Olfactory coding with all-or-nothing glomeruli

The primacy model and the structure of olfactory space

Understanding sensory processing involves relating the stimulus space, its neural representation, and perceptual quality. In olfaction, the difficulty in establishing these links lies partly in the complexity of the underlying odor input space and perceptual responses. Based on the recently proposed primacy model for concentration invariant odor identity representation and a few assumptions, we have developed a theoretical framework for mapping the odor input space to the response properties of olfactory receptors. We analyze a geometrical structure containing odor representations in a multidimensional space of receptor affinities and describe its low-dimensional implementation, the primacy hull. We propose the implications of the primacy hull for the structure of feedforward connectivity in early olfactory networks. We test the predictions of our theory by comparing the existing receptor-ligand affinity and connectivity data obtained in the fruit fly olfactory system. We find that the Kenyon cells of the insect mushroom body integrate inputs from the high-affinity (primacy) sets of olfactory receptors in agreement with the primacy theory.

Stimulus-Induced Theta-Band LFP Oscillations Format Neuronal Representations of Social Chemosignals in the Mouse Accessory Olfactory Bulb

Social communication is crucial for the survival of many species. In most vertebrates, a dedicated chemosensory system, the vomeronasal system (VNS), evolved to process ethologically relevant chemosensory cues. The first central processing stage of the VNS is the accessory olfactory bulb (AOB), which sends information to downstream brain regions via AOB mitral cells (AMCs). Recent studies provided important insights about the functional properties of AMCs, but little is known about the principles that govern their coordinated activity. Here, we recorded local field potentials (LFPs) and single-unit activity in the AOB of adult male and female mice during presentation of natural stimuli. Our recordings reveal prominent LFP theta-band oscillatory episodes with a characteristic spatial pattern across the AOB. Throughout an experiment, the AOB network shows varying degrees of similarity to this pattern, in a manner that depends on the sensory stimulus. Analysis of LFP signal polarity and single-unit activity indicates that oscillatory episodes are generated locally within the AOB, likely representing a reciprocal interaction between AMCs and granule cells. Notably, spike times of many AMCs are constrained to the negative LFP oscillation phase in a manner that can drastically affect integration by downstream processing stages. Based on these observations, we propose that LFP oscillations may gate, bind, and organize outgoing signals from individual AOB neurons to downstream processing stages. Our findings suggest that, as in other neuronal systems and brain regions, population-level oscillations play a key role in organizing and enhancing transmission of socially relevant chemosensory information.SIGNIFICANCE STATEMENT The accessory olfactory bulb (AOB) is the first central stage of the vomeronasal system, a chemosensory system dedicated to processing cues from other organisms. Information from the AOB is conveyed to other brain regions via activity of its principal neurons, AOB mitral cells (AMCs). Here, we show that socially relevant sensory stimulation of the mouse vomeronasal system leads not only to changes in AMC activity, but also to distinct theta-band (∼5 Hz) oscillatory episodes in the local field potential. Notably AMCs favor the negative phase of these oscillatory events. Our findings suggest a novel mechanism for the temporal coordination of distributed patterns of neuronal activity, which can serve to efficiently activate downstream processing stages.

Exploring natural odour landscapes: A case study with implications for human-biting insects

The natural world is full of odours-blends of volatile chemicals emitted by potential sources of food, social partners, predators, and pathogens. Animals rely heavily on these signals for survival and reproduction. Yet we remain remarkably ignorant of the composition of the chemical world. How many compounds do natural odours typically contain? How often are those compounds shared across stimuli? What are the best statistical strategies for discrimination? Answering these questions will deliver crucial insight into how brains can most efficiently encode olfactory information. Here, we undertake the first large-scale survey of vertebrate body odours, a set of stimuli relevant to blood-feeding arthropods. We quantitatively characterize the odour of 64 vertebrate species (mostly mammals), representing 29 families and 13 orders. We confirm that these stimuli are complex blends of relatively common, shared compounds and show that they are much less likely to contain unique components than are floral odours-a finding with implications for olfactory coding in blood feeders and floral visitors. We also find that vertebrate body odours carry little phylogenetic information, yet show consistency within a species. Human odour is especially unique, even compared to the odour of other great apes. Finally, we use our newfound understanding of odour-space statistics to make specific predictions about olfactory coding, which align with known features of mosquito olfactory systems. Our work provides one of the first quantitative descriptions of a natural odour space and demonstrates how understanding the statistics of sensory environments can provide novel insight into sensory coding and evolution.

What the odor is not: Estimation by elimination

Olfactory systems use a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. We propose a method of decoding such distributed representations by exploiting a statistical fact: Receptors that do not respond to an odor carry more information than receptors that do because they signal the absence of all odorants that bind to them. Thus, it is easier to identify what the odor is not rather than what the odor is. For realistic numbers of receptors, response functions, and odor complexity, this method of elimination turns an underconstrained decoding problem into a solvable one, allowing accurate determination of odorants in a mixture and their concentrations. We construct a neural network realization of our algorithm based on the structure of the olfactory pathway.

An Evolutionary Microcircuit Approach to the Neural Basis of High Dimensional Sensory Processing in Olfaction

Odor stimuli consist of thousands of possible molecules, each molecule with many different properties, each property a dimension of the stimulus. Processing these high dimensional stimuli would appear to require many stages in the brain to reach odor perception, yet, in mammals, after the sensory receptors this is accomplished through only two regions, the olfactory bulb and olfactory cortex. We take a first step toward a fundamental understanding by identifying the sequence of local operations carried out by microcircuits in the pathway. Parallel research provided strong evidence that processed odor information is spatial representations of odor molecules that constitute odor images in the olfactory bulb and odor objects in olfactory cortex. Paleontology provides a unique advantage with evolutionary insights providing evidence that the basic architecture of the olfactory pathway almost from the start ∼330 million years ago (mya) has included an overwhelming input from olfactory sensory neurons combined with a large olfactory bulb and olfactory cortex to process that input, driven by olfactory receptor gene duplications. We identify a sequence of over 20 microcircuits that are involved, and expand on results of research on several microcircuits that give the best insights thus far into the nature of the high dimensional processing.

Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception

How does neural activity generate perception? Finding the combinations of spatial or temporal activity features (such as neuron identity or latency) that are consequential for perception remains challenging. We trained mice to recognize synthetic odors constructed from parametrically defined patterns of optogenetic activation, then measured perceptual changes during extensive and controlled perturbations across spatiotemporal dimensions. We modeled recognition as the matching of patterns to learned templates. The templates that best predicted recognition were sequences of spatially identified units, ordered by latencies relative to each other (with minimal effects of sniff). Within templates, individual units contributed additively, with larger contributions from earlier-activated units. Our synthetic approach reveals the fundamental logic of the olfactory code and provides a general framework for testing links between sensory activity and perception.

The contribution of temporal coding to odor coding and odor perception in humans

Whether neurons encode information through their spike rates, their activity times or both is an ongoing debate in systems neuroscience. Here, we tested whether humans can discriminate between a pair of temporal odor mixtures (TOMs) composed of the same two components delivered in rapid succession in either one temporal order or its reverse. These TOMs presumably activate the same olfactory neurons but at different times and thus differ mainly in the time of neuron activation. We found that most participants could hardly discriminate between TOMs, although they easily discriminated between a TOM and one of its components. By contrast, participants succeeded in discriminating between the TOMs when they were notified of their successive nature in advance. We thus suggest that the time of glomerulus activation can be exploited to extract odor-related information, although it does not change the odor perception substantially, as should be expected from an odor code per se.

Decreased amplitude and reliability of odor-evoked responses in two mouse models of autism

Sensory processing deficits are increasingly recognized as core symptoms of autism spectrum disorders (ASDs). However the molecular and circuit mechanisms that lead to sensory deficits are unknown. We show that two molecularly disparate mouse models of autism display similar deficits in sensory-evoked responses in the mouse olfactory system. We find that both Cntnap2- and Shank3-deficient mice of both sexes exhibit reduced response amplitude and trial-to-trial reliability during repeated odor presentation. Mechanistically, we show that both mouse models have weaker and fewer synapses between olfactory sensory nerve (OSN) terminals and olfactory bulb tufted cells and weaker synapses between OSN terminals and inhibitory periglomerular cells. Consequently, deficits in sensory processing provide an excellent candidate phenotype for analysis in ASDs.NEW & NOTEWORTHY The genetics of autism spectrum disorder (ASD) are complex. How the many risk genes generate the similar sets of symptoms that define the disorder is unknown. In particular, little is understood about the functional consequences of these genetic alterations. Sensory processing deficits are important aspects of the ASD diagnosis and may be due to unreliable neural circuits. We show that two mouse models of autism, Cntnap2- and Shank3-deficient mice, display reduced odor-evoked response amplitudes and reliability. These data suggest that altered sensory-evoked responses may constitute a circuit phenotype in ASDs.

Primacy coding facilitates effective odor discrimination when receptor sensitivities are tuned

The olfactory system faces the difficult task of identifying an enormous variety of odors independent of their intensity. Primacy coding, where the odor identity is encoded by the receptor types that respond earliest, might provide a compact and informative representation that can be interpreted efficiently by the brain. In this paper, we analyze the information transmitted by a simple model of primacy coding using numerical simulations and statistical descriptions. We show that the encoded information depends strongly on the number of receptor types included in the primacy representation, but only weakly on the size of the receptor repertoire. The representation is independent of the odor intensity and the transmitted information is useful to perform typical olfactory tasks with close to experimentally measured performance. Interestingly, we find situations in which a smaller receptor repertoire is advantageous for discriminating odors. The model also suggests that overly sensitive receptor types could dominate the entire response and make the whole array useless, which allows us to predict how receptor arrays need to adapt to stay useful during environmental changes. Taken together, we show that primacy coding is more useful than simple binary and normalized coding, essentially because the sparsity of the odor representations is independent of the odor statistics, in contrast to the alternatives. Primacy coding thus provides an efficient odor representation that is independent of the odor intensity and might thus help to identify odors in the olfactory cortex.

Humans can identify odors independent of their intensity. Experimental data suggest that this is accomplished by representing the odor identity by the earliest responding receptor types. Using theoretical modeling, we here show that such a primacy code outperforms alternative encodings and allows discriminating odors with close to experimentally measured performance. This performance depends strongly on the number of receptors considered in the primacy code, but the receptor repertoire size is less important. The model also suggests a strong evolutionary pressure on the receptor sensitivities, which could explain observed receptor copy number adaptations. By predicting psycho-physical experiments, the model will thus contribute to our understanding of the olfactory system.

Deconstructing Odorant Identity via Primacy in Dual Networks

In the olfactory system, odor percepts retain their identity despite substantial variations in concentration, timing, and background. We study a novel strategy for encoding intensity-invariant stimulus identity that is based on representing relative rather than absolute values of stimulus features. For example, in what is known as the primacy coding model, odorant identities are represented by the conditions that some odorant receptors are activated more strongly than others. Because, in this scheme, odorant identity depends only on the relative amplitudes of olfactory receptor responses, identity is invariant to changes in both intensity and monotonic nonlinear transformations of its neuronal responses. Here we show that sparse vectors representing odorant mixtures can be recovered in a compressed sensing framework via elastic net loss minimization. In the primacy model, this minimization is performed under the constraint that some receptors respond to a given odorant more strongly than others. Using duality transformation, we show that this constrained optimization problem can be solved by a neural network whose Lyapunov function represents the dual Lagrangian and whose neural responses represent the Lagrange coefficients of primacy and other constraints. The connectivity in such a dual network resembles known features of connectivity in olfactory circuits. We thus propose that networks in the piriform cortex implement dual computations to compute odorant identity with the sparse activities of individual neurons representing Lagrange coefficients. More generally, we propose that sparse neuronal firing rates may represent Lagrange multipliers, which we call the dual brain hypothesis. We show such a formulation is well suited to solve problems with multiple interacting relative constraints.

Analysis of the Drosophila melanogaster anti-ovarian response to honey bee queen mandibular pheromone

Queen mandibular pheromone (QMP) is a potent reproductive signal to which honey bee workers respond by suppressing their ovaries and adopting alloparental roles within the colony. This anti-ovarian effect of QMP on workers can, surprisingly, be induced in other insects, including fruit flies, in which females exposed to synthetic QMP develop smaller ovaries with fewer eggs. In this study, we use the Drosophila melanogaster model to identify the components of synthetic QMP required for the anti-ovarian effect. We found that virgin females respond strongly to 9-oxo-2-decenoic acid and 10-hydroxy-2-decenoic acid (10HDA), suggesting that the decenoic acid components of QMP are essential for the anti-ovarian response. Further, a nuclear factor of activated T-cells reporter system revealed neurones expressing the olfactory receptors Or-56a, Or-49b and Or-98a are activated by QMP in the antenna. In addition, we used olfactory receptor GAL4 drivers and a neuronal activator (a neuronal activating bacterial sodium channel) to test whether the candidate neurones are potential labelled lines for a decenoic acid response. We identified Or-49b as a potential candidate receiver of the 10HDA signal. Finally, the anti-ovarian response to synthetic QMP is not mediated by decreasing the titre of the reproductive hormones ecdysone and juvenile hormone.

Odorant mixtures elicit less variable and faster responses than pure odorants

In natural environments, odors are typically mixtures of several different chemical compounds. However, the implications of mixtures for odor processing have not been fully investigated. We have extended a standard olfactory receptor model to mixtures and found through its mathematical analysis that odorant-evoked activity patterns are more stable across concentrations and first-spike latencies of receptor neurons are shorter for mixtures than for pure odorants. Shorter first-spike latencies arise from the nonlinear dependence of binding rate on odorant concentration, commonly described by the Hill coefficient, while the more stable activity patterns result from the competition between different ligands for receptor sites. These results are consistent with observations from numerical simulations and physiological recordings in the olfactory system of insects. Our results suggest that mixtures allow faster and more reliable olfactory coding, which could be one of the reasons why animals often use mixtures in chemical signaling.

Dynamic contrast enhancement and flexible odor codes

Sensory stimuli evoke spiking activities patterned across neurons and time that are hypothesized to encode information about their identity. Since the same stimulus can be encountered in a multitude of ways, how stable or flexible are these stimulus-evoked responses? Here we examine this issue in the locust olfactory system. In the antennal lobe, we find that both spatial and temporal features of odor-evoked responses vary in a stimulus-history dependent manner. The response variations are not random, but allow the antennal lobe circuit to enhance the uniqueness of the current stimulus. Nevertheless, information about the odorant identity is conf ounded due to this contrast enhancement computation. Notably, predictions from a linear logical classifier (OR-of-ANDs) that can decode information distributed in flexible subsets of neurons match results from behavioral experiments. In sum, our results suggest that a trade-off between stability and flexibility in sensory coding can be achieved using a simple computational logic.

Sensory stimuli are encountered in multiple ways necessitating a flexible and adaptive neural population code for identification. Here, the authors show that the dynamics of odor coding in the locust antennal lobe varies with stimulus context so as to enhance the target stimulus representation.

Implications for human odor sensing revealed from the statistics of odorant-receptor interactions

Binding of odorants to olfactory receptors (ORs) elicits downstream chemical and neural signals, which are further processed to odor perception in the brain. Recently, Mainland and colleagues have measured more than 500 pairs of odorant-OR interaction by a high-throughput screening assay method, opening a new avenue to understanding the principles of human odor coding. Here, using a recently developed minimal model for OR activation kinetics, we characterize the statistics of OR activation by odorants in terms of three empirical parameters: the half-maximum effective concentration EC₅₀, the efficacy, and the basal activity. While the data size of odorants is still limited, the statistics offer meaningful information on the breadth and optimality of the tuning of human ORs to odorants, and allow us to relate the three parameters with the microscopic rate constants and binding affinities that define the OR activation kinetics. Despite the stochastic nature of the response expected at individual OR-odorant level, we assess that the confluence of signals in a neuron released from the multitude of ORs is effectively free of noise and deterministic with respect to changes in odorant concentration. Thus, setting a threshold to the fraction of activated OR copy number for neural spiking binarizes the electrophysiological signal of olfactory sensory neuron, thereby making an information theoretic approach a viable tool in studying the principles of odor perception.

Despite the decades of research, quantitative details of human olfaction have remained largely unexplored. However, a high-throughput measurement has recently been carried out to produce dose-response data between a set of odorants and a repertoire of human olfactory receptors. We characterized each pair of odorant-receptor interaction in terms of EC50, efficacy, and basal level, a strategy often adopted in biochemical, pharmacological sciences to describe the response of receptors to cognate ligands. The distributions of EC50 values and efficacies acquired from the analysis provide glimpses into how human olfactory receptors are tuned to odorants. Specifically, the response of human ORs is optimized around ∼ 100μM of odorant. Next, the efficacies of OR responses to odorants are bi-exponentially distributed, which indicates that the strength of odorant-OR interaction is classified into strong and weak subgroups. By showing that the stochastic response of individual receptor to odorant can effectively be binarized at cellular level through olfactory processes, we also provide a theoretical basis for an information theoretical approach in studying the principles of odor perception.

Antagonism in olfactory receptor neurons and its implications for the perception of odor mixtures

Natural environments feature mixtures of odorants of diverse quantities, qualities and complexities. Olfactory receptor neurons (ORNs) are the first layer in the sensory pathway and transmit the olfactory signal to higher regions of the brain. Yet, the response of ORNs to mixtures is strongly non-additive, and exhibits antagonistic interactions among odorants. Here, we model the processing of mixtures by mammalian ORNs, focusing on the role of inhibitory mechanisms. We show how antagonism leads to an effective ‘normalization’ of the ensemble ORN response, that is, the distribution of responses of the ORN population induced by any mixture is largely independent of the number of components in the mixture. This property arises from a novel mechanism involving the distinct statistical properties of receptor binding and activation, without any recurrent neuronal circuitry. Normalization allows our encoding model to outperform non-interacting models in odor discrimination tasks, leads to experimentally testable predictions and explains several psychophysical experiments in humans.

When ordering in a coffee shop, you probably recognize and enjoy the aroma of freshly roasted coffee beans. But as well as coffee, you can also smell the croissants behind the counter and maybe even the perfume or cologne of the person next to you. Each of these scents consists of a collection of chemicals, or odorants. To distinguish between the aroma of coffee and that of croissants, your brain must group the odorants appropriately and then keep the groups separate from each other.

This is not a trivial task. Odorants bind to proteins called odorant receptors found on the surface of cells in the nose called olfactory receptor neurons. But each odorant does not have its own dedicated receptor. Instead, a single odorant will bind to multiple types of odorant receptors, and thus, each olfactory receptor neuron may respond to multiple odorants. So how does the brain encode mixtures of odorants in a way that allows us to distinguish one aroma from another?

Reddy, Zak et al. have developed a computational model to explain how this process works. The model assumes that an odorant triggers a response in an olfactory receptor neuron via two steps. First, the odorant binds to an odorant receptor. Second, the bound odorant activates the receptor. But the odorant that binds most strongly to a receptor will not necessarily be the odorant that is best at activating that receptor.

This allows a phenomenon called competitive antagonism to occur. This is when one odorant in a mixture binds more strongly to a receptor than the other odorants, but only weakly activates that receptor. In so doing, the strongly bound odorant prevents the other odorants from binding to and activating the receptor. This helps tame the dominating influence of background odors, which might otherwise saturate the responses of individual olfactory receptor neurons.

Reddy, Zak et al. show that processes such as competitive antagonism enable olfactory receptor neurons to encode all of the odors within a mixture. The model can explain various phenomena observed in experiments and it adds to our understanding of how the brain generates our sense of smell. The model may also be relevant to other biological systems that must filter weak signals from a dominant background. These include the immune system, which must distinguish a small set of foreign proteins from the much larger number of proteins that make up our bodies.

Behavioral readout of spatio-temporal codes in olfaction

Neural recordings performed at an increasing scale and resolution have revealed complex, spatio-temporally precise patterns of activity in the olfactory system. Multiple models may explain the functional consequences of the spatio-temporal olfactory code, but the link to behavior remains unclear. Recent evidence in the field suggests a behavioral sensitivity to both fine spatial and temporal features in the code. How these features and combinations of features give rise to olfactory behavior is the subject of active research in the field. Modern genetic and optogenetic methods show great promise in testing the link between olfactory codes and behavior.

Evidence for a shape-based recognition of odorants in vivo in the human nose from an analysis of the molecular mechanism of lily-of-the-valley odorants detection in the Lilial and Bourgeonal family using the C/Si/Ge/Sn switch strategy

We performed an analysis of possible mechanisms of ligand recognition in the human nose. The analysis is based on in vivo odor threshold determination and in vitro Ca2+ imaging assays with a C/Si/Ge/Sn switch strategy applied to the compounds Lilial and Bourgeonal, to differentiate between different molecular mechanisms of odorant detection. Our results suggest that odorant detection under threshold conditions is mainly based on the molecular shape, i.e. the van der Waals surface, and electrostatics of the odorants. Furthermore, we show that a single olfactory receptor type is responsible for odor detection of Bourgeonal at the threshold level in humans in vivo. Carrying out a QM analysis of vibrational energies contained in the odorants, there is no evidence for a vibration-based recognition.

Olfactory receptor neurons use gain control and complementary kinetics to encode intermittent odorant stimuli

Insects find food and mates by navigating odorant plumes that can be highly intermittent, with intensities and durations that vary rapidly over orders of magnitude. Much is known about olfactory responses to pulses and steps, but it remains unclear how olfactory receptor neurons (ORNs) detect the intensity and timing of natural stimuli, where the absence of scale in the signal makes detection a formidable olfactory task. By stimulating Drosophila ORNs in vivo with naturalistic and Gaussian stimuli, we show that ORNs adapt to stimulus mean and variance, and that adaptation and saturation contribute to naturalistic sensing. Mean-dependent gain control followed the Weber-Fechner relation and occurred primarily at odor transduction, while variance-dependent gain control occurred at both transduction and spiking. Transduction and spike generation possessed complementary kinetic properties, that together preserved the timing of odorant encounters in ORN spiking, regardless of intensity. Such scale-invariance could be critical during odor plume navigation.

Normalized Neural Representations of Complex Odors

The olfactory system removes correlations in natural odors using a network of inhibitory neurons in the olfactory bulb. It has been proposed that this network integrates the response from all olfactory receptors and inhibits them equally. However, how such global inhibition influences the neural representations of odors is unclear. Here, we study a simple statistical model of the processing in the olfactory bulb, which leads to concentration-invariant, sparse representations of the odor composition. We show that the inhibition strength can be tuned to obtain sparse representations that are still useful to discriminate odors that vary in relative concentration, size, and composition. The model reveals two generic consequences of global inhibition: (i) odors with many molecular species are more difficult to discriminate and (ii) receptor arrays with heterogeneous sensitivities perform badly. Comparing these predictions to experiments will help us to understand the role of global inhibition in shaping normalized odor representations in the olfactory bulb.

Reading Out Olfactory Receptors: Feedforward Circuits Detect Odors in Mixtures without Demixing

The olfactory system, like other sensory systems, can detect specific stimuli of interest amidst complex, varying backgrounds. To gain insight into the neural mechanisms underlying this ability, we imaged responses of mouse olfactory bulb glomeruli to mixtures. We used this data to build a model of mixture responses that incorporated nonlinear interactions and trial-to-trial variability and explored potential decoding mechanisms that can mimic mouse performance when given glomerular responses as input. We find that a linear decoder with sparse weights could match mouse performance using just a small subset of the glomeruli (∼15). However, when such a decoder is trained only with single odors, it generalizes poorly to mixture stimuli due to nonlinear mixture responses. We show that mice similarly fail to generalize, suggesting that they learn this segregation task discriminatively by adjusting task-specific decision boundaries without taking advantage of a demixed representation of odors.

Glomerular and Mitral-Granule Cell Microcircuits Coordinate Temporal and Spatial Information Processing in the Olfactory Bulb

The olfactory bulb processes inputs from olfactory receptor neurons (ORNs) through two levels: the glomerular layer at the site of input, and the granule cell level at the site of output to the olfactory cortex. The sequence of action of these two levels has not yet been examined. We analyze this issue using a novel computational framework that is scaled up, in three-dimensions (3D), with realistic representations of the interactions between layers, activated by simulated natural odors, and constrained by experimental and theoretical analyses. We suggest that the postulated functions of glomerular circuits have as their primary role transforming a complex and disorganized input into a contrast-enhanced and normalized representation, but cannot provide for synchronization of the distributed glomerular outputs. By contrast, at the granule cell layer, the dendrodendritic interactions mediate temporal decorrelation, which we show is dependent on the preceding contrast enhancement by the glomerular layer. The results provide the first insights into the successive operations in the olfactory bulb, and demonstrate the significance of the modular organization around glomeruli. This layered organization is especially important for natural odor inputs, because they activate many overlapping glomeruli.

Receptor arrays optimized for natural odor statistics

Natural odors typically consist of many molecules at different concentrations. It is unclear how the numerous odorant molecules and their possible mixtures are discriminated by relatively few olfactory receptors. Using an information theoretic model, we show that a receptor array is optimal for this task if it achieves two possibly conflicting goals: (i) Each receptor should respond to half of all odors and (ii) the response of different receptors should be uncorrelated when averaged over odors presented with natural statistics. We use these design principles to predict statistics of the affinities between receptors and odorant molecules for a broad class of odor statistics. We also show that optimal receptor arrays can be tuned to either resolve concentrations well or distinguish mixtures reliably. Finally, we use our results to predict properties of experimentally measured receptor arrays. Our work can thus be used to better understand natural olfaction, and it also suggests ways to improve artificial sensor arrays.

Neural Coding of Perceived Odor Intensity

Stimulus intensity is a fundamental perceptual feature in all sensory systems. In olfaction, perceived odor intensity depends on at least two variables: odor concentration; and duration of the odor exposure or adaptation. To examine how neural activity at early stages of the olfactory system represents features relevant to intensity perception, we studied the responses of mitral/tufted cells (MTCs) while manipulating odor concentration and exposure duration. Temporal profiles of MTC responses to odors changed both as a function of concentration and with adaptation. However, despite the complexity of these responses, adaptation and concentration dependencies behaved similarly. These similarities were visualized by principal component analysis of average population responses and were quantified by discriminant analysis in a trial-by-trial manner. The qualitative functional dependencies of neuronal responses paralleled psychophysics results in humans. We suggest that temporal patterns of MTC responses in the olfactory bulb contribute to an internal perceptual variable: odor intensity.

Compound valence is conserved in binary odor mixtures in Drosophila melanogaster

Most naturally occurring olfactory signals do not consist of monomolecular odorants but, rather, are mixtures whose composition and concentration ratios vary. While there is ample evidence for the relevance of complex odor blends in ecological interactions and for interactions of chemicals in both peripheral and central neuronal processing, a fine-scale analysis of rules governing the innate behavioral responses of Drosophila melanogaster towards odor mixtures is lacking. In this study we examine whether the innate valence of odors is conserved in binary odor mixtures. We show that binary mixtures of attractants are more attractive than individual mixture constituents. In contrast, mixing attractants with repellents elicits responses that are lower than the responses towards the corresponding attractants. This decrease in attraction is repellent-specific, independent of the identity of the attractant and more stereotyped across individuals than responses towards the repellent alone. Mixtures of repellents are either less attractive than the individual mixture constituents or these mixtures represent an intermediate. Within the limits of our data set, most mixture responses are quantitatively predictable on the basis of constituent responses. In summary, the valence of binary odor mixtures is predictable on the basis of valences of mixture constituents. Our findings will further our understanding of innate behavior towards ecologically relevant odor blends and will serve as a powerful tool for deciphering the olfactory valence code.

An olfactory cocktail party: figure-ground segregation of odorants in rodents

In odorant-rich environments, animals must be able to detect specific odorants of interest against variable backgrounds. However, several studies have suggested that both humans and rodents are very poor at analyzing the components of odorant mixtures, leading to the idea that olfaction is a synthetic sense in which mixtures are perceived holistically. We have developed a behavioral task to directly measure the ability of mice to perceive mixture components and found that mice can be easily trained to detect target odorants embedded in unpredictable and variable mixtures. We imaged the responses of olfactory bulb glomeruli to the individual odors used in the task in mice expressing the Ca⁺⁺ indicator GCaMP3 in olfactory receptor neurons. By relating behavioral performance to the glomerular response patterns, we found that the difficulty of segregating the target from the background was strongly dependent on the extent of overlap between the representations of the target and the background odors by olfactory receptors. Our study indicates that the olfactory system has powerful analytic abilities that are constrained by the limits of combinatorial neural representation of odorants at the level of the olfactory receptors.

From molecule to mind: an integrative perspective on odor intensity

A fundamental problem in systems neuroscience is mapping the physical properties of a stimulus to perceptual characteristics. In vision, wavelength translates into color; in audition, frequency translates into pitch. Although odorant concentration is a key feature of olfactory stimuli, we do not know how concentration is translated into perceived intensity by the olfactory system. A variety of neural responses at several levels of processing have been reported to vary with odorant concentration, suggesting specific coding models. However, it remains unclear which, if any, of these phenomena underlie the perception of odor intensity. Here, we provide an overview of current models at different stages of olfactory processing, and identify promising avenues for future research.

Cholinergic inputs from Basal forebrain add an excitatory bias to odor coding in the olfactory bulb

Cholinergic modulation of central circuits is associated with active sensation, attention, and learning, yet the neural circuits and temporal dynamics underlying cholinergic effects on sensory processing remain unclear. Understanding the effects of cholinergic modulation on particular circuits is complicated by the widespread projections of cholinergic neurons to telencephalic structures that themselves are highly interconnected. Here we examined how cholinergic projections from basal forebrain to the olfactory bulb (OB) modulate output from the first stage of sensory processing in the mouse olfactory system. By optogenetically activating their axons directly in the OB, we found that cholinergic projections from basal forebrain regulate OB output by increasing the spike output of presumptive mitral/tufted cells. Cholinergic stimulation increased mitral/tufted cell spiking in the absence of inhalation-driven sensory input and further increased spiking responses to inhalation of odorless air and to odorants. This modulation was rapid and transient, was dependent on local cholinergic signaling in the OB, and differed from modulation by optogenetic activation of cholinergic neurons in basal forebrain, which led to a mixture of mitral/tufted cell excitation and suppression. Finally, bulbar cholinergic enhancement of mitral/tufted cell odorant responses was robust and occurred independent of the strength or even polarity of the odorant-evoked response, indicating that cholinergic modulation adds an excitatory bias to mitral/tufted cells as opposed to increasing response gain or sharpening response spectra. These results are consistent with a role for the basal forebrain cholinergic system in dynamically regulating the sensitivity to or salience of odors during active sensing of the olfactory environment.

Multiple perceptible signals from a single olfactory glomerulus

Glomeruli are functional units in the olfactory system. The mouse olfactory bulb contains roughly 2,000 glomeruli, each receiving inputs from olfactory sensory neurons (OSNs) that express a specific odorant receptor gene. Odors typically activate many glomeruli in complex combinatorial patterns and it is unknown which features of neuronal activity in individual glomeruli contribute to odor perception. To address this, we used optogenetics to selectively activate single, genetically identified glomeruli in behaving mice. We found that mice could perceive the stimulation of a single glomerulus. Single-glomerulus stimulation was also detected on an intense odor background. In addition, different input intensities and the timing of input relative to sniffing were discriminated through one glomerulus. Our data suggest that each glomerulus can transmit odor information using identity, intensity and temporal coding cues. These multiple modes of information transmission may enable the olfactory system to efficiently identify and localize odor sources.

Synchronous firing of antennal-lobe projection neurons encodes the behaviorally effective ratio of sex-pheromone components in male Manduca sexta

Olfactory stimuli that are essential to an animal's survival and reproduction are often complex mixtures of volatile organic compounds in characteristic proportions. Here, we investigated how these proportions are encoded in the primary olfactory processing center, the antennal lobe, of male Manduca sexta moths. Two key components of the female's sex pheromone, present in an approximately 2:1 ratio, are processed in each of two neighboring glomeruli in the macroglomerular complex (MGC) of males of this species. In wind-tunnel flight experiments, males exhibited behavioral selectivity for ratios approximating the ratio released by conspecific females. The ratio between components was poorly represented, however, in the firing-rate output of uniglomerular MGC projection neurons (PNs). PN firing rate was mostly insensitive to the ratio between components, and individual PNs did not exhibit a preference for a particular ratio. Recording simultaneously from pairs of PNs in the same glomerulus, we found that the natural ratio between components elicited the most synchronous spikes, and altering the proportion of either component decreased the proportion of synchronous spikes. The degree of synchronous firing between PNs in the same glomerulus thus selectively encodes the natural ratio that most effectively evokes the natural behavioral response to pheromone.

Glomerular input patterns in the mouse olfactory bulb evoked by retronasal odor stimuli

Background

Odorant stimuli can access the olfactory epithelium either orthonasally, by inhalation through the external nares, or retronasally by reverse airflow from the oral cavity. There is evidence that odors perceived through these two routes can differ in quality and intensity. We were curious whether such differences might potentially have a neural basis in the peripheral mechanisms of odor coding. To explore this possibility, we compared olfactory receptor input to glomeruli in the dorsal olfactory bulb evoked by orthonasal and retronasal stimulation. Maps of glomerular response were acquired by optical imaging of transgenic mice expressing synaptopHluorin (spH), a fluorescent reporter of presynaptic activity, in olfactory nerve terminals.

Results

We found that retronasally delivered odorants were able to activate inputs to multiple glomeruli in the dorsal olfactory bulb. The retronasal responses were smaller than orthonasal responses to odorants delivered at comparable concentrations and flow rates, and they displayed higher thresholds and right-shifted dose–response curves. Glomerular maps of orthonasal and retronasal responses were usually well overlapped, with fewer total numbers of glomeruli in retronasal maps. However, maps at threshold could be quite distinct with little overlap. Retronasal responses were also more narrowly tuned to homologous series of aliphatic odorants of varying carbon chain length, with longer chain, more hydrophobic compounds evoking little or no response at comparable vapor levels.

Conclusions

Several features of retronasal olfaction are possibly referable to the observed properties of glomerular odorant responses. The finding that retronasal responses are weaker and sparser than orthonasal responses is consistent with psychophysical studies showing lower sensitivity for retronasal olfaction in threshold and suprathreshold tests. The similarity and overlap of orthonasal and retronasal odor maps at suprathreshold concentrations agrees with generally similar perceived qualities for the same odorant stimuli administered by the two routes. However, divergence of maps near threshold is a potential factor in perceptual differences between orthonasal and retronasal olfaction. Narrower tuning of retronasal responses suggests that they may be less influenced by chromatographic adsorption effects.

Illuminating vertebrate olfactory processing

The olfactory system encodes information about molecules by spatiotemporal patterns of activity across distributed populations of neurons and extracts information from these patterns to control specific behaviors. Recent studies used in vivo recordings, optogenetics, and other methods to analyze the mechanisms by which odor information is encoded and processed in the olfactory system, the functional connectivity within and between olfactory brain areas, and the impact of spatiotemporal patterning of neuronal activity on higher-order neurons and behavioral outputs. The results give rise to a faceted picture of olfactory processing and provide insights into fundamental mechanisms underlying neuronal computations. This review focuses on some of this work presented in a Mini-Symposium at the Annual Meeting of the Society for Neuroscience in 2012.

Psychophysical properties of odor processing can be quantitatively described by relative action potential latency patterns in mitral and tufted cells

Electrophysiological and population imaging data in rodents show that olfactory bulb (OB) activity is profoundly modulated by the odor sampling process while behavioral experiments indicate that odor discrimination can occur within a single sniff. This paper addresses the question of whether action potential (AP) latencies occurring across the mitral and tufted cell (M/TC) population within an individual sampling cycle could account for the psychophysical properties of odor processing. To determine this we created an OB model (50,000 M/TCs) exhibiting hallmarks of published in vivo properties and used a template-matching algorithm to assess stimulus separation. Such an AP latency-based scheme showed high reproducibility and sensitivity such that odor stimuli could be reliably separated independent of concentration. As in behavioral experiments we found that very dissimilar odors (“A vs. B”) were accurately and rapidly discerned while very similar odors (binary mixtures, 0.4A/0.6B vs. 0.6A/0.4B) required up to 90 ms longer. As in lesion studies we find that AP latency-based representation is rather insensitive to disruption of large regions of the OB. The AP latency-based scheme described here, therefore, captures both temporal and psychophysical properties of olfactory processing and suggests that the onset patterns of M/TC activity in the OB represent stimulus specific features of olfactory stimuli.

Glomerular latency coding in artificial olfaction

Sensory perception results from the way sensory information is subsequently transformed in the brain. Olfaction is a typical example in which odor representations undergo considerable changes as they pass from olfactory receptor neurons (ORNs) to second-order neurons. First, many ORNs expressing the same receptor protein yet presenting heterogeneous dose–response properties converge onto individually identifiable glomeruli. Second, onset latency of glomerular activation is believed to play a role in encoding odor quality and quantity in the context of fast information processing. Taking inspiration from the olfactory pathway, we designed a simple yet robust glomerular latency coding scheme for processing gas sensor data. The proposed bio-inspired approach was evaluated using an in-house SnO₂ sensor array. Glomerular convergence was achieved by noting the possible analogy between receptor protein expressed in ORNs and metal catalyst used across the fabricated gas sensor array. Ion implantation was another technique used to account both for sensor heterogeneity and enhanced sensitivity. The response of the gas sensor array was mapped into glomerular latency patterns, whose rank order is concentration-invariant. Gas recognition was achieved by simply looking for a “match” within a library of spatio-temporal spike fingerprints. Because of its simplicity, this approach enables the integration of sensing and processing onto a single-chip.

Analytical processing of binary mixture information by olfactory bulb glomeruli

Odors are rarely composed of a single compound, but rather contain a large and complex variety of chemical components. Often, these mixtures are perceived as having unique qualities that can be quite different than the combination of their components. In many cases, a majority of the components of a mixture cannot be individually identified. This synthetic processing of odor information suggests that individual component representations of the mixture must interact somewhere along the olfactory pathway. The anatomical nature of sensory neuron input into segregated glomeruli with the bulb suggests that initial input of odor information into the bulb is analytic. However, a large network of interneurons within the olfactory bulb could allow for mixture interactions via mechanisms such as lateral inhibition. Currently in mammals, it is unclear if postsynaptic mitral/tufted cell glomerular mixture responses reflect the analytical mixture input, or provide the initial basis for synthetic processing with the olfactory system. To address this, olfactory bulb glomerular binary mixture representations were compared to representations of each component using transgenic mice expressing the calcium indicator G-CaMP2 in olfactory bulb mitral/tufted cells. Overall, dorsal surface mixture representations showed little mixture interaction and often appeared as a simple combination of the component representations. Based on this, it is concluded that dorsal surface glomerular mixture representations remain largely analytical with nearly all component information preserved.

Sparse incomplete representations: a potential role of olfactory granule cells

Mitral/tufted cells of the olfactory bulb receive odorant information from receptor neurons and transmit this information to the cortex. Studies in awake behaving animals have found that sustained responses of mitral cells to odorants are rare, suggesting sparse combinatorial representation of the odorants. Careful alignment of mitral cell firing with the phase of the respiration cycle revealed brief transient activity in the larger population of mitral cells, which respond to odorants during a small fraction of the respiration cycle. Responses of these cells are therefore temporally sparse. Here, we propose a mathematical model for the olfactory bulb network that can reproduce both combinatorially and temporally sparse mitral cell codes. We argue that sparse codes emerge as a result of the balance between mitral cells' excitatory inputs and inhibition provided by the granule cells. Our model suggests functional significance for the dendrodendritic synapses mediating interactions between mitral and granule cells.

Structure-activity relationships on the odor detectability of homologous carboxylic acids by humans

We measured concentration detection functions for the odor detectability of the homologs: formic, acetic, butyric, hexanoic, and octanoic acids. Subjects (14 ≤ n ≤ 18) comprised young (19–37 years), healthy, nonsmoker, and normosmic participants from both genders. Vapors were delivered by air dilution olfactometry, using a three-alternative forced-choice procedure against carbon-filtered air, and an ascending concentration approach. Delivered concentrations were established by gas chromatography (flame ionization detector) in parallel with testing. Group and individual olfactory functions were modeled by a sigmoid (logistic) equation from which two parameters are calculated: C, the odor detection threshold (ODT) and D, the steepness of the function. Thresholds declined with carbon chain length along formic, acetic, and butyric acid where they reached a minimum (ODTs = 514, 5.2, and 0.26 ppb by volume, respectively). Then, they increased for hexanoic (1.0 ppb) and octanoic (0.86 ppb) acid. Odor thresholds and interindividual differences in olfactory acuity among these young, normosmic participants were lower than traditionally thought and reported. No significant effects of gender on odor detectability were observed. The finding of an optimum molecular size for odor potency along homologs confirms a prediction made by a model of ODTs based on a solvation equation. We discuss the mechanistic implications of this model for the process of olfactory detection.

Frequency transitions in odor-evoked neural oscillations

In many species, sensory stimuli elicit the oscillatory synchronization of groups of neurons. What determines the properties of these oscillations? In the olfactory system of the moth, we found that odors elicited oscillatory synchronization through a neural mechanism like that described in locust and Drosophila. During responses to long odor pulses, oscillations suddenly slowed as net olfactory receptor neuron (ORN) output decreased; thus, stimulus intensity appeared to determine oscillation frequency. However, changing the concentration of the odor had little effect upon oscillatory frequency. Our recordings in vivo and computational models based on these results suggested that the main effect of increasing odor concentration was to recruit additional, less well-tuned ORNs whose firing rates were tightly constrained by adaptation and saturation. Thus, in the periphery, concentration is encoded mainly by the size of the responsive ORN population, and oscillation frequency is set by the adaptation and saturation of this response.

Control of on/off glomerular signaling by a local GABAergic microcircuit in the olfactory bulb

Odors are coded at the input level of the olfactory bulb by a spatial map of activated glomeruli, reflecting different odorant receptors (ORs) stimulated in the nose. Here we examined the function of local synaptic processing within glomeruli in transforming these input patterns into an output for the bulb, using patch-clamp recordings and calcium imaging in rat bulb slices. Two types of transformations were observed at glomeruli, the first of which produced a bimodal, "on/off" glomerular signal that varied probabilistically depending on olfactory receptor neuron (ORN) input levels. The bimodal response behavior was seen in glomerular synaptic responses, as well as in action potential ("spike") firing, wherein all mitral cells affiliated with a glomerulus either engaged in prolonged spike bursts or did not spike at all. In addition, evidence was obtained that GABAergic periglomerular (PG) cells that surround a glomerulus can prevent activation of a glomerulus through inhibitory inputs targeted onto excitatory external tufted cells. The path of PG cell activation appeared to be confined to one glomerulus, such that ORNs at one glomerulus initiated inhibition of the same glomerulus. The observed glomerular "self-inhibition" provides a mechanism of filtering odor signals that would be an alternative to commonly proposed mechanisms of lateral inhibition between OR-specific glomeruli. In this case, selective suppression of weak odor signals could be achieved based on the difference in the input resistance of PG cells versus excitatory neurons at a glomerulus.

All-or-none population bursts temporally constrain surround inhibition between mouse olfactory glomeruli

With each sniff, the olfactory bulbs of the brain generate a neural activity pattern representing the odour environment, transmitting this to higher brain centres in the form of mitral cell output. Inhibitory circuits in the olfactory bulb glomerular and external plexiform layers may amplify contrast in these patterns, through surround inhibition of mitral cells. These circuits may operate in series, but their respective roles are unclear. A single sniff is sufficient for odour discrimination, but is not clear that the inhibitory circuits act within this timeframe. We used microdissected slices of mouse olfactory bulb to study each circuit in isolation. We found that unlike surround inhibition mediated in the external plexiform layer, surround inhibition mediated in the glomerular layer was activated by sensory synaptic input, but not by mitral cell output. The results also suggest that interactions between olfactory glomeruli are exclusively inhibitory, unlike in antennal lobe, and that surround inhibition mediated within the external plexiform layer may involve neural circuit elements not preserved in slice preparations. Surround inhibition was effective only after an interval corresponding to a single sniff in vivo. Surplus excitation, initiated by sensory input but generated by collective all-or-none responses of mitral cells, may delay surround inhibition and allow the synchronous activation of multiple glomeruli without each suppressing the other. Surround inhibition in the glomerular layer may subsequently allow a fresh representation of the odour environment to be generated with each sniff. These findings are consistent with combinatorial odour coding based on all-or-none glomerular responses.

Molecular tuning of odorant receptors and its implication for odor signal processing

The discovery of the odorant receptor (OR) family by Buck and Axel in 1991 provided a quantum jump in our understanding of olfactory function. However, the study of the responsiveness of ORs to odor ligands was challenging due to the difficulties in deorphanizing the receptors. In this manuscript, we review recent findings of OR responsiveness that have come about through improved OR deorphanization methods, site-directed mutagenesis, structural modeling studies, and studies of OR responses in situ in olfactory sensory neurons. Although there has been a major leap in our understanding of receptor-ligand interactions and how these contribute to the input to the olfactory system, an improvement of our understanding of receptor structure and dynamics and interactions with intracellular and extracellular proteins is necessary.

Inhibition shapes sex selectivity in the mouse accessory olfactory bulb

Laterally connected inhibitory circuitry is found throughout the nervous system, including many early sensory processing systems. The extent to which it plays a role in shaping neuronal stimulus selectivity in systems like olfaction, however, which lack a simple two-dimensional representation of their stimulus space, has remained controversial. We examined this issue using an experimental preparation that allowed electrophysiological recording from the accessory olfactory bulb of an anesthetized mouse during the controlled delivery of pheromonal stimuli, in this case derived from the urine of male and female mice. We found that individual neurons were often highly selective for the sex of the urine donor. Examination of both explicitly inhibitory responses, as well as responses to mixtures of male and female urine, revealed that laterally connected inhibition was both prevalent and of large magnitude, particularly for male-selective neurons. Pharmacological manipulation of this inhibition resulted in a shift in many neurons' stimulus selectivities. Finally, we found that a behavioral response (pregnancy block) evoked by the presence of unfamiliar male urine could be suppressed by the addition of female urine to the stimulus, demonstrating that this system displays a behavioral opponency consistent with neural inhibition. Together, these results indicate that laterally connected inhibitory circuitry in the accessory olfactory bulb plays an important role in shaping neural selectivity for natural stimuli.

A model of stimulus-specific neural assemblies in the insect antennal lobe

It has been proposed that synchronized neural assemblies in the antennal lobe of insects encode the identity of olfactory stimuli. In response to an odor, some projection neurons exhibit synchronous firing, phase-locked to the oscillations of the field potential, whereas others do not. Experimental data indicate that neural synchronization and field oscillations are induced by fast GABA(A)-type inhibition, but it remains unclear how desynchronization occurs. We hypothesize that slow inhibition plays a key role in desynchronizing projection neurons. Because synaptic noise is believed to be the dominant factor that limits neuronal reliability, we consider a computational model of the antennal lobe in which a population of oscillatory neurons interact through unreliable GABA(A) and GABA(B) inhibitory synapses. From theoretical analysis and extensive computer simulations, we show that transmission failures at slow GABA(B) synapses make the neural response unpredictable. Depending on the balance between GABA(A) and GABA(B) inputs, particular neurons may either synchronize or desynchronize. These findings suggest a wiring scheme that triggers stimulus-specific synchronized assemblies. Inhibitory connections are set by Hebbian learning and selectively activated by stimulus patterns to form a spiking associative memory whose storage capacity is comparable to that of classical binary-coded models. We conclude that fast inhibition acts in concert with slow inhibition to reformat the glomerular input into odor-specific synchronized neural assemblies.