Mixture and odorant processing in the olfactory systems of insects: a comparative perspective

Event Abstract Back to Event Can divergent connectivity generate reliable sparse activity patterns? The connectivity in the brain can be highly convergent and highly divergent. In the olfactory system of insects, for example, the connections from olfactory receptor neurons to projection (PNs) and local neurons (LNs) in the antennal lobe, the primary center for olfactory information processing, are highly convergent. The connections from the PNs to the Kenyon cells (KCs) in the secondary center of processing, the mushroom bodies, are, on the other hand, highly divergent. While the role of convergence and its properties in improving signal to noise ratios are if not fully understood at least generally accepted, the role of divergent connectivities is less clear. It has been suggested by us and others that divergence may serve to generate well separated, sparse activity patterns which are known to be beneficial for recognition (classification) and memory formation. In this work we analyze general implications of divergent connectivity in the framework of unspecific (randomly connected) feedforward networks of generic (McCulloch-Pitts) neurons. We find that the distribution for the number of active neurons in the target area is very skewed with large probabilities for no response as well as a fat tail of non-zero probabilities for overwhelming responses of many neurons. The results imply that in the example of the locust olfactory system, divergent connections by themselves, cannot generate the desirable, and experimentally observed, sparse activity patterns if the observed high density of PN-KC connections is correct. This apparent contradiction can be resolved by feedforward gain-control, which may be implemented by the antennal lobe - lateral horn - mushroom body pathway. The remainder of the work is dedicated to elaborating a hypothesis why nature may have chosen a much more costly solution - dense PN-KC connections and feedforward gain control - over a much simpler solution - sparse PN-KC connections. Our results are applicable to many questions in neuroscience as divergent connections are ubiquitous, another prominent example being the connections from the entorhinal cortex to the dentate gyrus in the mammalian hippocampal formation. This work was partially funded by the Biotechnology and Biological Sciences Research Council (grant number BB/F005113/1). Conference: Computational and systems neuroscience 2009, Salt Lake City, UT, United States, 26 Feb - 3 Mar, 2009. Presentation Type: Poster Presentation Topic: Poster Presentations Citation: (2009). Can divergent connectivity generate reliable sparse activity patterns?. Front. Syst. Neurosci. Conference Abstract: Computational and systems neuroscience 2009. doi: 10.3389/conf.neuro.06.2009.03.008 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 29 Jan 2009; Published Online: 29 Jan 2009. Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Google Google Scholar PubMed Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

The neurobiology of insect olfaction: Sensory processing in a comparative context

The mosquito Aedes aegypti is an important vector of diseases including dengue, Zika, chikungunya, and yellow fever. Olfaction is a critical modality for mosquitoes enabling them to locate hosts, sources of nectar, and sites for oviposition. GABA is an essential neurotransmitter in olfactory processing in the insect brain, including the primary olfactory center, the antennal lobe. Previous work with Ae. aegypti has suggested that antennal lobe inhibition via GABA may be involved in the processing of odors. However, little is known about GABA receptor expression in the mosquito brain, or how they may be involved in odor attraction. In this context, generating mutants that target the mosquito’s olfactory responses, and particularly the GABAergic system, is essential to achieve a better understanding of these diverse processes and olfactory coding in these disease vectors. Here we demonstrate the potential of a transgenic line using the QF2 transcription factor, GABA-B1QF2−ECFP, as a new neurogenetic tool to investigate the neural basis of olfaction in Ae. aegypti. Our results show that the gene insertion has a moderate impact on mosquito fitness. Moreover, the line presented here was crossed with a QUAS reporter line expressing the green fluorescent protein and used to determine the location of the metabotropic GABA-B1 receptor expression. We find high receptor expression in the antennal lobes, especially the cell bodies surrounding the antennal lobes. In the mushroom bodies, receptor expression was high in the Kenyon cells, but had low expression in the mushroom body lobes. Behavioral experiments testing the fruit odor attractants showed that the mutants lost their behavioral attraction. Together, these results show that the GABA-B1QF2−ECFP line provides a new tool to characterize GABAergic systems in the mosquito nervous system.

The gaseous neurotransmitters nitric oxide (NO) and carbon monoxide (CO) are prominent and universal components of the array of neurotransmitters found in olfactory information processing systems. These highly mobile communication compounds have effects on both second messenger signaling and directly on ion channel gating in olfactory receptors and central synaptic processing of receptor input. Olfactory systems are notable for the plasticity of their synaptic connections, revealed both in higher-order associative learning mechanisms using odor cues and developmental plasticity operating to maintain function during addition of new olfactory receptors and new central olfactory interneurons. We use the macrosmatic terrestrial mollusk Limax maximus to investigate the role of NO and CO in the dynamics of central odor processing and odor learning. The major central site of odor processing in the Limax CNS is the procerebral (PC) lobe of the cerebral ganglion, which displays oscillatory dynamics of its local field potential and periodic activity waves modulated by odor input. The bursting neurons in the PC lobe are dependent on local NO synthesis for maintenance of bursting activity and wave propagation. New data show that these bursting PC interneurons are also stimulated by carbon monoxide. The synthesizing enzyme for carbon monoxide, heme oxygenase 2, is present in the neuropil of the PC lobe. Since the PC lobe exhibits two forms of synaptic plasticity related to both associative odor learning and continual connection of new receptors and interneurons, the use of multiple gaseous neurotransmitters may be required to enable these multiple forms of synaptic plasticity.

The antennal lobe is the primary olfactory center in the insect brain and represents the anatomical and functional equivalent of the vertebrate olfactory bulb. Olfactory information in the external world is transmitted to the antennal lobe by olfactory sensory neurons (OSNs), which segregate to distinct regions of neuropil called glomeruli according to the specific olfactory receptor they express. Here, OSN axons synapse with both local interneurons (LNs), whose processes can innervate many different glomeruli, and projection neurons (PNs), which convey olfactory information to higher olfactory brain regions. Optical imaging of the activity of OSNs, LNs and PNs in the antennal lobe - traditionally using synthetic calcium indicators (e.g. calcium green, FURA-2) or voltage-sensitive dyes (e.g. RH414) - has long been an important technique to understand how olfactory stimuli are represented as spatial and temporal patterns of glomerular activity in many species of insects. Development of genetically-encoded neural activity reporters, such as the fluorescent calcium indicators G-CaMP and Cameleon, the bioluminescent calcium indicator GFP-aequorin, or a reporter of synaptic transmission, synapto-pHluorin has made the olfactory system of the fruitfly, Drosophila melanogaster, particularly accessible to neurophysiological imaging, complementing its comprehensively-described molecular, electrophysiological and neuroanatomical properties. These reporters can be selectively expressed via binary transcriptional control systems (e.g. GAL4/UAS, LexA/LexAop, Q system) in defined populations of neurons within the olfactory circuitry to dissect with high spatial and temporal resolution how odor-evoked neural activity is represented, modulated and transformed. Here we describe the preparation and analysis methods to measure odor-evoked responses in the Drosophila antennal lobe using G-CaMP. The animal preparation is minimally invasive and can be adapted to imaging using wide-field fluorescence, confocal and two-photon microscopes.

Olfactory system and emotion: Common substrates

Drosophila senses diverse kinds of olfactory stimuli in the external environment. These stimuli are often not pure chemicals, but rather mixtures of many odorants. The fly olfactory system, however, needs to extract the requisite information from this complex stimulus. This is done by converting odor representations into meaningful, discrete categories in the perceptual space. The first olfactory relay system in the Drosophila brain is the antennal lobe (AL) which consists of olfactory sensory neurons (OSNs), projection neurons (PNs) and local interneurons (LNs), and these three populations of neurons interact and process the odor stimuli. To observe any transformations of odor representations in terms of odor classification, linearly varying odor stimuli were presented. This was achieved using binary mixtures such that one odor was "morphed" into another. Three binary mixtures were made from combinations of three distinct odorants ,i.e., 4-methylcyclohexanol (MCH), 3-Octanol (3-Oct) and Pentyl acetate (PA). In the first step, I determined and confirmed that each single odor-evoked distinct odor representations across its different concentrations in the AL, especially in the OSNs. A second requirement was to determine the degree of similarity between the three odors in both OSNs and PNs. From their odor representations, it was found that PA was more similar to 3-Oct compared to MCH in OSNs. Moreover, the similarity between PA and 3-Oct became even stronger in PNs. After determining the prerequisites of using PA, 3-Oct and MCH for binary mixtures, odor-evoked Ca2+ activity patterns for the three different types of binary mixtures were determined in both OSNs and PNs. Each binary odor mixture showed a different kind of odor classification. The MCH/3-Oct binary mixtures showed no odor classification in OSNs, but in PNs two distinct categories were observed. However, the same could not be found in either of the other two odor mixtures. For MCH/PA binary mixtures, no odor classification was found in OSNs. But in PNs, all mixtures having greater than 0% PA got categorized and distinctly separated from the 100% MCH-0% PA. This was referred to as odor dominance of PA. The last odor mixture was of the similar odor pair, 3-Oct/PA, in which all the intermediate mixtures formed one cluster in both OSNs and PNs. This was due to the high degree of similarity already present between the individual odors in OSNs and PNs. The glomeruli in the AL are interconnected by a population of GABAergic LNs and they are known from previous studies to be involved in odor processing. GABA binds to two kinds of receptors: GABAA and GABAB. GABAA receptors are known to be involved in the early phase of the odor processing and they can be pharmacologically blocked by picrotoxin. Therefore, fly brains were subjected to picrotoxin solution and its effects were observed on the three types of odor classification found with the combination of the selected odors. GABAergic inhibition mediated via GABAA receptors was found to be required for the odor classification of binary mixtures of MCH/3-Oct. However, no changes were found due to picrotoxin on MCH/PA and 3-Oct/PA binary mixtures. In conclusion, different kinds of odor classification could be observed for different odors in the AL of the fly. GABAergic inhibition has been found to play a role in mediating odor classification of different stimuli. However, not every odor classification requires GABAergic inhibition, as was observed in the case of MCH/PA binary mixtures, thereby also suggesting an existence of other possible mechanisms for odor classification.

The olfactory system in insects has evolved to process the dynamic changes in the concentration of food odors or sex pheromones to localize the nutrients or conspecific mating partners. Experimental studies have suggested that projection neurons (PNs) in insects encode not only the stimulus intensity but also its rate-of-change (input gradient). In this study, we aim to develop a simple computational model for a PN to understand the mechanism underlying the coding of the rate-of-change information. We show that the spike frequency adaptation is a potential key mechanism for reproducing the phasic response pattern of the PN in Drosophila. We also demonstrate that this adaptation mechanism enables the PN to encode the rate-of-change of the input firing rate. Finally, our model predicts that the PN exhibits the intensity-invariant response for the pulse and ramp odor stimulus. These results suggest that the developed model is useful for investigating the coding principle underlying olfactory information processing in insects.

Odour molecules are recognised by specific receptor proteins associated with the dendritic membranes of olfactory receptor neurons (ORNs; Buck and Axel 1991; Chap. 2). The olfactory signal is then transmitted through ORN axons to the primary processing centre in the CNS: the olfactory bulb (OB) in vertebrates, the olfactory lobe (OL) in crustaceans, the antennal lobe (AL) in insects. In the ALs, the axon terminals of ORNs synapse onto the dendrites of a variety of interneurons associated with the first-order olfactory neuropil (Chap. 4). The AL is thus the level in the insect olfactory system where the molecular information associated with the odour stimulus is first processed, and where the temporal and spatial features of odours can be accentuated or attenuated. Neural processing in this neuropil involves not only excitatory and inhibitory synaptic and intrinsic membrane currents, but may also involve more complex circuit phenomena such as network oscillations, as more fully described in Chap. 6.

Honey bees have a rich repertoire of olfactory learning behaviors, and they therefore are an excellent model to study plasticity in olfactory circuits. Recent behavioral, physiological, and molecular evidence suggested that the antennal lobe, the first relay of the olfactory system in insects and analog to the olfactory bulb in vertebrates, is involved in associative and nonassociative olfactory learning. Here we use calcium imaging to reveal how responses across antennal lobe projection neurons change after association of an input odor with appetitive reinforcement. After appetitive conditioning to 1-hexanol, the representation of an odor mixture containing 1-hexanol becomes more similar to this odor and less similar to the background odor acetophenone. We then apply computational modeling to investigate how changes in synaptic connectivity can account for the observed plasticity. Our study suggests that experience-dependent modulation of inhibitory interactions in the antennal lobe aids perception of salient odor components mixed with behaviorally irrelevant background odors.

Insects have developed highly sophisticated and sensitive olfactory systems to find animal or plant hosts for feeding. Some insects vector pathogens that cause diseases in hundreds of millions of people and destroy billions of dollars of food products every year. There is great interest, therefore, in understanding how the insect olfactory system can be manipulated to reduce their contact with hosts. Here, we review recent advances in our understanding of insect olfactory detection mechanisms, which may serve as a foundation for designing insect control programs based on manipulation of their behaviors by using odorants. Because every insect species has a unique set of olfactory receptors and olfactory-mediated behaviors, we focus primarily on general principles of odor detection that potentially apply to most insects. While these mechanisms have emerged from studies on model systems for study of insect olfaction, such as Drosophila melanogaster, they provide a foundation for discovery of odorants to repel vectorinsects or reduce theirhost-seeking behavior.

Insects have an enormous impact on global public health as disease vectors and as agricultural enablers as well as pests and olfaction is an important sensory input to their behavior. As such it is of great value to understand the interplay of the molecular components of the olfactory system which, in addition to fostering a better understanding of insect neurobiology, may ultimately aid in devising novel intervention strategies to reduce disease transmission or crop damage. Since the first discovery of odorant receptors in vertebrates over a decade ago, much of our view on how the insect olfactory system might work has been derived from observations made in vertebrates and other invertebrates, such as lobsters or nematodes. Together with the advantages of a wide range of genetic tools, the identification of the first insect odorant receptors in Drosophila melanogaster in 1999 paved the way for rapid progress in unraveling the question of how olfactory signal transduction and processing occurs in the fruitfly. This review intends to summarize much of this progress and to point out some areas where advances can be expected in the near future.

Learned Odor Discrimination in Drosophila without Combinatorial Odor Maps in the Antennal Lobe

Characterization and Coding of Behaviorally Significant Odor Mixtures

A multitude of potential neurotransmitters and neuromodulators, including peptides, have been detected in the antennal lobe (AL), the first synaptic relay of the central olfactory pathway in the insect brain. However, the functional role of neuropeptides in this system has yet to be revealed. An important prerequisite to understanding the role of neuropeptides is to match the functionally different cell types in the AL with their peptide profiles by using electrophysiological recordings combined with immunocytochemical studies and/or single-cell mass spectrometry. The olfactory system of Periplaneta americana is particularly well suited to accomplish this goal because several physiologically distinct neuron types can be unequivocally identified. With the aim to analyze the neuropeptide inventory of the P. americana AL, this study is an essential step in this direction. First, we systematically analyzed different parts of the AL by matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry to obtain the complete set of neuropeptides present. Altogether, 56 ion signals could be assigned to products of 10 neuropeptide genes (allatostatins A, B, C, SIFamide, allatotropin, FMRFamide-related peptides [myosuppressin, short neuropeptides F, extended FMRFamides], crustacean cardioactive peptide, tachykinin-related peptides). In a second step, a combination of immunocytochemistry and mass spectrometric profiling of defined AL compartments was used to reveal the spatial distribution of neuropeptide-containing cells. Finally, we demonstrated the feasibility of MALDI-TOF mass spectrometric profiling of single AL neurons, which is an important precondition for combining electrophysiology with peptide profiling at the single-cell level.