Odor identification errors reveal cognitive aspects of age-associated smell loss.

Human olfaction can be extraordinarily sensitive, and its most common assessment method is odor identification (OID), where everyday odors are matched to word labels in a multiple-choice format. However, many older persons are unable to identify familiar odors, a deficit that is associated with the risk of future dementia and mortality. The underlying processes subserving OID in older adults are poorly understood. Here, we analyzed error patterns in OID to test whether errors could be explained by perceptual and/or semantic similarities among the response alternatives. We investigated the OID response patterns in a large, population-based sample of older adults in Sweden (n = 2479; age 60-100 years). Olfaction was assessed by a 'Sniffin ́ TOM OID test with 16 odors; each trial involved matching a target odor to a correct label among three distractors. We analyzed the pattern of misidentifications, and the results showed that some distractors were more frequently selected than others, suggesting cognitive or perceptual factors may be present. Relatedly, we conducted a large online survey of older adults (n = 959, age 60-90 years) who were asked to imagine and rate the perceptual similarity of the target odors and the three corresponding distractors (e.g. "How similar are these smells: apple and mint?"). We then used data from the Swedish web corpus and the Word2Vec neural network algorithm to quantify the semantic association strength between the labels of each target odor and its three distractors. These data sources were used to predict odor identification errors. We found that the error patterns were partly explained by both the semantic similarity between target-distractor pairs, and the imagined perceptual similarity of the target-distractor pair. Both factors had, however, a diminished prediction in older ages, as responses became gradually less systematic. In sum, our results suggest that OID tests not only reflect olfactory perception, but also likely involve the mental processing of odor-semantic associations. This may be the reason why these tests are useful in predicting dementia onset. Our insights into olfactory-language interactions could be harnessed to develop new olfactory tests that are tailored for specific clinical purposes.

A parosmia severity index based on word-classification predicts olfactory abilities and impairment.

Parosmia is an olfactory disorder that involves distortions of specific odors that may co-occur with anosmia, loss of smell of other odors. Little is known about which odors frequently trigger parosmia, and measures of parosmia severity are lacking. Here, we present an approach to understand and diagnose parosmia that is based on semantic properties (e.g., valence) of words describing odor sources ("fish", "coffee", etc.). Using a data-driven method based on natural language data, we identified 38 odor descriptors. Descriptors were evenly dispersed across an olfactory-semantic space, which was based on key odor dimensions. Parosmia patients (n = 48) classified the corresponding odors in terms of whether they trigger parosmic or anosmic sensations. We investigated whether these classifications are related to semantic properties of the descriptors. Parosmic sensations were most often reported for words describing unpleasant odors of inedibles that are highly associated to olfaction (e.g., "excrement"). Based on PCA modeling, we derived the Parosmia Severity Index-a measure of parosmia severity that can be determined solely from our non-olfactory behavioral task. This index predicts olfactory-perceptual abilities, self-reported olfactory impairment, and depression. We thus provide a novel approach for investigating parosmia and establishing its severity that does not require odor exposure. Our work may enhance our understanding of how parosmia changes over time and how it is expressed differently across individuals.

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.

Perceptual odor qualities predict successful odor identification in old age.

Odor identification is a common assessment of olfaction, and it is affected in a large number of diseases. Identification abilities decline with age, but little is known about whether there are perceptual odor features that can be used to predict identification. Here, we analyzed data from a large, population-based sample of 2,479 adults, aged 60 years or above, from the Swedish National study on Aging and Care in Kungsholmen. Participants performed both free and cued odor identification tests. In a separate experiment, we assessed perceived pleasantness, familiarity, intensity, and edibility of all odors in the first sample, and examined how odor identification performance is associated with these variables. The analysis showed that high-intensity odors are easier to identify than low-intensity odors overall, but also that they are more susceptible to the negative repercussions of old age. This result indicates that sensory decline is a major aspect of age-dependent odor identification impairment, and suggests a framework where identification likelihood is proportional to the perceived intensity of the odor. Additional analyses further showed that high-performing individuals can discriminate target odors from distractors along the pleasantness and edibility dimensions and that unpleasant and inedible odors show smaller age-related differences in identification. Altogether, these results may guide further development and optimization of brief and efficient odor identification tests as well as influence the design of odorous products targeted toward older consumers.

A Rational Model of Incremental Argument Interpretation: The Comprehension of Swedish Transitive Clauses.

A central component of sentence understanding is verb-argument interpretation, determining how the referents in the sentence are related to the events or states expressed by the verb. Previous work has found that comprehenders change their argument interpretations incrementally as the sentence unfolds, based on morphosyntactic (e.g., case, agreement), lexico-semantic (e.g., animacy, verb-argument fit), and discourse cues (e.g., givenness). However, it is still unknown whether these cues have a privileged role in language processing, or whether their effects on argument interpretation originate in implicit expectations based on the joint distribution of these cues with argument assignments experienced in previous language input. We compare the former, linguistic account against the latter, expectation-based account, using data from production and comprehension of transitive clauses in Swedish. Based on a large corpus of Swedish, we develop a rational (Bayesian) model of incremental argument interpretation. This model predicts the processing difficulty experienced at different points in the sentence as a function of the Bayesian surprise associated with changes in expectations over possible argument interpretations. We then test the model against reading times from a self-paced reading experiment on Swedish. We find Bayesian surprise to be a significant predictor of reading times, complementing effects of word surprisal. Bayesian surprise also captures the qualitative effects of morpho-syntactic and lexico-semantic cues. Additional model comparisons find that it-with a single degree of freedom-captures much, if not all, of the effects associated with these cues. This suggests that the effects of form- and meaning-based cues to argument interpretation are mediated through expectation-based processing.

Duality of Smell: Route-Dependent Effects on Olfactory Perception and Language.

Olfactory research in humans has largely focused on odors perceived via sniffing, orthonasal olfaction, whereas odors perceived from the mouth, retronasal olfaction, are less well understood. Prior work on retronasally presented odors involves animal models and focus mainly on odor sensitivity, but little is known about retronasal olfactory perception and cognition in humans. In this study, we compared orthonasal and retronasal odor presentation routes to investigate differences in odor descriptions and evaluations. Thirty-six individuals participated in a within-subjects study using twelve odors (varying in pleasantness and edibility) in perceptual and semantic tasks. Orthonasal presentation was associated with a better ability to identify odors, and with more concrete (and source-based) language. Exploratory analyses revealed that whereas orthonasal odors were described with words that had visual associations, retronasal odors were described with words that had interoceptive associations. Interestingly, these route-dependent differences in descriptor usage were not explained by differences in sensitivity and intensity, suggesting instead a cognitive and linguistic processing difference between odors presented orthonasally and retronasally. Our results indicate that olfaction is, in fact, a dual sense, in which the routes change the perception of an odor.

Olfactory Influences on Visual Categorization: Behavioral and ERP Evidence.

Visual stimuli often dominate nonvisual stimuli during multisensory perception. Evidence suggests higher cognitive processes prioritize visual over nonvisual stimuli during divided attention. Visual stimuli should thus be disproportionally distracting when processing incongruent cross-sensory stimulus pairs. We tested this assumption by comparing visual processing with olfaction, a "primitive" sensory channel that detects potentially hazardous chemicals by alerting attention. Behavioral and event-related brain potentials (ERPs) were assessed in a bimodal object categorization task with congruent or incongruent odor-picture pairings and a delayed auditory target that indicated whether olfactory or visual cues should be categorized. For congruent pairings, accuracy was higher for visual compared to olfactory decisions. However, for incongruent pairings, reaction times (RTs) were faster for olfactory decisions. Behavioral results suggested that incongruent odors interfered more with visual decisions, thereby providing evidence for an "olfactory dominance" effect. Categorization of incongruent pairings engendered a late "slow wave" ERP effect. Importantly, this effect had a later amplitude peak and longer latency during visual decisions, likely reflecting additional categorization effort for visual stimuli in the presence of incongruent odors. In sum, contrary to what might be inferred from theories of "visual dominance," incongruent odors may in fact uniquely attract mental processing resources during perceptual incongruence.

A protocol for a three-arm cluster randomized controlled superiority trial investigating the effects of two pedagogical methodologies in Swedish preschool settings on language and communication, executive functions, auditive selective attention, socioemotional skills and early maths skills.

BACKGROUND: During the preschool years, children develop abilities and skills in areas crucial for later success in life. These abilities include language, executive functions, attention, and socioemotional skills. The pedagogical methods used in preschools hold the potential to enhance these abilities, but our knowledge of which pedagogical practices aid which abilities, and for which children, is limited. The aim of this paper is to describe an intervention study designed to evaluate and compare two pedagogical methodologies in terms of their effect on the above-mentioned skills in Swedish preschool children. METHOD: The study is a randomized control trial (RCT) where two pedagogical methodologies were tested to evaluate how they enhanced children's language, executive functions and attention, socioemotional skills, and early maths skills during an intensive 6-week intervention. Eighteen preschools including 28 units and 432 children were enrolled in a municipality close to Stockholm, Sweden. The children were between 4;0 and 6;0 years old and each preschool unit was randomly assigned to either of the interventions or to the control group. Background information on all children was collected via questionnaires completed by parents and preschools. Pre- and post-intervention testing consisted of a test battery including tests on language, executive functions, selective auditive attention, socioemotional skills and early maths skills. The interventions consisted of 6 weeks of intensive practice of either a socioemotional and material learning paradigm (SEMLA), for which group-based activities and interactional structures were the main focus, or an individual, digitally implemented attention and math training paradigm, which also included a set of self-regulation practices (DIL). All preschools were evaluated with the ECERS-3. DISCUSSION: If this intervention study shows evidence of a difference between group-based learning paradigms and individual training of specific skills in terms of enhancing children's abilities in fundamental areas like language, executive functions and attention, socioemotional skills and early math, this will have big impact on the preschool agenda in the future. The potential for different pedagogical methodologies to have different impacts on children of different ages and with different backgrounds invites a wider discussion within the field of how to develop a preschool curriculum suited for all children.

Semantic Factors Predict the Rate of Lexical Replacement of Content Words.

The rate of lexical replacement estimates the diachronic stability of word forms on the basis of how frequently a proto-language word is replaced or retained in its daughter languages. Lexical replacement rate has been shown to be highly related to word class and word frequency. In this paper, we argue that content words and function words behave differently with respect to lexical replacement rate, and we show that semantic factors predict the lexical replacement rate of content words. For the 167 content items in the Swadesh list, data was gathered on the features of lexical replacement rate, word class, frequency, age of acquisition, synonyms, arousal, imageability and average mutual information, either from published databases or gathered from corpora and lexica. A linear regression model shows that, in addition to frequency, synonyms, senses and imageability are significantly related to the lexical replacement rate of content words-in particular the number of synonyms that a word has. The model shows no differences in lexical replacement rate between word classes, and outperforms a model with word class and word frequency predictors only.