Functional analysis of a higher olfactory center, the lateral horn

Olfactory system structure and function in newly hatched and adult locusts

An important question in neuroscience is how sensory systems change as animals grow and interact with the environment. Exploring sensory systems in animals as they develop can reveal how networks of neurons process information as the neurons themselves grow and the needs of the animal change. Here we compared the structure and function of peripheral parts of the olfactory pathway in newly hatched and adult locusts. We found that populations of olfactory sensory neurons (OSNs) in hatchlings and adults responded with similar tunings to a panel of odors. The morphologies of local neurons (LNs) and projection neurons (PNs) in the antennal lobes (ALs) were very similar in both age groups, though they were smaller in hatchlings, they were proportional to overall brain size. The odor evoked responses of LNs and PNs were also very similar in both age groups, characterized by complex patterns of activity including oscillatory synchronization. Notably, in hatchlings, spontaneous and odor-evoked firing rates of PNs were lower, and LFP oscillations were lower in frequency, than in the adult. Hatchlings have smaller antennae with fewer OSNs; removing antennal segments from adults also reduced LFP oscillation frequency. Thus, consistent with earlier computational models, the developmental increase in frequency is due to increasing intensity of input to the oscillation circuitry. Overall, our results show that locusts hatch with a fully formed olfactory system that structurally and functionally matches that of the adult, despite its small size and lack of prior experience with olfactory stimuli.

Aversive conditioning information transmission in Drosophila

Animals rapidly acquire surrounding information to perform the appropriate behavior. Although social learning is more efficient and accessible than self-learning for animals, the detailed regulatory mechanism of social learning remains unknown, mainly because of the complicated information transfer between animals, especially for aversive conditioning information transmission. The current study revealed that, during social learning, the neural circuit in observer flies used to process acquired aversive conditioning information from demonstrator flies differs from the circuit used for self-learned classic aversive conditioning. This aversive information transfer is species dependent. Solitary flies cannot learn this information through social learning, suggesting that this ability is not an innate behavior. Neurons used to process and execute avoidance behavior to escape from electrically shocked flies are all in the same brain region, indicating that the fly brain has a common center for integrating external stimuli with internal states to generate flight behavior.

Neural manifolds for odor-driven innate and acquired appetitive preferences

Sensory stimuli evoke spiking neural responses that innately or after learning drive suitable behavioral outputs. How are these spiking activities intrinsically patterned to encode for innate preferences, and could the neural response organization impose constraints on learning? We examined this issue in the locust olfactory system. Using a diverse odor panel, we found that ensemble activities both during ('ON response') and after stimulus presentations ('OFF response') could be linearly mapped onto overall appetitive preference indices. Although diverse, ON and OFF response patterns generated by innately appetitive odorants (higher palp-opening responses) were still limited to a low-dimensional subspace (a 'neural manifold'). Similarly, innately non-appetitive odorants evoked responses that were separable yet confined to another neural manifold. Notably, only odorants that evoked neural response excursions in the appetitive manifold could be associated with gustatory reward. In sum, these results provide insights into how encoding for innate preferences can also impact associative learning.

Multimodal Information Processing and Associative Learning in the Insect Brain

Simple Summary

Insect behaviors are a great indicator of evolution and provide useful information about the complexity of organisms. The realistic sensory scene of an environment is complex and replete with multisensory inputs, making the study of sensory integration that leads to behavior highly relevant. We summarize the recent findings on multimodal sensory integration and the behaviors that originate from them in our review.

Abstract

The study of sensory systems in insects has a long-spanning history of almost an entire century. Olfaction, vision, and gustation are thoroughly researched in several robust insect models and new discoveries are made every day on the more elusive thermo- and mechano-sensory systems. Few specialized senses such as hygro- and magneto-reception are also identified in some insects. In light of recent advancements in the scientific investigation of insect behavior, it is not only important to study sensory modalities individually, but also as a combination of multimodal inputs. This is of particular significance, as a combinatorial approach to study sensory behaviors mimics the real-time environment of an insect with a wide spectrum of information available to it. As a fascinating field that is recently gaining new insight, multimodal integration in insects serves as a fundamental basis to understand complex insect behaviors including, but not limited to navigation, foraging, learning, and memory. In this review, we have summarized various studies that investigated sensory integration across modalities, with emphasis on three insect models (honeybees, ants and flies), their behaviors, and the corresponding neuronal underpinnings.

How the insect central complex could coordinate multimodal navigation

The central complex of the insect midbrain is thought to coordinate insect guidance strategies. Computational models can account for specific behaviours, but their applicability across sensory and task domains remains untested. Here, we assess the capacity of our previous model (Sun et al. 2020) of visual navigation to generalise to olfactory navigation and its coordination with other guidance in flies and ants. We show that fundamental to this capacity is the use of a biologically plausible neural copy-and-shift mechanism that ensures sensory information is presented in a format compatible with the insect steering circuit regardless of its source. Moreover, the same mechanism is shown to allow the transfer cues from unstable/egocentric to stable/geocentric frames of reference, providing a first account of the mechanism by which foraging insects robustly recover from environmental disturbances. We propose that these circuits can be flexibly repurposed by different insect navigators to address their unique ecological needs.

Distinct protocerebral neuropils associated with attractive and aversive female-produced odorants in the male moth brain

The pheromone system of heliothine moths is an optimal model for studying principles underlying higher-order olfactory processing. In Helicoverpa armigera, three male-specific glomeruli receive input about three female-produced signals, the primary pheromone component, serving as an attractant, and two minor constituents, serving a dual function, that is, attraction versus inhibition of attraction. From the antennal-lobe glomeruli, the information is conveyed to higher olfactory centers, including the lateral protocerebrum, via three main paths – of which the medial tract is the most prominent. In this study, we traced physiologically identified medial-tract projection neurons from each of the three male-specific glomeruli with the aim of mapping their terminal branches in the lateral protocerebrum. Our data suggest that the neurons’ widespread projections are organized according to behavioral significance, including a spatial separation of signals representing attraction versus inhibition – however, with a unique capacity of switching behavioral consequence based on the amount of the minor components.

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.

Olfactory encoding within the insect antennal lobe: The emergence and role of higher order temporal correlations in the dynamics of antennal lobe spiking activity

In this review, we focus on the antennal lobe (AL) of three insect species - the fruit fly, sphinx moth, and locust. We first review the experimentally elucidated anatomy and physiology of the early olfactory system of each species; empirical studies of AL activity, however, often focus on assessing firing rates (averaged over time scales of about 100 ms), and hence the AL odor code is often analyzed in terms of a temporally evolving vector of firing rates. However, such a perspective necessarily misses the possibility of higher order temporal correlations in spiking activity within a single cell and across multiple cells over shorter time scales (of about 10 ms). Hence, we then review our prior theoretical work, where we constructed biophysically detailed, species-specific AL models within the fly, moth, and locust, finding that in each case higher order temporal correlations in spiking naturally emerge from model dynamics (i.e., without a prioriincorporation of elements designed to produce correlated activity). We therefore use our theoretical work to argue the perspective that temporal correlations in spiking over short time scales, which have received little experimental attention to-date, may provide valuable coding dimensions (complementing the coding dimensions provided by the vector of firing rates) that nature has exploited in the encoding of odors within the AL. We further argue that, if the AL does indeed utilize temporally correlated activity to represent odor information, such an odor code could be naturally and easily deciphered within the Mushroom Body.

Olfactory processing in the lateral horn of Drosophila

Sensing olfactory signals in the environment represents a crucial and significant task of sensory systems in almost all organisms to facilitate survival and reproduction. Notably, the olfactory system of diverse animal phyla shares astonishingly many fundamental principles with regard to anatomical and functional properties. Binding of odor ligands by chemosensory receptors present in the olfactory peripheral organs leads to a neuronal activity that is conveyed to first and higher-order brain centers leading to a subsequent odor-guided behavioral decision. One of the key centers for integrating and processing innate olfactory behavior is the lateral horn (LH) of the protocerebrum in insects. In recent years the LH of Drosophila has garnered increasing attention and many studies have been dedicated to elucidate its circuitry. In this review we will summarize the recent advances in mapping and characterizing LH-specific cell types, their functional properties with respect to odor tuning, their neurotransmitter profiles, their connectivity to pre-synaptic and post-synaptic partner neurons as well as their impact for olfactory behavior as known so far.

Antennal Lobe Atlas of an Emerging Corn Pest, Athetis dissimilis

Moths develop sophisticated olfactory systems to sense the airborne chemical cues from the environment. Understanding the structural basis in the neuronal center is a fundamental neuroethological step. Little is known about the emerging crop pest Athetis dissimilis with regard to its morphology or its neuronal organizations. Through antibody staining and digital 3D modeling, we re-constructed the primary olfactory center-the antennal lobe of A. dissimilis. In the antennal lobes 68.8 ± 3.1 male glomeruli and 70.8 ± 1.0 female glomeruli were identified with obvious sexual dimorphism. In particular, male adults of A. dissimilis contain a macroglomerular complex (MGC) that consists of three subunits, while the female lobe has four relatively enlarged glomeruli at the entrance of the antennal nerve. Glomeruli were later clustered with deviation and variance, and referring to reported olfactory related receptor family genes in seven different moth species, we found that glomerular counts of these insects are better related to the sum of odorant receptor and ionotropic receptor numbers, suggesting olfactory receptors and ionotropic receptors may both involved in olfaction of Noctuidae moths.

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.

Feedback inhibition and its control in an insect olfactory circuit

Inhibitory neurons play critical roles in regulating and shaping olfactory responses in vertebrates and invertebrates. In insects, these roles are performed by relatively few neurons, which can be interrogated efficiently, revealing fundamental principles of olfactory coding. Here, with electrophysiological recordings from the locust and a large-scale biophysical model, we analyzed the properties and functions of GGN, a unique giant GABAergic neuron that plays a central role in structuring olfactory codes in the locust mushroom body. Our simulations suggest that depolarizing GGN at its input branch can globally inhibit KCs several hundred microns away. Our in vivorecordings show that GGN responds to odors with complex temporal patterns of depolarization and hyperpolarization that can vary with odors and across animals, leading our model to predict the existence of a yet-undiscovered olfactory pathway. Our analysis reveals basic new features of GGN and the olfactory network surrounding it.

Optimality of sparse olfactory representations is not affected by network plasticity

The neural representation of a stimulus is repeatedly transformed as it moves from the sensory periphery to deeper layers of the nervous system. Sparsening transformations are thought to increase the separation between similar representations, encode stimuli with great specificity, maximize storage capacity of associative memories, and provide an energy efficient instantiation of information in neural circuits. In the insect olfactory system, odors are initially represented in the periphery as a combinatorial code with relatively simple temporal dynamics. Subsequently, in the antennal lobe this representation is transformed into a dense and complex spatiotemporal activity pattern. Next, in the mushroom body Kenyon cells (KCs), the representation is dramatically sparsened. Finally, in mushroom body output neurons (MBONs), the representation takes on a new dense spatiotemporal format. Here, we develop a computational model to simulate this chain of olfactory processing from the receptor neurons to MBONs. We demonstrate that representations of similar odorants are maximally separated, measured by the distance between the corresponding MBON activity vectors, when KC responses are sparse. Sparseness is maintained across variations in odor concentration by adjusting the feedback inhibition that KCs receive from an inhibitory neuron, the Giant GABAergic neuron. Different odor concentrations require different strength and timing of feedback inhibition for optimal processing. Importantly, as observed in vivo, the KC–MBON synapse is highly plastic, and, therefore, changes in synaptic strength after learning can change the balance of excitation and inhibition, potentially leading to changes in the distance between MBON activity vectors of two odorants for the same level of KC population sparseness. Thus, what is an optimal degree of sparseness before odor learning, could be rendered sub–optimal post learning. Here, we show, however, that synaptic weight changes caused by spike timing dependent plasticity increase the distance between the odor representations from the perspective of MBONs. A level of sparseness that was optimal before learning remains optimal post-learning.

Kenyon cells (KCs) of the mushroom body represent odors as a sparse code. When viewed from the perspective of follower neurons, mushroom body output neurons (MBONs) reveal an optimal level of coding sparseness that maximally separates the representations of odors. However, the KC–MBON synapse is highly plastic and may be potentiated or depressed by odor–driven experience that could, in turn, disrupt the optimality formed by pre–synaptic circuits. Contrary to this expectation, we show that synaptic plasticity based on spike timing of pre- and postsynaptic neurons improves the ability of the system to distinguish between the representations of similar odors while preserving the optimality determined by pre–synaptic circuits.

Morphology and physiology of olfactory neurons in the lateral protocerebrum of the silkmoth Bombyx mori

Insect olfaction is a suitable model to investigate sensory processing in the brain. Olfactory information is first processed in the antennal lobe and is then conveyed to two second-order centres—the mushroom body calyx and the lateral protocerebrum. Projection neurons processing sex pheromones and plant odours supply the delta area of the inferior lateral protocerebrum (∆ILPC) and lateral horn (LH), respectively. Here, we investigated the neurons arising from these regions in the brain of the silkmoth, Bombyx mori, using mass staining and intracellular recording with a sharp glass microelectrode. The output neurons from the ∆ILPC projected to the superior medial protocerebrum, whereas those from the LH projected to the superior lateral protocerebrum. The dendritic innervations of output neurons from the ∆ILPC formed a subdivision in the ∆ILPC. We discuss pathways for odour processing in higher order centres.

Neurogenetic dissection of the Drosophila lateral horn reveals major outputs, diverse behavioural functions, and interactions with the mushroom body

Animals exhibit innate behaviours to a variety of sensory stimuli including olfactory cues. In Drosophila, one higher olfactory centre, the lateral horn (LH), is implicated in innate behaviour. However, our structural and functional understanding of the LH is scant, in large part due to a lack of sparse neurogenetic tools for this region. We generate a collection of split-GAL4 driver lines providing genetic access to 82 LH cell types. We use these to create an anatomical and neurotransmitter map of the LH and link this to EM connectomics data. We find ~30% of LH projections converge with outputs from the mushroom body, site of olfactory learning and memory. Using optogenetic activation, we identify LH cell types that drive changes in valence behavior or specific locomotor programs. In summary, we have generated a resource for manipulating and mapping LH neurons, providing new insights into the circuit basis of innate and learned olfactory behavior.

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.

Evidence for absence of bilateral transfer of olfactory learned information in Apis dorsata and Apis mellifera

The capacity and condition under which the lateral transfer of olfactory memory is possible in insects is still debated. Here, we present evidence in two species of honeybees, Apis mellifera and Apis dorsata, consistent with the lack of ability to transfer olfactory associative memory in a proboscis extension response (PER) associative conditioning paradigm, where the untrained antenna is blocked by an insulating coat. We show that the olfactory system on each side of the bee can learn and retrieve information independently and the retrieval using the antenna on the side contralateral to the trained one is not affected by the training. Using the setup in which the memory on the contralateral side has been reported at 3 h after training, we see that the memory is available on the contralateral side immediately after training. In the same setup, coating the antenna with an insulator on the training side does not prevent learning, pointing to a possible insufficiency of the block of odor stimuli in this setup. Moreover, the behavior of the bee as a whole can be predicted if the sides are assumed to learn and store independently, and the organism as a whole is able to retrieve the memory if either of the sides have the memory.

Re-evaluating Circuit Mechanisms Underlying Pattern Separation

When animals interact with complex environments, their neural circuits must separate overlapping patterns of activity that represent sensory and motor information. Pattern separation is thought to be a key function of several brain regions, including the cerebellar cortex, insect mushroom body, and dentate gyrus. However, recent findings have questioned long-held ideas on how these circuits perform this fundamental computation. Here, we re-evaluate the functional and structural mechanisms underlying pattern separation. We argue that the dimensionality of the space available for population codes representing sensory and motor information provides a common framework for understanding pattern separation. We then discuss how these three circuits use different strategies to separate activity patterns and facilitate associative learning in the presence of trial-to-trial variability.

High Precision of Spike Timing across Olfactory Receptor Neurons Allows Rapid Odor Coding in Drosophila

In recent years, it has become evident that olfaction is a fast sense, and millisecond short differences in stimulus onsets are used by animals to analyze their olfactory environment. In contrast, olfactory receptor neurons are thought to be relatively slow and temporally imprecise. These observations have led to a conundrum: how, then, can an animal resolve fast stimulus dynamics and smell with high temporal acuity? Using parallel recordings from olfactory receptor neurons in Drosophila, we found hitherto unknown fast and temporally precise odorant-evoked spike responses, with first spike latencies (relative to odorant arrival) down to 3 ms and with a SD below 1 ms. These data provide new upper bounds for the speed of olfactory processing and suggest that the insect olfactory system could use the precise spike timing for olfactory coding and computation, which can explain insects' rapid processing of temporal stimuli when encountering turbulent odor plumes.

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Olfactory receptor neuron responses are fast and temporally precise

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Odor-evoked spikes can occur 3 ms after odorant arrival and jitter less than 1 ms

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First-spike timing varies over a wider concentration range than spike rate

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Neural network model demonstrates the plausibility of a spike-timing code for odors

A neural network model for familiarity and context learning during honeybee foraging flights

How complex is the memory structure that honeybees use to navigate? Recently, an insect-inspired parsimonious spiking neural network model was proposed that enabled simulated ground-moving agents to follow learned routes. We adapted this model to flying insects and evaluate the route following performance in three different worlds with gradually decreasing object density. In addition, we propose an extension to the model to enable the model to associate sensory input with a behavioral context, such as foraging or homing. The spiking neural network model makes use of a sparse stimulus representation in the mushroom body and reward-based synaptic plasticity at its output synapses. In our experiments, simulated bees were able to navigate correctly even when panoramic cues were missing. The context extension we propose enabled agents to successfully discriminate partly overlapping routes. The structure of the visual environment, however, crucially determines the success rate. We find that the model fails more often in visually rich environments due to the overlap of features represented by the Kenyon cell layer. Reducing the landmark density improves the agents route following performance. In very sparse environments, we find that extended landmarks, such as roads or field edges, may help the agent stay on its route, but often act as strong distractors yielding poor route following performance. We conclude that the presented model is valid for simple route following tasks and may represent one component of insect navigation. Additional components might still be necessary for guidance and action selection while navigating along different memorized routes in complex natural environments.

The role of the Drosophila lateral horn in olfactory information processing and behavioral response

Animals must rapidly and accurately process environmental information to produce the correct behavioral responses. Reactions to previously encountered as well as to novel but biologically important stimuli are equally important, and one understudied region in the insect brain plays a role in processing both types of stimuli. The lateral horn is a higher order processing center that mainly processes olfactory information and is linked via olfactory projection neurons to another higher order learning center, the mushroom body. This review focuses on the lateral horn of Drosophila where most functional studies have been performed. We discuss connectivity between the primary olfactory center, the antennal lobe, and the lateral horn and mushroom body. We also present evidence for the lateral horn playing roles in innate behavioral responses by encoding biological valence to novel odor cues and in learned responses to previously encountered odors by modulating neural activity within the mushroom body. We describe how these processes contribute to acceptance or avoidance of appropriate or inappropriate mates and food, as well as the identification of predators. The lateral horn is a sexually dimorphic and plastic region of the brain that modulates other regions of the brain to ensure that insects produce rapid and effective behavioral responses to both novel and learned stimuli, yet multiple gaps exist in our knowledge of this important center. We anticipate that future studies on olfactory processing, learning, and innate behavioral responses will include the lateral horn in their examinations, leading to a more comprehensive understanding of olfactory information relay and resulting behaviors.

Anatomical organization of the brain of a diurnal and a nocturnal dung beetle

To avoid the fierce competition for food, South African ball-rolling dung beetles carve a piece of dung off a dung-pile, shape it into a ball and roll it away along a straight line path. For this unidirectional exit from the busy dung pile, at night and day, the beetles use a wide repertoire of celestial compass cues. This robust and relatively easily measurable orientation behavior has made ball-rolling dung beetles an attractive model organism for the study of the neuroethology behind insect orientation and sensory ecology. Although there is already some knowledge emerging concerning how celestial cues are processed in the dung beetle brain, little is known about its general neural layout. Mapping the neuropils of the dung beetle brain is thus a prerequisite to understand the neuronal network that underlies celestial compass orientation. Here, we describe and compare the brains of a day-active and a night-active dung beetle species based on immunostainings against synapsin and serotonin. We also provide 3D reconstructions for all brain areas and many of the fiber bundles in the brain of the day-active dung beetle. Comparison of neuropil structures between the two dung beetle species revealed differences that reflect adaptations to different light conditions. Altogether, our results provide a reference framework for future studies on the neuroethology of insects in general and dung beetles in particular.

Oscillatory integration windows in neurons

Oscillatory synchrony among neurons occurs in many species and brain areas, and has been proposed to help neural circuits process information. One hypothesis states that oscillatory input creates cyclic integration windows: specific times in each oscillatory cycle when postsynaptic neurons become especially responsive to inputs. With paired local field potential (LFP) and intracellular recordings and controlled stimulus manipulations we directly test this idea in the locust olfactory system. We find that inputs arriving in Kenyon cells (KCs) sum most effectively in a preferred window of the oscillation cycle. With a computational model, we show that the non-uniform structure of noise in the membrane potential helps mediate this process. Further experiments performed in vivo demonstrate that integration windows can form in the absence of inhibition and at a broad range of oscillation frequencies. Our results reveal how a fundamental coincidence-detection mechanism in a neural circuit functions to decode temporally organized spiking.

A Single Pair of Serotonergic Neurons Counteracts Serotonergic Inhibition of Ethanol Attraction in Drosophila

Attraction to ethanol is common in both flies and humans, but the neuromodulatory mechanisms underlying this innate attraction are not well understood. Here, we dissect the function of the key regulator of serotonin signaling—the serotonin transporter–in innate olfactory attraction to ethanol in Drosophila melanogaster. We generated a mutated version of the serotonin transporter that prolongs serotonin signaling in the synaptic cleft and is targeted via the Gal4 system to different sets of serotonergic neurons. We identified four serotonergic neurons that inhibit the olfactory attraction to ethanol and two additional neurons that counteract this inhibition by strengthening olfactory information. Our results reveal that compensation can occur on the circuit level and that serotonin has a bidirectional function in modulating the innate attraction to ethanol. Given the evolutionarily conserved nature of the serotonin transporter and serotonin, the bidirectional serotonergic mechanisms delineate a basic principle for how random behavior is switched into targeted approach behavior.

Pleiotropic Effects of Loss of the Dα1 Subunit in Drosophila melanogaster: Implications for Insecticide Resistance

Nicotinic acetylcholine receptors (nAChRs) are a highly conserved gene family that form pentameric receptors involved in fast excitatory synaptic neurotransmission. The specific roles individual nAChR subunits perform in Drosophila melanogaster and other insects are relatively uncharacterized. Of the 10 D. melanogaster nAChR subunits, only three have described roles in behavioral pathways; Dα3 and Dα4 in sleep, and Dα7 in the escape response. Other subunits have been associated with resistance to several classes of insecticides. In particular, our previous work has demonstrated that an allele of the Dα1 subunit is associated with resistance to neonicotinoid insecticides. We used ends-out gene targeting to create a knockout of the Dα1 gene to facilitate phenotypic analysis in a controlled genetic background. To our knowledge, this is the first report of a native function for any nAChR subunits known to be targeted by insecticides. Loss of Dα1 function was associated with changes in courtship, sleep, longevity, and insecticide resistance. While acetylcholine signaling had previously been linked with mating behavior and reproduction in D. melanogaster, no specific nAChR subunit had been directly implicated. The role of Dα1 in a number of behavioral phenotypes highlights the importance of understanding the biological roles of nAChRs and points to the fitness cost that may be associated with neonicotinoid resistance.

A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning

Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies neuropile. The network devoted to context formation is able to reconstruct the learned sequence and also to trace the subsequences present in the provided input. A sensitivity analysis to parameter variation and noise is reported. Experiments on a roving robot are reported to show the capabilities of the architecture used as a neural controller.

Neuroethology of Olfactory-Guided Behavior and Its Potential Application in the Control of Harmful Insects

Harmful insects include pests of crops and storage goods, and vectors of human and animal diseases. Throughout their history, humans have been fighting them using diverse methods. The fairly recent development of synthetic chemical insecticides promised efficient crop and health protection at a relatively low cost. However, the negative effects of those insecticides on human health and the environment, as well as the development of insect resistance, have been fueling the search for alternative control tools. New and promising alternative methods to fight harmful insects include the manipulation of their behavior using synthetic versions of "semiochemicals", which are natural volatile and non-volatile substances involved in the intra- and/or inter-specific communication between organisms. Synthetic semiochemicals can be used as trap baits to monitor the presence of insects, so that insecticide spraying can be planned rationally (i.e., only when and where insects are actually present). Other methods that use semiochemicals include insect annihilation by mass trapping, attract-and- kill techniques, behavioral disruption, and the use of repellents. In the last decades many investigations focused on the neural bases of insect's responses to semiochemicals. Those studies help understand how the olfactory system detects and processes information about odors, which could lead to the design of efficient control tools, including odor baits, repellents or ways to confound insects. Here we review our current knowledge about the neural mechanisms controlling olfactory responses to semiochemicals in harmful insects. We also discuss how this neuroethology approach can be used to design or improve pest/vector management strategies.

Antennal-lobe tracts in the noctuid moth, Heliothis virescens: new anatomical findings

As in other insects, three main tracts in the moth brain form parallel connections between the antennal lobe and the protocerebrum. These tracts, which consist of the antennal-lobe projection-neuron axons, target two main areas in the protocerebrum, the calyces of the mushroom bodies and the lateral horn. In spite of the solid neuroanatomical knowledge already established, there are still unresolved issues regarding the antennal-lobe tracts of the moth. One is the proportion of lateral-tract neurons targeting the calyces. In the study presented here, we have performed both retrograde and anterograde labeling of the antennal-lobe projection neurons in the brain of the moth, Heliothis virescens. The results from the retrograde staining, obtained by applying dye in the calyces, demonstrated that the direct connection between the antennal lobe and this neuropil is maintained primarily by the medial antennal-lobe tract; only a few axons confined to the lateral tract were found to innervate the calyces. In addition, these staining experiments, which allowed us to explore the arborization pattern of labeled neurons within the antennal lobe, resulted in new findings regarding anatomical arrangement of roots and cell body clusters linked to the medial tract. The results from the anterograde staining, obtained by applying dye into the antennal lobe, visualized the total assembly of axons passing along the antennal-lobe tracts. In addition to the three classical tracts, we found a transverse antennal-lobe tract not previously described in the moth. Also, these staining experiments revealed an organized neuropil in the lateral horn formed by terminals of the four antennal-lobe tracts.

Classification of odorants across layers in locust olfactory pathway

Olfactory processing takes place across multiple layers of neurons from the transduction of odorants in the periphery, to odor quality processing, learning, and decision making in higher olfactory structures. In insects, projection neurons (PNs) in the antennal lobe send odor information to the Kenyon cells (KCs) of the mushroom bodies and lateral horn neurons (LHNs). To examine the odor information content in different structures of the insect brain, antennal lobe, mushroom bodies and lateral horn, we designed a model of the olfactory network based on electrophysiological recordings made in vivo in the locust. We found that populations of all types (PNs, LHNs, and KCs) had lower odor classification error rates than individual cells of any given type. This improvement was quantitatively different from that observed using uniform populations of identical neurons compared with spatially structured population of neurons tuned to different odor features. This result, therefore, reflects an emergent network property. Odor classification improved with increasing stimulus duration: for similar odorants, KC and LHN ensembles reached optimal discrimination within the first 300-500 ms of the odor response. Performance improvement with time was much greater for a population of cells than for individual neurons. We conclude that, for PNs, LHNs, and KCs, ensemble responses are always much more informative than single-cell responses, despite the accumulation of noise along with odor information.

A Novel Gene Controlling the Timing of Courtship Initiation in Drosophila melanogaster

Over the past 35 years, developmental geneticists have made impressive progress toward an understanding of how genes specify morphology and function, particularly as they relate to the specification of each physical component of an organism. In the last 20 years, male courtship behavior in Drosophila melanogaster has emerged as a robust model system for the study of genetic specification of behavior. Courtship behavior is both complex and innate, and a single gene, fruitless (fru), is both necessary and sufficient for all aspects of the courtship ritual. Typically, loss of male-specific Fruitless protein function results in male flies that perform the courtship ritual incorrectly, slowly, or not at all. Here we describe a novel requirement for fru: we have identified a group of cells in which male Fru proteins are required to reduce the speed of courtship initiation. In addition, we have identified a gene, Trapped in endoderm 1 (Tre1), which is required in these cells for normal courtship and mating behavior. Tre1 encodes a G-protein-coupled receptor required for establishment of cell polarity and cell migration and has previously not been shown to be involved in courtship behavior. We describe the results of feminization of the Tre1-expressing neurons, as well as the effects on courtship behavior of mutation of Tre1. In addition, we show that Tre1 is expressed in a sexually dimorphic pattern in the central and peripheral nervous systems and investigate the role of the Tre1 cells in mate identification.

Feed-Forward versus Feedback Inhibition in a Basic Olfactory Circuit

Inhibitory interneurons play critical roles in shaping the firing patterns of principal neurons in many brain systems. Despite difference in the anatomy or functions of neuronal circuits containing inhibition, two basic motifs repeatedly emerge: feed-forward and feedback. In the locust, it was proposed that a subset of lateral horn interneurons (LHNs), provide feed-forward inhibition onto Kenyon cells (KCs) to maintain their sparse firing—a property critical for olfactory learning and memory. But recently it was established that a single inhibitory cell, the giant GABAergic neuron (GGN), is the main and perhaps sole source of inhibition in the mushroom body, and that inhibition from this cell is mediated by a feedback (FB) loop including KCs and the GGN. To clarify basic differences in the effects of feedback vs. feed-forward inhibition in circuit dynamics we here use a model of the locust olfactory system. We found both inhibitory motifs were able to maintain sparse KCs responses and provide optimal odor discrimination. However, we further found that only FB inhibition could create a phase response consistent with data recorded in vivo. These findings describe general rules for feed-forward versus feedback inhibition and suggest GGN is potentially capable of providing the primary source of inhibition to the KCs. A better understanding of how inhibitory motifs impact post-synaptic neuronal activity could be used to reveal unknown inhibitory structures within biological networks.

Understanding how inhibitory neurons interact with excitatory neurons is critical for understanding the behaviors of neuronal networks. Here we address this question with simple but biologically relevant models based on the anatomy of the locust olfactory pathway. Two ubiquitous and basic inhibitory motifs were tested: feed-forward and feedback. Feed-forward inhibition typically occurs between different brain areas when excitatory neurons excite inhibitory cells, which then inhibit a group of postsynaptic excitatory neurons outside of the initializing excitatory neurons’ area. On the other hand, the feedback inhibitory motif requires a population of excitatory neurons to drive the inhibitory cells, which in turn inhibit the same population of excitatory cells. We found the type of the inhibitory motif determined the timing with which each group of cells fired action potentials in comparison to one another (relative timing). It also affected the range of inhibitory neurons’ activity, with the inhibitory neurons having a wider range in the feedback circuit than that in the feed-forward one. These results will allow predicting the type of the connectivity structure within unexplored biological circuits given only electrophysiological recordings.

It takes two-coincidence coding within the dual olfactory pathway of the honeybee

To rapidly process biologically relevant stimuli, sensory systems have developed a broad variety of coding mechanisms like parallel processing and coincidence detection. Parallel processing (e.g., in the visual system), increases both computational capacity and processing speed by simultaneously coding different aspects of the same stimulus. Coincidence detection is an efficient way to integrate information from different sources. Coincidence has been shown to promote associative learning and memory or stimulus feature detection (e.g., in auditory delay lines). Within the dual olfactory pathway of the honeybee both of these mechanisms might be implemented by uniglomerular projection neurons (PNs) that transfer information from the primary olfactory centers, the antennal lobe (AL), to a multimodal integration center, the mushroom body (MB). PNs from anatomically distinct tracts respond to the same stimulus space, but have different physiological properties, characteristics that are prerequisites for parallel processing of different stimulus aspects. However, the PN pathways also display mirror-imaged like anatomical trajectories that resemble neuronal coincidence detectors as known from auditory delay lines. To investigate temporal processing of olfactory information, we recorded PN odor responses simultaneously from both tracts and measured coincident activity of PNs within and between tracts. Our results show that coincidence levels are different within each of the two tracts. Coincidence also occurs between tracts, but to a minor extent compared to coincidence within tracts. Taken together our findings support the relevance of spike timing in coding of olfactory information (temporal code).

Trade-off between information format and capacity in the olfactory system

As information about the sensory environment passes between layers within the nervous system, the format of the information often changes. To examine how information format affects the capacity of neurons to represent stimuli, we measured the rate of information transmission in olfactory neurons in intact, awake locusts (Schistocerca americana) while pharmacologically manipulating patterns of correlated neuronal activity. Blocking the periodic inhibition underlying odor-elicited neural oscillatory synchronization increased information transmission rates. This suggests oscillatory synchrony, which serves other information processing roles, comes at a cost to the speed with which neurons can transmit information. Our results provide an example of a trade-off between benefits and costs in neural information processing.

Decoding odor quality and intensity in the Drosophila brain

To internally reflect the sensory environment, animals create neural maps encoding the external stimulus space. From that primary neural code relevant information has to be extracted for accurate navigation. We analyzed how different odor features such as hedonic valence and intensity are functionally integrated in the lateral horn (LH) of the vinegar fly, Drosophila melanogaster. We characterized an olfactory-processing pathway, comprised of inhibitory projection neurons (iPNs) that target the LH exclusively, at morphological, functional and behavioral levels. We demonstrate that iPNs are subdivided into two morphological groups encoding positive hedonic valence or intensity information and conveying these features into separate domains in the LH. Silencing iPNs severely diminished flies' attraction behavior. Moreover, functional imaging disclosed a LH region tuned to repulsive odors comprised exclusively of third-order neurons. We provide evidence for a feature-based map in the LH, and elucidate its role as the center for integrating behaviorally relevant olfactory information.

DOI:http://dx.doi.org/10.7554/eLife.04147.001

Organisms need to sense and adapt to their environment in order to survive. Senses such as vision and smell allow an organism to absorb information about the external environment and translate it into a meaningful internal image. This internal image helps the organism to remember incidents and act accordingly when they encounter similar situations again. A typical example is when organisms are repeatedly attracted to odors that are essential for survival, such as food and pheromones, and are repulsed by odors that threaten survival.

Strutz et al. addressed how attractiveness or repulsiveness of a smell, and also the strength of a smell, are processed by a part of the olfactory system called the lateral horn in fruit flies. This involved mapping the neuronal patterns that were generated in the lateral horn when a fly was exposed to particular odors.

Strutz et al. found that a subset of neurons called inhibitory projection neurons processes information about whether the odor is attractive or repulsive, and that a second subset of these neurons process information about the intensity of the odor. Other insects, such as honey bees and hawk moths, have olfactory systems with a similar architecture and might also employ a similar spatial approach to encode information regarding the intensity and identity of odors. Locusts, on the other hand, employ a temporal approach to encoding information about odors.

The work of Strutz et al. shows that certain qualities of odors are contained in a spatial map in a specific brain region of the fly. This opens up the question of how the information in this spatial map influences decisions made by the fly.

DOI:http://dx.doi.org/10.7554/eLife.04147.002

Central processing in the mushroom bodies

The mushroom bodies in the insect brain serve as a central information processing area. Here, focusing mainly on olfaction, we discuss functionally related roles the mushroom bodies play in signal gain control, response sparsening, the separation of similar signals (decorrelation), and learning and memory. In sum, the mushroom bodies assemble and format a context-appropriate representation of the insect's world.

A temporal channel for information in sparse sensory coding

BACKGROUND

Sparse codes are found in nearly every sensory system, but the role of spike timing in sparse sensory coding is unclear. Here, we use the olfactory system of awake locusts to test whether the timing of spikes in Kenyon cells, a population of neurons that responds sparsely to odors, carries sensory information to and influences the responses of follower neurons.

RESULTS

We characterized two major classes of direct followers of Kenyon cells. With paired intracellular and field potential recordings made during odor presentations, we found that these followers contain information about odor identity in the temporal patterns of their spikes rather than in the spike rate, the spike phase, or the identities of the responsive neurons. Subtly manipulating the relative timing of Kenyon cell spikes with temporally and spatially structured microstimulation reliably altered the response patterns of the followers.

CONCLUSIONS

Our results show that even remarkably sparse spiking responses can provide information through stimulus-specific variations in timing on the order of tens to hundreds of milliseconds and that these variations can determine the responses of downstream neurons. These results establish the importance of spike timing in a sparse sensory code.

The right dorsal habenula limits attraction to an odor in zebrafish

BACKGROUND

The habenula consists of an evolutionarily conserved set of nuclei that control neuromodulator release. In lower vertebrates, the dorsal habenula receives innervation from sensory regions, but the significance of this is unclear. Here, we address the role of the habenula in olfaction by imaging neural activity in larval zebrafish expressing GCaMP3 throughout the habenula and by carrying out behavioral assays.

RESULTS

Activity in several hundred neurons throughout the habenula was recorded using wide-field fluorescence microscopy, fast focusing, and deconvolution. This enabled the creation of 4D maps of odor-evoked activity. Odors activated the habenula in two broad spatiotemporal patterns. Increasing concentrations of a putative social cue (a bile salt) evoked a corresponding increase in neuronal activity in the right dorsal habenula. In behavioral assays, fish were attracted to intermediate concentration of this cue but avoided higher concentration. Increasing cholinergic activity through nicotine exposure rendered the intermediate concentration aversive in a habenula-dependent manner. Pharmacologically blocking nicotinic receptors or lesioning the right dorsal habenula attenuated avoidance.

CONCLUSIONS

These data provide physiological and functional evidence that the habenula functions as a higher center in zebrafish olfaction and suggest that activity in the right dorsal subdomain gates innate attraction to specific odors.

Shocking revelations and saccharin sweetness in the study of Drosophila olfactory memory

It is now almost forty years since the first description of learning in the fruit fly Drosophila melanogaster. Various incarnations of the classic mutagenesis approach envisaged in the early days have provided around one hundred learning defective mutant fly strains. Recent technological advances permit temporal control of neural function in the behaving fly. These approaches have radically changed experiments in the field and have provided a neural circuit perspective of memory formation, consolidation and retrieval. Combining neural perturbations with more classical mutant intervention allows investigators to interrogate the molecular and cellular processes of memory within the defined neural circuits. Here, we summarize some of the progress made in the last ten years that indicates a remarkable conservation of the neural mechanisms of memory formation between flies and mammals. We emphasize that considering an ethologically-relevant viewpoint might provide additional experimental power in studies of Drosophila memory.

Sparse, decorrelated odor coding in the mushroom body enhances learned odor discrimination

Sparse coding may be a general strategy of neural systems to augment memory capacity. In Drosophila, sparse odor coding by the Kenyon cells of the mushroom body is thought to generate a large number of precisely addressable locations for the storage of odor-specific memories. However, it remains untested how sparse coding relates to behavioral performance. Here we demonstrate that sparseness is controlled by a negative feedback circuit between Kenyon cells and the GABAergic anterior paired lateral (APL) neuron. Systematic activation and blockade of each leg of this feedback circuit show that Kenyon cells activate APL and APL inhibits Kenyon cells. Disrupting the Kenyon cell-APL feedback loop decreases the sparseness of Kenyon cell odor responses, increases inter-odor correlations, and prevents flies from learning to discriminate similar, but not dissimilar, odors. These results suggest that feedback inhibition suppresses Kenyon cell activity to maintain sparse, decorrelated odor coding and thus the odor-specificity of memories.

Olfactory coding in the honeybee lateral horn

Olfactory systems dynamically encode odor information in the nervous system. Insects constitute a well-established model for the study of the neural processes underlying olfactory perception. In insects, odors are detected by sensory neurons located in the antennae, whose axons project to a primary processing center, the antennal lobe. There, the olfactory message is reshaped and further conveyed to higher-order centers, the mushroom bodies and the lateral horn. Previous work has intensively analyzed the principles of olfactory processing in the antennal lobe and in the mushroom bodies. However, how the lateral horn participates in olfactory coding remains comparatively more enigmatic. We studied odor representation at the input to the lateral horn of the honeybee, a social insect that relies on both floral odors for foraging and pheromones for social communication. Using in vivo calcium imaging, we show consistent neural activity in the honeybee lateral horn upon stimulation with both floral volatiles and social pheromones. Recordings reveal odor-specific maps in this brain region as stimulations with the same odorant elicit more similar spatial activity patterns than stimulations with different odorants. Odor-similarity relationships are mostly conserved between antennal lobe and lateral horn, so that odor maps recorded in the lateral horn allow predicting bees' behavioral responses to floral odorants. In addition, a clear segregation of odorants based on pheromone type is found in both structures. The lateral horn thus contains an odor-specific map with distinct representations for the different bee pheromones, a prerequisite for eliciting specific behaviors.

Stereotyped connectivity and computations in higher-order olfactory neurons

In the first brain relay of the olfactory system, odors are encoded by combinations of glomeruli, but it is not known how glomerular signals are ultimately integrated. In Drosophila melanogaster, the majority of glomerular projections target the lateral horn. Here we show that lateral horn neurons (LHNs) receive input from sparse and stereotyped combinations of glomeruli that are coactivated by odors, and certain combinations of glomeruli are over-represented. One morphological LHN type is broadly tuned and sums input from multiple glomeruli. These neurons have a broader dynamic range than their individual glomerular inputs do. By contrast, a second morphological type is narrowly tuned and receives prominent odor-selective inhibition through both direct and indirect pathways. We show that this wiring scheme confers increased selectivity. The biased stereotyped connectivity of the lateral horn contrasts with the probabilistic wiring of the mushroom body, reflecting the distinct roles of these regions in innate as compared to learned behaviors.

An information theoretic model of information processing in the Drosophila olfactory system: the role of inhibitory neurons for system efficiency

Fruit flies (Drosophila melanogaster) rely on their olfactory system to process environmental information. This information has to be transmitted without system-relevant loss by the olfactory system to deeper brain areas for learning. Here we study the role of several parameters of the fly's olfactory system and the environment and how they influence olfactory information transmission. We have designed an abstract model of the antennal lobe, the mushroom body and the inhibitory circuitry. Mutual information between the olfactory environment, simulated in terms of different odor concentrations, and a sub-population of intrinsic mushroom body neurons (Kenyon cells) was calculated to quantify the efficiency of information transmission. With this method we study, on the one hand, the effect of different connectivity rates between olfactory projection neurons and firing thresholds of Kenyon cells. On the other hand, we analyze the influence of inhibition on mutual information between environment and mushroom body. Our simulations show an expected linear relation between the connectivity rate between the antennal lobe and the mushroom body and firing threshold of the Kenyon cells to obtain maximum mutual information for both low and high odor concentrations. However, contradicting all-day experiences, high odor concentrations cause a drastic, and unrealistic, decrease in mutual information for all connectivity rates compared to low concentration. But when inhibition on the mushroom body is included, mutual information remains at high levels independent of other system parameters. This finding points to a pivotal role of inhibition in fly information processing without which the system efficiency will be substantially reduced.