Context-dependent environmental adaptation of olfactory receptor abundances

Olfactory receptor usage is highly non-uniform, with some receptor types being orders of magnitude more abundant than others. In mammals, the receptor neurons are replaced regularly, and the receptor distribution changes in response to olfactory experience. The observed changes are mysteriously context-dependent, with increased exposure to odorants leading variously to increased, decreased or unchanged abundance of activated receptors. We propose a theoretical model that explains these observations: the receptor distribution is tuned to efficiently encode information about the olfactory environment. This adaptation occurs before olfactory signals are decorrelated, leading to a new regime of efficient coding in which the optimal receptor distribution is sensitive to the global context of the correlated responses of all receptor types in the population. We demonstrate how this effect reproduces the context-dependence seen in experiments. We also show that the optimal receptor distribution can be achieved by following simple dynamical rules for neural birth and death processes.

Related papers:

title: A novel multigene family may encode odorant receptors: A molecular basis for odor recognition
abstract: The mammalian olfactory system can recognize and discriminate a large number of different odorant molecules. The detection of chemically distinct odorants presumably results from the association of odorous ligands with specific receptors on olfactory sensory neurons. To address the problem of olfactory perception at a molecular level, we have cloned and characterized 18 different members of an extremely large multigene family that encodes seven transmembrane domain proteins whose expression is restricted to the olfactory epithelium. The members of this novel gene family are likely to encode a diverse family of odorant receptors.

title: Allelic inactivation regulates olfactory receptor gene expression
abstract: We suggest a model in which a hierarchy of controls is exerted on the family of odorant receptor genes to assure that a sensory neuron expresses a single receptor from a family of 1000 genes. We propose that a cis-regulatory element directs the stochastic expression of only one gene from a large array of linked receptor genes. Moreover, only one allelic array encoding multiple receptor genes is active in an individual neuron. We demonstrate that in a neuron expressing a given receptor, expression derives exclusively from one allele. In addition, we observe that alleles encoding the odorant receptors are replicated asynchronously, a phenomenon consistently associated with allelic inactivation. This model, involving inactivation of one allelic array and cis control of the active array, provides a mechanism such that individual neurons express one or a small number of receptors.

title: Olfactory sensory neurons transiently express multiple olfactory receptors during development
abstract: In mammals, each olfactory sensory neuron randomly expresses one, and only one, olfactory receptor (OR)—a phenomenon called the “one‐neuron‐one‐receptor” rule. Although extensively studied, this rule was never proven for all ~1,000 OR genes in one cell at once, and little is known about its dynamics. Here, we directly tested this rule by single‐cell transcriptomic sequencing of 178 cells from the main olfactory epithelium of adult and newborn mice. To our surprise, a subset of cells expressed multiple ORs. Most of these cells were developmentally immature. Our results illustrated how the “one‐neuron‐one‐receptor” rule may have been established: At first, a single neuron temporarily expressed multiple ORs—seemingly violating the rule—and then all but one OR were eliminated. This work provided experimental evidence that epigenetic regulation in the olfactory system selects a single OR by suppressing a few transiently expressed ORs in a single cell during development.

title: Evolution of insect olfactory receptors
abstract: The olfactory sense detects a plethora of behaviorally relevant odor molecules; gene families involved in olfaction exhibit high diversity in different animal phyla. Insects detect volatile molecules using olfactory (OR) or ionotropic receptors (IR) and in some cases gustatory receptors (GRs). While IRs are expressed in olfactory organs across Protostomia, ORs have been hypothesized to be an adaptation to a terrestrial insect lifestyle. We investigated the olfactory system of the primary wingless bristletail Lepismachilis y-signata (Archaeognatha), the firebrat Thermobia domestica (Zygentoma) and the neopteran leaf insect Phyllium siccifolium (Phasmatodea). ORs and the olfactory coreceptor (Orco) are with very high probability lacking in Lepismachilis; in Thermobia we have identified three Orco candidates, and in Phyllium a fully developed OR/Orco-based system. We suggest that ORs did not arise as an adaptation to a terrestrial lifestyle, but evolved later in insect evolution, with Orco being present before the appearance of ORs.

title: Neurogenesis and neuron regeneration in the olfactory system of mammals. II. Degeneration and reconstitution of the olfactory sensory neurons after axotomy
abstract: SummaryThis report describes the retrograde degeneration affecting olfactory sensory neurons of rats after severance of their axons and illustrates the reconstitution of new neurons originating from stem cells located at the base of the olfactory neuroepithelium.Degeneration of the mature, axotomized neurons, signalled by an increased electron density of their cytoplasmic matrix and by the appearance of lipofuscin-like granules, can be detected in the neuroepithelium as early as 24 h after surgery and becomes conspicuous between the second and the third day. Degenerating neurons can be observed in decreasing number up to the tenth post-operative day. They are removed by macrophages which invade the epithelium. The reconstitution of new neurons begins to occur after eight days, when the stem cells undergo vigorous mitotic activity and differentiate into neurons. The morphology of the reconstituted neurons has been described in detail at different stages of their maturation. After 30 days, the olfactory epithelium appears similar to controls. On the basis of both morphological (in rats) and autoradiographic (in mice) observations, the basal cells have been recognized as stem cells of the olfactory neurons.

title: Olfactory sensory neurons are trophically dependent on the olfactory bulb for their prolonged survival
abstract: In most neural systems, developing neurons are trophically dependent on contact with their synaptic target for their survival and for some features of their differentiation. However, in the olfactory system, it is unclear whether or not the survival and differentiation of olfactory sensory neurons depend on contact with the olfactory bulb (normally the sole synaptic target for these neurons). In order to address this issue, we examined neuronal life-span and differentiation in adult rats subjected to unilateral olfactory bulb ablation at least 1 month prior to use. Life-span of a newly generated cohort of olfactory neurons was determined by labeling them at their “birth” via the incorporation of 3H-thymidine. In the absence of the bulb, neurons are continually produced at a twofold greater rate. However, the epithelium on the ablated side is thinner, indicating that average neuronal life-span must be reduced in the targetless epithelium. Indeed, nearly 90% of the labeled neurons disappear from the bulbectomized side between 5 d and 2 weeks of neuronal age. Moreover, on electron microscopic examination, olfactory axons are degenerating in large numbers on the ablated side. Since labeled neurons migrate apically through the width of the epithelium during this same period, it appears that most, if not all, neurons on the ablated side have a life-span on the order of 2 weeks or less. In contrast, there is a more moderate degree of neuronal loss on the unoperated side of the same animals during the first 2 weeks after tracer injection, and that occurs while the neurons are concentrated in the deeper half of the epithelium, suggesting that there is a preexisting population of neurons in the control epithelium that does not die during this period. Likewise, degenerating axons are much less frequent on the unoperated side. We conclude that life-span is significantly shorter for olfactory neurons born in the targetless epithelium and that olfactory neurons are trophically dependent on the presence of the bulb for their prolonged survival. Neuronal differentiation in the absence of the bulb was assessed according to ultrastructural criteria and the pattern of protein expression using antisera to the growth associated protein GAP-43 and the olfactory marker protein. By both measures, most neurons in the epithelium on the bulbectomized side, but not all, are immature.(ABSTRACT TRUNCATED AT 400

title: The activity-dependent histone variant H2BE modulates the life span of olfactory neurons
abstract: We have identified a replication-independent histone variant, Hist2h2be (referred to herein as H2be), which is expressed exclusively by olfactory chemosensory neurons. Levels of H2BE are heterogeneous among olfactory neurons, but stereotyped according to the identity of the co-expressed olfactory receptor (OR). Gain- and loss-of-function experiments demonstrate that changes in H2be expression affect olfactory function and OR representation in the adult olfactory epithelium. We show that H2BE expression is reduced by sensory activity and that it promotes neuronal cell death, such that inactive olfactory neurons display higher levels of the variant and shorter life spans. Post-translational modifications (PTMs) of H2BE differ from those of the canonical H2B, consistent with a role for H2BE in altering transcription. We propose a physiological function for H2be in modulating olfactory neuron population dynamics to adapt the OR repertoire to the environment.

title: Activity-Dependent Modulation of Odorant Receptor Gene Expression in the Mouse Olfactory Epithelium
abstract: Activity plays critical roles in development and maintenance of the olfactory system, which undergoes considerable neurogenesis throughout life. In the mouse olfactory epithelium, each olfactory sensory neuron (OSN) stably expresses a single odorant receptor (OR) type out of a repertoire of ∼1200 and the OSNs with the same OR identity are distributed within one of the few broadly-defined zones. However, it remains elusive whether and how activity modulates such OR expression patterns. Here we addressed this question by investigating OR gene expression via in situ hybridization when sensory experience or neuronal excitability is manipulated. We first examined the expression patterns of fifteen OR genes in mice which underwent neonatal, unilateral naris closure. After four-week occlusion, the cell density in the closed (sensory-deprived) side was significantly lower (for four ORs), similar (for three ORs), or significantly higher (for eight ORs) as compared to that in the open (over-stimulated) side, suggesting that sensory inputs have differential effects on OSNs expressing different OR genes. We next examined the expression patterns of seven OR genes in transgenic mice in which mature OSNs had reduced neuronal excitability. Neuronal silencing led to a significant reduction in the cell density for most OR genes tested and thinner olfactory epithelium with an increased density of apoptotic cells. These results suggest that sensory experience plays important roles in shaping OR gene expression patterns and the neuronal activity is critical for survival of OSNs.

title: Parental olfactory experience influences behavior and neural structure in subsequent generations
abstract: Using olfactory molecular specificity, we examined the inheritance of parental traumatic exposure, a phenomenon that has been frequently observed, but not understood. We subjected F0 mice to odor fear conditioning before conception and found that subsequently conceived F1 and F2 generations had an increased behavioral sensitivity to the F0-conditioned odor, but not to other odors. When an odor (acetophenone) that activates a known odorant receptor (Olfr151) was used to condition F0 mice, the behavioral sensitivity of the F1 and F2 generations to acetophenone was complemented by an enhanced neuroanatomical representation of the Olfr151 pathway. Bisulfite sequencing of sperm DNA from conditioned F0 males and F1 naive offspring revealed CpG hypomethylation in the Olfr151 gene. In addition, in vitro fertilization, F2 inheritance and cross-fostering revealed that these transgenerational effects are inherited via parental gametes. Our findings provide a framework for addressing how environmental information may be inherited transgenerationally at behavioral, neuroanatomical and epigenetic levels.

title: Postnatal Odorant Exposure Induces Peripheral Olfactory Plasticity at the Cellular Level
abstract: Mammalian olfactory sensory neurons (OSNs) form the primary elements of the olfactory system. Inserted in the olfactory mucosa lining of the nasal cavity, they are exposed to the environment and their lifespan is brief. Several reports say that OSNs are regularly regenerated during the entire life and that odorant environment affects the olfactory epithelium. However, little is known about the impact of the odorant environment on OSNs at the cellular level and more precisely in the context of early postnatal olfactory exposure. Here we exposed MOR23-green fluorescent protein (GFP) and M71-GFP mice to lyral or acetophenone, ligands for MOR23 or M71, respectively. Daily postnatal exposure to lyral induces plasticity in the population of OSNs expressing MOR23. Their density decreases after odorant exposure, whereas the amount of MOR23 mRNA and protein remain stable in the whole epithelium. Meanwhile, quantitative PCR indicates that each MOR23 neuron has higher levels of olfactory receptor transcripts and also expresses more CNGA2 and phosphodiesterase 1C, fundamental olfactory transduction pathway proteins. Transcript levels return to baseline after 4 weeks recovery. Patch-clamp recordings reveal that exposed MOR23 neurons respond to lyral with higher sensitivity and broader dynamic range while the responses' kinetics were faster. These effects are specific to the odorant–receptor pair lyral–MOR23: there was no effect of acetophenone on MOR23 neurons and no effect of acetophenone and lyral on the M71 population. Together, our results clearly demonstrate that OSNs undergo specific anatomical, molecular, and functional adaptation when chronically exposed to odorants in the early stage of life.

title: Variation in olfactory neuron repertoires is genetically controlled and environmentally modulated
abstract: The mouse olfactory sensory neuron (OSN) repertoire is composed of 10 million cells and each expresses one olfactory receptor (OR) gene from a pool of over 1000. Thus, the nose is sub-stratified into more than a thousand OSN subtypes. Here, we employ and validate an RNA-sequencing-based method to quantify the abundance of all OSN subtypes in parallel, and investigate the genetic and environmental factors that contribute to neuronal diversity. We find that the OSN subtype distribution is stereotyped in genetically identical mice, but varies extensively between different strains. Further, we identify cis-acting genetic variation as the greatest component influencing OSN composition and demonstrate independence from OR function. However, we show that olfactory stimulation with particular odorants results in modulation of dozens of OSN subtypes in a subtle but reproducible, specific and time-dependent manner. Together, these mechanisms generate a highly individualized olfactory sensory system by promoting neuronal diversity.

title: Possible Principles Underlying the Transformations of Sensory Messages
abstract: and

title: A Simple Coding Procedure Enhances a Neuron's Information Capacity
abstract: The contrast-response function of a class of first order intemeurons in the fly's compound eye approximates to the cumulative probability distribution of contrast levels in natural scenes. Elementary information theory shows that this matching enables the neurons to encode contrast fluctuations most efficiently.

title: Emergence of simple-cell receptive field properties by learning a sparse code for natural images
abstract: THE receptive fields of simple cells in mammalian primary visual cortex can be characterized as being spatially localized, oriented1–4 and bandpass (selective to structure at different spatial scales), comparable to the basis functions of wavelet transforms5,6. One approach to understanding such response properties of visual neurons has been to consider their relationship to the statistical structure of natural images in terms of efficient coding7–12. Along these lines, a number of studies have attempted to train unsupervised learning algorithms on natural images in the hope of developing receptive fields with similar properties13–18, but none has succeeded in producing a full set that spans the image space and contains all three of the above properties. Here we investigate the proposal8,12 that a coding strategy that maximizes sparseness is sufficient to account for these properties. We show that a learning algorithm that attempts to find sparse linear codes for natural scenes will develop a complete family of localized, oriented, bandpass receptive fields, similar to those found in the primary visual cortex. The resulting sparse image code provides a more efficient representation for later stages of processing because it possesses a higher degree of statistical independence among its outputs.

title: Natural image statistics and neural representation.
abstract: It has long been assumed that sensory neurons are adapted, through both evolutionary and developmental processes, to the statistical properties of the signals to which they are exposed. Attneave (1954)Barlow (1961) proposed that information theory could provide a link between environmental statistics and neural responses through the concept of coding efficiency. Recent developments in statistical modeling, along with powerful computational tools, have enabled researchers to study more sophisticated statistical models for visual images, to validate these models empirically against large sets of data, and to begin experimentally testing the efficient coding hypothesis for both individual neurons and populations of neurons.

title: Efficiency and ambiguity in an adaptive neural code
abstract: We examine the dynamics of a neural code in the context of stimuli whose statistical properties are themselves evolving dynamically. Adaptation to these statistics occurs over a wide range of timescales—from tens of milliseconds to minutes. Rapid components of adaptation serve to optimize the information that action potentials carry about rapid stimulus variations within the local statistical ensemble, while changes in the rate and statistics of action-potential firing encode information about the ensemble itself, thus resolving potential ambiguities. The speed with which information is optimized and ambiguities are resolved approaches the physical limit imposed by statistical sampling and noise.

title: Efficient coding of natural sounds
abstract: The auditory system encodes sound by decomposing the amplitude signal arriving at the ear into multiple frequency bands whose center frequencies and bandwidths are approximately exponential functions of the distance from the stapes. This organization is thought to result from the adaptation of cochlear mechanisms to the animal's auditory environment. Here we report that several basic auditory nerve fiber tuning properties can be accounted for by adapting a population of filter shapes to encode natural sounds efficiently. The form of the code depends on sound class, resembling a Fourier transformation when optimized for animal vocalizations and a wavelet transformation when optimized for non-biological environmental sounds. Only for the combined set does the optimal code follow scaling characteristics of physiological data. These results suggest that auditory nerve fibers encode a broad set of natural sounds in a manner consistent with information theoretic principles.

title: What the fly’s nose tells the fly’s brain
abstract: This work is significant for three reasons. First, a new way the brain represents information is identified, one in which the information present in a large population of neurons can be gotten from a small subset of any neurons rather that from a subset of certain specific neurons. Second, the nature of the combinatorial code used to specify odor identity is identified, and this same type of code may be used in other contexts. Third, the way fly olfaction works can potentially provide a model for understanding the function of important vertebrate brain regions that appear to share the same neural circuit architecture. The fly olfactory system has a three-layer architecture: The fly’s olfactory receptor neurons send odor information to the first layer (the encoder) where this information is formatted as combinatorial odor code, one which is maximally informative, with the most informative neurons firing fastest. This first layer then sends the encoded odor information to the second layer (decoder), which consists of about 2,000 neurons that receive the odor information and “break” the code. For each odor, the amplitude of the synaptic odor input to the 2,000 second-layer neurons is approximately normally distributed across the population, which means that only a very small fraction of neurons receive a large input. Each odor, however, activates its own population of large-input neurons and so a small subset of the 2,000 neurons serves as a unique tag for the odor. Strong inhibition prevents most of the second-stage neurons from firing spikes, and therefore spikes from only the small population of large-input neurons is relayed to the third stage. This selected population provides the third stage (the user) with an odor label that can be used to direct behavior based on what odor is present.

title: Influence of odorant receptor repertoire on odor perception in humans and fruit flies
abstract: The olfactory system is thought to recognize odors with multiple odorant receptors (ORs) that are activated by overlapping sets of odorous molecules, ultimately generating an odor percept in the brain. We investigated how the odor percept differs between humans and Drosophila melanogaster fruit flies, species with very different OR repertoires. We devised high-throughput single fly behavior paradigms to ask how a given OR contributes to the odor percept in Drosophila. Wild-type flies showed dose- and stimulus-dependent responses to 70 of 73 odors tested, whereas mutant flies missing one OR showed subtle behavioral deficits that could not be predicted from the physiological responses of the OR. We measured human and fly judgments of odor intensity and quality and found that intensity perception is conserved between species, whereas quality judgments are species-specific. This study bridges the gap between the activation of olfactory sensory neurons and the odor percept.

title: Receptor arrays optimized for natural odor statistics
abstract: Natural odors typically consist of many molecules at different concentrations, which together determine the odor identity. This information is collectively encoded by olfactory receptors and then forwarded to the brain. However, it is unclear how the receptor activity can encode both the composition of the odor and the concentrations of its constituents. We study a simple model of the olfactory receptors from which we derive design principles for optimally communicating odor information in a given natural environment. We use these results to discuss biological olfactory systems, and we propose how they can be used to improve artificial sensor arrays. 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.

title: Predictive coding: a fresh view of inhibition in the retina
abstract: Interneurons exhibiting centre-surround antagonism within their receptive fields are commonly found in peripheral visual pathways. We propose that this organization enables the visual system to encode spatial detail in a manner that minimizes the deleterious effects of intrinsic noise, by exploiting the spatial correlation that exists within natural scenes. The antagonistic surround takes a weighted mean of the signals in neighbouring receptors to generate a statistical prediction of the signal at the centre. The predicted value is subtracted from the actual centre signal, thus minimizing the range of outputs transmitted by the centre. In this way the entire dynamic range of the interneuron can be devoted to encoding a small range of intensities, thus rendering fine detail detectable against intrinsic noise injected at later stages in processing. This predictive encoding scheme also reduces spatial redundancy, thereby enabling the array of interneurons to transmit a larger number of distinguishable images, taking into account the expected structure of the visual world. The profile of the required inhibitory field is derived from statistical estimation theory. This profile depends strongly upon the signal: noise ratio and weakly upon the extent of lateral spatial correlation. The receptive fields that are quantitatively predicted by the theory resemble those of X-type retinal ganglion cells and show that the inhibitory surround should become weaker and more diffuse at low intensities. The latter property is unequivocally demonstrated in the first-order interneurons of the fly’s compound eye. The theory is extended to the time domain to account for the phasic responses of fly interneurons. These comparisons suggest that, in the early stages of processing, the visual system is concerned primarily with coding the visual image to protect against subsequent intrinsic noise, rather than with reconstructing the scene or extracting specific features from it. The treatment emphasizes that a neuron’s dynamic range should be matched to both its receptive field and the statistical properties of the visual pattern expected within this field. Finally, the analysis is synthetic because it is an extension of the background suppression hypothesis (Barlow & Levick 1976), satisfies the redundancy reduction hypothesis (Barlow 1961 a, b) and is equivalent to deblurring under certain conditions (Ratliff 1965).

title: Variance predicts salience in central sensory processing
abstract: Information processing in the sensory periphery is shaped by natural stimulus statistics. In the periphery, a transmission bottleneck constrains performance; thus efficient coding implies that natural signal components with a predictably wider range should be compressed. In a different regime—when sampling limitations constrain performance—efficient coding implies that more resources should be allocated to informative features that are more variable. We propose that this regime is relevant for sensory cortex when it extracts complex features from limited numbers of sensory samples. To test this prediction, we use central visual processing as a model: we show that visual sensitivity for local multi-point spatial correlations, described by dozens of independently-measured parameters, can be quantitatively predicted from the structure of natural images. This suggests that efficient coding applies centrally, where it extends to higher-order sensory features and operates in a regime in which sensitivity increases with feature variability.

title: Mechanisms of olfactory discrimination: converging evidence for common principles across phyla.
abstract: Olfaction begins with the transduction of the information carried by odor molecules into electrical signals in sensory neurons. The activation of different subsets of sensory neurons to different degrees is the basis for neural encoding and further processing of the odor information by higher centers in the olfactory pathway. Recent evidence has converged on a set of transduction mechanisms, involving G-protein-coupled second-messenger systems, and neural processing mechanisms, involving modules called glomeruli, that appear to be adapted for the requirements of different species. The evidence is highlighted in this review by focusing on studies in selected vertebrates and in insects and crustaceans among invertebrates. The findings support the hypothesis that olfactory transduction and neural processing in the peripheral olfactory pathway involve basic mechanisms that are universal across most species in most phyla.

title: Principles of Glomerular Organization in the Human Olfactory Bulb – Implications for Odor Processing
abstract: Olfactory sensory neurons (OSN) in mice express only 1 of a possible 1,100 odor receptors (OR) and axons from OSNs expressing the same odor receptor converge into ∼2 of the 1,800 glomeruli in each olfactory bulb (OB) in mice; this yields a convergence ratio that approximates 2∶1, 2 glomeruli/OR. Because humans express only 350 intact ORs, we examined human OBs to determine if the glomerular convergence ratio of 2∶1 established in mice was applicable to humans. Unexpectedly, the average number of human OB glomeruli is >5,500 yielding a convergence ratio of ∼16∶1. The data suggest that the initial coding of odor information in the human OB may differ from the models developed for rodents and that recruitment of additional glomeruli for subpopulations of ORs may contribute to more robust odor representation.

title: An Olfactory Sensory Map in the Fly Brain
abstract: We have isolated the "complete" repertoire of genes encoding the odorant receptors in Drosophila and employ these genes to provide a molecular description of the organization of the peripheral olfactory system. The repertoire of Drosophila odorant receptors is encoded by 57 genes. Individual sensory neurons are likely to express only a single receptor gene. Neurons expressing a given gene project axons to one or two spatially invariant glomeruli in the antennal lobe. The insect brain therefore retains a two-dimensional map of receptor activation such that the quality of an odor may be encoded by different spatial patterns of activity in the antennal lobe.

title: Novel Behavioral Paradigm Reveals Lower Temporal Limits on Mouse Olfactory Decisions
abstract: Temporal limits on perceptual decisions set strict boundaries on the possible underlying neural computations. How odor information is encoded in the olfactory system is still poorly understood. Here, we sought to define the limit on the speed of olfactory processing. To achieve this, we trained mice to discriminate different odor concentrations in a novel behavioral setup with precise odor delivery synchronized to the sniffing cycle. Mice reported their choice by moving a horizontal treadmill with their front limbs. We found that mice reported discriminations of 75% accuracy in 70–90 ms after odor inhalation. For a low concentration and nontrigeminal odorant, this time was 90–140 ms, showing that mice process odor information rapidly even in the absence of trigeminal stimulation. These response times establish, after accounting for odor transduction and motor delays, that olfactory processing can take tens of milliseconds. This study puts a strong limit on the underlying neural computations and suggests that the action potentials forming the neural basis for these decisions are fired in a few tens of milliseconds.  Understanding how sensory information is processed requires different approaches that span multiple levels of investigation from genes to neurons to behavior. Limits on behavioral performance constrain the possible neural mechanisms responsible for specific computations. Using a novel behavioral paradigm, we established that mice can make decisions about odor intensity surprisingly fast. After accounting for sensory and motor delays, the limit on some olfactory neural computations can be as low as a few tens of milliseconds, which suggests that only the first action potentials across a population of neurons contribute to these computations.

title: Odour encoding by temporal sequences of firing in oscillating neural assemblies
abstract: STIMULUS-EVOKED oscillatory synchronization of activity has been observed in many neural systems, including the cerebral cortex of mammals and the brain of insects1–8. The possible functions of such rhythmic synchronization in neural coding, however, remain largely speculative9–13. In the locust, odours evoke activity in dynamic (evolving) ensembles of transiently synchronized neurons8,14,15. We report here that the active neurons composing these ensembles change in a stimulus-specific manner and with a high degree of reliability on a cycle-by-cycle basis during an odour response. Hence, information about an odour is contained not only in the neural assembly active at each oscillation cycle, but also in the precise temporal sequence in which these assemblies are updated during an odour response. Neural coding with oscillations thus allows combinatorial representations in time as well as in space.

title: Neural Encoding of Odors during Active Sampling and in Turbulent Plumes
abstract: Sensory inputs are often fluctuating and intermittent, yet animals reliably utilize them to direct behavior. Here we ask how natural stimulus fluctuations influence the dynamic neural encoding of odors. Using the locust olfactory system, we isolated two main causes of odor intermittency: chaotic odor plumes and active sampling behaviors. Despite their irregularity, chaotic odor plumes still drove dynamic neural response features including the synchronization, temporal patterning, and short-term plasticity of spiking in projection neurons, enabling classifier-based stimulus identification and activating downstream decoders (Kenyon cells). Locusts can also impose odor intermittency through active sampling movements with their unrestrained antennae. Odors triggered immediate, spatially targeted antennal scanning that, paradoxically, weakened individual neural responses. However, these frequent but weaker responses were highly informative about stimulus location. Thus, not only are odor-elicited dynamic neural responses compatible with natural stimulus fluctuations and important for stimulus identification, but locusts actively increase intermittency, possibly to improve stimulus localization.

title: Predicting odor perceptual similarity from odor structure
abstract: not submitted for publication.  16 April 2014 doi:10.1186/2044-7248-3-S1-O2 Cite this article as: Snitz et al.: Predicting odor perceptual similarity from odor structure. Flavour 2014 3(Suppl 1):O2. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel Snitz et al. Flavour 2014, 3(Suppl 1):O2 http://www.flavourjournal.com/content/3/S1/O2 © 2014 Snitz et al; licensee BioMed Central Ltd.

title: Identification of latent variables in a semantic odor profile database using principal component analysis.
abstract: Many classifications of odors have been proposed, but none of them have yet gained wide acceptance. Odor sensation is usually described by means of odor character descriptors. If these semantic profiles are obtained for a large diversity of compounds, the resulting database can be considered representative of odor perception space. Few of these comprehensive databases are publicly available, being a valuable source of information for fragrance research. Their statistical analysis has revealed that the underlying structure of odor space is high dimensional and not governed by a few primary odors. In a new effort to study the underlying sensory dimensions of the multivariate olfactory perception space, we have applied principal component analysis to a database of 881 perfume materials with semantic profiles comprising 82 odor descriptors. The relationships identified between the descriptors are consistent with those reported in similar studies and have allowed their classification into 17 odor classes.

title: In search of the structure of human olfactory space
abstract: Materials and Methods responses to odorants Responses to 144 odorants were obtained from Dravnieks (1985) and represented in a set of 146D vectors ri → (i = 1...144). We used the percent used (PU) set of responses from Dravnieks (1985). PU describes the fraction of about 150 observers that thought that a given descriptor applies to an odorant. We verified that our conclusions do not change substantially if other parameters are used instead of PU. We performed principle component analysis (PCA) on the vectors using the single value decomposition (SVD) procedure. All computations were performed using MATLAB (Mathworks, Inc.). Before applying PCA we normalized response vectors to have unit length in terms of the L 2 measure. This implies that the vectors resided on a unit sphere in 146D. This reduced somewhat the dimensionality of the dataset to 145D. The normalization step was intended to equalize the odorants in their perceived intensity or concentration. We verified that our conclusions do not change qualitatively if other measures (L 2 through L 9 ) are used for normalization. We noticed some deterioration of the fits beyond this range.

title: Coding of Odors by a Receptor Repertoire
abstract: We provide a systematic analysis of how odor quality, quantity, and duration are encoded by the odorant receptor repertoire of the Drosophila antenna. We test the receptors with a panel of over 100 odors and find that strong responses are sparse, with response density dependent on chemical class. Individual receptors range along a continuum from narrowly tuned to broadly tuned. Broadly tuned receptors are most sensitive to structurally similar odorants. Strikingly, inhibitory responses are widespread among receptors. The temporal dynamics of the receptor repertoire provide a rich representation of odor quality, quantity, and duration. Receptors with similar odor sensitivity often map to widely dispersed glomeruli in the antennal lobe. We construct a multidimensional "odor space" based on the responses of each individual receptor and find that the positions of odors depend on their chemical class, concentration, and molecular complexity. The space provides a basis for predicting behavioral responses to odors.

title: Odor Coding by a Mammalian Receptor Repertoire
abstract: Identification of mammalian olfactory receptor agonists enables development of a predictive model of receptor activation. To Shape a Smell? Our ability to detect and discriminate among the numerous odorous compounds to which we are exposed depends on odorant recognition by members of a large family of heterotrimeric guanine nucleotide–binding protein (G protein)–coupled odorant receptors (ORs). However, the specific physicochemical properties that enable a particular odorant to act as a ligand for a particular receptor—and thus the initial stage in determining how that odorant is perceived—remain unclear. Saito et al. used a heterologous expression system to test the responses of a large library of human and mouse ORs with a panel of 93 odorants. Analysis of ligand properties and OR sequences enabled the authors to develop a model for predicting interactions between ORs and their ligands. Deciphering olfactory encoding requires a thorough description of the ligands that activate each odorant receptor (OR). In mammalian systems, however, ligands are known for fewer than 50 of more than 1400 human and mouse ORs, greatly limiting our understanding of olfactory coding. We performed high-throughput screening of 93 odorants against 464 ORs expressed in heterologous cells and identified agonists for 52 mouse and 10 human ORs. We used the resulting interaction profiles to develop a predictive model relating physicochemical odorant properties, OR sequences, and their interactions. Our results provide a basis for translating odorants into receptor neuron responses and for unraveling mammalian odor coding.

title: Convex Optimization
abstract: Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.

title: Neurogenesis and cell death in olfactory epithelium.
abstract: The olfactory epithelium (OE) of the mammal is uniquely suited as a model system for studying how neurogenesis and cell death interact to regulate neuron number during development and regeneration. To identify factors regulating neurogenesis and neuronal death in the OE, and to determine the mechanisms by which these factors act, investigators studied OE using two major experimental paradigms: tissue culture of OE; and ablation of the olfactory bulb or severing the olfactory nerve in adult animals, procedures that induce cell death and a subsequent surge of neurogenesis in the OE in vivo. These studies characterized the cellular stages in the olfactory receptor neuron (ORN) lineage, leading to the realization that at least three distinct stages of proliferating neuronal precursor cells are employed in generating ORNs. The identification of a number of factors that act to regulate proliferation and survival of ORNs and their precursors suggests that these multiple developmental stages may serve as control points at which cell number is regulated by extrinsic factors. In vivo surgical studies, which have shown that all cell types in the neuronal lineage of the OE undergo apoptotic cell death, support this idea. These studies, and the possible coregulation of neuronal birth and apoptosis in the OE, are discussed.

title: The Value of Information for Populations in Varying Environments
abstract: The notion of information pervades informal descriptions of biological systems, but formal treatments face the problem of defining a quantitative measure of information rooted in a concept of fitness, which is itself an elusive notion. Here, we present a model of population dynamics where this problem is amenable to a mathematical analysis. In the limit where any information about future environmental variations is common to the members of the population, our model is equivalent to known models of financial investment. In this case, the population can be interpreted as a portfolio of financial assets and previous analyses have shown that a key quantity of Shannon’s communication theory, the mutual information, sets a fundamental limit on the value of information. We show that this bound can be violated when accounting for features that are irrelevant in finance but inherent to biological systems, such as the stochasticity present at the individual level. This leads us to generalize the measures of uncertainty and information usually encountered in information theory.

title: Retina is structured to process an excess of darkness in natural scenes
abstract: Retinal ganglion cells that respond selectively to a dark spot on a brighter background (OFF cells) have smaller dendritic fields than their ON counterparts and are more numerous. OFF cells also branch more densely, and thus collect more synapses per visual angle. That the retina devotes more resources to processing dark contrasts predicts that natural images contain more dark information. We confirm this across a range of spatial scales and trace the origin of this phenomenon to the statistical structure of natural scenes. We show that the optimal mosaics for encoding natural images are also asymmetric, with OFF elements smaller and more numerous, matching retinal structure. Finally, the concentration of synapses within a dendritic field matches the information content, suggesting a simple principle to connect a concrete fact of neuroanatomy with the abstract concept of information: equal synapses for equal bits.

title: Predictive information in a sensory population
abstract: Prediction is an essential part of life. However, are we really “good” at making predictions? More specifically, are pieces of our brain close to being optimal predictors? To assess the efficiency of prediction, we need to measure the information that neurons carry about the future of our sensory experiences. We show how to do this, at least in simplified contexts, and find that groups of neurons in the retina indeed are close to maximally efficient at separating predictive information from the nonpredictive background. Efficient coding of predictive information is a principle that can be applied at every stage of neural computation. Guiding behavior requires the brain to make predictions about the future values of sensory inputs. Here, we show that efficient predictive computation starts at the earliest stages of the visual system. We compute how much information groups of retinal ganglion cells carry about the future state of their visual inputs and show that nearly every cell in the retina participates in a group of cells for which this predictive information is close to the physical limit set by the statistical structure of the inputs themselves. Groups of cells in the retina carry information about the future state of their own activity, and we show that this information can be compressed further and encoded by downstream predictor neurons that exhibit feature selectivity that would support predictive computations. Efficient representation of predictive information is a candidate principle that can be applied at each stage of neural computation.

title: Optimal Prediction in the Retina and Natural Motion Statistics
abstract: Almost all behaviors involve making predictions. Whether an organism is trying to catch prey, avoid predators, or simply move through a complex environment, the organism uses the data it collects through its senses to guide its actions by extracting from these data information about the future state of the world. A key aspect of the prediction problem is that not all features of the past sensory input have predictive power, and representing all features of the external sensory world is prohibitively costly both due to space and metabolic constraints. This leads to the hypothesis that neural systems are optimized for prediction. Here we describe theoretical and computational efforts to define and quantify the efficient representation of the predictive information by the brain. Another important feature of the prediction problem is that the physics of the world is diverse enough to contain a wide range of possible statistical ensembles, yet not all inputs are probable. Thus, the brain might not be a generalized predictive machine; it might have evolved to specifically solve the prediction problems most common in the natural environment. This paper summarizes recent results on predictive coding and optimal predictive information in the retina and suggests approaches for quantifying prediction in response to natural motion. Basic statistics of natural movies reveal that general patterns of spatiotemporal correlation are present across a wide range of scenes, though individual differences in motion type may be important for optimal processing of motion in a given ecological niche.

title: Generating random correlation matrices based on vines and extended onion method
abstract: We extend and improve two existing methods of generating random correlation matrices, the onion method of Ghosh and Henderson [S. Ghosh, S.G. Henderson, Behavior of the norta method for correlated random vector generation as the dimension increases, ACM Transactions on Modeling and Computer Simulation (TOMACS) 13 (3) (2003) 276-294] and the recently proposed method of Joe [H. Joe, Generating random correlation matrices based on partial correlations, Journal of Multivariate Analysis 97 (2006) 2177-2189] based on partial correlations. The latter is based on the so-called D-vine. We extend the methodology to any regular vine and study the relationship between the multiple correlation and partial correlations on a regular vine. We explain the onion method in terms of elliptical distributions and extend it to allow generating random correlation matrices from the same joint distribution as the vine method. The methods are compared in terms of time necessary to generate 5000 random correlation matrices of given dimensions.