Structured Odorant Response Patterns across a Complete Olfactory Receptor Neuron Population

Dynamics of two distinct memory interactions during water seeking in Drosophila

Forming and forgetting memories shape our self-awareness and help us face future challenges. Therefore, understanding how memories are formed and how different memories interact in the brain is important. Previous studies have shown that thirsty flies sense humidity through ionotropic receptors, which help them locate water sources. Here, we showed that thirsty flies can be trained to associate specific odors with humidity to form a humidity memory that lasts for 30 min after association. Humidity memory formation requires the Ir93a and Ir40a ionotropic receptors, which are essential for environmental humidity sensing. Water memory takes precedence, leading to the forgetting of humidity memory by activating a small subset of dopaminergic neurons called protocerebral anterior medial (PAM)-γ4, that project to the restricted region of the mushroom body (MB) γ lobes. Adult-stage-specific silencing of Dop2R dopaminergic receptors in MB γ neurons prolongs humidity memory for 3 h. Live-brain calcium imaging and dopamine sensor studies revealed significantly increased PAM-γ4 neural activity after odor/humidity association, suggesting its role in forgetting the humidity memory. Our results suggest that overlapping neural circuits are responsible for the acquisition of water memory and forgetting humidity memory in thirsty flies.

Nonlinear high-activity neuronal excitation enhances odor discrimination

Discrimination between different signals is crucial for animals' survival. Inhibition that suppresses weak neural activity is crucial for pattern decorrelation. Our understanding of alternative mechanics that allow efficient signal classification remains incomplete. We show that Drosophila olfactory receptor neurons (ORNs) have numerous intraglomerular axo-axonal connections mediated by the G protein-coupled receptor (GPCR), muscarinic type B receptor (mAChR-B). Contrary to its usual inhibitory role, mAChR-B participates in ORN excitation. The excitatory effect of mAChR-B only occurs at high ORN firing rates. A computational model demonstrates that nonlinear intraglomerular or global excitation decorrelates the activity patterns of ORNs of different types and improves odor classification and discrimination, while acting in concert with the previously known inhibition. Indeed, knocking down mAChR-B led to increased correlation in odor-induced ORN activity, which was associated with impaired odor discrimination, as shown in behavioral experiments. Furthermore, knockdown (KD) of mAChR-B and the GABAergic GPCR, GABAB-R, has an additive behavioral effect, causing reduced odor discrimination relative to single-KD flies. Together, this study unravels a novel mechanism for neuronal pattern decorrelation, which is based on nonlinear intraglomerular excitation.

Olfactory Receptor Responses to Pure Odorants in Drosophila melanogaster

Olfactory coding relies on primary information from olfactory receptor cells that respond to volatile airborne substances. Despite extensive efforts, our understanding of odor-response profiles across receptors is still poor, because of the vast number of possible ligands (odorants), the high sensitivity even to trace compounds (creating false positive responses), and the diversity of olfactory receptors. Here, we linked chemical purification with a gas chromatograph to single-receptor type recording with transgenic flies using calcium imaging to record olfactory responses to a large panel of chemicals in seven Drosophila ORs: Or10a, Or13a, Or22a, Or42b, Or47a, Or56a, and Or92a. We analyze the data using linear-nonlinear modeling and reveal that most receptors have "simple" response types (mostly positive: Or10a, Or13a, Or22a, Or47a, and Or56a). However, two receptors (Or42b and Or92a) have, in addition to "simple" responses, "complex" response types to some ligands, either positive with a negative second phase or negative with a positive second phase, suggesting the presence of multiple binding sites and/or transduction cascades. We show that some ligands reported in the literature are false positives, because of contaminations in the stimulus. We recorded all stimuli across concentrations, showing that at different concentrations, different substances appear as best ligands. Our data show that studying combinatorial olfactory coding must consider temporal response properties and odorant concentration and, in addition, is strongly influenced by the presence of trace amounts of ligands (contaminations) in the samples. These observations have important repercussions for our thinking about how animals navigate their olfactory environment.

Glia control experience-dependent plasticity in an olfactory critical period

Sensory experience during developmental critical periods has lifelong consequences for circuit function and behavior, but the molecular and cellular mechanisms through which experience causes these changes are not well understood. The Drosophila antennal lobe houses synapses between olfactory sensory neurons (OSNs) and downstream projection neurons (PNs) in stereotyped glomeruli. Many glomeruli exhibit structural plasticity in response to early-life odor exposure, indicating a general sensitivity of the fly olfactory circuitry to early sensory experience. We recently found that glia shape antennal lobe development in young adults, leading us to ask if glia also drive experience-dependent plasticity during this period. Here, we define a critical period for structural and functional plasticity of OSN-PN synapses in the ethyl butyrate (EB)-sensitive glomerulus VM7. EB exposure for the first 2 days post-eclosion drives large-scale reductions in glomerular volume, presynapse number, and post- synaptic activity. Crucially, pruning during the critical period has long-term consequences for circuit function since both OSN-PN synapse number and spontaneous activity of PNs remain persistently decreased following early-life odor exposure. The highly conserved engulfment receptor Draper is required for this critical period plasticity as ensheathing glia upregulate Draper, invade the VM7 glomerulus, and phagocytose OSN presynaptic terminals in response to critical-period EB exposure. Loss of Draper fully suppresses the morphological and physiological consequences of critical period odor exposure, arguing that phagocytic glia engulf intact synaptic terminals. These data demonstrate experience-dependent pruning of synapses and argue that Drosophila olfactory circuitry is a powerful model for defining the function of glia in critical period plasticity.

Glia control experience-dependent plasticity in an olfactory critical period

Sensory experience during developmental critical periods has lifelong consequences for circuit function and behavior, but the molecular and cellular mechanisms through which experience causes these changes are not well understood. The Drosophila antennal lobe houses synapses between olfactory sensory neurons (OSNs) and downstream projection neurons (PNs) in stereotyped glomeruli. Many glomeruli exhibit structural plasticity in response to early-life odor exposure, indicating a general sensitivity of the fly olfactory circuitry to early sensory experience. We recently found that glia shape antennal lobe development in young adults, leading us to ask if glia also drive experience-dependent plasticity during this period. Here we define a critical period for structural and functional plasticity of OSN-PN synapses in the ethyl butyrate (EB)-sensitive glomerulus VM7. EB exposure for the first two days post-eclosion drives large-scale reductions in glomerular volume, presynapse number, and post-synaptic activity. Crucially, pruning during the critical period has long-term consequences for circuit function since both OSN-PN synapse number and spontaneous activity of PNs remain persistently decreased following early-life odor exposure. The highly conserved engulfment receptor Draper is required for this critical period plasticity as ensheathing glia upregulate Draper, invade the VM7 glomerulus, and phagocytose OSN presynaptic terminals in response to critical-period EB exposure. Loss of Draper fully suppresses the morphological and physiological consequences of critical period odor exposure, arguing that phagocytic glia engulf intact synaptic terminals. These data demonstrate experience-dependent pruning of synapses and argue that Drosophila olfactory circuitry is a powerful model for defining the function of glia in critical period plasticity.

Bifurcation enhances temporal information encoding in the olfactory periphery

Living systems continually respond to signals from the surrounding environment. Survival requires that their responses adapt quickly and robustly to the changes in the environment. One particularly challenging example is olfactory navigation in turbulent plumes, where animals experience highly intermittent odor signals while odor concentration varies over many length- and timescales. Here, we show theoretically that Drosophila olfactory receptor neurons (ORNs) can exploit proximity to a bifurcation point of their firing dynamics to reliably extract information about the timing and intensity of fluctuations in the odor signal, which have been shown to be critical for odor-guided navigation. Close to the bifurcation, the system is intrinsically invariant to signal variance, and information about the timing, duration, and intensity of odor fluctuations is transferred efficiently. Importantly, we find that proximity to the bifurcation is maintained by mean adaptation alone and therefore does not require any additional feedback mechanism or fine-tuning. Using a biophysical model with calcium-based feedback, we demonstrate that this mechanism can explain the measured adaptation characteristics of Drosophila ORNs.

Bifurcation enhances temporal information encoding in the olfactory periphery

Living systems continually respond to signals from the surrounding environment. Survival requires that their responses adapt quickly and robustly to the changes in the environment. One particularly challenging example is olfactory navigation in turbulent plumes, where animals experience highly intermittent odor signals while odor concentration varies over many length- and timescales. Here, we show theoretically that Drosophila olfactory receptor neurons (ORNs) can exploit proximity to a bifurcation point of their firing dynamics to reliably extract information about the timing and intensity of fluctuations in the odor signal, which have been shown to be critical for odor-guided navigation. Close to the bifurcation, the system is intrinsically invariant to signal variance, and information about the timing, duration, and intensity of odor fluctuations is transferred efficiently. Importantly, we find that proximity to the bifurcation is maintained by mean adaptation alone and therefore does not require any additional feedback mechanism or fine-tuning. Using a biophysical model with calcium-based feedback, we demonstrate that this mechanism can explain the measured adaptation characteristics of Drosophila ORNs.

Stimulus duration encoding occurs early in the moth olfactory pathway

Pheromones convey rich ethological information and guide insects' search behavior. Insects navigating in turbulent environments are tasked with the challenge of coding the temporal structure of an odor plume, obliging recognition of the onset and offset of whiffs of odor. The coding mechanisms that shape odor offset recognition remain elusive. We designed a device to deliver sharp pheromone pulses and simultaneously measured the response dynamics from pheromone-tuned olfactory receptor neurons (ORNs) in male moths and Drosophila. We show that concentration-invariant stimulus duration encoding is implemented in moth ORNs by spike frequency adaptation at two time scales. A linear-nonlinear model fully captures the underlying neural computations and offers an insight into their biophysical mechanisms. Drosophila use pheromone cis-vaccenyl acetate (cVA) only for very short distance communication and are not faced with the need to encode the statistics of the cVA plume. Their cVA-sensitive ORNs are indeed unable to encode odor-off events. Expression of moth pheromone receptors in Drosophila cVA-sensitive ORNs indicates that stimulus-offset coding is receptor independent. In moth ORNs, stimulus-offset coding breaks down for short ( < 200 ms) whiffs. This physiological constraint matches the behavioral latency of switching from the upwind surge to crosswind cast flight upon losing contact with the pheromone.

The olfactory system of sharks and rays in numbers

Cartilaginous fishes have large and elaborate olfactory organs, but only a small repertoire of olfactory receptor genes. Here, we quantitatively analyze the olfactory system of 21 species of sharks and rays, assessing many features of the olfactory organ (OOR) (number of primary lamellae, branches of the secondary folds, sensory surface area, and density and number of sensory neurons) and the olfactory bulb (OB) (number of neurons and non-neuronal cells), and estimate the ratio between the number of neurons in the two structures. We show that the number of lamellae in the OOR does not correlate with the sensory surface area, while the complexity of the lamellar shape does. The total number of olfactory receptor neurons ranges from 30.5 million to 4.3 billion and the total number of OB neurons from 1.5 to 90 million. The number of neurons in the olfactory epithelium is 16 to 158 times higher (median ratio is 46) than the number of neurons in the OB. These ratios considerably exceed those reported in mammals. High convergence from receptor neurons to neurons processing olfactory information, together with the remarkably small olfactory receptor repertoire, strongly suggests that the olfactory system of sharks and rays is well adapted to detect a limited number of odorants with high sensitivity.

Tracking the Navigation Behavior of Drosophila Larvae in Real and Virtual Odor Gradients by Using the Raspberry Pi Virtual Reality (PiVR) System

In a closed-loop experimental paradigm, an animal experiences a modulation of its sensory input as a function of its own behavior. Tools enabling closed-loop experiments are crucial for delineating causal relationships between the activity of genetically labeled neurons and specific behavioral responses. We have recently developed an experimental platform known as "Raspberry Pi Virtual Reality" (PiVR) that is used to perform closed-loop optogenetic stimulation of neurons in unrestrained animals. PiVR is a system that operates at high temporal resolution (>30-Hz) and with low latencies. Larvae of the fruit fly Drosophila melanogaster are ideal to study the role of individual neurons in modulating behavior to aid the understanding of the neural pathways underlying various guided behaviors. Here, we introduce larval chemotaxis as an example of a navigational behavior in which an animal seeks to locate a target-in this case, the attractive source of an odor-by tracking a concentration gradient. The methodologies that we describe here combine the use of PiVR with the study of larval chemotaxis in real and virtual odor gradients, but these can also be readily adapted to other sensory modalities.

Common principles for odour coding across vertebrates and invertebrates

The olfactory system is an ideal and tractable system for exploring how the brain transforms sensory inputs into behaviour. The basic tasks of any olfactory system include odour detection, discrimination and categorization. The challenge for the olfactory system is to transform the high-dimensional space of olfactory stimuli into the much smaller space of perceived objects and valence that endows odours with meaning. Our current understanding of how neural circuits address this challenge has come primarily from observations of the mechanisms of the brain for processing other sensory modalities, such as vision and hearing, in which optimized deep hierarchical circuits are used to extract sensory features that vary along continuous physical dimensions. The olfactory system, by contrast, contends with an ill-defined, high-dimensional stimulus space and discrete stimuli using a circuit architecture that is shallow and parallelized. Here, we present recent observations in vertebrate and invertebrate systems that relate the statistical structure and state-dependent modulation of olfactory codes to mechanisms of perception and odour-guided behaviour.

Fly Me to the Micron: Microtechnologies for Drosophila Research

Multicellular model organisms, such as Drosophila melanogaster (fruit fly), are frequently used in a myriad of biological research studies due to their biological significance and global standardization. However, traditional tools used in these studies generally require manual handling, subjective phenotyping, and bulk treatment of the organisms, resulting in laborious experimental protocols with limited accuracy. Advancements in microtechnology over the course of the last two decades have allowed researchers to develop automated, high-throughput, and multifunctional experimental tools that enable novel experimental paradigms that would not be possible otherwise. We discuss recent advances in microtechnological systems developed for small model organisms using D. melanogaster as an example. We critically analyze the state of the field by comparing the systems produced for different applications. Additionally, we suggest design guidelines, operational tips, and new research directions based on the technical and knowledge gaps in the literature. This review aims to foster interdisciplinary work by helping engineers to familiarize themselves with model organisms while presenting the most recent advances in microengineering strategies to biologists.

Prediction error drives associative learning and conditioned behavior in a spiking model of Drosophila larva

Predicting reinforcement from sensory cues is beneficial for goal-directed behavior. In insect brains, underlying associations between cues and reinforcement, encoded by dopaminergic neurons, are formed in the mushroom body. We propose a spiking model of the Drosophila larva mushroom body. It includes a feedback motif conveying learned reinforcement expectation to dopaminergic neurons, which can compute prediction error as the difference between expected and present reinforcement. We demonstrate that this can serve as a driving force in learning. When combined with synaptic homeostasis, our model accounts for theoretically derived features of acquisition and loss of associations that depend on the intensity of the reinforcement and its temporal proximity to the cue. From modeling olfactory learning over the time course of behavioral experiments and simulating the locomotion of individual larvae toward or away from odor sources in a virtual environment, we conclude that learning driven by prediction errors can explain larval behavior.

Pheromone and Host Plant Odor Detection in Eastern Spruce Budworm, Choristoneura fumiferana Clemens (Lepidoptera: Tortricidae)

Spruce budworm, Choristoneura fumiferana Clemens, is an ecologically significant defoliator of spruce and balsam fir in North America. Optimization of semiochemical-mediated control is needed to improve the existing integrated pest management systems such as mating disruption and population estimation. This study used single sensillum recordings (SSR) to identify the responses of olfactory receptor neurons (ORNs) in the antennal sensilla of adult male and female C. fumiferana to host plant volatiles, and female sex pheromones. There have been few SSR studies done on spruce budworm, and to our knowledge, the present study represents the first attempt to examine the responses of ORNs from antennal sensilla in response to a range of host and conspecific stimuli. A total of 86 sensilla were characterized and sorted into 15 possible sensillum categories based on odor responses. We observed that specialist sensilla responding to few ligands were more abundant in both male and female than sensilla exhibiting more generalized odorant responses. (E/Z)-11-tetradecenal elicited responses from ORNs from any sensilla which were sensitive to pheromones in both males and females. Female C. fumiferana ORNs were able to detect and physiologically respond to female-produced sex pheromones with the same degree of sensitivity as their male counterparts. Together, these data improve our knowledge of mechanisms by which adult budworms respond to pheromone and host plant volatiles and provide insights that may be complementary to existing integrated pest management (IPM) strategies based on the chemical ecology of spruce budworm.

Normative and mechanistic model of an adaptive circuit for efficient encoding and feature extraction

One major question in neuroscience is how to relate connectomes to neural activity, circuit function, and learning. We offer an answer in the peripheral olfactory circuit of the Drosophila larva, composed of olfactory receptor neurons (ORNs) connected through feedback loops with interconnected inhibitory local neurons (LNs). We combine structural and activity data and, using a holistic normative framework based on similarity-matching, we formulate biologically plausible mechanistic models of the circuit. In particular, we consider a linear circuit model, for which we derive an exact theoretical solution, and a nonnegative circuit model, which we examine through simulations. The latter largely predicts the ORN [Formula: see text] LN synaptic weights found in the connectome and demonstrates that they reflect correlations in ORN activity patterns. Furthermore, this model accounts for the relationship between ORN [Formula: see text] LN and LN-LN synaptic counts and the emergence of different LN types. Functionally, we propose that LNs encode soft cluster memberships of ORN activity, and partially whiten and normalize the stimulus representations in ORNs through inhibitory feedback. Such a synaptic organization could, in principle, autonomously arise through Hebbian plasticity and would allow the circuit to adapt to different environments in an unsupervised manner. We thus uncover a general and potent circuit motif that can learn and extract significant input features and render stimulus representations more efficient. Finally, our study provides a unified framework for relating structure, activity, function, and learning in neural circuits and supports the conjecture that similarity-matching shapes the transformation of neural representations.

Functional imaging and quantification of multineuronal olfactory responses in C. elegans

Many animals perceive odorant molecules by collecting information from ensembles of olfactory neurons, where each neuron uses receptors that are tuned to recognize certain odorant molecules with different binding affinity. Olfactory systems are able, in principle, to detect and discriminate diverse odorants using combinatorial coding strategies. We have combined microfluidics and multineuronal imaging to study the ensemble-level olfactory representations at the sensory periphery of the nematode Caenorhabditis elegans. The collective activity of C. elegans chemosensory neurons reveals high-dimensional representations of olfactory information across a broad space of odorant molecules. We reveal diverse tuning properties and dose-response curves across chemosensory neurons and across odorants. We describe the unique contribution of each sensory neuron to an ensemble-level code for volatile odorants. We show that a natural stimuli, a set of nematode pheromones, are also encoded by the sensory ensemble. The integrated activity of the C. elegans chemosensory neurons contains sufficient information to robustly encode the intensity and identity of diverse chemical stimuli.

Androstadienone sensitivity is associated with attention to emotions, social interactions, and sexual behavior in older U.S. adults

Δ 4,16-androstadien-3-one (androstadienone) is a putative human pheromone often linked to sexual attraction in young adults, although specific associations with sexual behavior are not yet established. Androstadienone also serves a broader social-emotional function beyond the sexual domain, specifically tuning the brain to efficiently process emotional information. Whether these effects persist throughout the lifespan into post-reproductive life is unknown. In a laboratory study of older adults, those with greater androstadienone odor sensitivity paid greater attention to subliminal emotional information, specifically, angry faces (p = 0.05), with a similar relationship to happy faces. In contrast, the physical odor n-butanol (a control) did not affect emotional attention (p = 0.49). We then extended this laboratory research and determined whether sensitivity to androstadienone affects the everyday lives of older adults by measuring their social and sexual behavior. In this second study, we surveyed in a nationally representative sample of US older adults living in their homes (National Social Life and Aging Project, 62-90 years; n = 2,086), along with their sensitivity to androstadienone, general olfactory function, health and demographics. Greater sensitivity to androstadienone was associated with richer social lives: having more friends, increased communication with close friends and family, and more participation in organized social events and volunteer activities (all p's ≤ 0.05, generalized linear models, adjusted for age and gender). It was also associated with more recent sexual activity, more frequent sexual thoughts, and viewing sex as an important part of life (all p's ≤ 0.05). General olfactory function did not explain these associations, supporting a specialized function for this pheromone during everyday life, and expanding its role to social life as well as sexual behavior, likely mediated by enhanced attention to emotional information.

Depolarization block in olfactory sensory neurons expands the dimensionality of odor encoding

Upon strong and prolonged excitation, neurons can undergo a silent state called depolarization block that is often associated with disorders such as epileptic seizures. Here, we show that neurons in the peripheral olfactory system undergo depolarization block as part of their normal physiological function. Typically, olfactory sensory neurons enter depolarization block at odor concentrations three orders of magnitude above their detection threshold, thereby defining receptive fields over concentration bands. The silencing of high-affinity olfactory sensory neurons produces sparser peripheral odor representations at high-odor concentrations, which might facilitate perceptual discrimination. Using a conductance-based model of the olfactory transduction cascade paired with spike generation, we provide numerical and experimental evidence that depolarization block arises from the slow inactivation of sodium channels-a process that could affect a variety of sensory neurons. The existence of ethologically relevant depolarization block in olfactory sensory neurons creates an additional dimension that expands the peripheral encoding of odors.

Internal state affects local neuron function in an early sensory processing center to shape olfactory behavior in Drosophila larvae

Crawling insects, when starved, tend to have fewer head wavings and travel in straighter tracks in search of food. We used the Drosophila melanogaster larva to investigate whether this flexibility in the insect's navigation strategy arises during early olfactory processing and, if so, how. We demonstrate a critical role for Keystone-LN, an inhibitory local neuron in the antennal lobe, in implementing head-sweep behavior. Keystone-LN responds to odor stimuli, and its inhibitory output is required for a larva to successfully navigate attractive and aversive odor gradients. We show that insulin signaling in Keystone-LN likely mediates the starvation-dependent changes in head-sweep magnitude, shaping the larva's odor-guided movement. Our findings demonstrate how flexibility in an insect's navigation strategy can arise from context-dependent modulation of inhibitory neurons in an early sensory processing center. They raise new questions about modulating a circuit's inhibitory output to implement changes in a goal-directed movement.

Mapping odorant sensitivities reveals a sparse but structured representation of olfactory chemical space by sensory input to the mouse olfactory bulb

In olfactory systems, convergence of sensory neurons onto glomeruli generates a map of odorant receptor identity. How glomerular maps relate to sensory space remains unclear. We sought to better characterize this relationship in the mouse olfactory system by defining glomeruli in terms of the odorants to which they are most sensitive. Using high-throughput odorant delivery and ultrasensitive imaging of sensory inputs, we imaged responses to 185 odorants presented at concentrations determined to activate only one or a few glomeruli across the dorsal olfactory bulb. The resulting datasets defined the tuning properties of glomeruli - and, by inference, their cognate odorant receptors - in a low-concentration regime, and yielded consensus maps of glomerular sensitivity across a wide range of chemical space. Glomeruli were extremely narrowly tuned, with ~25% responding to only one odorant, and extremely sensitive, responding to their effective odorants at sub-picomolar to nanomolar concentrations. Such narrow tuning in this concentration regime allowed for reliable functional identification of many glomeruli based on a single diagnostic odorant. At the same time, the response spectra of glomeruli responding to multiple odorants was best predicted by straightforward odorant structural features, and glomeruli sensitive to distinct odorants with common structural features were spatially clustered. These results define an underlying structure to the primary representation of sensory space by the mouse olfactory system.

Synthesis of Cyclic Fragrances via Transformations of Alkenes, Alkynes and Enynes: Strategies and Recent Progress

With increasing demand for customized commodities and the greater insight and understanding of olfaction, the synthesis of fragrances with diverse structures and odor characters has become a core task. Recent progress in organic synthesis and catalysis enables the rapid construction of carbocycles and heterocycles from readily available unsaturated molecular building blocks, with increased selectivity, atom economy, sustainability and product diversity. In this review, synthetic methods for creating cyclic fragrances, including both natural and synthetic ones, will be discussed, with a focus on the key transformations of alkenes, alkynes, dienes and enynes. Several strategies will be discussed, including cycloaddition, catalytic cyclization, ring-closing metathesis, intramolecular addition, and rearrangement reactions. Representative examples and the featured olfactory investigations will be highlighted, along with some perspectives on future developments in this area.

Mechanisms of Variability Underlying Odor-Guided Locomotion

Changes in locomotion mediated by odors (odor-guided locomotion) are an important mechanism by which animals discover resources important to their survival. Odor-guided locomotion, like most other behaviors, is highly variable. Variability in behavior can arise at many nodes along the circuit that performs sensorimotor transformation. We review these sources of variability in the context of the Drosophila olfactory system. While these sources of variability are important, using a model for locomotion, we show that another important contributor to behavioral variability is the stochastic nature of decision-making during locomotion as well as the persistence of these decisions: Flies choose the speed and curvature stochastically from a distribution and locomote with the same speed and curvature for extended periods. This stochasticity in locomotion will result in variability in behavior even if there is no noise in sensorimotor transformation. Overall, the noise in sensorimotor transformation is amplified by mechanisms of locomotion making odor-guided locomotion in flies highly variable.

A closer look at sex pheromone autodetection in the Oriental fruit moth

Female moths emit sex pheromone to attracts males, and although they are not attracted to their own sex pheromone, they appear to detect it as it affects their behavior. In order to elucidate the mechanism of pheromone "autodetection" we compared responses of olfactory receptor neurons (ORNs) of male and female Grapholita molesta, a species with reported pheromone autodetection. Two concentrations of the major (Z8-12:Ac) and minor (E8-12:Ac) sex pheromone components, a plant-volatile blend containing methyl salicylate, terpinyl acetate and (E)-β-farnesene, and the male-produced hair-pencil (i.e., courtship) pheromone (ethyl trans-cinnamate) were tested in 45 male and 305 female ORNs. Hierarchical cluster analysis showed radically different peripheral olfactory systems between sexes that could be linked to their specific roles. In males 63% of the ORNs were tuned specifically to the major or minor female sex pheromone components, and 4% to the plant volatile blend, while the remaining 33% showed unspecific responses to the stimulus panel. In females 3% of the ORNs were specifically tuned to the male hair-pencil pheromone, 6% to the plant volatile blend, 91% were unspecific, and no ORN was tuned their own sex pheromone components. The lack of sex pheromone-specific ORNs in females suggests that they are not able to discriminate pheromone blends, and thus pheromone autodetection is unlikely in this species. We discuss our results in the context of the methodological limitations inherent to odor stimulation studies.

Modulation of sensory perception by hydrogen peroxide enables Caenorhabditis elegans to find a niche that provides both food and protection from hydrogen peroxide

Hydrogen peroxide (H2O2) is the most common chemical threat that organisms face. Here, we show that H2O2 alters the bacterial food preference of Caenorhabditis elegans, enabling the nematodes to find a safe environment with food. H2O2 induces the nematodes to leave food patches of laboratory and microbiome bacteria when those bacterial communities have insufficient H2O2-degrading capacity. The nematode's behavior is directed by H2O2-sensing neurons that promote escape from H2O2 and by bacteria-sensing neurons that promote attraction to bacteria. However, the input for H2O2-sensing neurons is removed by bacterial H2O2-degrading enzymes and the bacteria-sensing neurons' perception of bacteria is prevented by H2O2. The resulting cross-attenuation provides a general mechanism that ensures the nematode's behavior is faithful to the lethal threat of hydrogen peroxide, increasing the nematode's chances of finding a niche that provides both food and protection from hydrogen peroxide.

Circuits for integrating learned and innate valences in the insect brain

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. We used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all mushroom body (MB) output neurons (encoding learned valences) and characterized their patterns of interaction with lateral horn (LH) neurons (encoding innate valences) in Drosophila larva. The connectome revealed multiple convergence neuron types that receive convergent MB and LH inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. We confirmed functional connectivity from LH and MB pathways and behavioral roles of two of these neurons. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this, we speculate that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, our study provides insights into the circuits that integrate learned and innate valences to modify behavior.

Short-Term Plasticity Regulates Both Divisive Normalization and Adaptive Responses in Drosophila Olfactory System

In Drosophila, olfactory information received by olfactory receptor neurons (ORNs) is first processed by an incoherent feed forward neural circuit in the antennal lobe (AL) that consists of ORNs (input), inhibitory local neurons (LNs), and projection neurons (PNs). This “early” olfactory information processing has two important characteristics. First, response of a PN to its cognate ORN is normalized by the overall activity of other ORNs, a phenomenon termed “divisive normalization.” Second, PNs respond strongly to the onset of ORN activities, but they adapt to prolonged or continuously varying inputs. Despite the importance of these characteristics for learning and memory, their underlying mechanisms are not fully understood. Here, we develop a circuit model for describing the ORN-LN-PN dynamics by including key neuron-neuron interactions such as short-term plasticity (STP) and presynaptic inhibition (PI). By fitting our model to experimental data quantitatively, we show that a strong STP balanced between short-term facilitation (STF) and short-term depression (STD) is responsible for the observed nonlinear divisive normalization in Drosophila. Our circuit model suggests that either STP or PI alone can lead to adaptive response. However, by comparing our model results with experimental data, we find that both STP and PI work together to achieve a strong and robust adaptive response. Our model not only helps reveal the mechanisms underlying two main characteristics of the early olfactory process, it can also be used to predict PN responses to arbitrary time-dependent signals and to infer microscopic properties of the circuit (such as the strengths of STF and STD) from the measured input-output relation. Our circuit model may be useful for understanding the role of STP in other sensory systems.

The chemosensory system of the Drosophila larva: an overview of current understanding

Animals must sense their surroundings and be able to distinguish between relevant and irrelevant cues. An enticing area of research aims to uncover the mechanisms by which animals respond to chemical signals that constitute critical sensory input. In this review, we describe the principles of a model chemosensory system: the Drosophila larva. While distinct in many ways, larval behaviour is reminiscent of the dogmatic goals of life: to reach a stage of reproductive potential. It takes into account a number of distinct and identifiable parameters to ultimately provoke or modulate appropriate behavioural output. In this light, we describe current knowledge of chemosensory anatomy, genetic components, and the processing logic of chemical cues. We outline recent advancements and summarize the hypothesized neural circuits of sensory systems. Furthermore, we note yet-unanswered questions to create a basis for further investigation of molecular and systemic mechanisms of chemosensation in Drosophila and beyond.

Building population models for large-scale neural recordings: Opportunities and pitfalls

Modern recording technologies now enable simultaneous recording from large numbers of neurons. This has driven the development of new statistical models for analyzing and interpreting neural population activity. Here, we provide a broad overview of recent developments in this area. We compare and contrast different approaches, highlight strengths and limitations, and discuss biological and mechanistic insights that these methods provide.

Efficient population coding depends on stimulus convergence and source of noise

Sensory organs transmit information to downstream brain circuits using a neural code comprised of spikes from multiple neurons. According to the prominent efficient coding framework, the properties of sensory populations have evolved to encode maximum information about stimuli given biophysical constraints. How information coding depends on the way sensory signals from multiple channels converge downstream is still unknown, especially in the presence of noise which corrupts the signal at different points along the pathway. Here, we calculated the optimal information transfer of a population of nonlinear neurons under two scenarios. First, a lumped-coding channel where the information from different inputs converges to a single channel, thus reducing the number of neurons. Second, an independent-coding channel when different inputs contribute independent information without convergence. In each case, we investigated information loss when the sensory signal was corrupted by two sources of noise. We determined critical noise levels at which the optimal number of distinct thresholds of individual neurons in the population changes. Comparing our system to classical physical systems, these changes correspond to first- or second-order phase transitions for the lumped- or the independent-coding channel, respectively. We relate our theoretical predictions to coding in a population of auditory nerve fibers recorded experimentally, and find signatures of efficient coding. Our results yield important insights into the diverse coding strategies used by neural populations to optimally integrate sensory stimuli in the presence of distinct sources of noise.

NeuroPAL: A Multicolor Atlas for Whole-Brain Neuronal Identification in C. elegans

Comprehensively resolving neuronal identities in whole-brain images is a major challenge. We achieve this in C. elegans by engineering a multicolor transgene called NeuroPAL (a neuronal polychromatic atlas of landmarks). NeuroPAL worms share a stereotypical multicolor fluorescence map for the entire hermaphrodite nervous system that resolves all neuronal identities. Neurons labeled with NeuroPAL do not exhibit fluorescence in the green, cyan, or yellow emission channels, allowing the transgene to be used with numerous reporters of gene expression or neuronal dynamics. We showcase three applications that leverage NeuroPAL for nervous-system-wide neuronal identification. First, we determine the brainwide expression patterns of all metabotropic receptors for acetylcholine, GABA, and glutamate, completing a map of this communication network. Second, we uncover changes in cell fate caused by transcription factor mutations. Third, we record brainwide activity in response to attractive and repulsive chemosensory cues, characterizing multimodal coding for these stimuli.

Adaptive temporal processing of odor stimuli

The olfactory system translates chemical signals into neuronal signals that inform behavioral decisions of the animal. Odors are cues for source identity, but if monitored long enough, they can also be used to localize the source. Odor representations should therefore be robust to changing conditions and flexible in order to drive an appropriate behavior. In this review, we aim at discussing the main computations that allow robust and flexible encoding of odor information in the olfactory neural pathway.

Internal state configures olfactory behavior and early sensory processing in Drosophila larvae

Animals exhibit different behavioral responses to the same sensory cue depending on their internal state at a given moment. How and where in the brain are sensory inputs combined with state information to select an appropriate behavior? Here, we investigate how food deprivation affects olfactory behavior in Drosophila larvae. We find that certain odors repel well-fed animals but attract food-deprived animals and that feeding state flexibly alters neural processing in the first olfactory center, the antennal lobe. Hunger differentially modulates two output pathways required for opposing behavioral responses. Upon food deprivation, attraction-mediating uniglomerular projection neurons show elevated odor-evoked activity, whereas an aversion-mediating multiglomerular projection neuron receives odor-evoked inhibition. The switch between these two pathways is regulated by the lone serotonergic neuron in the antennal lobe, CSD. Our findings demonstrate how flexible behaviors can arise from state-dependent circuit dynamics in an early sensory processing center.

Useful road maps: studying Drosophila larva's central nervous system with the help of connectomics

The larva of Drosophila melanogaster is emerging as a powerful model system for comprehensive brain-wide understanding of the circuit implementation of neural computations. With an unprecedented amount of tools in hand, including synaptic-resolution connectomics, whole-brain imaging, and genetic tools for selective targeting of single neuron types, it is possible to dissect which circuits and computations are at work behind behaviors that have an interesting level of complexity. Here we present some of the recent advances regarding multisensory integration, learning, and action selection in Drosophila larva.

Mini-brain computations converting dynamic olfactory inputs into orientation behavior

The neural logic underlying the conversion of non-stationary (dynamic) olfactory inputs into odor-search behaviors has been difficult to crack due to the distributed nature of the olfactory code - food odors typically co-activate multiple olfactory sensory neurons. In the Drosophila larva, the activity of a single olfactory sensory neuron is sufficient to direct accurate reorientation maneuvers in odor gradients (chemotaxis). In this reduced sensory system, a descending pathway essential for larval chemotaxis has been delineated from the peripheral olfactory system down to the premotor system. Here, I review how anatomical and functional inspections of this pathway have advanced our understanding of the neural mechanisms that convert behaviorally relevant sensory signals into orientation responses.

Inferring population statistics of receptor neurons sensitivities and firing-rates from general functional requirements

On the basis of the evident ability of neuronal olfactory systems to evaluate the intensity of an odorous stimulus and at the same time also recognise the identity of the odorant over a large range of concentrations, a few biologically-realistic hypotheses on some of the underlying neural processes are made. In particular, it is assumed that the receptor neurons mean firing-rate scale monotonically with odorant intensity, and that the receptor sensitivities range widely across odorants and receptor neurons hence leading to highly distributed representations of the stimuli. The mathematical implementation of the phenomenological postulates allows for inferring explicit functional relationships between some measurable quantities. It results that both the dependence of the mean firing-rate on odorant concentration and the statistical distribution of receptor sensitivity across the neuronal population are power-laws, whose respective exponents are in an arithmetic, testable relationship. In order to test quantitatively the prediction of power-law dependence of population mean firing-rate on odorant concentration, a probabilistic model is created to extract information from data available in the experimental literature. The values of the free parameters of the model are estimated by an info-geometric Bayesian maximum-likelihood inference which keeps into account the prior distribution of the parameters. The eventual goodness of fit is quantified by means of a distribution-independent test. The probabilistic model results to be accurate with high statistical significance, thus confirming the theoretical prediction of a power-law dependence on odorant concentration. The experimental data available about the distribution of sensitivities also agree with the other predictions, though they are not statistically sufficient for a very stringent verification. Furthermore, the theory suggests a potential evolutionary reason for the exponent of the sensitivity power-law to be significantly different from the unit. The power-law dependence on concentration is consistent with the psychophysical Stevens Law. On the whole, from the formalisation of just a few phenomenological observations a compact model is derived that may fit experimental findings from several levels of research on olfaction.

Fly-on-a-Chip: Microfluidics for Drosophila melanogaster Studies

The fruit fly or Drosophila melanogaster has been used as a promising model organism in genetics, developmental and behavioral studies as well as in the fields of neuroscience, pharmacology, and toxicology. Not only all the developmental stages of Drosophila, including embryonic, larval, and adulthood stages, have been used in experimental in vivo biology, but also the organs, tissues, and cells extracted from this model have found applications in in vitro assays. However, the manual manipulation, cellular investigation and behavioral phenotyping techniques utilized in conventional Drosophila-based in vivo and in vitro assays are mostly time-consuming, labor-intensive, and low in throughput. Moreover, stimulation of the organism with external biological, chemical, or physical signals requires precision in signal delivery, while quantification of neural and behavioral phenotypes necessitates optical and physical accessibility to Drosophila. Recently, microfluidic and lab-on-a-chip devices have emerged as powerful tools to overcome these challenges. This review paper demonstrates the role of microfluidic technology in Drosophila studies with a focus on both in vivo and in vitro investigations. The reviewed microfluidic devices are categorized based on their applications to various stages of Drosophila development. We have emphasized technologies that were utilized for tissue- and behavior-based investigations. Furthermore, the challenges and future directions in Drosophila-on-a-chip research, and its integration with other advanced technologies, will be discussed.

Controlling and measuring dynamic odorant stimuli in the laboratory

Animals experience complex odorant stimuli that vary widely in composition, intensity and temporal properties. However, stimuli used to study olfaction in the laboratory are much simpler. This mismatch arises from the challenges in measuring and controlling them precisely and accurately. Even simple pulses can have diverse kinetics that depend on their molecular identity. Here, we introduce a model that describes how stimulus kinetics depend on the molecular identity of the odorant and the geometry of the delivery system. We describe methods to deliver dynamic odorant stimuli of several types, including broadly distributed stimuli that reproduce some of the statistics of naturalistic plumes, in a reproducible and precise manner. Finally, we introduce a method to calibrate a photo-ionization detector to any odorant it can detect, using no additional components. Our approaches are affordable and flexible and can be used to advance our understanding of how olfactory neurons encode real-world odor signals.

Functional diversity among sensory neurons from efficient coding principles

In many sensory systems the neural signal is coded by the coordinated response of heterogeneous populations of neurons. What computational benefit does this diversity confer on information processing? We derive an efficient coding framework assuming that neurons have evolved to communicate signals optimally given natural stimulus statistics and metabolic constraints. Incorporating nonlinearities and realistic noise, we study optimal population coding of the same sensory variable using two measures: maximizing the mutual information between stimuli and responses, and minimizing the error incurred by the optimal linear decoder of responses. Our theory is applied to a commonly observed splitting of sensory neurons into ON and OFF that signal stimulus increases or decreases, and to populations of monotonically increasing responses of the same type, ON. Depending on the optimality measure, we make different predictions about how to optimally split a population into ON and OFF, and how to allocate the firing thresholds of individual neurons given realistic stimulus distributions and noise, which accord with certain biases observed experimentally.

Optimal compressed sensing strategies for an array of nonlinear olfactory receptor neurons with and without spontaneous activity

There are numerous different odorant molecules in nature but only a relatively small number of olfactory receptor neurons (ORNs) in brains. This "compressed sensing" challenge is compounded by the constraint that ORNs are nonlinear sensors with a finite dynamic range. Here, we investigate possible optimal olfactory coding strategies by maximizing mutual information between odor mixtures and ORNs' responses with respect to the bipartite odor-receptor interaction network (ORIN) characterized by sensitivities between all odorant-ORN pairs. For ORNs without spontaneous (basal) activity, we find that the optimal ORIN is sparse-a finite fraction of sensitives are zero, and the nonzero sensitivities follow a broad distribution that depends on the odor statistics. We show analytically that sparsity in the optimal ORIN originates from a trade-off between the broad tuning of ORNs and possible interference. Furthermore, we show that the optimal ORIN enhances performances of downstream learning tasks (reconstruction and classification). For ORNs with a finite basal activity, we find that having inhibitory odor-receptor interactions increases the coding capacity and the fraction of inhibitory interactions increases with the ORN basal activity. We argue that basal activities in sensory receptors in different organisms are due to the trade-off between the increase in coding capacity and the cost of maintaining the spontaneous basal activity. Our theoretical findings are consistent with existing experiments and predictions are made to further test our theory. The optimal coding model provides a unifying framework to understand the peripheral olfactory systems across different organisms.

Order in Odors: A Power Law Structures the Encoding of Stimulus Identity and Intensity

Odorant molecules are detected through the combinatorial activation of ensembles of olfactory sensory neurons. By capitalizing on the numerical simplicity of the Drosophila larval brain, Si et al. (2019) uncover principles constraining the representation of the quality and intensity of olfactory stimuli.

Front-end Weber-Fechner gain control enhances the fidelity of combinatorial odor coding

We showed previously (Gorur-Shandilya et al., 2017) that Drosophila olfactory receptor neurons (ORNs) expressing the co-receptor Orco scale their gain inversely with mean odor intensity according to Weber-Fechner's law. Here, we show that this front-end adaptation promotes the reconstruction of odor identity from dynamic odor signals, even in the presence of confounding background odors and rapid intensity fluctuations. These enhancements are further aided by known downstream transformations in the antennal lobe and mushroom body. Our results, which are applicable to various odor classification and reconstruction schemes, stem from the fact that this adaptation mechanism is not intrinsic to the identity of the receptor involved. Instead, a feedback mechanism adjusts receptor sensitivity based on the activity of the receptor-Orco complex, according to Weber-Fechner's law. Thus, a common scaling of the gain across Orco-expressing ORNs may be a key feature of ORN adaptation that helps preserve combinatorial odor codes in naturalistic landscapes.

Slow presynaptic mechanisms that mediate adaptation in the olfactory pathway of Drosophila

The olfactory system encodes odor stimuli as combinatorial activity of populations of neurons whose response depends on stimulus history. How and on which timescales previous stimuli affect these combinatorial representations remains unclear. We use in vivo optical imaging in Drosophila to analyze sensory adaptation at the first synaptic step along the olfactory pathway. We show that calcium signals in the axon terminals of olfactory receptor neurons (ORNs) do not follow the same adaptive properties as the firing activity measured at the antenna. While ORNs calcium responses are sustained on long timescales, calcium signals in the postsynaptic projection neurons (PNs) adapt within tens of seconds. We propose that this slow component of the postsynaptic response is mediated by a slow presynaptic depression of vesicle release and enables the combinatorial population activity of PNs to adjust to the mean and variance of fluctuating odor stimuli.

Olfactory Navigation and the Receptor Nonlinearity

The demands on a sensory system depend not only on the statistics of its inputs but also on the task. In olfactory navigation, for example, the task is to find the plume source; allocation of sensory resources may therefore be driven by aspects of the plume that are informative about source location, rather than concentration per se. Here we explore the implications of this idea for encoding odor concentration. To formalize the notion that sensory resources are limited, we considered coding strategies that partitioned the odor concentration range into a set of discriminable intervals. We developed a dynamic programming algorithm that, given the distribution of odor concentrations at several locations, determines the partitioning that conveys the most information about location. We applied this analysis to planar laser-induced fluorescence measurements of spatiotemporal odor fields with realistic advection speeds (5-20 cm/s), with or without a nearby boundary or obstacle. Across all environments, the optimal coding strategy allocated more resources (i.e., more and finer discriminable intervals) to the upper end of the concentration range than would be expected from histogram equalization, the optimal strategy if the goal were to reconstruct the plume, rather than to navigate. Finally, we show that ligand binding, as captured by the Hill equation, transforms odorant concentration into response levels in a way that approximates information maximization for navigation. This behavior occurs when the Hill dissociation constant is near the mean odor concentration, an adaptive set-point that has been observed in the olfactory system of flies.SIGNIFICANCE STATEMENT The first step of olfactory processing is receptor binding, and the resulting relationship between odorant concentration and the bound receptor fraction is a saturating one. While this Hill nonlinearity can be viewed as a distortion that is imposed by the biophysics of receptor binding, here we show that it also plays an important information-processing role in olfactory navigation. Specifically, by combining a novel dynamic-programming algorithm with physical measurements of turbulent plumes, we determine the optimal strategy for encoding odor concentration when the goal is to determine location. This strategy is distinct from histogram equalization, the strategy that maximizes information about plume concentration, and is closely approximated by the Hill nonlinearity when the binding constant is near the ambient mean.