Olfactory coding in the insect brain: data and conjectures

Comparing cognition across major transitions using the hierarchy of formal automata

The evolution of cognition can be understood in terms of a few major transitions-changes in the computational architecture of nervous systems that changed what cognitive capacities could be evolved by downstream lineages. We demonstrate how the idea of a major cognitive transition can be modeled in terms of where a system's effective computational architecture falls on the well-studied hierarchy of formal automata (HFA). We then use recent work connecting artificial neural networks to the HFA, which provides a way to make the structure-architecture link in natural systems. We conclude with reflections on the power and the challenges of traditional thinking when applied to neural architectures. This article is categorized under: Cognitive Biology > Evolutionary Roots of Cognition Psychology > Comparative Philosophy > Foundations of Cognitive Science.

Synergistic olfactory processing for social plasticity in desert locusts

Desert locust plagues threaten the food security of millions. Central to their formation is crowding-induced plasticity, with social phenotypes changing from cryptic (solitarious) to swarming (gregarious). Here, we elucidate the implications of this transition on foraging decisions and corresponding neural circuits. We use behavioral experiments and Bayesian modeling to decompose the multi-modal facets of foraging, revealing olfactory social cues as critical. To this end, we investigate how corresponding odors are encoded in the locust olfactory system using in-vivo calcium imaging. We discover crowding-dependent synergistic interactions between food-related and social odors distributed across stable combinatorial response maps. The observed synergy was specific to the gregarious phase and manifested in distinct odor response motifs. Our results suggest a crowding-induced modulation of the locust olfactory system that enhances food detection in swarms. Overall, we demonstrate how linking sensory adaptations to behaviorally relevant tasks can improve our understanding of social modulation in non-model organisms.

Plasticity in inhibitory networks improves pattern separation in early olfactory processing

Distinguishing between nectar and non-nectar odors presents a challenge for animals due to shared compounds in complex mixtures, where changing ratios often signify differences in reward. Changes in nectar production throughout the day and potentially many times within a forager's lifetime add to the complexity. The honeybee olfactory system, containing less than a 1000 of principal neurons in the early olfactory relay, the antennal lobe (AL), must learn to associate diverse volatile blends with rewards. We used a computational network model and live imaging of the honeybee's AL to explore the neural mechanisms and functions of the AL plasticity. Our findings revealed that when trained with a set of rewarded and unrewarded odors, the AL inhibitory network suppresses shared chemical compounds while enhancing responses to distinct compounds. This results in improved pattern separation and a more concise and efficient neural code. Our Ca2+ imaging data support our model's predictions. Furthermore, we applied these contrast enhancement principles to a Graph Convolutional Network (GCN) and found that similar mechanisms could enhance the performance of artificial neural networks. Our model provides insights into how plasticity at the inhibitory network level reshapes coding for efficient learning of complex odors.

Sensory collectives in natural systems

Groups of animals inhabit vastly different sensory worlds, or umwelten, which shape fundamental aspects of their behaviour. Yet the sensory ecology of species is rarely incorporated into the emerging field of collective behaviour, which studies the movements, population-level behaviours, and emergent properties of animal groups. Here, we review the contributions of sensory ecology and collective behaviour to understanding how animals move and interact within the context of their social and physical environments. Our goal is to advance and bridge these two areas of inquiry and highlight the potential for their creative integration. To achieve this goal, we organise our review around the following themes: (1) identifying the promise of integrating collective behaviour and sensory ecology; (2) defining and exploring the concept of a 'sensory collective'; (3) considering the potential for sensory collectives to shape the evolution of sensory systems; (4) exploring examples from diverse taxa to illustrate neural circuits involved in sensing and collective behaviour; and (5) suggesting the need for creative conceptual and methodological advances to quantify 'sensescapes'. In the final section, (6) applications to biological conservation, we argue that these topics are timely, given the ongoing anthropogenic changes to sensory stimuli (e.g. via light, sound, and chemical pollution) which are anticipated to impact animal collectives and group-level behaviour and, in turn, ecosystem composition and function. Our synthesis seeks to provide a forward-looking perspective on how sensory ecologists and collective behaviourists can both learn from and inspire one another to advance our understanding of animal behaviour, ecology, adaptation, and evolution.

Predator-prey systems as models for integrative research in biology: the value of a non-consumptive effects framework

Predator-prey interactions are a cornerstone of many ecological and evolutionary processes that influence various levels of biological organization, from individuals to ecosystems. Predators play a crucial role in shaping ecosystems through the consumption of prey species and non-consumptive effects. Non-consumptive effects (NCEs) can induce changes in prey behavior, including altered foraging strategies, habitat selection, life history and anti-predator responses. These defensive strategies have physiological consequences for prey, affecting their growth, reproduction and immune function to name a few. Numerous experimental studies have incorporated NCEs in investigating predator-prey dynamics in the past decade. Interestingly, predator-prey systems can also be used as experimental models to answer physiology, cognition and adaptability questions. In this Commentary, I highlight research that uses NCEs in predator-prey systems to provide novel insights into cognition, adaptation, epigenetic inheritance and aging. I discuss the evolution of instinct, anxiety and other cognitive disorders, the shaping of brain connectomes, stress-induced aging and the development of behavioral coping styles. I outline how studies can integrate the investigation of NCEs with advanced behavioral, genomic and neurological tools to provide novel insights into physiological and cognitive health.

The Relationship between Cognition and Brain Size or Neuron Number

The comparative approach is a powerful way to explore the relationship between brain structure and cognitive function. Thus far, the field has been dominated by the assumption that a bigger brain somehow means better cognition. Correlations between differences in brain size or neuron number between species and differences in specific cognitive abilities exist, but these correlations are very noisy. Extreme differences exist between clades in the relationship between either brain size or neuron number and specific cognitive abilities. This means that correlations become weaker, not stronger, as the taxonomic diversity of sampled groups increases. Cognition is the outcome of neural networks. Here we propose that considering plausible neural network models will advance our understanding of the complex relationships between neuron number and different aspects of cognition. Computational modelling of networks suggests that adding pathways, or layers, or changing patterns of connectivity in a network can all have different specific consequences for cognition. Consequently, models of computational architecture can help us hypothesise how and why differences in neuron number might be related to differences in cognition. As methods in connectomics continue to improve and more structural information on animal brains becomes available, we are learning more about natural network structures in brains, and we can develop more biologically plausible models of cognitive architecture. Natural animal diversity then becomes a powerful resource to both test the assumptions of these models and explore hypotheses for how neural network structure and network size might delimit cognitive function.

How honey bees make fast and accurate decisions

Honey bee ecology demands they make both rapid and accurate assessments of which flowers are most likely to offer them nectar or pollen. To understand the mechanisms of honey bee decision-making, we examined their speed and accuracy of both flower acceptance and rejection decisions. We used a controlled flight arena that varied both the likelihood of a stimulus offering reward and punishment and the quality of evidence for stimuli. We found that the sophistication of honey bee decision-making rivalled that reported for primates. Their decisions were sensitive to both the quality and reliability of evidence. Acceptance responses had higher accuracy than rejection responses and were more sensitive to changes in available evidence and reward likelihood. Fast acceptances were more likely to be correct than slower acceptances; a phenomenon also seen in primates and indicative that the evidence threshold for a decision changes dynamically with sampling time. To investigate the minimally sufficient circuitry required for these decision-making capacities, we developed a novel model of decision-making. Our model can be mapped to known pathways in the insect brain and is neurobiologically plausible. Our model proposes a system for robust autonomous decision-making with potential application in robotics.

Drug effect and addiction research with insects - From Drosophila to collective reward in honeybees

Animals and humans share similar reactions to the effects of addictive substances, including those of their brain networks to drugs. Our review focuses on simple invertebrate models, particularly the honeybee (Apis mellifera), and on the effects of drugs on bee behaviour and brain functions. The drug effects in bees are very similar to those described in humans. Furthermore, the honeybee community is a superorganism in which many collective functions outperform the simple sum of individual functions. The distribution of reward functions in this superorganism is unique - although sublimated at the individual level, community reward functions are of higher quality. This phenomenon of collective reward may be extrapolated to other animal species living in close and strictly organised societies, i.e. humans. The relationship between sociality and reward, based on use of similar parts of the neural network (social decision-making network in mammals, mushroom body in bees), suggests a functional continuum of reward and sociality in animals.

In Search for the Retrievable Memory Trace in an Insect Brain

The search strategy for the memory trace and its semantics is exemplified for the case of olfactory learning in the honeybee brain. The logic of associative learning is used to guide the experimental approach into the brain by identifying the anatomical and functional convergence sites of the conditioned stimulus and unconditioned stimulus pathways. Two of the several convergence sites are examined in detail, the antennal lobe as the first-order sensory coding area, and the input region of the mushroom body as a higher order integration center. The memory trace is identified as the pattern of associative changes on the level of synapses. The synapses are recruited, drop out, and change the transmission properties for both specifically associated stimulus and the non-associated stimulus. Several rules extracted from behavioral studies are found to be mirrored in the patterns of synaptic change. The strengths and the weaknesses of the honeybee as a model for the search for the memory trace are addressed in a comparison with Drosophila. The question is discussed whether the memory trace exists as a hidden pattern of change if it is not retrieved and whether an external reading of the content of the memory trace may ever be possible. Doubts are raised on the basis that the retrieval circuits are part of the memory trace. The concept of a memory trace existing beyond retrieval is defended by referring to two well-documented processes also in the honeybee, memory consolidation during sleep, and transfer of memory across brain areas.

Higher-order olfactory neurons in the lateral horn support odor valence and odor identity coding in Drosophila

Understanding neuronal representations of odor-evoked activities and their progressive transformation from the sensory level to higher brain centers features one of the major aims in olfactory neuroscience. Here, we investigated how odor information is transformed and represented in higher-order neurons of the lateral horn, one of the higher olfactory centers implicated in determining innate behavior, using Drosophila melanogaster. We focused on a subset of third-order glutamatergic lateral horn neurons (LHNs) and characterized their odor coding properties in relation to their presynaptic partner neurons, the projection neurons (PNs) by two-photon functional imaging. We show that odors evoke reproducible, stereotypic, and odor-specific response patterns in LHNs. Notably, odor-evoked responses in these neurons are valence-specific in a way that their response amplitude is positively correlated with innate odor preferences. We postulate that this valence-specific activity is the result of integrating inputs from multiple olfactory channels through second-order neurons. GRASP and micro-lesioning experiments provide evidence that glutamatergic LHNs obtain their major excitatory input from uniglomerular PNs, while they receive an odor-specific inhibition through inhibitory multiglomerular PNs. In summary, our study indicates that odor representations in glutamatergic LHNs encode hedonic valence and odor identity and primarily retain the odor coding properties of second-order neurons.

All-optical manipulation of the Drosophila olfactory system

Thanks to its well-known neuroanatomy, limited brain size, complex behaviour, and the extensive genetic methods, Drosophila has become an indispensable model in neuroscience. A vast number of studies have focused on its olfactory system and the processing of odour information. Optogenetics is one of the recently developed genetic tools that significantly advance this field of research, allowing to replace odour stimuli by direct neuronal activation with light. This becomes a universal all-optical toolkit when spatially selective optogenetic activation is combined with calcium imaging to read out neuronal responses. Initial experiments showed a successful implementation to study the olfactory system in fish and mice, but the olfactory system of Drosophila has been so far precluded from an application. To fill this gap, we present here optogenetic tools to selectively stimulate functional units in the Drosophila olfactory system, combined with two-photon calcium imaging to read out the activity patterns elicited by these stimuli at different levels of the brain. This method allows to study the spatial and temporal features of the information flow and reveals the functional connectivity in the olfactory network.

Olfactory Strategies in the Defensive Behaviour of Insects

Most animals must defend themselves in order to survive. Defensive behaviour includes detecting predators or intruders, avoiding them by staying low-key or escaping or deterring them away by means of aggressive behaviour, i.e., attacking them. Responses vary across insect species, ranging from individual responses to coordinated group attacks in group-living species. Among different modalities of sensory perception, insects predominantly use the sense of smell to detect predators, intruders, and other threats. Furthermore, social insects, such as honeybees and ants, communicate about danger by means of alarm pheromones. In this review, we focus on how olfaction is put to use by insects in defensive behaviour. We review the knowledge of how chemical signals such as the alarm pheromone are processed in the insect brain. We further discuss future studies for understanding defensive behaviour and the role of olfaction.

Competing beetles attract egg laying in a hawkmoth

In nature, plant-insect interactions occur in complex settings involving multiple trophic levels, often with multiple species at each level.¹ Herbivore attack of a host plant typically dramatically alters the plant's odor emission in terms of concentration and composition.^2,3 Therefore, a well-adapted herbivore should be able to predict whether a plant is still suitable as a host by judging these changes in the emitted bouquet. Although studies have demonstrated that oviposition preferences of successive insects were affected by previous infestations,^4,5 the underlying molecular and olfactory mechanisms remain unknown. Here, we report that tobacco hawkmoths (Manduca sexta) preferentially oviposit on Jimson weed (Datura wrightii) that is already infested by a specialist, the three-lined potato beetle (Lema daturaphila). Interestingly, the moths' offspring do not benefit directly, as larvae develop more slowly when feeding together with Lema beetles. However, one of M. sexta's main enemies, the parasitoid wasp Cotesia congregata, prefers the headspace of M. sexta-infested plants to that of plants infested by both herbivores. Hence, we conclude that female M. sexta ignore the interspecific competition with beetles and oviposit deliberately on beetle-infested plants to provide their offspring with an enemy-reduced space, thus providing a trade-off that generates a net benefit to the survival and fitness of the subsequent generation. We identify that α-copaene, emitted by beetle-infested Datura, plays a role in this preference. By performing heterologous expression and single-sensillum recordings, we show that odorant receptor (Or35) is involved in α-copaene detection.

Repellency of Wild Oregano Plant Volatiles, Plectranthus Amboinicus, and Their Essential Oils to the Silverleaf Whitefly, Bemisia Tabaci, on Tomato

The Bemisia tabaci (Gennadius) whitefly is a major economically damaging pest of many crops such as tomato (Solanum lycopersicum L.). Pesticides are widely used to control B. tabaci while the use of aromatic plants is an alternative control method. The aim of this study was to assess the B.tabaci repellent effect of wild oregano, Plectranthus amboinicus (Lour.) Spreng, a widespread aromatic plant in the West Indies. We tested three origins of wild oregano, including northern, central, and southern Martinique (French West Indies). Our results showed that all essential oils of wild oregano had either masking properties or were true repellents-the mean percentage of whiteflies present in the upper part of the still-air olfactometer was 1.3- to 1.9-fold lower than in the controls. The ethanolic solution of volatile organic compounds of wild oregano from southern Martinique also had a true repellent effect-the mean percentage of whiteflies present in the upper part of the still-air olfactometer was 1.3-fold lower than in the controls. Moreover, in a greenhouse insect-proof cage, there were 1.5 fewer adult whiteflies on tomato intercropped with wild oregano from southern Martinique than on tomato alone after 96 h exposure. Our study generated further insight into the potential of P. amboinicus for B. tabaci biocontrol on tomato crops. Wild oregano extracts were repellent to B. tabaci and could be used as a companion plant to prevent whitefly infestations on tomato crops. However, the B. tabaci behavior depends on the plant origin.

GPCR voltage dependence controls neuronal plasticity and behavior

G-protein coupled receptors (GPCRs) play a paramount role in diverse brain functions. Almost 20 years ago, GPCR activity was shown to be regulated by membrane potential in vitro, but whether the voltage dependence of GPCRs contributes to neuronal coding and behavioral output under physiological conditions in vivo has never been demonstrated. Here we show that muscarinic GPCR mediated neuronal potentiation in vivo is voltage dependent. This voltage dependent potentiation is abolished in mutant animals expressing a voltage independent receptor. Depolarization alone, without a muscarinic agonist, results in a nicotinic ionotropic receptor potentiation that is mediated by muscarinic receptor voltage dependency. Finally, muscarinic receptor voltage independence causes a strong behavioral effect of increased odor habituation. Together, this study identifies a physiological role for the voltage dependency of GPCRs by demonstrating crucial involvement of GPCR voltage dependence in neuronal plasticity and behavior. Thus, this study suggests that GPCR voltage dependency plays a role in many diverse neuronal functions including learning and memory.

Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies

When flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, they must solve several challenges, including reliably identifying mixtures of odorants and their intensities, and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and just mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these challenges. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic ("ephaptic") interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla. We find that NSIs improve mixture ratio detection and plume structure sensing and do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. The best performance is achieved when both mechanisms work in synergy. However, we also found that NSIs decrease the dynamic range of co-housed ORNs, especially when they have similar sensitivity to an odorant. These results shed light, from a functional perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Local olfactory interneurons provide the basis for neurochemical regionalization of olfactory glomeruli in crustaceans

The primary olfactory centers of metazoans as diverse as arthropods and mammals consist of an array of fields of dense synaptic neuropil, the olfactory glomeruli. However, the neurochemical structure of crustacean olfactory glomeruli is largely understudied when compared to the insects. We analyzed the glomerular architecture in selected species of hermit crabs using immunohistochemistry against presynaptic proteins, the neuropeptides orcokinin, RFamide and allatostatin, and the biogenic amine serotonin. Our study reveals an unexpected level of structural complexity, unmatched by what is found in the insect olfactory glomeruli. Peptidergic and aminergic interneurons provide the structural basis for a regionalization of the crustacean glomeruli into longitudinal and concentric compartments. Our data suggest that local olfactory interneurons take a central computational role in modulating the information transfer from olfactory sensory neurons to projection neurons within the glomeruli. Furthermore, we found yet unknown neuronal elements mediating lateral inhibitory interactions across the glomerular array that may play a central role in modulating the transfer of sensory input to the output neurons through presynaptic inhibition. Our study is another step in understanding the function of crustacean olfactory glomeruli as highly complex units of local olfactory processing.

Genealogical relationships of mushroom bodies, hemiellipsoid bodies, and their afferent pathways in the brains of Pancrustacea: Recent progress and open questions

According to all latest phylogenetic analyses, the taxon Pancrustacea embraces the crustaceans in the traditional sense and the hexapods. Members of the Pancrustacea for a long time have been known to display distinct similarities in the architecture of their brains. Here, we review recent progress and open questions concerning structural and functional communalities of selected higher integrative neuropils in the lateral protocerebrum of pancrustaceans, the mushroom bodies and hemiellipsoid bodies. We also discuss the projection neuron pathway which provides a distinct input channel to both mushroom and hemiellipsoid bodies from the primary chemosensory centers in the deutocerebrum. Neuronal characters are mapped on a current pancrustacean phylogeny in order to extract those characters that are part of the pancrustacean ground pattern. Furthermore, we summarize recent insights into the evolutionary transformation of mushroom body morphology across the Pancrustacea.

Neural and behavioural responses of the pollen-specialist bee Andrena vaga to Salix odours

An effective means of finding food is crucial for organisms. Whereas specialized animals select a small number of potentially available food sources, generalists use a broader range. Specialist (oligolectic) bees forage on a small range of flowering plants for pollen and use primarily olfactory and visual cues to locate their host flowers. So far, however, little is known about the specific cues oligoleges use to discriminate between hosts and non-hosts and how floral scent compounds of hosts and non-hosts are processed in the bees' olfactory system. In this study, we recorded physiological responses of the antennae (electroantennographic detection coupled to gas chromatography; GC-EAD) and in the brain (optical imaging; GC imaging), and studied host-finding behaviour of oligolectic Andrena vaga bees, a specialist on Salix plants. In total, we detected 37 physiologically active compounds in host and non-host scents. 4-Oxoisophorone, a common constituent in the scent of many Salix species, evoked strong responses in the antennal lobe glomeruli of A. vaga, but not the generalist honeybee Apis mellifera. The specific glomerular responses to 4-oxoisophorone in natural Salix scents reveals a high degree of specialization in A. vaga for this typical Salix odorant component. In behavioural experiments, we found olfactory cues to be the key attractants for A. vaga to Salix hosts, which are also used to discriminate between hosts and non-hosts, and A. vaga demonstrated a behavioural activity for 4-oxoisophorone. A high sensitivity to floral scents enables the specialized bees to effectively find flowers and it appears that A. vaga bees are highly tuned to 4-oxoisophorone at a very low concentration.

Antennal-lobe neurons in the moth Helicoverpa armigera: Morphological features of projection neurons, local interneurons, and centrifugal neurons

The relatively large primary olfactory center of the insect brain, the antennal lobe (AL), contains several heterogeneous neuronal types. These include projection neurons (PNs), providing olfactory information to higher‐order neuropils via parallel pathways, and local interneurons (LNs), which provide lateral processing within the AL. In addition, various types of centrifugal neurons (CNs) offer top‐down modulation onto the other AL neurons. By performing iontophoretic intracellular staining, we collected a large number of AL neurons in the moth, Helicoverpa armigera, to examine the distinct morphological features of PNs, LNs, and CNs. We characterize 190 AL neurons. These were allocated to 25 distinct neuronal types or sub‐types, which were reconstructed and placed into a reference brain. In addition to six PN types comprising 15 sub‐types, three LN and seven CN types were identified. High‐resolution confocal images allowed us to analyze AL innervations of the various reported neurons, which demonstrated that all PNs innervating ventroposterior glomeruli contact a protocerebral neuropil rarely targeted by other PNs, that is the posteriorlateral protocerebrum. We also discuss the functional roles of the distinct CNs, which included several previously uncharacterized types, likely involved in computations spanning from multisensory processing to olfactory feedback signalization into the AL.

Built to Last: Functional and Structural Mechanisms in the Moth Olfactory Network Mitigate Effects of Neural Injury

Most organisms suffer neuronal damage throughout their lives, which can impair performance of core behaviors. Their neural circuits need to maintain function despite injury, which in particular requires preserving key system outputs. In this work, we explore whether and how certain structural and functional neuronal network motifs act as injury mitigation mechanisms. Specifically, we examine how (i) Hebbian learning, (ii) high levels of noise, and (iii) parallel inhibitory and excitatory connections contribute to the robustness of the olfactory system in the Manduca sexta moth. We simulate injuries on a detailed computational model of the moth olfactory network calibrated to data. The injuries are modeled on focal axonal swellings, a ubiquitous form of axonal pathology observed in traumatic brain injuries and other brain disorders. Axonal swellings effectively compromise spike train propagation along the axon, reducing the effective neural firing rate delivered to downstream neurons. All three of the network motifs examined significantly mitigate the effects of injury on readout neurons, either by reducing injury’s impact on readout neuron responses or by restoring these responses to pre-injury levels. These motifs may thus be partially explained by their value as adaptive mechanisms to minimize the functional effects of neural injury. More generally, robustness to injury is a vital design principle to consider when analyzing neural systems.

Drosophila reward system - A summary of current knowledge

The fruit fly Drosophila melanogaster brain is the most extensively investigated model of a reward system in insects. Drosophila can discriminate between rewarding and punishing environmental stimuli and consequently undergo associative learning. Functional models, especially those modelling mushroom bodies, are constantly being developed using newly discovered information, adding to the complexity of creating a simple model of the reward system. This review aims to clarify whether its reward system also includes a hedonic component. Neurochemical systems that mediate the 'wanting' component of reward in the Drosophila brain are well documented, however, the systems that mediate the pleasure component of reward in mammals, including those involving the endogenous opioid and endocannabinoid systems, are unlikely to be present in insects. The mushroom body components exhibit differential developmental age and different functional processes. We propose a hypothetical hierarchy of the levels of reinforcement processing in response to particular stimuli, and the parallel processes that take place concurrently. The possible presence of activity-silencing and meta-satiety inducing levels in Drosophila should be further investigated.

Functional properties of insect olfactory receptors: ionotropic receptors and odorant receptors

The majority of insect olfactory receptors belong to two distinct protein families, the ionotropic receptors (IRs), which are related to the ionotropic glutamate receptor family, and the odorant receptors (ORs), which evolved from the gustatory receptor family. Both receptor types assemble to heteromeric ligand-gated cation channels composed of odor-specific receptor proteins and co-receptor proteins. We here present in short the current view on evolution, function, and regulation of IRs and ORs. Special attention is given on how their functional properties can meet the environmental and ecological challenges an insect has to face.

Olfactory coding in honeybees

With less than a million neurons, the western honeybee Apis mellifera is capable of complex olfactory behaviors and provides an ideal model for investigating the neurophysiology of the olfactory circuit and the basis of olfactory perception and learning. Here, we review the most fundamental aspects of honeybee's olfaction: first, we discuss which odorants dominate its environment, and how bees use them to communicate and regulate colony homeostasis; then, we describe the neuroanatomy and the neurophysiology of the olfactory circuit; finally, we explore the cellular and molecular mechanisms leading to olfactory memory formation. The vastity of histological, neurophysiological, and behavioral data collected during the last century, together with new technological advancements, including genetic tools, confirm the honeybee as an attractive research model for understanding olfactory coding and learning.

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

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

Muscarinic Modulation of Antennal Lobe GABAergic Local Neurons Shapes Odor Coding and Behavior

In the antennal lobe (AL), the first olfactory relay of Drosophila, excitatory neurons are predominantly cholinergic. Ionotropic nicotinic receptors play a vital role in the effects of acetylcholine in the AL. However, the AL also has a high expression level of metabotropic muscarinic acetylcholine receptors type A (mAChRs-A). Nevertheless, the neurons expressing them and their role in the AL are unknown. Elucidating their function may reveal principles in olfactory modulation. Here, we show that mAChRs-A shape AL output and affect behavior. We localized mAChRs-A effects to a sub-population of GABAergic local neurons (iLNs), where they play a dual role: direct excitation of iLNs and stabilization of the synapse between receptor neurons and iLNs, which undergoes strong short-term depression. Our results reveal modulatory functions of the AL main excitatory neurotransmitter. Striking similarities to the mammalian olfactory system predict that mammalian glutamatergic metabotropic receptors could be associated with similar modulations.

Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies.. [DOI: 10.1101/2020.07.23.217216]

When flies explore their environment, they encounter odors in complex, highly intermittent plumes. To navigate a plume and, for example, find food, they must solve several challenges, including reliably identifying mixtures of odorants and their intensities, and discriminating odorant mixtures emanating from a single source from odorants emitted from separate sources and just mixing in the air. Lateral inhibition in the antennal lobe is commonly understood to help solving these challenges. With a computational model of the Drosophila olfactory system, we analyze the utility of an alternative mechanism for solving them: Non-synaptic (“ephaptic”) interactions (NSIs) between olfactory receptor neurons that are stereotypically co-housed in the same sensilla.

We found that NSIs improve mixture ratio detection and plume structure sensing and they do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. However, we also found that NSIs decrease the dynamic range of co-housed ORNs, especially when they have similar sensitivity to an odorant. These results shed light, from a functional perspective, on the role of NSIs, which are normally avoided between neurons, for instance by myelination.

Author summary

Myelin is important to isolate neurons and avoid disruptive electrical interference between them; it can be found in almost any neural assembly. However, there are a few exceptions to this rule and it remains unclear why. One particularly interesting case is the electrical interaction between olfactory sensory neurons co-housed in the sensilla of insects. Here, we created a computational model of the early stages of the Drosophila olfactory system and observed that the electrical interference between olfactory receptor neurons can be a useful trait that can help flies, and other insects, to navigate the complex plumes of odorants in their natural environment.

With the model we were able to shed new light on the trade-off of adopting this mechanism: We found that the non-synaptic interactions (NSIs) improve both the identification of the concentration ratio in mixtures of odorants and the discrimination of odorant mixtures emanating from a single source from odorants emitted from separate sources – both highly advantageous. However, they also decrease the dynamic range of the olfactory sensory neurons – a clear disadvantage.

Association between olfactory sensitivity and behavioral responses of Drosophila suzukii to naturally occurring volatile compounds

Drosophila suzukii Matsumura (Diptera: Drosophilidae) is an invasive, destructive crop pest that originated in South East Asia. D. suzukii recently invaded Western countries and is threatening both European and American fruit industries. It is extremely attracted to otherwise undamaged, ripening fruits, unlike most other Drosophila species that attack only decaying or rotten fruits. Recent studies on different insect species showed that several naturally occurring compounds of easy market availability showing deterrent action may be used to supplement mass catches with food traps. Based on these considerations, the aim of the present work was to test the effects of some natural compounds (alone or in the mixture) on the olfactory system of the D. suzukii and the behavioral responses evoked. We measured by electroantennogram (EAG) recordings, the olfactory sensitivity of antennae to increasing concentrations of eugenol, vanillin, menthol, cis-jasmone; eugenol + vanillin, +menthol, +cis-jasmone; vanillin + menthol, +cis-jasmone. In addition, the behavioral responses to the same compounds and mixtures were evaluated. Our electrophysiological results show a dose-response relationship between the EAG amplitudes and the increasing concentrations of the olfactory compound. The behavioral results show that the number of laid eggs is significantly different between the standard diet and the standard diet + natural compound. These results underline a specificity in the olfactory sensitivity and in the ovipositing behavior of D. suzukii females; also, they could be valuable for the identification of key chemicals aimed at the future development of strategies in the management and control of this harmful insect for crops.

Chemosensation: Hate Mosquitoes? Peel Beetroots!

Finding the right lure for trapping pest insects is difficult. The typical smell of rain and humid soil, geosmin, now turns out to be a strong attractant for the yellow fever mosquito Aedes aegypti.

Functional morphology of the primary olfactory centers in the brain of the hermit crab Coenobita clypeatus (Anomala, Coenobitidae)

Terrestrial hermit crabs of the genus Coenobita display strong behavioral responses to volatile odors and are attracted by chemical cues of various potential food sources. Several aspects of their sense of aerial olfaction have been explored in recent years including behavioral aspects and structure of their peripheral and central olfactory pathway. Here, we use classical histological methods and immunohistochemistry against the neuropeptides orcokinin and allatostatin as well as synaptic proteins and serotonin to provide insights into the functional organization of their primary olfactory centers in the brain, the paired olfactory lobes. Our results show that orcokinin is present in the axons of olfactory sensory neurons, which target the olfactory lobe. Orcokinin is also present in a population of local olfactory interneurons, which may relay lateral inhibition across the array of olfactory glomeruli within the lobes. Extensive lateral connections of the glomeruli were also visualized using the histological silver impregnation method according to Holmes-Blest. This technique also revealed the structural organization of the output pathway of the olfactory system, the olfactory projection neurons, the axons of which target the lateral protocerebrum. Within the lobes, the course of their axons seems to be reorganized in an axon-sorting zone before they exit the system. Together with previous results, we combine our findings into a model on the functional organization of the olfactory system in these animals.

Circuit and Cellular Mechanisms Facilitate the Transformation from Dense to Sparse Coding in the Insect Olfactory System

Transformations between sensory representations are shaped by neural mechanisms at the cellular and the circuit level. In the insect olfactory system, the encoding of odor information undergoes a transition from a dense spatiotemporal population code in the antennal lobe to a sparse code in the mushroom body. However, the exact mechanisms shaping odor representations and their role in sensory processing are incompletely identified. Here, we investigate the transformation from dense to sparse odor representations in a spiking model of the insect olfactory system, focusing on two ubiquitous neural mechanisms: spike frequency adaptation at the cellular level and lateral inhibition at the circuit level. We find that cellular adaptation is essential for sparse representations in time (temporal sparseness), while lateral inhibition regulates sparseness in the neuronal space (population sparseness). The interplay of both mechanisms shapes spatiotemporal odor representations, which are optimized for the discrimination of odors during stimulus onset and offset. Response pattern correlation across different stimuli showed a nonmonotonic dependence on the strength of lateral inhibition with an optimum at intermediate levels, which is explained by two counteracting mechanisms. In addition, we find that odor identity is stored on a prolonged timescale in the adaptation levels but not in the spiking activity of the principal cells of the mushroom body, providing a testable hypothesis for the location of the so-called odor trace.

Coding of odour and space in the hemimetabolous insect Periplaneta americana

The general architecture of the olfactory system is highly conserved from insects to humans, but neuroanatomical and physiological differences can be observed across species. The American cockroach, inhabiting dark shelters with a rather stable olfactory landscape, is equipped with long antennae used for sampling the surrounding air-space for orientation and navigation. The antennae's exceptional length provides a wide spatial working range for odour detection; however, it is still largely unknown whether and how this is also used for mapping the structure of the olfactory environment. By selectively labelling antennal lobe projection neurons with a calcium-sensitive dye, we investigated the logic of olfactory coding in this hemimetabolous insect. We show that odour responses are stimulus specific and concentration dependent, and that structurally related odorants evoke physiologically similar responses. By using spatially confined stimuli, we show that proximal stimulations induce stronger and faster responses than distal ones. Spatially confined stimuli of the female pheromone periplanone B activate a subregion of the male macroglomerulus. Thus, we report that the combinatorial logic of odour coding deduced from holometabolous insects applies also to this hemimetabolous species. Furthermore, a fast decrease in sensitivity along the antenna, not supported by a proportionate decrease in sensillar density, suggests a neural architecture that strongly emphasizes neuronal inputs from the proximal portion of the antenna.

Insect Odorscapes: From Plant Volatiles to Natural Olfactory Scenes

Olfaction is an essential sensory modality for insects and their olfactory environment is mostly made up of plant-emitted volatiles. The terrestrial vegetation produces an amazing diversity of volatile compounds, which are then transported, mixed, and degraded in the atmosphere. Each insect species expresses a set of olfactory receptors that bind part of the volatile compounds present in its habitat. Insect odorscapes are thus defined as species-specific olfactory spaces, dependent on the local habitat, and dynamic in time. Manipulations of pest-insect odorscapes are a promising approach to answer the strong demand for pesticide-free plant-protection strategies. Moreover, understanding their olfactory environment becomes a major concern in the context of global change and environmental stresses to insect populations. A considerable amount of information is available on the identity of volatiles mediating biotic interactions that involve insects. However, in the large body of research devoted to understanding how insects use olfaction to locate resources, an integrative vision of the olfactory environment has rarely been reached. This article aims to better apprehend the nature of the insect odorscape and its importance to insect behavioral ecology by reviewing the literature specific to different disciplines from plant ecophysiology to insect neuroethology. First, we discuss the determinants of odorscape composition, from the production of volatiles by plants (section "Plant Metabolism and Volatile Emissions") to their filtering during detection by the olfactory system of insects (section "Insect Olfaction: How Volatile Plant Compounds Are Encoded and Integrated by the Olfactory System"). We then summarize the physical and chemical processes by which volatile chemicals distribute in space (section "Transportation of Volatile Plant Compounds and Spatial Aspects of the Odorscape") and time (section "Temporal Aspects: The Dynamics of the Odorscape") in the atmosphere. The following sections consider the ecological importance of background odors in odorscapes and how insects adapt to their olfactory environment. Habitat provides an odor background and a sensory context that modulate the responses of insects to pheromones and other olfactory signals (section "Ecological Importance of Odorscapes"). In addition, insects do not respond inflexibly to single elements in their odorscape but integrate several components of their environment (section "Plasticity and Adaptation to Complex and Variable Odorscapes"). We finally discuss existing methods of odorscape manipulation for sustainable pest insect control and potential future developments in the context of agroecology (section "Odorscapes in Plant Protection and Agroecology").

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.

Putting a bug in ML: The moth olfactory network learns to read MNIST

We seek to (i) characterize the learning architectures exploited in biological neural networks for training on very few samples, and (ii) port these algorithmic structures to a machine learning context. The moth olfactory network is among the simplest biological neural systems that can learn, and its architecture includes key structural elements and mechanisms widespread in biological neural nets, such as cascaded networks, competitive inhibition, high intrinsic noise, sparsity, reward mechanisms, and Hebbian plasticity. These structural biological elements, in combination, enable rapid learning. MothNet is a computational model of the moth olfactory network, closely aligned with the moth's known biophysics and with in vivo electrode data collected from moths learning new odors. We assign this model the task of learning to read the MNIST digits. We show that MothNet successfully learns to read given very few training samples (1-10 samples per class). In this few-samples regime, it outperforms standard machine learning methods such as nearest-neighbors, support-vector machines, and neural networks (NNs), and matches specialized one-shot transfer-learning methods but without the need for pre-training. The MothNet architecture illustrates how algorithmic structures derived from biological brains can be used to build alternative NNs that may avoid the high training data demands of many current engineered NNs.

Functional and anatomical specificity in a higher olfactory centre

Most sensory systems are organized into parallel neuronal pathways that process distinct aspects of incoming stimuli. In the insect olfactory system, second order projection neurons target both the mushroom body, required for learning, and the lateral horn (LH), proposed to mediate innate olfactory behavior. Mushroom body neurons form a sparse olfactory population code, which is not stereotyped across animals. In contrast, odor coding in the LH remains poorly understood. We combine genetic driver lines, anatomical and functional criteria to show that the Drosophila LH has ~1400 neurons and >165 cell types. Genetically labeled LHNs have stereotyped odor responses across animals and on average respond to three times more odors than single projection neurons. LHNs are better odor categorizers than projection neurons, likely due to stereotyped pooling of related inputs. Our results reveal some of the principles by which a higher processing area can extract innate behavioral significance from sensory stimuli.

Neuroscience: An Olfactory Homunculus in the Insect Brain

Animals can follow olfactory traces to find food, detect a sexual mate, or avoid predators. A new study reveals that pheromone-specific projection neurons in the cockroach have a spatially tuned receptive field, and allow encoding spatial information of an odorant.

Olfactory Object Recognition Based on Fine-Scale Stimulus Timing in Drosophila

Odorants of behaviorally relevant objects (e.g., food sources) intermingle with those from other sources. Therefore to determine whether an odor source is good or bad—without actually visiting it—animals first need to segregate the odorants from different sources. To do so, animals could use temporal stimulus cues, because odorants from one source exhibit correlated fluctuations, whereas odorants from different sources are less correlated. However, the behaviorally relevant timescales of temporal stimulus cues for odor source segregation remain unclear. Using behavioral experiments with free-flying flies, we show that (1) odorant onset asynchrony increases flies' attraction to a mixture of two odorants with opposing innate or learned valence and (2) attraction does not increase when the attractive odorant arrives first. These data suggest that flies can use stimulus onset asynchrony for odor source segregation and imply temporally precise neural mechanisms for encoding odors and for segregating them into distinct objects.

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Flies can detect whether two mixed odorants arrive synchronously or asynchronously

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This temporal sensitivity occurs for odorants with innate and learned valences

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Flies' behavior suggests use of odor onset asynchrony for odor source segregation

Cooperative defence operates by social modulation of biogenic amine levels in the honey bee brain

The defence of a society often requires that some specialized members coordinate to repel a threat at personal risk. This is especially true for honey bee guards, which defend the hive and may sacrifice their lives upon stinging. Central to this cooperative defensive response is the sting alarm pheromone, which has isoamyl acetate (IAA) as its main component. Although this defensive behaviour has been well described, the neural mechanisms triggered by IAA to coordinate stinging have long remained unknown. Here we show that IAA upregulates brain levels of serotonin and dopamine, thereby increasing the likelihood of an individual bee to attack and sting. Pharmacological enhancement of the levels of both amines induces higher defensive responsiveness, while decreasing them via antagonists decreases stinging. Our results thus uncover the neural mechanism by which an alarm pheromone recruits individuals to attack and repel a threat, and suggest that the alarm pheromone of honey bees acts on their response threshold rather than as a direct trigger.

Social foraging extends associative odor-food memory expression in an automated learning assay for Drosophila

Animals socially interact during foraging and share information about the quality and location of food sources. The mechanisms of social information transfer during foraging have been mostly studied at the behavioral level, and its underlying neural mechanisms are largely unknown. Fruit flies have become a model for studying the neural bases of social information transfer, because they provide a large genetic toolbox to monitor and manipulate neuronal activity, and they show a rich repertoire of social behaviors. Fruit flies aggregate, they use social information for choosing a suitable mating partner and oviposition site, and they show better aversive learning when in groups. However, the effects of social interactions on associative odor-food learning have not yet been investigated. Here we present an automated learning and memory assay for walking flies that allows studying the effect of group size on social interactions and on the formation and expression of associative odor-food memories. We found that both inter-fly attraction and the duration of odor-food memory expression increase with group size. We discuss possible behavioral and neural mechanisms of this social effect on odor-food memory expression. This study opens up opportunities to investigate how social interactions during foraging are relayed in the neural circuitry of learning and memory expression.

Biological Mechanisms for Learning: A Computational Model of Olfactory Learning in the Manduca sexta Moth, With Applications to Neural Nets

The insect olfactory system, which includes the antennal lobe (AL), mushroom body (MB), and ancillary structures, is a relatively simple neural system capable of learning. Its structural features, which are widespread in biological neural systems, process olfactory stimuli through a cascade of networks where large dimension shifts occur from stage to stage and where sparsity and randomness play a critical role in coding. Learning is partly enabled by a neuromodulatory reward mechanism of octopamine stimulation of the AL, whose increased activity induces synaptic weight updates in the MB through Hebbian plasticity. Enforced sparsity in the MB focuses Hebbian growth on neurons that are the most important for the representation of the learned odor. Based upon current biophysical knowledge, we have constructed an end-to-end computational firing-rate model of the Manduca sexta moth olfactory system which includes the interaction of the AL and MB under octopamine stimulation. Our model is able to robustly learn new odors, and neural firing rates in our simulations match the statistical features of in vivo firing rate data. From a biological perspective, the model provides a valuable tool for examining the role of neuromodulators, like octopamine, in learning, and gives insight into critical interactions between sparsity, Hebbian growth, and stimulation during learning. Our simulations also inform predictions about structural details of the olfactory system that are not currently well-characterized. From a machine learning perspective, the model yields bio-inspired mechanisms that are potentially useful in constructing neural nets for rapid learning from very few samples. These mechanisms include high-noise layers, sparse layers as noise filters, and a biologically-plausible optimization method to train the network based on octopamine stimulation, sparse layers, and Hebbian growth.

Neuronal Response Latencies Encode First Odor Identity Information across Subjects

Odorants are coded in the primary olfactory processing centers by spatially and temporally distributed patterns of glomerular activity. Whereas the spatial distribution of odorant-induced responses is known to be conserved across individuals, the universality of its temporal structure is still debated. Via fast two-photon calcium imaging, we analyzed the early phase of neuronal responses in the form of the activity onset latencies in the antennal lobe projection neurons of honeybee foragers. We show that each odorant evokes a stimulus-specific response latency pattern across the glomerular coding space. Moreover, we investigate these early response features for the first time across animals, revealing that the order of glomerular firing onsets is conserved across individuals and allows them to reliably predict odorant identity, but not concentration. These results suggest that the neuronal response latencies provide the first available code for fast odor identification.SIGNIFICANCE STATEMENT Here, we studied early temporal coding in the primary olfactory processing centers of the honeybee brain by fast imaging of glomerular responses to different odorants across glomeruli and across individuals. Regarding the elusive role of rapid response dynamics in olfactory coding, we were able to clarify the following aspects: (1) the rank of glomerular activation is conserved across individuals, (2) its stimulus prediction accuracy is equal to that of the response amplitude code, and (3) it contains complementary information. Our findings suggest a substantial role of response latencies in odor identification, anticipating the static response amplitude code.

Abstract concept learning in a simple neural network inspired by the insect brain

The capacity to learn abstract concepts such as 'sameness' and 'difference' is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly have this capacity. Here we report a model of the structures of the honey bee brain that can learn sameness and difference, as well as a range of complex and simple associative learning tasks. Our model is constrained by the known connections and properties of the mushroom body, including the protocerebral tract, and provides a good fit to the learning rates and performances of real bees in all tasks, including learning sameness and difference. The model proposes a novel mechanism for learning the abstract concepts of 'sameness' and 'difference' that is compatible with the insect brain, and is not dependent on top-down or executive control processing.

Glomerular Organization in the Antennal Lobe of the Oriental Fruit Fly Bactrocera dorsalis

The oriental fruit fly, Bactrocera dorsalis is one of the most destructive pests of horticultural crops in tropical and subtropical Asia. The insect relies heavily on its olfactory system to select suitable hosts for development and reproduction. To understand the neural basis of its odor-driven behaviors, it is fundamental to characterize the anatomy of its olfactory system. In this study, we investigated the anatomical organization of the antennal lobe (AL), the primary olfactory center, in B. dorsalis, and constructed a 3D glomerular atlas of the AL based on synaptic antibody staining combined with computerized 3D reconstruction. To facilitate identification of individual glomeruli, we also applied mass staining of olfactory sensory neurons (OSNs) and projection neurons (PNs). In total, 64 or 65 glomeruli are identifiable in both sexes based on their shape, size, and relative spatial relationship. The overall glomerular volume of two sexes is not statistically different. However, eight glomeruli are sexually dimorphic: four (named AM2, C1, L2, and L3) are larger in males, and four are larger in females (A3, AD1, DM3, and M1). The results from anterograde staining, obtained by applying dye in the antennal lobe, show that three typical medial, media lateral, and lateral antennal-lobe tracts form parallel connections between the antennal lobe and protocerebrum. In addition to these three tracts, we also found a transverse antennal-lobe tract. Based on the retrograde staining of the calyx in the mushroom body, we also characterize the arrangement of roots and cell body clusters linked to the medial antennal-lobe tracts. These data provide a foundation for future studies on the olfactory processing of host odors in B. dorsalis.

Calcium in Kenyon Cell Somata as a Substrate for an Olfactory Sensory Memory in Drosophila

Animals can form associations between temporally separated stimuli. To do so, the nervous system has to retain a neural representation of the first stimulus until the second stimulus appears. The neural substrate of such sensory stimulus memories is unknown. Here, we search for a sensory odor memory in the insect olfactory system and characterize odorant-evoked Ca2+ activity at three consecutive layers of the olfactory system in Drosophila: in olfactory receptor neurons (ORNs) and projection neurons (PNs) in the antennal lobe, and in Kenyon cells (KCs) in the mushroom body. We show that the post-stimulus responses in ORN axons, PN dendrites, PN somata, and KC dendrites are odor-specific, but they are not predictive of the chemical identity of past olfactory stimuli. However, the post-stimulus responses in KC somata carry information about the identity of previous olfactory stimuli. These findings show that the Ca2+ dynamics in KC somata could encode a sensory memory of odorant identity and thus might serve as a basis for associations between temporally separated stimuli.

Normalizing brain activity across individuals using functional reference mapping

Neural activity can be mapped across individuals using brain atlases, but when spatial relationships are not equal, these techniques collapse. We map activity across individuals using functional registration, based on physiological responses to predetermined reference stimuli. Data from several individuals are integrated into a common multidimensional stimulus space, where dimensionality and axes are defined by these reference stimuli. We used this technique to discriminate volatile compounds with a cohort of Drosophila flies, by recording odor responses in receptor neurons on the flies’ antennae. We propose this technique for the development of reliable biological sensors when activity raw data cannot be calibrated. In particular, this technique will be useful for evaluating physiological measurements in natural chemosensory systems, and therefore will allow to exploit the sensitivity and selectivity of olfactory receptors present in the animal kingdom for analytical purposes.

Crustacean olfactory systems: A comparative review and a crustacean perspective on olfaction in insects

Malacostracan crustaceans display a large diversity of sizes, morphs and life styles. However, only a few representatives of decapod taxa have served as models for analyzing crustacean olfaction, such as crayfish and spiny lobsters. Crustaceans bear multiple parallel chemosensory pathways represented by different populations of unimodal chemosensory and bimodal chemo- and mechanosensory sensilla on the mouthparts, the walking limbs and primarily on their two pairs of antennae. Here, we focus on the olfactory pathway associated with the unimodal chemosensory sensilla on the first antennal pair, the aesthetascs. We explore the diverse arrangement of these sensilla across malacostracan taxa and point out evolutionary transformations which occurred in the central olfactory pathway. We discuss the evolution of chemoreceptor proteins, comparative aspects of active chemoreception and the temporal resolution of crustacean olfactory system. Viewing the evolution of crustacean brains in light of energetic constraints can help us understand their functional morphology and suggests that in various crustacean lineages, the brains were simplified convergently because of metabolic limitations. Comparing the wiring of afferents, interneurons and output neurons within the olfactory glomeruli suggests a deep homology of insect and crustacean olfactory systems. However, both taxa followed distinct lineages during the evolutionary elaboration of their olfactory systems. A comparison with insects suggests their olfactory systems ö especially that of the vinegar fly ö to be superb examples for "economy of design". Such a comparison also inspires new thoughts about olfactory coding and the functioning of malacostracan olfactory systems in general.

The evolution of honey bee dance communication: a mechanistic perspective

Honey bee dance has been intensively studied as a communication system, and yet we still know very little about the neurobiological mechanisms supporting how dances are produced and interpreted. Here, we discuss how new information on the functions of the central complex (CX) of the insect brain might shed some light on possible neural mechanisms of dance behaviour. We summarise the features of dance communication across the species of the genus Apis. We then propose that neural mechanisms of orientation and spatial processing found to be supported by the CX may function in dance communication also, and that this mechanistic link could explain some specific features of the dance form. This is purely a hypothesis, but in proposing this hypothesis, and how it might be investigated, we hope to stimulate new mechanistic analyses of dance communication.