Effect of nasal dilators on nasal structures, sniffing strategies, and olfactory ability.

This paper describes the effects that nasal dilators have on olfactory ability. Experimental results demonstrate that nasal dilators increase odorant identification, lower odorant threshold, and increase perceptual odorant intensity. In other experiments, magnetic resonance imaging (MRI) data demonstrates that the size of the nasal cavity especially around the region of the nasal valve is increased when nasal dilators are worn. Additionally, pneumotachograph data demonstrates that during a sniff, the peak flow, maximum flow rate, volume, and duration are all increased when nasal dilators are worn. Taken together, the increase in olfactory ability can most easily be explained by an increase in both the amount and the proportion of inspired odorant molecules that are directed to the olfactory mucosa and are, therefore, available for odorant perception.

Odorant confusion matrix: the influence of patient history on patterns of odorant identification and misidentification in hyposmia.

The odorant confusion matrix (OCM) is an odorant identification test in which the number of correct odorant identifications quantifies the level of olfactory function. As with other confusion matrices, the OCM reflects distortions of sensory perception as errors in identification. Previous work with the OCM suggests that, within an individual, hyposmia is associated with a stable shift in odorant perception. The current study examined whether consistent shifts in odorant perception are also characteristic of the various pathologies that lead to an olfactory loss. In a retrospective study, OCM response patterns for 135 hyposmic patients were fit into a five-dimensional space in which the distances between subjects reflected the dissimilarities between their OCM response patterns. Multivariate regression was performed relating position in the five-dimensional space to each of 11 factors representing 33 demographic and medical history variables. One factor, named congestion (gathering the variables of past polyposis, current polyposis, and current nasal obstruction due to swelling), was significantly indicative of patterns of responses on the OCM, independent of the level of hyposmia. These data suggest that conductive olfactory loss may be associated with alterations in odorant perception, which are reflected in consistent odorant confusions. Such alterations in perception may eventually serve as a basis for a clinical test to provide differential diagnoses as to the sources of olfactory losses.

Sequence and analysis of chromosome 1 of the plant Arabidopsis thaliana.

The genome of the flowering plant Arabidopsis thaliana has five chromosomes. Here we report the sequence of the largest, chromosome 1, in two contigs of around 14.2 and 14.6 megabases. The contigs extend from the telomeres to the centromeric borders, regions rich in transposons, retrotransposons and repetitive elements such as the 180-base-pair repeat. The chromosome represents 25% of the genome and contains about 6,850 open reading frames, 236 transfer RNAs (tRNAs) and 12 small nuclear RNAs. There are two clusters of tRNA genes at different places on the chromosome. One consists of 27 tRNA(Pro) genes and the other contains 27 tandem repeats of tRNA(Tyr)-tRNA(Tyr)-tRNA(Ser) genes. Chromosome 1 contains about 300 gene families with clustered duplications. There are also many repeat elements, representing 8% of the sequence.

Odorant quality perception: a metric individual differences approach.

Perceptual spaces, in which similar stimuli are located close to each other and dissimilar stimuli are located far apart, have aided in the understanding of the physiological and psychological bases for sensory quality coding. Differences in perception between individuals should be reflected by differences in the spatial relationships between stimuli. If the dimensionality of the perceptual space is small (e.g., color space), individual differences that reflect specific pathologies are readily apparent from visual inspection. On the other hand, if the dimensionality of the perceptual space is large (as is proposed for odor space), visual inspection alone may not reveal individual differences in quality perception. The present work presents an information-theory-based method for quantifying individual differences in quality perception from perceptual confusion matrices. The ability of this method to quantify individual differences in quality perception is shown in a hypothetical example of specific anosmia. Finally, the method is applied to the examination of intrasubject consistency of odorant quality perception.

The labeled dissimilarity scale: a metric of perceptual dissimilarity.

Fundamental to the concept of psychological distance is the idea that confusability allows discovery of the perceptual relationships between objects, which provides understanding of the underlying principles that govern the functioning of a system. Thus, judgments of dissimilarity (conceptually proportional to the inverse of confusability) may provide insight into the elusive underlying quality-coding mechanisms in that sensory system. In the present experiments, a labeled dissimilarity scale (LDS) that reflects the magnitude of odorant dissimilarity was developed in a fashion similar to that reported by Green (Green, Shaffer, & Gilmore, 1993). This scale was produced by rating the perceptual intensity implied by adverbs describing different levels of dissimilarity, and then attaching those descriptors to appropriate locations on a numerical scale. The usefulness of the scale was demonstrated by its ability to produce visual color space with ratings of dissimilarity of Munsell color chips. The stability and reliability of the LDS was evaluated by comparing it with the traditional scaling technique of magnitude estimation (ME). It was found that the scales produced similar ratings of odorant dissimilarity and showed a similar susceptibility to the effects of contrast convergence. However, the coefficients of variation of dissimilarities rated with ME were much higher than those produced with the LDS. The subjects also dealt with the LDS without the anxiety that usually accompanies first-time users of ME. The LDS provided stable ratings of odorant dissimilarity and preserved the inferred ratio scale properties of ME.

What a tangled web we weave: discriminating between malingering and anosmia.

Two groups of normosmic subjects were instructed to feign a total olfactory loss when tested with the Olfactory Confusion Matrix (OCM). One of the groups was given specific instructions as to the number of odorants and trials in the test, as well as the number of items that might be expected to be correctly identified by chance. The responses of both groups of malingerers were compared with responses gathered from a group of anosmic patients. The groups did not differ in terms of performance level (percent correct). In spite of the similarity in terms of accuracy level, an analysis of the pattern of OCM responses to an irritant allowed the anosmic patients to be distinguished from subjects attempting to feign a loss. Subjects were given explicit details about the test performed at the same level as those simply told to feign a loss. These results suggest that the OCM is an effective tool in separating malingering from anosmia.

Phonological and perceptual components of short-term memory for odors.

Just as a written word can be encoded and retained in memory verbally or visually, an odor might be retained as a verbal description or perceptual (olfactory) code. However, one view holds that olfactory memory in the short term does not exist as a separate perceptual code. This was examined in an experiment in which memory errors could be seen as deriving from the substitution of similar verbal or olfactory codes. The odorants presented for recall were divided into three groups: base odorants (which might be replaced in memory by similar verbal or olfactory representations), verbal foils (stimuli dissimilar to the base stimuli in odor but similar in name), and odor foils (the reverse). The substitution errors made in attempting to recall test odorants were classified as verbal or olfactory. A substantial proportion of the errors were olfactory, but verbal errors also occurred. These results support the presence of short-term perceptual olfactory memory rather than simply verbal encoding of olfactory perceptions.

The olfactory loss that accompanies an HIV infection.

A number of studies have shown that HIV infection is associated with decreased olfactory ability. Additionally, it has been hypothesized that a reduced odorant identification may precede the advent of AIDS Dementia Complex (ADC). However, it is not known whether changes in olfactory ability are a manifestation of neurocognitive decline which may precede the appearance of AIDS Dementia Complex, damage to the peripheral olfactory system from opportunistic infection, or whether olfactory structures have a particular sensitivity to HIV. These issues were addressed in a cross-sectional study examining variability in the neuropsychological, neurological, otolaryngological, auditory, and olfactory status in HIV-positive subjects. A stepwise regression provided evidence that the ability to identify odorants was influenced by age, nasal structure and pathology, neurocognitive ability, and level of AIDS Dementia Complex. On the other hand, only nasal pathologies accounted for the variability in olfactory thresholds. These data suggest that identification and thresholds tests may reflect different olfactory pathologies. Additionally, these data suggest at least part of the decline in olfactory ability accompanying an HIV infection may be secondary to nasal pathologies. Because of their rapidly changing neurocognitive status, HIV-positive patients represent an excellent group in which to study the determinants of olfactory ability.

Metrics of odorant dissimilarity. Labeled magnitude scale vs magnitude estimation.

Magnitude estimation (ME) has long been the standard rating tool for stimulus intensity because of the simplicity and generalizability of the resultant power function relationships. However, the choice of a scaling procedure for rating complex stimuli (odorant) dissimilarity must be based on a different set of criteria due to an inability to evaluate relationships against a physical continuum. Recently, chemosensory labeled magnitude scales (LMS) have been developed, which produce ratings with many of the same properties as ME. The current study sought compare LMS to ME as metrics for describing the magnitude of perceived odorant dissimilarity. Forty subjects rated pair-wise odorant dissimilarity with either a LMS or ME. Each subject evaluated two sets of odorants with differing ranges of dissimilarity (high contrast and low contrast) in order to compare the sensitivity of the two measures to possible contrast convergence. The ME ratings were normalized such that the two metrics produced equal means. The scales produced similar ratings of odorant dissimilarity (r = 0.92) and showed small but similar effects of contrast convergence. However, the coefficient of variation of dissimilarities rated with ME was 2.8 times that of dissimilarities rated with the LMS. Subjects accepted the LMS without the usual anxiety that accompanies first time users of ME. LMS provide stable ratings of odorant dissimilarity while preserving the inferred ratio scale properties of ME.

Phonological and perceptual components of short-term memory for odors.

Just as a written word can be encoded and retained in memory either verbally or in a visual form, so it might seem that an odor might be retained as either a verbal description/name or as a perceptual (olfactory) code. However, one view has it that olfactory memory in the short term does not exist as a separate perceptual code. This was examined in an experimental paradigm in which errors in memory could be recognized as deriving from the substitution of similar verbal codes or of similar olfactory codes. The set of odorants presented for recall was divided into three groups: (i) base odorants (odorants that might be replaced in memory either by similar verbal or similar olfactory representations); (ii) verbal foils (stimuli dissimilar to the base stimuli in odor but which is similar in name); and (iii) odor foils (the reverse). The substitution errors made when attempting to recall test odorants were classified as verbal errors or olfactory errors. A substantial proportion of the errors were olfactory, but verbal errors also occurred. These results support the presence of short-term perceptual olfactory memory, rather than simply verbal encoding of olfactory perceptions.

Effect of nasal dilators on perceived odor intensity.

Subjects wearing nasal dilators rated olfactory stimuli as being more intense compared with ratings done without nasal expansion. The results support a perceptual constancy model in olfaction.

Olfactory stimulation variables. Which model best predicts the olfactory nerve response?

Mozell et al. (1984. J. Gen. Physiol. 83:233-267) have examined the traditional manner in which olfactory stimulus-response relationships have been addressed. They developed a model that describes the olfactory nerve response as a function of three factors, viz., the number of odorant molecules (N), the stimulus duration (T), and the stimulus volume (V). In addition, two models derived from this three-variable model were also found to predict the response well. These were the [F, N] model involving flow rate (F = V/T) and, ranking closely behind, the [C, T] model involving concentration (C = N/V). A model involving the delivery rate (D = N/T) and volume was found to predict the response poorly. These models imply very different stimulus-response relationships. The present study was designed to assess the validity of this earlier approach by testing specific predictions drawn from each of the models. Because of the excellence of the [F, N] model, one would predict that the response will not change when F and N are held constant in spite of proportional increases in V and T. Similarly, one would predict from the [C, T] model that the response will be constant when C and T are held constant in spite of proportional increases in N and V. Because of the poor showing of the [D, V] model, one would predict changes in the response even when D and V are held constant while N and T are increased proportionately. It was observed that when F and N were held constant, the response was, in fact, constant. When D and V were held constant, the response increased dramatically. When C and T were held constant, there was a statistically significant, but small, change in the response. These results support the approach taken by Mozell et al. (op. cit.) and highlight the applicability of the [F, N] model to peripheral olfactory processing. The results are discussed in terms of their impact on the traditional manner in which olfactory stimulus-response relationships are conceived.

A parametric study of the stimulation variables affecting the magnitude of the olfactory nerve response.

The magnitude of olfactory responses can be related to three primary variables [number of odorant molecules (N), sniff volume (V), and sniff duration (T)] and three derived variables [concentration (C = N/V), flow rate (F = V/T), and delivery rate (D = N/T)]. To evaluate the effects of these interdependent variables upon the olfactory response, the summated multiunit discharges were recorded from the olfactory nerves of nine frogs in response to octane presented at two levels (in 2:1 ratio) of each primary variable. This presentation defined eight "sniff" combinations representing three levels of each derived variable. In an ANOVA of the logs of the responses, the effect of each primary variable was highly significant, with no significant interactions. A multiplicative regression model incorporating the effects of the three primary variables represented responses exceedingly well, with positive effects of N and T and a negative effect of V. When, with this model, the effect of each of the derived variables was isolated from the effects of all other variables, the analysis showed a positive effect for C, a near-zero positive effect for D, and a negative effect for F. Placing certain constraints upon the model parameters generates 13 distinct one- and two-variable models (e.g., the [C, T] model requires N and V to have equal but opposite effects). In ranking these reduced models in terms of their ability to predict the neural response, the predictive ability of [F, N] and [C, T] was at least as good as that of the three-variable model.