Multidimensional representation of odors in the human olfactory cortex

The topology and geometry of neural representations

A central question for neuroscience is how to characterize brain representations of perceptual and cognitive content. An ideal characterization should distinguish different functional regions with robustness to noise and idiosyncrasies of individual brains that do not correspond to computational differences. Previous studies have characterized brain representations by their representational geometry, which is defined by the representational dissimilarity matrix (RDM), a summary statistic that abstracts from the roles of individual neurons (or responses channels) and characterizes the discriminability of stimuli. Here, we explore a further step of abstraction: from the geometry to the topology of brain representations. We propose topological representational similarity analysis, an extension of representational similarity analysis that uses a family of geotopological summary statistics that generalizes the RDM to characterize the topology while de-emphasizing the geometry. We evaluate this family of statistics in terms of the sensitivity and specificity for model selection using both simulations and functional MRI (fMRI) data. In the simulations, the ground truth is a data-generating layer representation in a neural network model and the models are the same and other layers in different model instances (trained from different random seeds). In fMRI, the ground truth is a visual area and the models are the same and other areas measured in different subjects. Results show that topology-sensitive characterizations of population codes are robust to noise and interindividual variability and maintain excellent sensitivity to the unique representational signatures of different neural network layers and brain regions.

Leveraging Multi-Echo EPI to Enhance BOLD Sensitivity in Task-based Olfactory fMRI

Functional magnetic resonance imaging (fMRI) using blood-oxygenation-level-dependent (BOLD) contrast relies on gradient echo echo-planar imaging (GE-EPI) to quantify dynamic susceptibility changes associated with the hemodynamic response to neural activity. However, acquiring BOLD fMRI in human olfactory regions is particularly challenging due to their proximity to the sinuses where large susceptibility gradients induce magnetic field distortions. BOLD fMRI of the human olfactory system is further complicated by respiratory artifacts that are highly correlated with event onsets in olfactory tasks. Multi-echo EPI (ME-EPI) acquires gradient echo data at multiple echo times (TEs) during a single acquisition and can leverage signal evolution over the multiple echo times to enhance BOLD sensitivity and reduce artifactual signal contributions. In the current study, we developed a ME-EPI acquisition protocol for olfactory task-based fMRI and demonstrated significant improvement in BOLD signal sensitivity over conventional single-echo EPI (1E-EPI). The observed improvement arose from both an increase in BOLD signal changes through a T 2 * -weighted echo combination and a reduction in non-BOLD artifacts through the application of the Multi-Echo Independent Components Analysis (ME-ICA) denoising method. This study represents one of the first direct comparisons between 1E-EPI and ME-EPI in high-susceptibility regions and provides compelling evidence in favor of using ME-EPI for future task-based fMRI studies.

Decomposition of an odorant in olfactory perception and neural representation

Molecules-the elementary units of substances-are commonly considered the units of processing in olfactory perception, giving rise to undifferentiated odour objects invariant to environmental variations. By selectively perturbing the processing of chemical substructures with adaptation ('the psychologist's microelectrode') in a series of psychophysical and neuroimaging experiments (458 participants), we show that two perceptually distinct odorants sharing part of their structural features become significantly less discernible following adaptation to a third odorant containing their non-shared structural features, in manners independent of olfactory intensity, valence, quality or general olfactory adaptation. The effect is accompanied by reorganizations of ensemble activity patterns in the posterior piriform cortex that parallel subjective odour quality changes, in addition to substructure-based neural adaptations in the anterior piriform cortex and amygdala. Central representations of odour quality and the perceptual outcome thus embed submolecular structural information and are malleable by recent olfactory encounters.

Semantic context-dependent neural representations of odors in the human piriform cortex revealed by 7T MRI

Olfactory perception depends not only on olfactory inputs but also on semantic context. Although multi-voxel activity patterns of the piriform cortex, a part of the primary olfactory cortex, have been shown to represent odor perception, it remains unclear whether semantic contexts modulate odor representation in this region. Here, we investigated whether multi-voxel activity patterns in the piriform cortex change when semantic context modulates odor perception and, if so, whether the modulated areas communicate with brain regions involved in semantic and memory processing beyond the piriform cortex. We also explored regional differences within the piriform cortex, which are influenced by olfactory input and semantic context. We used 2 × 2 combinations of word labels and odorants that were perceived as congruent and measured piriform activity with a 1-mm isotropic resolution using 7T MRI. We found that identical odorants labeled with different words were perceived differently. This labeling effect was observed in multi-voxel activity patterns in the piriform cortex, as the searchlight decoding analysis distinguished identical odors with different labels for half of the examined stimulus pairs. Significant functional connectivity was observed between parts of the piriform cortex that were modulated by labels and regions associated with semantic and memory processing. While the piriform multi-voxel patterns evoked by different olfactory inputs were also distinguishable, the decoding accuracy was significant for only one stimulus pair, preventing definitive conclusions regarding the locational differences between areas influenced by word labels and olfactory inputs. These results suggest that multi-voxel patterns of piriform activity can be modulated by semantic context, possibly due to communication between the piriform cortex and the semantic and memory regions.

Representational maps in the brain: concepts, approaches, and applications

Neural systems have evolved to process sensory stimuli in a way that allows for efficient and adaptive behavior in a complex environment. Recent technological advances enable us to investigate sensory processing in animal models by simultaneously recording the activity of large populations of neurons with single-cell resolution, yielding high-dimensional datasets. In this review, we discuss concepts and approaches for assessing the population-level representation of sensory stimuli in the form of a representational map. In such a map, not only are the identities of stimuli distinctly represented, but their relational similarity is also mapped onto the space of neuronal activity. We highlight example studies in which the structure of representational maps in the brain are estimated from recordings in humans as well as animals and compare their methodological approaches. Finally, we integrate these aspects and provide an outlook for how the concept of representational maps could be applied to various fields in basic and clinical neuroscience.

High-precision mapping reveals the structure of odor coding in the human brain

Odor perception is inherently subjective. Previous work has shown that odorous molecules evoke distributed activity patterns in olfactory cortices, but how these patterns map on to subjective odor percepts remains unclear. In the present study, we collected neuroimaging responses to 160 odors from 3 individual subjects (18 h per subject) to probe the neural coding scheme underlying idiosyncratic odor perception. We found that activity in the orbitofrontal cortex (OFC) represents the fine-grained perceptual identity of odors over and above coarsely defined percepts, whereas this difference is less pronounced in the piriform cortex (PirC) and amygdala. Furthermore, the implementation of perceptual encoding models enabled us to predict olfactory functional magnetic resonance imaging responses to new odors, revealing that the dimensionality of the encoded perceptual spaces increases from the PirC to the OFC. Whereas encoding of lower-order dimensions generalizes across subjects, encoding of higher-order dimensions is idiosyncratic. These results provide new insights into cortical mechanisms of odor coding and suggest that subjective olfactory percepts reside in the OFC.

Physicochemical features partially explain olfactory crossmodal correspondences

During the olfactory perception process, our olfactory receptors are thought to recognize specific chemical features. These features may contribute towards explaining our crossmodal perception. The physicochemical features of odors can be extracted using an array of gas sensors, also known as an electronic nose. The present study investigates the role that the physicochemical features of olfactory stimuli play in explaining the nature and origin of olfactory crossmodal correspondences, which is a consistently overlooked aspect of prior work. Here, we answer the question of whether the physicochemical features of odors contribute towards explaining olfactory crossmodal correspondences and by how much. We found a similarity of 49% between the perceptual and the physicochemical spaces of our odors. All of our explored crossmodal correspondences namely, the angularity of shapes, smoothness of textures, perceived pleasantness, pitch, and colors have significant predictors for various physicochemical features, including aspects of intensity and odor quality. While it is generally recognized that olfactory perception is strongly shaped by context, experience, and learning, our findings show that a link, albeit small (6-23%), exists between olfactory crossmodal correspondences and their underlying physicochemical features.

Odor discrimination is immune to the effects of verbal labels

For many odors that we encounter in daily life, we perceive their qualities without being able to specifically identify their sources-an experience termed the "tip-of-the-nose" phenomenon. Does learning an odor's identity alter our experience of it? Past work has shown that labeling odors can alter how we describe and react to them, but it remains an open question whether such changes extend to the level of perception, making an odor actually smell different. Here, in a set of odor classification experiments we tested whether attaching labels to odors can alter their perceptual discriminability. We found that even for odors whose reported similarity changed markedly when their identities were revealed, their discriminability remained unchanged by labels. Our findings indicate that two critical functions of olfaction-parsing the odor environment and supporting the subjective experience of odor qualities-access distinct odor representations within the olfactory processing stream.

Odor Pleasantness Modulates Functional Connectivity in the Olfactory Hedonic Processing Network

Olfactory hedonic evaluation is the primary dimension of olfactory perception and thus central to our sense of smell. It involves complex interactions between brain regions associated with sensory, affective and reward processing. Despite a recent increase in interest, several aspects of olfactory hedonic evaluation remain ambiguous: uncertainty surrounds the communication between, and interaction among, brain areas during hedonic evaluation of olfactory stimuli with different levels of pleasantness, as well as the corresponding supporting oscillatory mechanisms. In our study we investigated changes in functional interactions among brain areas in response to odor stimuli using electroencephalography (EEG). To this goal, functional connectivity networks were estimated based on phase synchronization between EEG signals using the weighted phase lag index (wPLI). Graph theoretic metrics were subsequently used to quantify the resulting changes in functional connectivity of relevant brain regions involved in olfactory hedonic evaluation. Our results indicate that odor stimuli of different hedonic values evoke significantly different interaction patterns among brain regions within the olfactory cortex, as well as in the anterior cingulate and orbitofrontal cortices. Furthermore, significant hemispheric laterality effects have been observed in the prefrontal and anterior cingulate cortices, specifically in the beta ((13–30) Hz) and gamma ((30–40) Hz) frequency bands.

Neural signatures of individual variability in context-dependent perception of ambiguous facial expression

How do we incorporate contextual information to infer others' emotional state? Here we employed a naturalistic context-dependent facial expression estimation task where participants estimated pleasantness levels of others' ambiguous expression faces when sniffing different contextual cues (e.g., urine, fish, water, and rose). Based on their pleasantness rating data, we placed participants on a context-dependency continuum and mapped the individual variability in the context-dependency onto the neural representation using a representational similarity analysis. We found that the individual variability in the context-dependency of facial expression estimation correlated with the activity level of the pregenual anterior cingulate cortex (pgACC) and the amygdala and was also decoded by the neural representation of the ventral anterior insula (vAI). A dynamic causal modeling revealed that those with higher context-dependency exhibited a greater degree of the modulation from vAI to the pgACC. These findings provide novel insights into the neural circuitry associated with the individual variability in context-dependent facial expression estimation and the first empirical evidence for individual variability in the predictive accounts of affective states.

Spatiotemporal dynamics of odor representations in the human brain revealed by EEG decoding

To elucidate when and where in the brain different aspects of odor perception emerge, we decoded odors from an electroencephalogram and associated the results with perception and source activities. The odor information was decoded 100 ms after odor onset at the earliest, with its signal sources estimated in and around the olfactory areas. The neural representation of odor unpleasantness emerged 300 ms after odor onset, followed by pleasantness and perceived quality at 500 ms. During this time, brain regions representing odor information spread rapidly from the olfactory areas to regions associated with emotional, semantic, and memory processing. The results suggested that odor perception emerges through computations in these areas, with different perceptual aspects having different spatiotemporal dynamics.

How the human brain translates olfactory inputs into diverse perceptions, from pleasurable floral smells to sickening smells of decay, is one of the fundamental questions in olfaction. To examine how different aspects of olfactory perception emerge in space and time in the human brain, we performed time-resolved multivariate pattern analysis of scalp-recorded electroencephalogram responses to 10 perceptually diverse odors and associated the resulting decoding accuracies with perception and source activities. Mean decoding accuracies of odors exceeded the chance level 100 ms after odor onset and reached maxima at 350 ms. The result suggests that the neural representations of individual odors were maximally separated at 350 ms. Perceptual representations emerged following the decoding peak: unipolar unpleasantness (neutral to unpleasant) from 300 ms, and pleasantness (neutral to pleasant) and perceptual quality (applicability to verbal descriptors such as “fruity” or “flowery”) from 500 ms after odor onset, with all these perceptual representations reaching their maxima after 600 ms. A source estimation showed that the areas representing the odor information, estimated based on the decoding accuracies, were localized in and around the primary and secondary olfactory areas at 100 to 350 ms after odor onset. Odor representations then expanded into larger areas associated with emotional, semantic, and memory processing, with the activities of these later areas being significantly associated with perception. These results suggest that initial odor information coded in the olfactory areas (<350 ms) evolves into their perceptual realizations (300 to >600 ms) through computations in widely distributed cortical regions, with different perceptual aspects having different spatiotemporal dynamics.

Validation of Olfactory Network Based on Brain Structural Connectivity and Its Association With Olfactory Test Scores

Olfactory perception is a complicated process involving multiple cortical and subcortical regions, of which the underlying brain dynamics are still not adequately mapped. Even in the definition of the olfactory primary cortex, there is a large degree of variation in parcellation templates used for investigating olfaction in neuroimaging studies. This complicates comparison between human olfactory neuroimaging studies. The present study aims to validate an olfactory parcellation template derived from both functional and anatomical data that applies structural connectivity (SC) to ensure robust connectivity to key secondary olfactory regions. Furthermore, exploratory analyses investigate if different olfactory parameters are associated with differences in the strength of connectivity of this structural olfactory fingerprint. By combining diffusion data with an anatomical atlas and advanced probabilistic tractography, we found that the olfactory parcellation had a robust SC network to key secondary olfactory regions. Furthermore, the study indicates that higher ratings of olfactory significance were associated with increased intra- and inter-hemispheric SC of the primary olfactory cortex. Taken together, these results suggest that the patterns of SC between the primary olfactory cortex and key secondary olfactory regions has potential to be used for investigating the nature of olfactory significance, hence strengthening the theory that individual differences in olfactory behaviour are encoded in the structural network fingerprint of the olfactory cortex.

Clinical Implications of Psychophysical Olfactory Testing: Assessment, Diagnosis, and Treatment Outcome

Purpose of Review

Olfactory dysfunction dramatically impairs quality of life with a prevalence of 20% in the general adult population. Psychophysical olfactory testing has been widely used to evaluate the ability to smell due to its validated utility and feasibility in clinic. This review summarizes the current literature regarding psychophysical olfactory testing and the clinical relevance of the olfactory testing with different components. Furthermore, the review highlights the diagnosis and treatment value of olfactory subtests in patients with olfactory dysfunction.

Recent Findings

With the accumulation of studies of psychophysical olfactory testing in olfactory disorders, the clinical relevance of olfactory testing with different components is expanding. Different olfactory domains present with distinct olfactory processing and cortical activity. Psychophysical assessment of olfaction with three domains reveals different levels of olfactory processing and might assist with analyzing the pathophysiologic mechanism of the various olfactory disorders. Furthermore, olfactory thresholds provided the largest amount of non-redundant information to the olfactory diagnosis. Sinonasal olfactory dysfunction and non-sinonasal-related olfactory dysfunction are emerging classifications of smell disorders with certain characteristics of olfactory impairment and different responses to the therapy including steroids, sinus surgery, and olfactory training.

Summary

These recent advancements should promote the understanding of psychophysical olfactory testing, the association between individual subcomponents and neurophysiological processes, and pave the way for precision assessment and treatment of the olfactory dysfunction.

Individual odor hedonic perception is coded in temporal joint network activity

INTRO

The human sense of smell is highly individual and characterized by a strong variability in the perception and evaluation of olfactory stimuli, depending on cultural imprint and current physiological conditions. Since this individual perspective has often been neglected in fMRI studies on olfactory hedonic coding, this study focuses on the neuronal activity and connectivity patterns resulting from subject-specific olfactory stimulation.

METHODS

Thirty-one normosmic participants took part in a fMRI block designed paradigm consisting of three olfactory stimulation sessions. The most pleasant and unpleasant odors were individually specified during a pre-test for each participant and validated in the main experiment. Mean activation and functional connectivity analysis focusing on the right and left piriform cortex were performed for the predefined olfactory regions-of-interest (ROIs) and compared between the three olfactory conditions.

RESULTS

Individual unpleasant olfactory stimulation as compared to pleasant or neutral did not alter mean BOLD activation in the predefined olfactory ROIs but led to a change in connectivity pattern in the right piriform cortex.

CONCLUSION

Our data suggests that the individual pleasantness of odors is not detectable by average BOLD magnitude changes in primary or secondary olfactory brain areas, but reflected in temporal patterns of joint activation that create a network between the right piriform cortex, the left insular cortex, the orbitofrontal cortex, and the precentral gyrus. This network may serve the evolutionary defense mechanism of olfaction by preparing goal-directed action.

SMILES to Smell: Decoding the Structure-Odor Relationship of Chemical Compounds Using the Deep Neural Network Approach

Finding the relationship between the structure of an odorant molecule and its associated smell has always been an extremely challenging task. The major limitation in establishing the structure-odor relation is the vague and ambiguous nature of the descriptor-labeling, especially when the sources of odorant molecules are different. With the advent of deep networks, data-driven approaches have been substantiated to achieve more accurate linkages between the chemical structure and its smell. In this study, the deep neural network (DNN) with physiochemical properties and molecular fingerprints (PPMF) and the convolution neural network (CNN) with chemical-structure images (IMG) are developed to predict the smells of chemicals using their SMILES notations. A data set of 5185 chemical compounds with 104 smell percepts was used to develop the multilabel prediction models. The accuracies of smell prediction from DNN + PPMF and CNN + IMG (Xception based) were found to be 97.3 and 98.3%, respectively, when applied on an independent test set of chemicals. The deep learning architecture combining both DNN + PPMF and CNN + IMG prediction models is proposed, which classifies smells and may help understand the generic mechanism underlying the relationship between chemical structure and smell perception.

Accounting for Subjectivity in Experimental Research on Human Olfaction

Although olfaction is a modality with great interindividual perceptual disparities, its subjective dimension has been let aside in modern research, in line with the overall neglect of consciousness in experimental psychology. However, following the renewed interest for the neural bases of consciousness, some methodological leads have been proposed to include subjectivity in experimental protocols. Here, we argue that adapting such methods to the field of olfaction will allow to rigorously acquire subjective reports, and we present several ways to do so. This will improve the understanding of diversity in odor perception and its underlying neural mechanisms.

Sustained effects of pleasant and unpleasant smells on resting state brain activity

Research suggests that transient emotional episodes produces sustained effects on psychological functions and brain activity during subsequent resting state. In this fMRI study we investigated whether transient emotions induced by smells could impact brain connectivity at rest in a valence-specific manner. The results suggest a sustained reconfiguration of parts of the default mode network which become more connected with areas implicated in olfactory processing, emotional learning, and action control. We found lingering effects of odorants on subsequent resting state that predominantly involved connections of the precuneus with a network comprising the insula, amygdala, medial orbital gyrus. Unpleasant smells in particular predicted greater coupling between insula, hippocampal structures, and prefrontal cortex, possible reflecting enhanced aversive learning and avoidance motivation. More broadly, our study illustrates a novel approach to characterize the impact of smells on brain function and differentiate the neural signatures of their valence, during task-free rest conditions.

Structure and flexibility in cortical representations of odour space

The cortex organizes sensory information to enable discrimination and generalization1-4. As systematic representations of chemical odour space have not yet been described in the olfactory cortex, it remains unclear how odour relationships are encoded to place chemically distinct but similar odours, such as lemon and orange, into perceptual categories, such as citrus5-7. Here, by combining chemoinformatics and multiphoton imaging in the mouse, we show that both the piriform cortex and its sensory inputs from the olfactory bulb represent chemical odour relationships through correlated patterns of activity. However, cortical odour codes differ from those in the bulb: cortex more strongly clusters together representations for related odours, selectively rewrites pairwise odour relationships, and better matches odour perception. The bulb-to-cortex transformation depends on the associative network originating within the piriform cortex, and can be reshaped by passive odour experience. Thus, cortex actively builds a structured representation of chemical odour space that highlights odour relationships; this representation is similar across individuals but remains plastic, suggesting a means through which the olfactory system can assign related odour cues to common and yet personalized percepts.

Central olfactory structures

Axons from the olfactory bulb (OB) project to multiple central structures of the brain, many of which, in turn, send axons back into the OB and/or to one another. These secondary sensory regions underlie many aspects of odor representation, valence, and learning, as well as serving some nonolfactory functions, though many details remain unclear. We here describe the connectivity and essential structural and functional properties of these postbulbar olfactory regions in the mammalian brain.

A methodological investigation of a flexible surface MRI coil to obtain functional signals from the human olfactory bulb

BACKGROUND

Mammalian olfaction begins with transduction in olfactory receptors, continues with extensive processing in the olfactory bulb, and culminates in cortical representation. Most rodent studies on the functional neuroanatomy of olfaction have concentrated on the olfactory bulb, yet whether this structure is tuned only to basic chemical features of odorants or also to higher-order perceptual features is unclear.

NEW METHOD

Whereas studies of the human brain can typically uncover involvement of higher-order feature extraction, this has not been possible in the case of the olfactory bulb, inaccessible to fMRI. The present study examined whether a novel method of acquisition using a facial coil could overcome this limitation.

RESULTS

A series of experiments provided preliminary evidence of odor-driven responses in the human olfactory bulb, and found that these responses differed between individuals.

COMPARISON WITH EXISTING METHODS AND CONCLUSIONS

The present preliminary technical achievement renders possible to design novel human odor fMRI studies by considering the olfactory system from the olfactory bulb to associative areas.

Odor quality profile is partially influenced by verbal cues

Characterizing an odor quality is difficult for humans. Ever-increasing physiological and behavioral studies have characterized odor quality and demonstrated high performance of human odor categorization. However, there are no precise methods for measuring the multidimensional axis of an odor quality. Furthermore, it can be altered by individual experience, even when using existing measurement methods for the multidimensional axis of odor such as odor profiling. It is, therefore, necessary to characterize patterns of odor quality with odor profiling and observe alterations in odor profiles under the influence of subjective rating conditions such as verbal cues. Considering the high performance of human odor categorization, we hypothesized that odor may have specific odor quality that is scarcely altered by verbal cues. We assessed odor responses to isovaleric acid with and without verbal cues and compared the results in each stimulation condition. We found that verbal cues influenced the rating of odor quality descriptors. Verbal cues weakly influenced the odor quality descriptors of high-rated value (upper 25%) compared to odor quality descriptors of low-rated value (lower 75%) by the survey test. Even under different verbal cue conditions, the same odor was classified in the same class when using high-rated odor quality descriptors. Our study suggests that people extract essential odor quality descriptors that represent the odor itself in order to efficiently quantify odor quality.

Individual Differences as a Key Factor to Uncover the Neural Underpinnings of Hedonic and Social Functions of Human Olfaction: Current Findings from PET and fMRI Studies and Future Considerations

The hedonic and social dimensions of olfactory perception are characterized by a great diversity across people. Whereas the cerebral processing underlying these aspects of odor perception have been widely explored in the last decades, very few brain imaging studies considered individual differences. This lack of consideration weakens the current models in the field, where the paradigm of universality is the norm. The present review is aimed at examining this issue. Through a synthetic summary, we will first present past studies suggesting that (1) hedonics are represented consistently throughout the olfactory system from primary to secondary areas, with a progressive cognitive modulation and integration with other senses, (2) social dimension of odors may be represented in a distinct pathway involving social and attentional networks. In a second, and more critical part, we will highlight the importance of individual differences for the cerebral study of human olfaction.

Specific intranasal and central trigeminal electrophysiological responses in Parkinson's disease

Olfactory dysfunction is a frequent early non-motor symptom of Parkinson's disease (PD). There is evidence that with regard to trigeminal perception, PD-related olfactory dysfunction is different from other olfactory disorders. More specifically, trigeminal sensitivity, when measured behaviorally, was unimpaired in PD patients as opposed to patients with non-Parkinsonian olfactory dysfunction (NPOD). We sought to investigate the trigeminal pathway by measuring electrophysiological recordings from the nasal epithelium and EEG-derived event-related potentials in response to a specific trigeminal stimulus in 21 PD patients and compare them to 23 patients with NPOD and 25 controls (C). The peripheral trigeminal response, as measured by the negative-mucosa potential, showed no difference between patients with PD and controls whereas PD patients showed faster responses than patients with NPOD, the latter having shown slower and larger responses than controls (18 PD, 14 NPOD, 20 C). The central trigeminal response, as measured by event-related potentials, revealed larger early component response in PD patients compared to patients with NPOD (15 PD, 21 NPOD, 23 C). As expected, psychophysical olfactory testing showed impaired olfactory function in both groups of patients as opposed to controls. Discriminant analysis revealed a model that could predict group membership for 80% of participants based on the negative-mucosa potential latency, olfactory threshold and discrimination tests. These results provide novel insights into the pattern of trigeminal activation in PD which will help to differentiate PD-related olfactory loss from NPOD, a crucial step towards establishing early screening batteries for PD including smell tests.

fMRI-Based Brain Responses to Olfactory Stimulation with Two Putatively Orexigenic Functional Food Ingredients at Two Different Concentrations in the Pig Model

Natural plant extracts are increasingly used as functional feed ingredients in animal husbandry and food ingredients in human alternative medicine to improve welfare and health. We investigated in 20 growing pigs via functional magnetic resonance imaging (fMRI) the brain blood oxygen level-dependent (BOLD) responses to olfactory stimulation with two sensory functional feed ingredients, A and B, at two different concentrations. Functional ingredient A contained extracts from Citrus sinensis (60% to 80%), and ingredient B contained a mixture of extracts Oreganum vulgarae (40% to 55%) and Cymbopogon flexuosus (20% to 25%). Increased concentration of ingredients induced a higher activation in reward and cognitive areas compared to lower concentrations. Moreover, considering both ingredients at the highest concentration, the ingredient A elicited higher brain responses in brain areas involved in hedonism/pleasantness compared to ingredient B, and more specifically in the caudate nucleus and orbitofrontal cortex. Our findings shed new light in the scope of emotion regulation through olfactory modulation via sensory functional ingredients, which opens the way to further preclinical studies in animal models and translational research in the context of nutrition, welfare, and health. PRACTICAL APPLICATION: Functional food/feed ingredients are gaining interest for improving health and welfare in humans and animals. Besides representing an alternative to antibiotics for example, food ingredients and their sensory characteristics might have a positive impact on emotions and consequently on well-being. Functional brain imaging in large animals such as in the pig model is a promising approach to investigate the central and behavioural effects of food ingredients, and determine the most effective blends and concentrations to modulate internal and emotional states.

Characterizing functional pathways of the human olfactory system

The central processing pathways of the human olfactory system are not fully understood. The olfactory bulb projects directly to a number of cortical brain structures, but the distinct networks formed by projections from each of these structures to the rest of the brain have not been well-defined. Here, we used functional magnetic resonance imaging and k-means clustering to parcellate human primary olfactory cortex into clusters based on whole-brain functional connectivity patterns. Resulting clusters accurately corresponded to anterior olfactory nucleus, olfactory tubercle, and frontal and temporal piriform cortices, suggesting dissociable whole-brain networks formed by the subregions of primary olfactory cortex. This result was replicated in an independent data set. We then characterized the unique functional connectivity profiles of each subregion, producing a map of the large-scale processing pathways of the human olfactory system. These results provide insight into the functional and anatomical organization of the human olfactory system.

Impaired Odor Perception in Autism Spectrum Disorder Is Associated with Decreased Activity in Olfactory Cortex

Autism Spectrum Disorders (ASDs) are characterized by atypical sensory functioning in the visual, tactile, and auditory systems. Although less explored, olfactory changes have been reported in ASD patients. To explore these changes on a neural level, 18 adults with ASD and 18 healthy neurotypical controls were examined in a 2-phase study. Participants were first tested for odor threshold and odor identification. Then, (i) structural magnetic resonance (MR) images of the olfactory bulb were acquired, and (ii) a functional MR imaging olfaction study was conducted. ASD patients exhibited decreased function for odor thresholds and odor identification; this was accompanied by a relatively decreased activation in the piriform cortex. In conclusion, these findings suggest, that the known alterations in olfaction in ASD are rooted in the primary olfactory cortex.

Chemical features mining provides new descriptive structure-odor relationships

An important goal in researching the biology of olfaction is to link the perception of smells to the chemistry of odorants. In other words, why do some odorants smell like fruits and others like flowers? While the so-called stimulus-percept issue was resolved in the field of color vision some time ago, the relationship between the chemistry and psycho-biology of odors remains unclear up to the present day. Although a series of investigations have demonstrated that this relationship exists, the descriptive and explicative aspects of the proposed models that are currently in use require greater sophistication. One reason for this is that the algorithms of current models do not consistently consider the possibility that multiple chemical rules can describe a single quality despite the fact that this is the case in reality, whereby two very different molecules can evoke a similar odor. Moreover, the available datasets are often large and heterogeneous, thus rendering the generation of multiple rules without any use of a computational approach overly complex. We considered these two issues in the present paper. First, we built a new database containing 1689 odorants characterized by physicochemical properties and olfactory qualities. Second, we developed a computational method based on a subgroup discovery algorithm that discriminated perceptual qualities of smells on the basis of physicochemical properties. Third, we ran a series of experiments on 74 distinct olfactory qualities and showed that the generation and validation of rules linking chemistry to odor perception was possible. Taken together, our findings provide significant new insights into the relationship between stimulus and percept in olfaction. In addition, by automatically extracting new knowledge linking chemistry of odorants and psychology of smells, our results provide a new computational framework of analysis enabling scientists in the field to test original hypotheses using descriptive or predictive modeling.

An important issue in olfaction sciences deals with the question of how a chemical information can be translated into percepts. This is known as the stimulus-percept problem. Here, we set out to better understand this issue by combining knowledge about the chemistry and cognition of smells with computational olfaction. We also assumed that not only one, but several physicochemical models may describe a given olfactory quality. To achieve this aim, a first challenge was to set up a database with ~1700 molecules characterized by chemical features and described by olfactory qualities (e.g. fruity, woody). A second challenge consisted in developing a computational model enabling the discrimination of olfactory qualities based on these chemical features. By meeting these 2 challenges, we provided for several olfactory qualities new chemical models describing why an odorant molecule smells fruity or woody (among others). For most qualities, multiple (rather than a single) chemical models were generated. These findings provide new elements of knowledge about the relationship between odorant chemistry and perception. They also make it possible to envisage concrete applications in the aroma and fragrance field where chemical characterization of smells is an important step in the design of new products.

Odorant features differentially modulate beta/gamma oscillatory patterns in anterior versus posterior piriform cortex

Oscillatory activity is a prominent characteristic of the olfactory system. We previously demonstrated that beta and gamma oscillations occurrence in the olfactory bulb (OB) is modulated by the physical properties of the odorant. However, it remains unknown whether such odor-related modulation of oscillatory patterns is maintained in the piriform cortex (PC) and whether those patterns are similar between the anterior PC (aPC) and posterior PC (pPC). The present study was designed to analyze how different odorant molecular features can affect the local field potential (LFP) oscillatory signals in both the aPC and the pPC in anesthetized rats. As reported in the OB, three oscillatory patterns were observed: standard pattern (gamma + beta), gamma-only and beta-only patterns. These patterns occurred with significantly different probabilities in the two PC areas. We observed that odor identity has a strong influence on the probability of occurrence of LFP beta and gamma oscillatory activity in the aPC. Thus, some odor coding mechanisms observed in the OB are retained in the aPC. By contrast, probability of occurrence of different oscillatory patterns is homogeneous in the pPC with beta-only pattern being the most prevalent one for all the different odor families. Overall, our results confirmed the functional heterogeneity of the PC with its anterior part tightly coupled with the OB and mainly encoding odorant features whereas its posterior part activity is not correlated with odorant features but probably more involved in associative and multi-sensory encoding functions.

Machine Learning in Human Olfactory Research

The complexity of the human sense of smell is increasingly reflected in complex and high-dimensional data, which opens opportunities for data-driven approaches that complement hypothesis-driven research. Contemporary developments in computational and data science, with its currently most popular implementation as machine learning, facilitate complex data-driven research approaches. The use of machine learning in human olfactory research included major approaches comprising 1) the study of the physiology of pattern-based odor detection and recognition processes, 2) pattern recognition in olfactory phenotypes, 3) the development of complex disease biomarkers including olfactory features, 4) odor prediction from physico-chemical properties of volatile molecules, and 5) knowledge discovery in publicly available big databases. A limited set of unsupervised and supervised machine-learned methods has been used in these projects, however, the increasing use of contemporary methods of computational science is reflected in a growing number of reports employing machine learning for human olfactory research. This review provides key concepts of machine learning and summarizes current applications on human olfactory data.

Neuroimaging of smell and taste

The senses of taste and smell developed early in evolution and are of high ecological and clinical relevance in humans. Chemosensory systems function, in large part, as hazard avoidance systems, thereby ensuring survival. Moreover, they play a critical role in nutrition and in determining the flavor of foods and beverages. Their dysfunction has been shown to be a key element of early stages of a number of diseases, including Alzheimer's and Parkinson's diseases. Advanced neuroimaging methods provide a unique means for understanding, in vivo, neural and psychological processing of smell, taste, and flavor, and how diseases can impact such processing. This chapter provides, from a neuroimaging perspective, a comprehensive overview of the anatomy and physiology involved in the odor and taste processing in the central nervous system. Some methodological challenges associated with chemosensory neuroimaging research are discussed. Multisensory integration, the mechanisms that enable holistic sensory experiences, is emphasized.

Learning to name smells increases activity in heteromodal semantic areas

Semantic description of odors is a cognitively demanding task. Learning to name smells is, however, possible with training. This study set out to examine how improvement in olfactory semantic knowledge following training reorganizes the neural representation of smells. First, 19 nonexpert volunteers were trained for 3 days; they were exposed (i) to odorants presented without verbal labels (perceptual learning) and (ii) to other odorants paired with lexicosemantic labels (associative learning). Second, the same participants were tested in a brain imaging study (fMRI) measuring hemodynamic responses to learned odors presented in both the perceptual and associative learning conditions. The lexicosemantic training enhanced the ability to describe smells semantically. Neurally, this change was associated with enhanced activity in a set of heteromodal areas-including superior frontal gyrus-and parietal areas. These findings demonstrate that odor-name associative learning induces recruitment of brain areas involved in the integration and representation of semantic attributes of sensory events. They also offer new insights into the brain plasticity underlying the acquisition of olfactory expertise in lay people. Hum Brain Mapp 38:5958-5969, 2017. © 2017 Wiley Periodicals, Inc.

Brain fingerprints of olfaction: a novel structural method for assessing olfactory cortical networks in health and disease

Olfactory deficits are a common (often prodromal) symptom of neurodegenerative or psychiatric disorders. As such, olfaction could have great potential as an early biomarker of disease, for example using neuroimaging to investigate the breakdown of structural connectivity profile of the primary olfactory networks. We investigated the suitability for this purpose in two existing neuroimaging maps of olfactory networks. We found problems with both existing neuroimaging maps in terms of their structural connectivity to known secondary olfactory networks. Based on these findings, we were able to merge the existing maps to a new template map of olfactory networks with connections to all key secondary olfactory networks. We introduce a new method that combines diffusion tensor imaging with probabilistic tractography and pattern recognition techniques. This method can obtain comprehensive and reliable fingerprints of the structural connectivity underlying the neural processing of olfactory stimuli in normosmic adults. Combining the novel proposed method for structural fingerprinting with the template map of olfactory networks has great potential to be used for future neuroimaging investigations of olfactory function in disease. With time, the proposed method may even come to serve as structural biomarker for early detection of disease.