancers differ in their mode of action, the cognitive domain they target, the time scale they work on, their availability and side effects, and how they differentially affect different groups of subjects. Here we disentangle the dimensions of cognitive enhancement, review prominent examples of cognitive enhancers that differ across these dimensions, and thereby provide a framework for both theoretical discussions and empirical research.

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Taste research has been hampered by technical difficulties, mostly because liquid taste stimuli are difficult to control in terms of timing and application area. Exact stimulus control requires a gustometer, but the existing devices are either not well-documented or rather inflexible. We designed a gustometer based on a computer-controlled, modular pump system, which can be extended via additional hardware modules-for example, for heating of the stimuli or sending and receiving triggers. All components are available for purchase "off the shelf." The pumps deliver liquids through plastic tubing and can be connected to commercially available or custom-made mouthpieces. We determined the temporal precision of the device. Onset delays showed minuscule variation within pumps (SD < 3 ms) and small differences between pumps (< 4.5 ms). The rise time was less than 2 ms (SD < 2 ms), and the dosage volume bias was only 2%. To test whether hemitongues could be stimulated independently, we conducted a behavioral experiment. A total of 18 participants received tasteless stimuli to the left, right, or both sides of the tongue. The side of stimulation was correctly identified on 91% of trials, indicating that the setup is suitable for lateralized stimulation. Electroencephalographic responses to water and salty stimuli were recorded from two participants; the stimulation successfully evoked event-related responses, demonstrating the suitability of the device for use in electrophysiological investigations. We provide a Python-based open-source software package and a Web interface to easily operate the system. We thereby hope to facilitate access to state-of-the-art taste research methods and to increase reproducibility across laboratories.

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