Discrimination of Complex Odor Mixtures: A Study Using Wine Aroma Models

There are key unanswered questions when it comes to multi-component odor discrimination. This study was designed to assess discrimination of odorant mixtures that elicit a singular percept. We collected data to address the following two questions: 1) What odor features do humans notice when attempting to discriminate between subtly different odor mixtures? 2) Are odor mixtures easier to discriminate when an odorant is added, compared to when a component is removed? Using modern aroma chemistry techniques, an odor mixture resembling a generic white wine was constructed. This wine odor mixture was modified using a series of 3 esters which are commonly found in white wines that vary in chain length and branching. Participants performed a sequence of discrimination tasks for the addition / subtraction of modifiers to the base wine at different concentrations. Only one of the esters (ethyl-propanoate) led to a discriminable odor mixture. As concentration of the modifying odorant was increased, discrimination of odor mixtures was first reported because of changes in odor mixture familiarity and then intensity. We found similar sensitivity to changes in odor mixtures regardless whether the modifying compound was added or subtracted, suggesting that perceptual stability of odor mixtures is equally dependent on both imputing missing information (pattern completion) and disregarding extraneous information.

Decoding Odor Mixtures in the Dog Brain: An Awake fMRI Study

In working and practical contexts, dogs rely upon their ability to discriminate a target odor from distracting odors and other sensory stimuli. Using awake functional magnetic resonance imaging (fMRI) in 18 dogs, we examined the neural mechanisms underlying odor discrimination between 2 odors and a mixture of the odors. Neural activation was measured during the presentation of a target odor (A) associated with a food reward, a distractor odor (B) associated with nothing, and a mixture of the two odors (A+B). Changes in neural activation during the presentations of the odor stimuli in individual dogs were measured over time within three regions known to be involved with odor processing: the caudate nucleus, the amygdala, and the olfactory bulbs. Average activation within the amygdala showed that dogs maximally differentiated between odor stimuli based on the stimulus-reward associations by the first run, while activation to the mixture (A+B) was most similar to the no-reward (B) stimulus. To clarify the neural representation of odor mixtures in the dog brain, we used a random forest classifier to compare multilabel (elemental) versus multiclass (configural) models. The multiclass model performed much better than the multilabel (weighted-F1 0.44 vs. 0.14), suggesting the odor mixture was processed configurally. Analysis of the subset of high-performing dogs’ brain classification metrics revealed a network of olfactory information-carrying brain regions that included the amygdala, piriform cortex, and posterior cingulate. These results add further evidence for the configural processing of odor mixtures in dogs and suggest a novel way to identify high-performers based on brain classification metrics.

Configural perception of a binary olfactory mixture in honey bees, as in humans, rodents and newborn rabbits

ABSTRACTHow animals perceive and learn complex stimuli, such as mixtures of odorants, is a difficult problem, for which the definition of general rules across the animal kingdom remains elusive. Recent experiments conducted in human and rodent adults as well as newborn rabbits suggested that these species process particular odor mixtures in a similar, configural manner. Thus, the binary mixture of ethyl isobutyrate (EI) and ethyl maltol (EM) induces configural processing in humans, who perceive a mixture odor quality (pineapple) that is distinct from the quality of each component (strawberry and caramel). Similarly, rabbit neonates treat the mixture differently, at least in part, from its components. In the present study, we asked whether the properties of the EI.EM mixture extend to an influential invertebrate model, the honey bee Apis mellifera. We used appetitive conditioning of the proboscis extension response to evaluate how bees perceive the EI.EM mixture. In a first experiment, we measured perceptual similarity between this mixture and its components in a generalization protocol. In a second experiment, we measured the ability of bees to differentiate between the mixture and both of its components in a negative patterning protocol. In each experimental series, the performance of bees with this mixture was compared with that obtained with four other mixtures, chosen from previous work in humans, newborn rabbits and bees. Our results suggest that when having to differentiate mixture and components, bees treat the EI.EM in a robust configural manner, similarly to mammals, suggesting the existence of common perceptual rules across the animal kindgdom.

Discrimination of Complex Odor Mixtures: A Study Using Wine Aroma Models

There are key unanswered questions when it comes to odor mixture discrimination. This study was designed to assess some of those questions regarding configural odor mixture discrimination in humans. We collected data to address the following two questions: 1) What odor features do humans notice when attempting to discriminate between subtly different odor mixtures? 2) Are odor mixtures easier to discriminate when an odorant is added, compared to when a component is removed? Using modern aroma chemistry techniques, an odor mixture resembling a generic white wine was constructed. This wine odor mixture was modified using a series of 3 esters which are commonly found in white wines that vary in chain length and branching. Participants performed a sequence of discrimination tasks for the addition / subtraction of modifiers to the base wine at different concentrations. Only one of the esters (ethyl-propanoate) led to a discriminable odor mixture. As concentration of the modifying odorant was increased, discrimination of odor mixtures was first reported because of changes in odor mixture familiarity and then intensity. We found similar sensitivity odor mixture discrimination regardless of addition or subtraction of modifying compounds, suggesting that perceptual stability of odor mixtures is equally dependent on both imputing missing information (pattern completion) and disregarding extraneous information.

Odor mixture perception: can molecular complexity be a factor determining elemental or configural perception?

Odor mixtures can evoke smells that differ from those of their individual odor components. Research has revealed the existence of two perceptual modes, in which a mixture can be perceived as either the original smells of its individual components (elemental) or as a novel smell (configural). However, the factors underlying the perceptual transformation that occurs when smelling a mixture versus its original components remain unclear. Therefore, the present study aimed to identify the properties of odorants that affect olfactory perception of odor mixtures, focusing on the structural complexity of an odorant. We conducted psychophysical experiments in which different groups of participants were instructed to provide olfactory perceptual descriptions of low-, medium-, and high-complexity odor mixtures or components, respectively. To investigate the perceptual modes induced by the mixtures, we compared the participants’ evaluations between mixtures and components via two types of analyses. First, we compared each olfactory description following quantification via principal component analysis. We then compared data based on seven major olfactory perceptual groups. We observed that odor mixtures composed of low-complexity odorants were perceived as relatively novel smells with regard to both minor (olfactory descriptions) and major (perceptual community) odor qualities than medium- and high-complexity mixtures. Such information may further our understanding of the olfactory perceptual modes of odor mixtures.

Habituation as a neural algorithm for online odor discrimination

Habituation is a form of simple memory that suppresses neural activity in response to repeated, neutral stimuli. This process is critical in helping organisms guide attention toward the most salient and novel features in the environment. Here, we follow known circuit mechanisms in the fruit fly olfactory system to derive a simple algorithm for habituation. We show, both empirically and analytically, that this algorithm is able to filter out redundant information, enhance discrimination between odors that share a similar background, and improve detection of novel components in odor mixtures. Overall, we propose an algorithmic perspective on the biological mechanism of habituation and use this perspective to understand how sensory physiology can affect odor perception. Our framework may also help toward understanding the effects of habituation in other more sophisticated neural systems.

Widespread receptor-driven modulation in peripheral olfactory coding

Olfactory responses to single odors have been well characterized but in reality we are continually presented with complex mixtures of odors. We performed high-throughput analysis of single-cell responses to odor blends using Swept Confocally Aligned Planar Excitation (SCAPE) microscopy of intact mouse olfactory epithelium, imaging ~10,000 olfactory sensory neurons in parallel. In large numbers of responding cells, mixtures of odors did not elicit a simple sum of the responses to individual components of the blend. Instead, many neurons exhibited either antagonism or enhancement of their response in the presence of another odor. All eight odors tested acted as both agonists and antagonists at different receptors. We propose that this peripheral modulation of responses increases the capacity of the olfactory system to distinguish complex odor mixtures.

Superior Identification of Component Odors in a Mixture Is Linked to Autistic Traits in Children and Adults

Most familiar odors are complex mixtures of volatile molecules, which the olfactory system automatically synthesizes into a perceptual whole. However, odors are rarely encountered in isolation; thus, the brain must also separate distinct odor objects from complex and variable backgrounds. In vision, autistic traits are associated with superior performance in tasks that require focus on the local features of a perceptual scene. The aim of the present study was to determine whether the same advantage was observed in the analysis of olfactory scenes. To do this, we compared the ability of 1) 40 young adults (aged 16–35) with high (n = 20) and low levels of autistic traits and 2) 20 children (aged 7–11), with (n = 10) and without an autism spectrum disorder diagnosis, to identify individual odor objects presented within odor mixtures. First, we used a 4-alternative forced choice task to confirm that both adults and children were able to reliably identify 8 blended fragrances, representing food-related odors, when presented individually. We then used the same forced choice format to test participants’ ability to identify the odors when they were combined in either binary or ternary mixtures. Adults with high levels of autistic traits showed superior performance on binary but not ternary mixture trials, whereas children with an autism spectrum disorder diagnosis outperformed age-matched neurotypical peers, irrespective of mixture complexity. These findings indicate that the local processing advantages associated with high levels of autistic traits in visual tasks are also apparent in a task requiring analytical processing of odor mixtures.