Inhibitory connections in the honeybee antennal lobe are spatially patchy

Gain modulation and odor concentration invariance in early olfactory networks

The broad receptive field of the olfactory receptors constitutes the basis of a combinatorial code that allows animals to detect and discriminate many more odorants than the actual number of receptor types that they express. One drawback is that high odor concentrations recruit lower affinity receptors which can lead to the perception of qualitatively different odors. Here we addressed the contribution that signal-processing in the antennal lobe makes to reduce concentration dependence in odor representation. By means of calcium imaging and pharmacological approach we describe the contribution that GABA receptors play in terms of the amplitude and temporal profiles of the signals that convey odor information from the antennal lobes to higher brain centers. We found that GABA reduces the amplitude of odor elicited signals and the number of glomeruli that are recruited in an odor-concentration-dependent manner. Blocking GABA receptors decreases the correlation among glomerular activity patterns elicited by different concentrations of the same odor. In addition, we built a realistic mathematical model of the antennal lobe that was used to test the viability of the proposed mechanisms and to evaluate the processing properties of the AL network under conditions that cannot be achieved in physiology experiments. Interestingly, even though based on a rather simple topology and cell interactions solely mediated by GABAergic lateral inhibitions, the AL model reproduced key features of the AL response upon different odor concentrations and provides plausible solutions for concentration invariant recognition of odors by artificial sensors.

Granger Causality Analysis of Transient Calcium Dynamics in the Honey Bee Antennal Lobe Network

Odorant processing presents multiple parallels across animal species, and insects became relevant models for the study of olfactory coding because of the tractability of the underlying neural circuits. Within the insect brain, odorants are received by olfactory sensory neurons and processed by the antennal lobe network. Such a network comprises multiple nodes, named glomeruli, that receive sensory information and are interconnected by local interneurons participating in shaping the neural representation of an odorant. The study of functional connectivity between the nodes of a sensory network in vivo is a challenging task that requires simultaneous recording from multiple nodes at high temporal resolutions. Here, we followed the calcium dynamics of antennal lobe glomeruli and applied Granger causality analysis to assess the functional connectivity among network nodes in the presence and absence of an odorous stimulus. This approach revealed the existence of causal connectivity links between antennal lobe glomeruli in the absence of olfactory stimulation, while at odor arrival, the connectivity network's density increased and became stimulus-specific. Thus, such an analytical approach may provide a new tool for the investigation of neural network plasticity in vivo.

Learning-dependent plasticity in the antennal lobe improves discrimination and recognition of odors in the honeybee

Honeybees are extensively used to study olfactory learning and memory processes thanks to their ability to discriminate and remember odors and because of their advantages for optophysiological recordings of the circuits involved in memory and odor perception. There are evidences that the encoding of odors in areas of primary sensory processing is not rigid, but undergoes changes caused by olfactory experience. The biological meaning of these changes is focus of intense discussions. Along this review, we present evidences of plasticity related to different forms of learning and discuss its function in the context of olfactory challenges that honeybees have to solve. So far, results in honeybees are consistent with a model in which changes in early olfactory processing contributes to the ability of an animal to recognize the presence of relevant odors and facilitates the discrimination of odors in a way adjusted to its own experience.

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.

Effect of Interglomerular Inhibitory Networks on Olfactory Bulb Odor Representations

Lateral inhibition is a fundamental feature of circuits that process sensory information. In the mammalian olfactory system, inhibitory interneurons called short axon cells (SACs) comprise the first network mediating lateral inhibition between glomeruli, the functional units of early olfactory coding and processing. The connectivity of this network and its impact on odor representations is not well understood. To explore this question, we constructed a computational model of the interglomerular inhibitory network using detailed characterizations of SAC morphologies taken from mouse olfactory bulb (OB). We then examined how this network transformed glomerular patterns of odorant-evoked sensory input (taken from previously-published datasets) as a function of the selectivity of interglomerular inhibition. We examined three connectivity schemes: selective (each glomerulus connects to few others with heterogeneous strength), nonselective (glomeruli connect to most others with heterogenous strength), or global (glomeruli connect to all others with equal strength). We found that both selective and nonselective interglomerular networks could mediate heterogeneous patterns of inhibition across glomeruli when driven by realistic sensory input patterns, but that global inhibitory networks were unable to produce input-output transformations that matched experimental data and were poor mediators of intensity-dependent gain control. We further found that networks whose interglomerular connectivities were tuned by sensory input profile decorrelated odor representations moreeffectively. These results suggest that, despite their multiglomerular innervation patterns, SACs are capable of mediating odorant-specific patterns of inhibition between glomeruli that could, theoretically, be tuned by experience or evolution to optimize discrimination of particular odorants.SIGNIFICANCE STATEMENT Lateral inhibition is a key feature of circuitry in many sensory systems including vision, audition, and olfaction. We investigate how lateral inhibitory networks mediated by short axon cells (SACs) in the mouse olfactory bulb (OB) might shape odor representations as a function of their interglomerular connectivity. Using a computational model of interglomerular connectivity derived from experimental data, we find that SAC networks, despite their broad innervation patterns, can mediate heterogeneous patterns of inhibition across glomeruli, and that the canonical model of global inhibition does not generate experimentally observed responses to stimuli. In addition, inhibitory connections tuned by input statistics yield enhanced decorrelation of similar input patterns. These results elucidate how the organization of inhibition between neural elements may affect computations.

Comparative study of chemical neuroanatomy of the olfactory neuropil in mouse, honey bee, and human

Despite divergent evolutionary origins, the organization of olfactory systems is remarkably similar across phyla. In both insects and mammals, sensory input from receptor cells is initially processed in synaptically dense regions of neuropil called glomeruli, where neural activity is shaped by local inhibition and centrifugal neuromodulation prior to being sent to higher-order brain areas by projection neurons. Here we review both similarities and several key differences in the neuroanatomy of the olfactory system in honey bees, mice, and humans, using a combination of literature review and new primary data. We have focused on the chemical identity and the innervation patterns of neuromodulatory inputs in the primary olfactory system. Our findings show that serotonergic fibers are similarly distributed across glomeruli in all three species. Octopaminergic/tyraminergic fibers in the honey bee also have a similar distribution, and possibly a similar function, to noradrenergic fibers in the mammalian OBs. However, preliminary evidence suggests that human OB may be relatively less organized than its counterparts in honey bee and mouse.

Differential Processing by Two Olfactory Subsystems in the Honeybee Brain

Among insects, Hymenoptera present a striking olfactory system with a clear neural dichotomy from the periphery to higher order centers, based on two main tracts of second-order (projection) neurons: the medial and lateral antennal lobe tracts (m-ALT and l-ALT). Despite substantial work on this dual pathway, its exact function is yet unclear. Here, we ask how attributes of odor quality and odor quantity are represented in the projection neurons (PNs) of the two pathways. Using in vivo calcium imaging, we compared the responses of m-ALT and l-ALT PNs of the honey bee Apis mellifera to a panel of 16 aliphatic odorants, and to three chosen odorants at eight concentrations. The results show that each pathway conveys differential information about odorants' chemical features or concentration to higher order centers. While the l-ALT primarily conveys information about odorants' chain length, the m-ALT informs about odorants' functional group. Furthermore, each tract can only predict chemical distances or bees' behavioral responses for odorants that differ according to its main feature, chain length or functional group. Generally l-ALT neurons displayed more graded dose-response relationships than m-ALT neurons, with a correspondingly smoother progression of inter-odor distances with increasing concentration. Comparison of these results with previous data recorded at AL input reveals differential processing by local networks within the two pathways. These results support the existence of parallel processing of odorant features in the insect brain.

Olfactory learning without the mushroom bodies: Spiking neural network models of the honeybee lateral antennal lobe tract reveal its capacities in odour memory tasks of varied complexities

The honeybee olfactory system is a well-established model for understanding functional mechanisms of learning and memory. Olfactory stimuli are first processed in the antennal lobe, and then transferred to the mushroom body and lateral horn through dual pathways termed medial and lateral antennal lobe tracts (m-ALT and l-ALT). Recent studies reported that honeybees can perform elemental learning by associating an odour with a reward signal even after lesions in m-ALT or blocking the mushroom bodies. To test the hypothesis that the lateral pathway (l-ALT) is sufficient for elemental learning, we modelled local computation within glomeruli in antennal lobes with axons of projection neurons connecting to a decision neuron (LHN) in the lateral horn. We show that inhibitory spike-timing dependent plasticity (modelling non-associative plasticity by exposure to different stimuli) in the synapses from local neurons to projection neurons decorrelates the projection neurons' outputs. The strength of the decorrelations is regulated by global inhibitory feedback within antennal lobes to the projection neurons. By additionally modelling octopaminergic modification of synaptic plasticity among local neurons in the antennal lobes and projection neurons to LHN connections, the model can discriminate and generalize olfactory stimuli. Although positive patterning can be accounted for by the l-ALT model, negative patterning requires further processing and mushroom body circuits. Thus, our model explains several-but not all-types of associative olfactory learning and generalization by a few neural layers of odour processing in the l-ALT. As an outcome of the combination between non-associative and associative learning, the modelling approach allows us to link changes in structural organization of honeybees' antennal lobes with their behavioural performances over the course of their life.

Different Roles for Honey Bee Mushroom Bodies and Central Complex in Visual Learning of Colored Lights in an Aversive Conditioning Assay

The honey bee is an excellent visual learner, but we know little about how and why it performs so well, or how visual information is learned by the bee brain. Here we examined the different roles of two key integrative regions of the brain in visual learning: the mushroom bodies and the central complex. We tested bees' learning performance in a new assay of color learning that used electric shock as punishment. In this assay a light field was paired with electric shock. The other half of the conditioning chamber was illuminated with light of a different wavelength and not paired with shocks. The unrestrained bee could run away from the light stimulus and thereby associate one wavelength with punishment, and the other with safety. We compared learning performance of bees in which either the central complex or mushroom bodies had been transiently inactivated by microinjection of the reversible anesthetic procaine. Control bees learned to escape the shock-paired light field and to spend more time in the safe light field after a few trials. When ventral lobe neurons of the mushroom bodies were silenced, bees were no longer able to associate one light field with shock. By contrast, silencing of one collar region of the mushroom body calyx did not alter behavior in the learning assay in comparison to control treatment. Bees with silenced central complex neurons did not leave the shock-paired light field in the middle trials of training, even after a few seconds of being shocked. We discussed how mushroom bodies and the central complex both contribute to aversive visual learning with an operant component.

DNA methylation mediates neural processing after odor learning in the honeybee

DNA methyltransferases (Dnmts) - epigenetic writers catalyzing the transfer of methyl-groups to cytosine (DNA methylation) - regulate different aspects of memory formation in many animal species. In honeybees, Dnmt activity is required to adjust the specificity of olfactory reward memories and bees' relearning capability. The physiological relevance of Dnmt-mediated DNA methylation in neural networks, however, remains unknown. Here, we investigated how Dnmt activity impacts neuroplasticity in the bees' primary olfactory center, the antennal lobe (AL) an equivalent of the vertebrate olfactory bulb. The AL is crucial for odor discrimination, an indispensable process in forming specific odor memories. Using pharmacological inhibition, we demonstrate that Dnmt activity influences neural network properties during memory formation in vivo. We show that Dnmt activity promotes fast odor pattern separation in trained bees. Furthermore, Dnmt activity during memory formation increases both the number of responding glomeruli and the response magnitude to a novel odor. These data suggest that Dnmt activity is necessary for a form of homoeostatic network control which might involve inhibitory interneurons in the AL network.

Spatially resolved time-frequency analysis of odour coding in the insect antennal lobe

Antennal lobes constitute the first neurophils in the insect brain involved in coding and processing of olfactory information. With their stereotyped functional and anatomical organization, they provide an accessible model with which to investigate information processing of an external stimulus in a neural network in vivo. Here, by combining functional calcium imaging with time-frequency analysis, we have been able to monitor the oscillatory components of neural activity upon olfactory stimulation. The aim of this study is to investigate the presence of stimulus-induced oscillatory patterns in the honeybee antennal lobe, and to analyse the distribution of those patterns across the antennal lobe glomeruli. Fast two-photon calcium imaging reveals the presence of low-frequency oscillations, the intensity of which is perturbed by an incoming stimulus. Moreover, analysis of the spatial arrangement of this activity indicates that it is not homogeneous throughout the antennal lobe. On the contrary, each glomerulus displays an odorant-specific time-frequency profile, and acts as a functional unit of the oscillatory activity. The presented approach allows simultaneous recording of complex activity patterns across several nodes of the antennal lobe, providing the means to better understand the network dynamics regulating olfactory coding and leading to perception.

Asymmetric neural coding revealed by in vivo calcium imaging in the honey bee brain

Left-right asymmetries are common properties of nervous systems. Although lateralized sensory processing has been well studied, information is lacking about how asymmetries are represented at the level of neural coding. Using in vivo functional imaging, we identified a population-level left-right asymmetry in the honey bee's primary olfactory centre, the antennal lobe (AL). When both antennae were stimulated via a frontal odour source, the inter-odour distances between neural response patterns were higher in the right than in the left AL. Behavioural data correlated with the brain imaging results: bees with only their right antenna were better in discriminating a target odour in a cross-adaptation paradigm. We hypothesize that the differences in neural odour representations in the two brain sides serve to increase coding capacity by parallel processing.

Synaptic clusters function as odor operators in the olfactory bulb

How the olfactory bulb organizes and processes odor inputs through fundamental operations of its microcircuits is largely unknown. To gain new insight we focus on odor-activated synaptic clusters related to individual glomeruli, which we call glomerular units. Using a 3D model of mitral and granule cell interactions supported by experimental findings, combined with a matrix-based representation of glomerular operations, we identify the mechanisms for forming one or more glomerular units in response to a given odor, how and to what extent the glomerular units interfere or interact with each other during learning, their computational role within the olfactory bulb microcircuit, and how their actions can be formalized into a theoretical framework in which the olfactory bulb can be considered to contain "odor operators" unique to each individual. The results provide new and specific theoretical and experimentally testable predictions.

Colocalization of allatotropin and tachykinin-related peptides with classical transmitters in physiologically distinct subtypes of olfactory local interneurons in the cockroach (Periplaneta americana)

In the insect antennal lobe different types of local interneurons mediate complex excitatory and inhibitory interactions between the glomerular pathways to structure the spatiotemporal representation of odors. Mass spectrometric and immunohistochemical studies have shown that in local interneurons classical neurotransmitters are likely to colocalize with a variety of substances that can potentially act as cotransmitters or neuromodulators. In the antennal lobe of the cockroach Periplaneta americana, gamma-aminobutyric acid (GABA) has been identified as the potential inhibitory transmitter of spiking type I local interneurons, whereas acetylcholine is most likely the excitatory transmitter of nonspiking type IIa1 local interneurons. This study used whole-cell patch clamp recordings combined with single-cell labeling and immunohistochemistry to test if the GABAergic type I local interneurons and the cholinergic type IIa1 local interneurons express allatotropin and tachykinin-related neuropeptides (TKRPs). These are two of the most abundant types of peptides in the insect antennal lobe. GABA-like and choline acetyltransferase (ChAT)-like immunoreactivity were used as markers for GABAergic and cholinergic neurons, respectively. About 50% of the GABA-like immunoreactive (-lir) spiking type I local interneurons were allatotropin-lir, and ∼ 40% of these neurons were TKRP-lir. About 20% of nonspiking ChAT-lir type IIa1 local interneurons were TKRP-lir. Our results suggest that in subpopulations of GABAergic and cholinergic local interneurons, allatotropin and TKRPs might act as cotransmitters or neuromodulators. To unequivocally assign neurotransmitters, cotransmitters, and neuromodulators to identified classes of antennal lobe neurons is an important step to deepen our understanding of information processing in the insect olfactory system.

Simultaneous encoding of odors by channels with diverse sensitivity to inhibition

Odorant receptors in the periphery map precisely onto olfactory glomeruli ("coding channels") in the brain. However, the odor tuning of a glomerulus is not strongly correlated with its spatial position. This raises the question of whether lateral inhibition between glomeruli is specific or nonspecific. Here we show that, in the Drosophila brain, focal activation of even a single glomerulus recruits GABAergic interneurons in all glomeruli. Moreover, the relative level of interneuron activity in different glomeruli is largely odor invariant. Although interneurons are recruited nonspecifically, glomeruli differ dramatically in their sensitivity to interneuron activity, and this is explained by their varying sensitivity to GABA. Interestingly, a stimulus is typically encoded in parallel by channels having high and low sensitivity to inhibition. Because lateral inhibition confers both costs and benefits, the brain might rely preferentially on "high" and "low" channels in different behavioral contexts.

Computational models to understand decision making and pattern recognition in the insect brain

Odor stimuli reaching olfactory systems of mammals and insects are characterized by remarkable non-stationary and noisy time series. Their brains have evolved to discriminate subtle changes in odor mixtures and find meaningful variations in complex spatio-temporal patterns. Insects with small brains can effectively solve two computational tasks: identify the presence of an odor type and estimate the concentration levels of the odor. Understanding the learning and decision making processes in the insect brain can not only help us to uncover general principles of information processing in the brain, but it can also provide key insights to artificial chemical sensing. Both olfactory learning and memory are dominantly organized in the Antennal Lobe (AL) and the Mushroom Bodies (MBs). Current computational models yet fail to deliver an integrated picture of the joint computational roles of the AL and MBs. This review intends to provide an integrative overview of the computational literature analyzed in the context of the problem of classification (odor discrimination) and regression (odor concentration estimation), particularly identifying key computational ingredients necessary to solve pattern recognition.

Olfactory coding in the insect brain: data and conjectures

Much progress has been made recently in understanding how olfactory coding works in insect brains. Here, I propose a wiring diagram for the major steps from the first processing network (the antennal lobe) to behavioral readout. I argue that the sequence of lateral inhibition in the antennal lobe, non-linear synapses, threshold-regulating gated spring network, selective lateral inhibitory networks across glomeruli, and feedforward inhibition to the lateral protocerebrum cover most of the experimental results from different research groups and model species. I propose that the main difference between mushroom bodies and the lateral protocerebrum is not about learned vs. innate behavior. Rather, mushroom bodies perform odor identification, whereas the lateral protocerebrum performs odor evaluation (both learned and innate). I discuss the concepts of labeled line and combinatorial coding and postulate that, under restrictive experimental conditions, these networks lead to an apparent existence of 'labeled line' coding for special odors. Modulatory networks are proposed as switches between different evaluating systems in the lateral protocerebrum. A review of experimental data and theoretical conjectures both contribute to this synthesis, creating new hypotheses for future research.

Mixture processing and odor-object segregation in insects

When enjoying the scent of grinded coffee or cut grass, most of us are unaware that these scents consist of up to hundreds of volatile substances. We perceive these odorant mixtures as a unitary scent rather than a combination of multiple odorants. The olfactory system processes odor mixtures into meaningful odor objects to provide animals with information that is relevant in everyday tasks, such as habitat localization, foraging, social communication, reproduction, and orientation. For example, odor objects can be a particular flower species on which a bee feeds or the receptive female moth which attracts males by its specific pheromone blend. Using odor mixtures as cues for odor-driven behavior rather than single odorants allows unambiguous identification of a potentially infinite number of odor objects. When multiple odor objects are present at the same time, they form a temporally complex mixture. In order to segregate this mixture into its meaningful constituents, animals must have evolved odor-object segregation mechanisms which are robust against the interference by background odors. In this review, we describe how insects use information of the olfactory environment to either bind odorants into unitary percepts or to segregate them from each other.

The looks of an odour--visualising neural odour response patterns in real time

BACKGROUND

Calcium imaging in insects reveals the neural response to odours, both at the receptor level on the antenna and in the antennal lobe, the first stage of olfactory information processing in the brain. Changes of intracellular calcium concentration in response to odour presentations can be observed by employing calcium-sensitive, fluorescent dyes. The response pattern across all recorded units is characteristic for the odour.

METHOD

Previously, extraction of odour response patterns from calcium imaging movies was performed offline, after the experiment. We developed software to extract and to visualise odour response patterns in real time. An adaptive algorithm in combination with an implementation for the graphics processing unit enables fast processing of movie streams. Relying on correlations between pixels in the temporal domain, the calcium imaging movie can be segmented into regions that correspond to the neural units.

RESULTS

We applied our software to calcium imaging data recorded from the antennal lobe of the honeybee Apis mellifera and from the antenna of the fruit fly Drosophila melanogaster. Evaluation on reference data showed results comparable to those obtained by previous offline methods while computation time was significantly lower. Demonstrating practical applicability, we employed the software in a real-time experiment, performing segmentation of glomeruli--the functional units of the honeybee antennal lobe--and visualisation of glomerular activity patterns.

CONCLUSIONS

Real-time visualisation of odour response patterns expands the experimental repertoire targeted at understanding information processing in the honeybee antennal lobe. In interactive experiments, glomeruli can be selected for manipulation based on their present or past activity, or based on their anatomical position. Apart from supporting neurobiology, the software allows for utilising the insect antenna as a chemosensor, e.g. to detect or to classify odours.

Glomerular interactions in olfactory processing channels of the antennal lobes

An open question in olfactory coding is the extent of interglomerular connectivity: do olfactory glomeruli and their neurons regulate the odorant responses of neurons innervating other glomeruli? In the olfactory system of the moth Manduca sexta, the response properties of different types of antennal olfactory receptor cells are known. Likewise, a subset of antennal lobe glomeruli has been functionally characterized and the olfactory tuning of their innervating neurons identified. This provides a unique opportunity to determine functional interactions between glomeruli of known input, specifically, (1) glomeruli processing plant odors and (2) glomeruli activated by antennal stimulation with pheromone components of conspecific females. Several studies describe reciprocal inhibitory effects between different types of pheromone-responsive projection neurons suggesting lateral inhibitory interactions between pheromone component-selective glomerular neural circuits. Furthermore, antennal lobe projection neurons that respond to host plant volatiles and innervate single, ordinary glomeruli are inhibited during antennal stimulation with the female's sex pheromone. The studies demonstrate the existence of lateral inhibitory effects in response to behaviorally significant odorant stimuli and irrespective of glomerular location in the antennal lobe. Inhibitory interactions are present within and between olfactory subsystems (pheromonal and non-pheromonal subsystems), potentially to enhance contrast and strengthen odorant discrimination.

Apis mellifera octopamine receptor 1 (AmOA1) expression in antennal lobe networks of the honey bee (Apis mellifera) and fruit fly (Drosophila melanogaster)

Octopamine (OA) underlies reinforcement during appetitive conditioning in the honey bee and fruit fly, acting via different subtypes of receptors. Recently, antibodies raised against a peptide sequence of one honey bee OA receptor, AmOA1, were used to study the distribution of these receptors in the honey bee brain (Sinakevitch et al., 2011). These antibodies also recognize an isoform of the AmOA1 ortholog in the fruit fly (OAMB, mushroom body OA receptor). Here we describe in detail the distribution of AmOA1 receptors in different types of neurons in the honey bee and fruit fly antennal lobes. We integrate this information into a detailed anatomical analysis of olfactory receptor neurons (ORNs), uni- and multi-glomerular projection neurons (uPNs, and mPNs) and local interneurons (LNs) in glomeruli of the antennal lobe. These neurons were revealed by dye injection into the antennal nerve, antennal lobe, medial and lateral antenno-protocerbral tracts (m-APT and l-APT), and lateral protocerebral lobe (LPL) by use of labeled cell lines in the fruit fly or by staining with anti-GABA. We found that ORN receptor terminals and uPNs largely do not show immunostaining for AmOA1. About seventeen GABAergic mPNs leave the antennal lobe through the ml-APT and branch into the LPL. Many, but not all, mPNs show staining for AmOA1. AmOA1 receptors are also in glomeruli on GABAergic processes associated with LNs. The data suggest that in both species one important action of OA in the antennal lobe involves modulation of different types of inhibitory neurons via AmOA1 receptors. We integrated this new information into a model of circuitry within glomeruli of the antennal lobes of these species.

Gain control network conditions in early sensory coding

Gain control is essential for the proper function of any sensory system. However, the precise mechanisms for achieving effective gain control in the brain are unknown. Based on our understanding of the existence and strength of connections in the insect olfactory system, we analyze the conditions that lead to controlled gain in a randomly connected network of excitatory and inhibitory neurons. We consider two scenarios for the variation of input into the system. In the first case, the intensity of the sensory input controls the input currents to a fixed proportion of neurons of the excitatory and inhibitory populations. In the second case, increasing intensity of the sensory stimulus will both, recruit an increasing number of neurons that receive input and change the input current that they receive. Using a mean field approximation for the network activity we derive relationships between the parameters of the network that ensure that the overall level of activity of the excitatory population remains unchanged for increasing intensity of the external stimulation. We find that, first, the main parameters that regulate network gain are the probabilities of connections from the inhibitory population to the excitatory population and of the connections within the inhibitory population. Second, we show that strict gain control is not achievable in a random network in the second case, when the input recruits an increasing number of neurons. Finally, we confirm that the gain control conditions derived from the mean field approximation are valid in simulations of firing rate models and Hodgkin-Huxley conductance based models.

Octopamine modulates activity of neural networks in the honey bee antennal lobe

Neuronal plasticity allows an animal to respond to environmental changes by modulating its response to stimuli. In the honey bee (Apis mellifera), the biogenic amine octopamine plays a crucial role in appetitive odor learning, but little is known about how octopamine affects the brain. We investigated its effect in the antennal lobe, the first olfactory center in the brain, using calcium imaging to record background activity and odor responses before and after octopamine application. We show that octopamine increases background activity in olfactory output neurons, while reducing average calcium levels. Odor responses were modulated both upwards and downwards, with more odor response increases in glomeruli with negative or weak odor responses. Importantly, the octopamine effect was variable across glomeruli, odorants, odorant concentrations and animals, suggesting that the octopaminergic network is shaped by plasticity depending on an individual animal's history and possibly other factors. Using RNA interference, we show that the octopamine receptor AmOA1 (homolog of the Drosophila OAMB receptor) is involved in the octopamine effect. We propose a network model in which octopamine receptors are plastic in their density and located on a subpopulation of inhibitory neurons in a disinhibitory pathway. This would improve odor-coding of behaviorally relevant, previously experienced odors.