Impact Factor 3.394

The world's 3rd most-cited Physiology journal

This article is part of the Research Topic

Coding properties in invertebrate sensory systems

Review ARTICLE

Front. Physiol., 30 June 2016 | https://doi.org/10.3389/fphys.2016.00271

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

  • 1Department of Molecular and Cell Biology and Essig Museum of Entomology, University of California, Berkeley, Berkeley, CA, USA
  • 2Department of Neuroscience, University of Arizona, Tucson, AZ, USA
  • 3Lab. de Estudio de la Biología de Insectos, CICyTTP-CONICET, Diamante, Argentina
  • 4Facultad de Ingeniería, Universidad Nacional de Entre Ríos, Oro Verde, Argentina

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.

Introduction

Humans benefit from insects, mainly as pollinators of crops, but an important number of other insects are pests of crops or damage storage goods, are vectors of serious human and animal diseases, or are simply a nuisance. For centuries, humans have been fighting harmful insects, and the use of synthetic or genetically modified plant-produced chemical insecticides has made this fight much more efficient. However, the use and overuse of those chemicals has led to a number of undesirable consequences, such as contamination of our environment, food and water, and insecticide resistance. In addition, the rising of the organic agriculture movement demands insecticide-free food (van der Goes van Naters and Carlson, 2006).

Chemicals other than insecticides can be used to fight insects through the manipulation of specific olfactory behaviors, profiting from the existence of natural compounds used for communication between organisms, the semiochemicals (Pickett et al., 1997). Pheromones are perhaps the most well-known class of semiochemicals. Pheromones mediate interactions between organisms of the same species, and include, sex, aggregation, and alarm substances, while allelochemicals are semiochemicals that mediate inter-specific interactions (see Dusenbery, 1992; Wyatt, 2003 for further details).

The potential use of semiochemicals to monitor, disrupt, lure, repel, confuse, or mass-trap insect pests was rapidly acknowledged and has fueled much research (Wyatt, 2003; Witzgall et al., 2010) with the promise of clean, safe, and highly specific pest and vector control tools. For instance, mating disruption, in which large amounts of a synthetic sex pheromone are released in a crop, has been used to eradicate insect pests that became resistant to pesticides (Wyatt, 2003; Witzgall et al., 2010). Semiochemicals can also be used for trapping insects in integrated pest and vector control management strategies. Thus, when trapping devices include insecticides, insects attracted to a semiochemical also pick up lethal substances or pathogens (a strategy known as “lure and kill”; Pickett et al., 1997; Wyatt, 2003).

In the last decades, many studies focused on the neural mechanisms underlying behavioral responses to semiochemicals. These investigations aid the design of odor-based strategies for insect control, as they help understanding how the olfactory system processes information about odors and also allow generating predictions about the insect's olfactory behavior (e.g., Hildebrand, 1996; Guerenstein and Hildebrand, 2008). Unfortunately, research in the fields of neuroethology and insect control has been often segregated, which may hamper the development of novel and efficient control tools and strategies. In light of this, here we review our current knowledge about the neural mechanisms controlling olfactory responses to semiochemicals in harmful insects, and also discuss how this neuroethology approach can be used to manipulate insect behavior and therefore improve pest/vector management strategies. We start by briefly summarizing the structure and function of the insect olfactory system.

The Insect Olfactory System

Olfactory receptor cells (ORCs) are the first neural elements in the olfactory pathway and are housed in variable numbers in hair-like, multi-porous structures known as olfactory sensilla. Olfactory sensilla are located mainly on the antennae and in some insects also in the mouthparts. After entering the sensillum through its wall pores, odors diffuse in the aqueous sensillum lymph (sometimes transported by odorant binding proteins, Vogt and Riddiford, 1981; Tsuchihara et al., 2005; Leal, 2013) and reach the dendrites of the ORCs. There, odors interact with different classes of chemoreceptor proteins: odorant receptors (ORs), ionotropic receptors (IRs), or gustatory receptors (GRs; Vosshall et al., 1999; Larsson et al., 2004; Vosshall and Stocker, 2007; Vosshall and Hansson, 2011; Suh et al., 2014). Many ORCs respond to only one or a few related odor compounds, particularly when tested at behaviorally relevant and naturally-occurring concentrations, but others are more broadly tuned (e.g., de Bruyne et al., 1999; Hansson et al., 1999; Stranden et al., 2003; Yao et al., 2005; Hallem and Carlson, 2006; Martelli et al., 2013). In all cases their response spectra depends on the odor tuning of the chemoreceptor protein/s expressed (e.g., Hallem and Carlson, 2006; Andersson et al., 2015). Each type of ORC usually expresses only one type of OR, IR, or GR (e.g., Vosshall et al., 1999; Galizia and Sachse, 2010). However, in some ORCs more than one OR, IR, or GR types, and even different chemoreceptor protein types (most commonly ORs and IRs), are co-expressed, and in those cases odors interact with more than one chemoreceptor protein type (e.g., Fishilevich and Vosshall, 2005; Abuin et al., 2011; Rytz et al., 2013; Hussain et al., 2016; see below).

Odorant receptors are usually expressed in ORCs within single-walled (basiconic or trichoid) sensilla. They are part of a heteromeric complex consisting of an OR-subunit which binds the odor ligand (thus conferring odor specificity) and the highly conserved OR co-receptor (ORCO). Experimental evidence suggests alternative mechanisms of odor activation, one in which OR-ORCO forms a non-selective ligand-activated cation channel, and the other in which ORCO itself functions as a cation channel (Sato et al., 2008; Wicher et al., 2008). Although ORCO orthologs exist in many insect species, to date there is no agreement on how ORCO functions during olfactory transduction in vivo (Stengl and Funk, 2013).

ORCs that respond to compounds such as ammonia, short chain carboxylic acids and amines are housed in double-walled (grooved peg and coeloconic) sensilla (Pappenberger et al., 1996; Diehl et al., 2003; Benton et al., 2009; Hussain et al., 2016) and do not express ORs but instead IRs. The IRs form ionic channels activated by ligands (Benton et al., 2009) and are expressed with one or two broadly expressed co-receptors different from ORCO (Abuin et al., 2011; Ai et al., 2013; Rytz et al., 2013). In addition, the very volatile molecule CO2, which is of primordial importance for the olfactory orientation of blood-sucking insects and some herbivores (Guerenstein and Hildebrand, 2008), is detected by two to three members of the GR family co-expressed in a single ORC type (Suh et al., 2004; Jones et al., 2007; Kwon et al., 2007; Lu et al., 2007; Kent et al., 2008; Wang et al., 2013).

The axons of the ORCs project to the first processing center of olfactory information in the insect brain, the antennal lobe (AL; e.g., Anton and Homberg, 1999). The AL, analogous to the vertebrate olfactory bulb, is composed of distinct spheroid structures called glomeruli (Anton and Homberg, 1999; Fishilevich and Vosshall, 2005). Usually, the terminals of ORCs expressing the same chemoreceptor protein converge onto a single glomerulus (Vosshall et al., 2000; Guerenstein et al., 2004a; Rytz et al., 2013; Suh et al., 2014; Hussain et al., 2016). Each glomerulus also houses neurites of local interneurons (LNs) and of projection neurons (PNs). LNs are restricted to the AL and have dendritic arborizations in several glomeruli; PNs usually arborize in one glomerulus and have an axon that projects to higher brain areas in the protocerebrum such as the lateral horn, the inferior lateral PC, and the calyces of the ipsilateral mushroom body (Homberg et al., 1988, 1989; Jefferis et al., 2007; Galizia and Rössler, 2010; Tanaka et al., 2012; Roussel et al., 2014). Neurons in these higher-order brain centers show diverse responses and integrate information about different odor compounds (e.g., Jefferis et al., 2007; Turner et al., 2008; Gupta and Stopfer, 2012; Lei et al., 2013); neurons receiving input from the mushroom body calyces are involved in mediating learning and memory processes (e.g., Davis, 2004; Fahrbach, 2006; Liu et al., 2012). Further downstream, circuits in the lateral accessory lobe and the ventral protocerebrum have been linked, particularly in moths, to important aspects of olfactory behaviors (e.g., Olberg, 1983; Iwano et al., 2010).

In the next sections we review current knowledge about the neural and behavioral mechanisms underlying responses to diverse classes of pheromones, host odors, and plant volatiles, mechanisms of olfactory repellence, disruption of olfactory behavior, and the effects of experience and learning in olfactory-driven behaviors.

Olfactory Attraction for Monitoring and Trapping

Use of Sex Pheromones

Pheromones are usually mixtures of several compounds. Thus, the development of synthetic pheromone-blend attractants as trap lures involves knowledge of the compound identities, their concentrations, and their relative proportions. In several sympatric moth species, females release sex pheromones of overlapping chemical composition but with species-specific compound ratios, suggesting that males use this information to find conspecific females. For instance, different strains of the European corn borer (Ostrinia nubilalis) are attracted to precise pheromone blend ratios (Klun et al., 1973). Similarly, different species of Yponomeuta moths, which feed on the same host and share the same three pheromone constituents, are reproductively isolated due to differential attraction to species-specific blend ratios (Löfstedt et al., 1991). Similar findings were also reported on aphids (Dewhirst et al., 2010) and plant bugs (Byers et al., 2013). While the importance of ratios is crucial for the design of trap lures, the neural mechanisms underlying this phenomenon just began to be understood (e.g., Martin et al., 2013).

Sex pheromones can be used for monitoring and trapping many insect species. While we review and discuss what is known across different insect species, much is known about the neurobiological bases of mate seeking and finding in the moth Manduca sexta. Knowledge gained through studies in this insect could be applied to other insect-pest species, particularly other moths, as it is likely that similar neural mechanisms underlie mate odor-guided seeking behavior.

In moths and cockroaches, information about the female sex pheromone is processed by a small number of male-specific AL glomeruli forming a distinct structure, the macroglomerular complex (MGC; e.g., Boeckh and Boeckh, 1979; Hildebrand et al., 1980). Although the MGC sub-system of moths is distinctive and particularly large, the synaptic organization and structure of its constituent glomeruli is akin to that of the rest of the AL glomeruli. In some moth species, each MGC glomerulus processes a cognate pheromone component (e.g., Heliothis virescens; Berg et al., 1998), but in other species multiple components are encoded in the same MGC subcompartment (e.g., Spodoptera littoralis; Anton and Hansson, 1995). In other cases, pheromones and plant odorants are processed by the same MGC neurons (e.g., Agrotis ipsilon; Rouyar et al., 2015). Given this complexity, the use of simpler model systems (e.g., see next) can be experimentally advantageous and help the discovery of common, basic principles underlying the processing of complex odor blends.

The MGC of M. sexta has two main glomeruli, the Cumulus and the Toroid, each processing information about one of the two major female sex pheromone blend components (Hansson et al., 1991, 1992; Heinbockel et al., 1999). Because only these two components (out of eight total) are required to elicit odor-induced orientation behaviors in males (Tumlinson et al., 1989), this provides a simple binary system to investigate the neural mechanisms mediating pheromone processing, including blend ratio processing. When males are stimulated with the pheromone blend, two distinct populations of ORCs are specifically activated by those two essential components, one evoking excitatory responses in Cumulus projection neurons (cPNs) and the other in Toroid projection neurons (tPNs; Kaissling et al., 1989; Hansson et al., 1992; Hildebrand, 1996; Heinbockel et al., 1999; Lei et al., 2002). Additionally, recent findings suggest that cPNs and tPNs correlate their synaptic output to signal the presence of the pheromone blend (Lei et al., 2013; Martin et al., 2013). In principle, the odor-evoked spiking activity of cPNs and tPNs could serve to report the chemical identity and concentration of each blend component. However, since their outputs converge in the same regions in the protocerebrum (the delta region of the lateral horn and the mushroom body calyces), the relative timing of input spikes from cPNs and tPNs in postsynaptic neurons may have a physiological effect, that is, coincident spikes would evoke a stronger response in postsynaptic neurons than sequential spikes, allowing the representation of an odor mixture as a single odor object (see also Section Effects of Background Odor).

Indeed, using simultaneous dual-electrode intracellular recordings, Lei et al. (2002) showed inter- and intra-glomerular spike synchrony among PNs in response to pheromone blend stimulation. Odor-induced interglomerular synchrony in the AL was also reported in cockroaches using voltage-sensitive-dye imaging methods, suggesting that the synchrony code operates at a broad spatial scale (Watanabe, 2012). Moreover, experiments that simultaneously recorded neuronal activity across the glomerular array in M. sexta showed that neurons with the most similar odor response profiles produced the highest degree of coincident spikes (Lei et al., 2004). These results support the notion that PNs may use a correlative neural code. In addition, local field potential oscillations in the mushroom bodies, which are thought to reflect evolving ensemble synchrony of PNs across the entire array of AL glomeruli, were reported in many insect species, including locusts, fruit flies, and moths (MacLeod and Laurent, 1996; Ito et al., 2009; Tanaka et al., 2009). Further, it has been shown that spike coincidence in M. sexta AL neurons is modulated by the pheromone blend ratio. Behaviorally, the moths respond best to the mixture of the two essential pheromone components at the naturally occurring 1:2 ratio, and deviations from this ratio deteriorate blend attractiveness (Martin et al., 2013). By stimulating AL neurons with varying blend ratios while simultaneously recording the activity of PN pairs, it was shown that MGC-PNs produce peak correlations at the natural 1:2 blend ratio, and those correlations significantly deteriorate in response to stimulation with behaviorally sub-optimal blend proportions (Martin et al., 2013). Such stimulus-quality-affected correlations in the PN spikes were also reported for glomeruli other than those of the MGC, in experiments that manipulated the ratios of naturally-occurring hostplant blends (Riffell et al., 2009a).

The mechanisms determining spike correlations are unknown, but balanced inhibition may be involved. Upon pheromonal stimulation, both PNs and LNs are activated, with cPNs and tPNs excited by their cognate pheromone constituents and reciprocally inhibited through GABAergic LNs (Lei et al., 2002). LNs likely respond in a dose-dependent manner, allowing the inhibitory effect exerted onto PNs to be modulated by the relative proportion of the blend constituents. Moreover, the degree of spike coincidence between PNs is positively correlated with the strength of the inhibitory input onto those PNs (Lei et al., 2002). Similarly, in the AL of cockroaches, GABAergic LNs also mediate synchronization of PN outputs (Watanabe, 2012). Thus, balanced lateral inhibition is a plausible mechanism by which stimulation with a pheromone blend of optimal ratio can produce the highest degree of correlated spikes in PNs. These ideas are yet to be experimentally confirmed, but have already been explored to some extent in a modeling study (Zavada et al., 2011). Given the diversity of LNs in the AL (Wilson and Laurent, 2005; Seki and Kanzaki, 2008; Reisenman et al., 2011), lateral inhibition may involve particular LN types. Indeed, a recent study on the silkmoth B. mori revealed the existence of both spiking and non-spiking LNs, and showed that non-spiking LNs can inhibit PNs (Tabuchi et al., 2015). Some of these effects may be species-specific, as spiking LNs in the AL of the cockroach Periplaneta americana can inhibit PNs (Warren and Kloppenburg, 2014), while non-spiking LNs (at least those surveyed) do not (Husch et al., 2009).

If the observed spike correlations are meaningful, then the correlated code should be read by postsynaptic neurons. Indeed, although rare, some lateral horn protocerebral neurons, which are known to receive direct input from AL neurons and thought to mostly mediate innate behaviors (e.g., Homberg et al., 1989; Anton and Homberg, 1999; Jefferis et al., 2007; Galizia and Rössler, 2010; Roussel et al., 2014; Kohl et al., 2015), produce the strongest response to the two-component pheromone blend presented at the naturally occurring ratio (Lei et al., 2013). Such correlation hypothesis is also supported by a recent study in Drosophila melanogaster. The odor-evoked spikes of PNs innervating a particular glomerulus (DA1) are highly correlated and provide converging input to their target neurons in the lateral horn (Jeanne and Wilson, 2015). Although the ligand of DA1-PNs is a single pheromone compound (cis-vaccenyl acetate), these experiments demonstrate that synchrony between PNs (arborizing in the same glomerulus in this case) occur, and could be related to coincident detection in post-synaptic neurons (Jeanne and Wilson, 2015). The identity of other Drosophila volatile pheromone compounds, and their processing circuits, were recently reported, although it is not yet known which mixtures are behaviorally significant in this species (Dweck et al., 2015).

In summary, both behavioral and neurobiological data indicate that not just the identity of the sex pheromone constituents, but also the constituents' ratios, are of paramount importance in mediating natural behavior. The neural mechanisms underlying the coding of ratios, particularly at the higher brain level, are still not fully understood. Because responses to sex pheromone mixtures are often species-specific, those mixtures represent an effective way to control specific species, which is much preferable to the use of insecticides as these often affect non-target species.

Use of Other Pheromones

In this section we focus on aggregation and alarm pheromones, since those are the only non-sex pheromone types that have been used to manipulate olfactory behavior. We will briefly review what is known for the major groups of harmful insects.

Aggregation pheromones promote conglomerates of individuals and are ubiquitous among arthropods, including many harmful species of beetles, moths, thrips, triatomines, locusts, mosquitoes, sand flies, and ticks (Wertheim et al., 2005; Sonenshine, 2006; Cook et al., 2007; Lorenzo Figueiras et al., 2009). Often, the decay, fermentation and pathogenesis associated with insect aggregations are the cause of important economic damage to crops and goods (Wertheim et al., 2005; van der Goes van Naters and Carlson, 2006). For instance, all throughout North America pine forests have been succumbing to massive bark beetle infestations that destroyed expanse forests and increase the risks of mudslides and forest fires (Chapman et al., 2012; Raffa et al., 2013). Beetle aggregation pheromones have been used for monitoring and mass-trapping, and also to recruit large number of insects on trap trees that are then destroyed (see Cook et al., 2007 for a review). A recent study used single-sensillum recordings to investigate the odor response profiles of ORCs in both sexes of the brown spruce longhorn beetle Tetropium fuscum. Interestingly, it was found that the responses to aggregation pheromones and plant volatiles are not completely segregated and can be synergized by the presence of volatiles indicative of host stress (MacKay et al., 2015).

While in general aggregation pheromones attract both sexes (Wertheim et al., 2005), in some species gravid females are attracted to a pheromone that induces aggregated oviposition. For instance, females of the sandfly Lutzomia longipalpis, which transmit leshmaniasis, use an oviposition aggregation pheromone which benefits the offspring of unrelated individuals by preventing fungal contamination of larval food (Wertheim et al., 2005). Culex quinquefasciatus gravid females, which are vectors of filariasis and West Nile Virus (among others), are attracted to a pheromone released from maturing eggs in conjunction with an indole compound derived from grass infusions (Mboera et al., 2000; Logan and Birkett, 2007), and these components evoke electrophysiological activity from antennal ORCs (Mordue et al., 1992; Blackwell et al., 1993). In other non-insect arthropods such as ticks, which transmit Lyme disease, fecal components promote arrestment and aggregation, and tarsi contact chemoreceptors respond to some of these components (e.g., guanine) with extremely high sensitivity (Grenacher et al., 2001; Sonenshine, 2006). Such information about the most effective bioactive components can have practical applications for tick control. For instance, aggregation pheromones can be used together with an acaricide that when applied to vegetation or livestock kills ticks upon contact (Sonenshine, 2006).

Alarm pheromones inform or alert a conspecific about impending danger; they are highly volatile, disperse quickly, and do not persist long (see Napper and Pickett, 2008 for a review). They are released by a variety of glands and include compounds belonging to different chemical classes (e.g., terpenes, hydrocarbons, nitrogen compounds). In blood-sucking insects, alarm pheromones could be used as repellents. Bed bugs release alarm pheromones in response to injury and ant attacks, causing conspecifics to disperse (Levinson et al., 1974a). This alarm pheromone is species-specific to a certain extent, and consists of two major components detected by antennal sensilla (Levinson et al., 1974b; Reinhardt and Siva-Jothy, 2007; Olson et al., 2009). When disturbed, adult triatomines release an alarm pheromone mainly composed of isobutyric acid that repels conspecifics (Guerenstein and Guerin, 2004; Manrique et al., 2006; May-Concha et al., 2013; Minoli et al., 2013a,b), which could be used as a triatomine monitoring tool (Minoli et al., 2013b). Isobutyric acid is detected by ORCs in grooved peg sensilla on the triatomine antenna (Guerenstein and Guerin, 2001), likely through the action of an IR (Guidobaldi et al., 2014).

Alarm signals are also conspicuously present in other hemipterans of economic importance such as stink bugs. Heteropteran alarm semiochemicals often have a six-carbon skeleton (e.g., trans-2-hexenal) and have little species specificity (Napper and Pickett, 2008). Insects of economic importance in other orders that produce an alarm pheromone include thrips and aphids. The alarm pheromone of thrips reduces oviposition and causes larvae to fall from plants, and thus could be used to pull insects away from crops (Pickett et al., 1997). When aphids are attacked, they release an alarm pheromone (trans-ß-farnesene; Bowers et al., 1972; Dewhirst et al., 2010; Vandermoten et al., 2012) that causes dispersion of other nearby aphids, including inter-specific responses across subfamilies (Napper and Pickett, 2008). This and other alarm aphid compounds have been used for controlling aphids in both greenhouse and field settings (Pickett et al., 1997; Dewhirst et al., 2010; Vandermoten et al., 2012).

Interestingly, sometimes a semiochemical can function as an alarm or an aggregation pheromone, depending on its concentration. This has been shown for trans-2-hexenal in cockroaches (Napper and Pickett, 2008), and for isobutyric acid in the blood-sucking triatomine bug Rhodnius prolixus (Guerenstein and Guerin, 2004; Manrique et al., 2006; Minoli et al., 2013a). Thus, not only the compound identity needs to be considered in tools for insect control, but also its concentration and behavioral context. While aggregation and alarm pheromones could be used to manipulate the olfactory behavior of harmful insects, we just started to understand how these signals are processed, particularly at the peripheral level. Control strategies can certainly benefit from a deeper understanding of the neural mechanisms controlling these olfactory-driven behaviors.

Use of Host Odors

Many insects that feed or oviposit on a host such as a plant or a vertebrate are pests of crops or transmit human and/or animal diseases. It is well-established that host odors, including CO2, are a key cue for host detection and orientation (van der Goes van Naters and Carlson, 2006; Guerenstein and Hildebrand, 2008; McMeniman et al., 2014; van Breugel and Dickinson, 2014; Reisenman and Riffell, 2015). Much work has been done on the attraction of harmful insects toward natural and synthetic host odors and its neurobiological bases (Guidobaldi et al., 2014 and references therein), information that sometimes has been used to develop odor baits for traps (e.g., Krockel et al., 2006; Ryelandt et al., 2011; Mukabana et al., 2012; Guidobaldi and Guerenstein, 2013). Importantly, manipulation of host-seeking behavior offers many opportunities to disrupt harmful insects. Insects usually respond to specific mixtures of host odorants, even when they include ubiquitous (including non-host) odorants (Bruce and Pickett, 2011). Even when some constituents of those odor mixtures are essential to evoke a behavioral response (e.g., Geier et al., 1996; Guidobaldi and Guerenstein, 2013), in some cases certain components could have redundant roles and therefore, could be removed without decreasing attraction (e.g., Cha et al., 2008). Moreover, key components could be replaced without affecting attractiveness (Tasin et al., 2007). The neurophysiological bases of this phenomenon are not clear, but it is possible that in certain cases key odorants are detected by broadly tuned ORCs (that is, the same ORC could be involved in the detection of several behaviorally redundant key odorants). Thus, studies on the physiological responses of ORCs can have important implications for the design of attractive odor baits. Indeed, ORCs detecting different constituents of a natural odor mixture are sometimes co-localized in the same sensilla (Stensmyr et al., 2003). This, along with the finding that sometimes ORCs within a single sensillum interact (Nikonov and Leal, 2002; Ochieng et al., 2002, Su et al., 2012), makes possible the simultaneous detection and processing of mixture components already at the peripheral level.

As a general rule, odorant identities in the AL are encoded in spatial patterns of glomerular activation (Carlsson et al., 2002; Hansson et al., 2003; Wang et al., 2003; Lei et al., 2004), with some glomeruli narrowly tuned to certain odorants, including hostplant volatiles. For instance, PNs in a specific glomerulus of the M. sexta AL are extremely sensitive and narrowly tuned to the plant volatile cis-3-hexenyl acetate (Reisenman et al., 2005). Moreover, other PNs in a female-specific glomerulus can discriminate, with high sensitivity, the (+) and (−) enantiomers of linalool (Reisenman et al., 2004). PNs in sexually isomorphic glomeruli, in contrast, are equally responsive to both enantiomers of linalool (Reisenman et al., 2004). Interestingly, these neurophysiological findings served to predict behavioral responses that were readily tested. Thus, later studies found that the two enantiomers of linalool respectively mediate oviposition attraction and repellence (Reisenman et al., 2010, 2013), and that these two compounds are equally effective in mediating feeding (Reisenman et al., 2010).

Different features of host odor blends are encoded in glomerular activity patterns. For instance, the encoding of odor mixture identity involves synchronous firing of PNs throughout the activated glomeruli, which may serve to “bind” the components of the odor mixture (Riffell et al., 2009a,b). In addition, stimulation with an odor mixture can evoke a glomerular activation pattern which is different from that evoked by the summation of the activity patterns evoked by each component (see below). The importance of ratios in the detection of host odor mixtures has been shown in different insects (e.g., Najar-Rodriguez et al., 2010; Guidobaldi and Guerenstein, 2016). In oriental fruit moths, for instance, particular ratios within a synthetic plant odor mixture affected oviposition attraction negatively. Corresponding neurophysiological studies found that information about component ratios occurs non-uniformly across AL glomeruli, and that further processing takes place in higher-order brain centers (Najar-Rodriguez et al., 2010).

As mentioned above, insects usually respond to specific host odor mixtures (e.g., Geier et al., 1999a; Barrozo and Lazzari, 2004a; Krockel et al., 2006). For example, triatomines are sensitive to various human compounds (e.g., CO2, lactic acid, ammonia, carboxylic acids; Guerenstein and Lazzari, 2009), and a mixture of ammonia, lactic acid, and pentanoic acid evokes attraction, whereas there is low or no attraction to the single constituents (Guidobaldi and Guerenstein, 2013). Furthermore, in aphids, individual constituents of an otherwise attractive blend can have repellent effects (Webster et al., 2010). Some constituents of host odor mixtures can act synergistically to evoke attraction (e.g., Bosch et al., 2000; Barrozo and Lazzari, 2004a; Smallegange et al., 2005; Piñero et al., 2008; Guidobaldi and Guerenstein, 2013). In females of the oriental fruit moth Cydia molesta, minute amounts of benzonitrile added to an unattractive mixture resulted in a mixture that is as attractive as a natural blend. At the AL level, this bioactive mixture evoked strong activation and synergistic effects in an additional glomerulus not activated by the unattractive mixture (Piñero et al., 2008). Besides synergistic phenomena, additive effects in response to odor mixtures are also found at the central level (e.g., Lei and Vickers, 2008). Therefore, multi-component odor baits will likely be more attractive than single odorants, as they may form specific and reliable “odor objects” (e.g., Späthe et al., 2013, see Section Effects of Background Odor). Interestingly, it has been proposed that just a few (sometimes just three) key components of an odor blend are sufficient for reliable host recognition, even when the insects can detect a higher number of host odorants (Qiu et al., 2007; Riffell et al., 2009a; Guerenstein and Lazzari, 2010; Bruce and Pickett, 2011; Guidobaldi and Guerenstein, 2013).

CO2 is a food and/or oviposition host cue used by some herbivorous and hematophagous insects (Guerenstein and Hildebrand, 2008). Glomerulus-specific CO2 PNs in the AL of M. sexta can follow high frequency CO2 pulses, suggesting that these PNs report information about long-distance CO2 cues (Guerenstein et al., 2004a). This idea is also supported by the finding that nectar-rich flowers emit relatively high levels of CO2 (Guerenstein et al., 2004b). In fact, foraging moths use floral CO2 as a long-distance cue to find those flowers (Thom et al., 2004; Goyret et al., 2008). This and other examples (e.g., van Breugel et al., 2015) again show that neurobiological studies can predict behavior, and ultimately can inspire odor-based control strategies (van der Goes van Naters and Carlson, 2006). The fact that blood-sucking insects are proving difficult to control (Logan and Birkett, 2007), and that they transmit an ever increasing number of diseases to humans and animals, emphasizes that further studies are needed to develop effective tools for insect behavioral manipulation. It should be noted that any odor-based control strategy should consider that different types of natural odor stimuli (including background odors) often interact (e.g., Chaffiol et al., 2012, 2014, see also Section Effects of Background Odor). In addition, it should be considered that the physiological state of the insects (e.g., mating, feeding) as well as learning affects their responses to odors (e.g., Barrozo et al., 2010; Saveer et al., 2012; Reisenman, 2014; Matthews et al., 2016; Section Plasticity in the Responses to Semiochemicals).

Combined Use of Pheromones and Plant Volatiles

When insects detect a mate, their olfactory system is confronted with not only sex pheromones, but also background odors such as plant volatiles. In principle, sex pheromones admixed with green leaf volatiles should be very attractive to phytophagous insects because such mixture may indicate the presence of a calling mate in a proper context. Therefore, at least in certain cases, it would be important to include hostplant volatiles in sex pheromone traps. For instance, in the case of the codling moth Cydia pomonella, addition of plant volatiles [e.g., (E)-β-farnesene] to the sex pheromone (codlemone) significantly increased the proportion of males flying to the pheromone in wind tunnel experiments (Schmera and Guerin, 2012; Trona et al., 2013). In addition, it has been shown that females of the Egyptian cotton leafworm S. littoralis exposed to cotton volatiles start calling earlier than females exposed to non-host volatiles, and that mating pairs exposed to these volatiles start mating earlier. Also, more males reach (or arrive nearby) the pheromone source when hostplants, rather than non-hosts, are present (Binyameen et al., 2013).

Integration of sex pheromone and plant volatile information may occur at the peripheral level. For example, in the noctuid moth Agrotis ipsilon pheromone ORCs can be directly excited by plant volatiles (Rouyar et al., 2015). Moreover, in pheromone-specific ORCs of Helicoverpa zea, stimulations with binary mixtures of sex pheromone and single hostplant odorants [either linalool or (Z)-3-hexenol] produce stronger responses than stimulation with the sex pheromone alone due to interactions between ORCs (Ochieng et al., 2002). Mixtures containing pheromone and plant odorants can also have a suppressive effect. For instance, in S. littoralis, herbivore-induced plant odorants can directly suppress the response of pheromone-specific ORCs (Hatano et al., 2015). Direct suppression has also been observed in Heliothis virescences males upon stimulation of pheromone-specific ORCs with a sex pheromone component and a number of plant volatiles (Pregitzer et al., 2012). Suppressive effects can also be due to interactions between ORCs (Andersson et al., 2010). Interestingly, in woodboring beetles (T. fuscum), some ORCs respond specifically to their aggregation pheromone, although other ORCs specifically respond to the aggregation pheromone combined with at least one plant compound (MacKay et al., 2015).

The olfactory sub-system dealing with the processing of sex pheromone signals has traditionally been considered as a specialized system different from the “main” olfactory sub-system dealing with the processing of host/food odors. This notion was strongly supported by the identification of pheromone-specific ORCs (Bray and Amrein, 2003; Mitsuno et al., 2008; Krieger et al., 2009; Grosse-Wilde et al., 2010; Montagné et al., 2012; Zhang et al., 2015) which in some insect species (particularly within Lepidoptera) project to a small but distinct number of male-specific glomeruli (the aforementioned MGC; Kanzaki and Shibuya, 1983; Christensen and Hildebrand, 1987; Hansson et al., 1992, 1995, 2003; Berg et al., 1998; Rospars and Hildebrand, 2000; Masante-Roca et al., 2002; Sadek et al., 2002; Lei et al., 2004). In spite of this anatomical and often functional separation, it is clear that the two olfactory sub-systems also interact at the AL level. Both suppressive and additive interactions between pheromone and plant odorants have been reported in the MGC of different Lepidoptera species. In some cases, suppressive effects were observed (Chaffiol et al., 2012; Deisig et al., 2012), while in others responses were enhanced (Namiki et al., 2008). The responses of neurons in sexually isomorphic glomeruli can also be affected by the presence of female pheromones in several species, but showed more interspecific variations (Namiki et al., 2008; Chaffiol et al., 2014). Moreover, in C. pomonella, both response enhancement and suppression in response to mixtures of pheromones and plant odors has been observed in sexually dimorphic and isomorphic glomeruli, respectively (Trona et al., 2013). Interactions between the two sub-systems are not necessarily reciprocal or determined by spatial proximity (Namiki et al., 2008; Reisenman et al., 2008; Trona et al., 2013). Furthermore, additive effects for single and pulsed stimulations with mixtures of pheromone and plant odors have been reported (Chaffiol et al., 2014). Because in most cases ORCs that respond to plant odorants do not respond to sex pheromones (and are located in different sensilla), the responses of AL neurons to sex pheromones in sexually isomorphic glomeruli likely result from AL network interactions (Reisenman et al., 2008; Deisig et al., 2012; Chaffiol et al., 2014). The processing of combined signals (i.e., pheromone and non-pheromonal) in higher brain centers is less understood, but it is likely that neurons in these centers further contribute to this interaction.

All these results, both at the peripheral (ORC) and AL level challenge the traditional idea that pheromone and hostplant odor reception and processing are segregated. Thus, these results indicate that olfactory neural circuits are perhaps far more functionally diverse than previously thought. At the same time, these findings highlight the idea that in order to develop efficient tools to manipulate mate-finding behavior it is important to consider the odor context of that signal (e.g., if appropriate for the species, pheromonal baits could also include a host odor).

Visual cues play important roles in modulating the olfactory behavior of insects (e.g., Green, 1986, 1993; Cardé and Gibson, 2010; Willis et al., 2011; Gaudry et al., 2012; McQuate, 2014; van Breugel et al., 2015), and thus, visual cues are often added to odor baits in traps (e.g., Green, 1994). As integration of visual and olfactory stimuli at the CNS has already been documented (e.g., Balkenius et al., 2009), further studies in higher brain centers could help improve the development of multimodal baits. Even when this integration of information is relevant for the manipulation of olfactory behavior, it exceeds the aim of this review, and will not be discussed here.

Effects of Background Odor

Odor mixtures are thought to be represented in the insect brain as single “odor objects,” so that the unique mixture identity prevails over the information about its constituents (Lei and Vickers, 2008; Wilson and Sullivan, 2011; Stierle et al., 2013). When odor baits (usually odor mixtures) are used in the field for insect monitoring and control, they are necessarily presented against an odorous dynamic background (another odor mixture/s). Background odors can either be irrelevant, “mask” the target odor (making it unrecognizable), or can enhance the response to a target odor (Schroeder and Hilker, 2008). In principle, it is conceivable that the bait (target) plus the background odor are perceived as a single mixture, creating a new and emergent “odor object” that can interfere with the identification of the target odor. If that were the case, how do insects orient toward natural odor sources such as hosts, mates, and oviposition sites? In this section we review the importance of background odors in shaping the responses to a target odor bait.

Detecting and discriminating a target odor mixture requires binding its different components (e.g., Deisig et al., 2006; Riffell et al., 2009b), and this “odor object” should be salient even in the presence of background odors. How do nervous systems accomplish this task? In rats, prolonged odor stimulation leads to fast habituation of neurons in the olfactory cortex, so that new odors evoke clear, distinct, responses. As a result, when the two odors are present, the constant odor (background) is filtered while the target odor evokes a neural response, suggesting that animals can separate the target stimulus from its background (Kadohisa and Wilson, 2006; Linster et al., 2007). This idea is also supported by experiments in honeybees, in which odorants presented simultaneously (simulating components of a single odor source) were represented as a single object, while odorants presented with an inter-stimulus delay were represented separately (Szyszka et al., 2012; Stierle et al., 2013). Although interglomerular inhibitory interactions contribute to bind components into a single odor object (e.g., Deisig et al., 2006; Riffell et al., 2009b; Stierle et al., 2013), it has been shown that asynchronous mixtures activate more inhibitory interactions than synchronous mixtures (Stierle et al., 2013). How could this target-background object separation happen in natural odor plumes? Since insect ORCs can have short (<2 ms) response latencies, the thin filaments of target odors that intermingle with those of background odors could be resolved temporally, thus allowing target-background odor segregation (Szyszka et al., 2014).

Convincing and exciting experiments in moths showed that constant odor backgrounds that are chemically different from the target odor do not affect the representation of the target odor, whereas backgrounds that contain a constituent in common with the target odor do (Riffell et al., 2014), a phenomenon akin to the masking effect reported in mosquitoes and other insects (Logan et al., 2008; Schroeder and Hilker, 2008, see Section Odor Masking). Background odors with a constituent in common with the target evoke a change in the balance of excitation and inhibition in AL neurons with respect to the response to the target odor alone, thus altering the representation of the target odor (Riffell et al., 2014). Pre-exposure to this type of background odors produces an exacerbated change in the response to the target odor, resulting from neurons being adapted to the common constituent (Riffell et al., 2014). Stierle et al. (2013, see above) used a different insect species and different experimental conditions, although also tested dissimilar target- background odors presented simultaneously, and arrived to different conclusions (Stierle et al., 2013). These authors found that this mixture is represented as a single distinctive odor object, while Riffell et al. (2014) reported efficient target-background discrimination.

Still, there is an experimental situation that has not been tested yet: similar target- background odors (or target and background with a common blend constituent) presented asynchronously. Because in nature background odor plumes can have a different temporal structure than target odor plumes, insects could exploit these temporal differences to segregate a target odor from its background, even when these have common constituents (Stierle et al., 2013; Szyszka, 2014; Rusch et al., 2016). Experience may also help this segregation, as learning increases the distinction between different scents (Fernandez et al., 2009; Riffell et al., 2013). While in the work described synthetic blends were used, it would be most informative to use complete natural blends as targets since in principle, it should be easier to alter the neural representation of a synthetic mixture consisting of just a few constituents than that of a multi-component natural odor. Somewhat related to this idea, it has been suggested that redundant odor blends reduce uncertainty as they convey more robust information (Wilson et al., 2015).

As mentioned above (Section Combined Use of Pheromones and Plant Volatiles), plant odors could influence the response to pheromones both at the peripheral and the AL levels. Moreover, supression of attraction to the sex pheromone by hervivore-induced plant volatiles has been reported in S. littoralis (Hatano et al., 2015). However, H. virescens males can be effectively attracted to the conspecific female sex pheromone in a constant background of naturally-occurring hostplant odors, including hervivore-induced plant volatiles (Badeke et al., 2016). While these results parallel those reported by Riffell et al. (2014), the attraction of H. virescens to the female pheromone is impaired in a background of high and supra-natural plant odor concentrations (Badeke et al., 2016). These results not only further underlie the importance of using natural, realistic stimuli, but also that additional studies are necessary to fully understand the mechanisms underlying target/background discrimination, as the chemical identity of the odors used, as well as the species under study, could certainly influence the results.

A particular constituent of the volatile background, CO2, also affects the behavior of at least some insects (Guerenstein and Hildebrand, 2008). Information about this odor cue is processed as information about other odors, while the background level of CO2 is simultaneously encoded (Guerenstein et al., 2004a). In hematophagous insects this cue is used to detect and find vertebrate hosts (e.g., Geier et al., 1999b; Barrozo and Lazzari, 2004b), while in moths it is used to detect and find oviposition sites and nectar resources (Stange, 1997; Thom et al., 2004; Goyret et al., 2008). While those CO2 sources evoke clear responses from the CO2 ORCs at natural CO2 background levels, higher CO2 background levels interfere with those responses (Guerenstein and Hildebrand, 2008). In mosquitoes, an elevated CO2 background impedes take-off and source contact by masking the stimulus signal (Majeed et al., 2014). Moreover, the oviposition behavior of Cactoblastis cactorum, a moth particularly sensitive to CO2, is also affected by elevated CO2 backgrounds (Stange, 1997) because ORCs stop firing at such high CO2 levels (Stange et al., 1995). However, the behavior and ORC responses of M. sexta moths are not affected by moderate increases in CO2 background levels, but instead by high-amplitude CO2 oscillations (Abrell et al., 2005). In addition, certain background odorants can modulate the activity of CO2 ORCs (e.g., Guerenstein et al., 2004a) or even evoke a response per se in those receptors (Turner et al., 2011), thus interfering with CO2-mediated behaviors.

In conclusion, the odor background can affect responses to target odors (e.g., Büchel et al., 2014). Thus, for example, efficient odor baits developed in the laboratory could fail to attract insects under field conditions, where different background odors are present. Although more research is needed to understand its role in insect behavior, the odor background should be taken into account when planning an odor-based pest/vector management strategy. In addition, it would be important to investigate the feasibility of techniques to disrupt natural olfactory behavior using masking (see Section Odor Masking) and/or background odorants, as this could improve the methods currently used to disrupt behavior using natural odorants (see Section Disruption of Natural Olfactory Behavior).

Olfactory Repellence

According to Barton-Browne (1977) a repellent is “a chemical that acting in the vapor phase prevents an insect from reaching a target to which it would otherwise be attracted.” A repellent has also been defined as a product causing the insect “to leave the prospective host, with true behavioral repellency involving avoidance of the source of the repellent material, whether placed on the prospective host or near it” (Pickett et al., 2008). While these definitions are based on behavioral effects, the mechanisms of action of repellents are not considered. Repellents are used to stop a pest from finding a valued resource; topical repellents are usually applied onto the skin offering individual protection, while spatial repellents volatilize into the air, creating a vector-free space which provides protection for multiple individuals (Achee et al., 2012). Typically, volatile repellents are used to protect humans from insect (and other arthropod) bites, particularly from arthropods which are vectors of diseases (Foster and Harris, 1997). Repellents have also been used to protect crops: for example, the alarm pheromone of a number of aphids has been used against these pests (Foster and Harris, 1997; Pickett et al., 1997).

For centuries humans have used diverse parts of plants to repel biting insects (Moore and Lenglet, 2004). Among these so-called “botanical repellents,” various species of basil (Ocimum spp.) have been historically used to repel mosquitoes. In addition, oil extract from the leaves of neem (Azadirachta indica) has also been used as a personal mosquito and sandfly repellent (Yarnell and Abascal, 2004). Other botanical insect repellents include the oil from leaves of citronella (Cymbopogon nardus), palmarosa (C. martinii martinii), lemongrass (C. citratus), and Eucaliptus (Eucalyptus spp.). The active components of these botanical repellents are often unknown although citral, a major ingredient in volatiles from lemongrass oil, and p-menthane-3,8-diol, from lemon eucalyptus, have repellent effects on a variety of mosquitoes (Yarnell and Abascal, 2004). Repellents can also be derived from other natural sources such as insects (as in the case of alarm pheromones or defense secretions), or may be purely artificial (Foster and Harris, 1997).

The world's most widely used synthetic topical insect repellent, with broad effectiveness against many insects, is N,N-diethyl-3-methylbenzamide, also known as N,N-diethyl-m-toluamide (DEET; White, 2007; Syed et al., 2011). Other synthetic repellents include Picaridin and IR3535 (or EBAAP, Ethyl Butyl-acetyl-aminopropionate). A full understanding of the mechanism of action of insect repellents and in particular, the identification of their molecular targets, can help design safer and more effective compounds. DEET appears to act both as a contact chemo-repellent that stimulates insect gustatory receptor cells that respond to aversive compounds (Lee et al., 2010), and as a volatile chemo-repellent acting on the olfactory system.

The mode of action of volatile repellents is still under debate and has been comprehensively reviewed recently (Leal, 2014); therefore, here we briefly summarize the most relevant investigations. In D. melanogaster and in the mosquitoes Aedes aegypti and Anopheles gambiae DEET appears to modulate the responses of ORCs to attractive odors (Davis and Sokolove, 1976; Ditzen et al., 2008). This effect depends both on ORCO (Ditzen et al., 2008) and on the molecular identity of the OR in the OR-ORCO complex (Pellegrino et al., 2011). However, for other repellents, it was proposed that DEET acts by just blocking ORCO (Tsitoura et al., 2015). On the other hand, Syed and Leal (2008) suggested that the mosquito C. quinquefasciatus can smell DEET directly and that that stimulation results in avoidance even in the absence of other odor cues. Similar results were reported in triatomines, suggesting a common mode of action for the repellent action of DEET (Zermoglio et al., 2015). Moreover, other additional findings further support the hypothesis that insects can smell DEET: (1) the existence of an ORC in D. melanogaster which is sensitive to DEET, picaridin and IR3535 (Syed et al., 2011) and, (2) electroantennogram (EAG) and single sensillum responses to DEET in A. aegypti (Stanczyk et al., 2010, 2013).

In an attempt to clarify some of these apparently contradictory results, Bohbot and Dickens (2010) characterized the effects of a number of repellents [DEET, 2-undecanone (2-U), IR3535 and Picaridin] on two OR-ORCO heteromers of A. aegypti individually expressed in Xenopus oocytes. Their results suggest that different mechanisms mediate the action of different repellents. That is, repellents could be smelled directly (acting as receptor agonists) or could inhibit the responses to odors (acting as receptor antagonists; Bohbot and Dickens, 2010).

It is now well established that insects can smell DEET (Leal, 2014). Studies in mosquitos suggest that ORCO and the OR pathway are necessary for the repellent effects of DEET as: (1) wild-type A. aegypti avoid DEET whereas ORCO mutants do not (DeGennaro et al., 2013) and, (2) in C. quinquefasciatus, different repellents activate a particular OR (CquiOR136) in a dose-dependent manner, whereas knockdown of this OR resulted in loss of EAG and behavioral responses to DEET (Xu et al., 2014). These results suggest that an OR is involved in the direct detection of DEET (Xu et al., 2014). As the natural plant repellent methyl jasmonate elicits responses in ORCs expressing CquiOR136, it has been proposed that this OR is tuned to natural repellents with long insect–plant evolutionary histories (Xu et al., 2014).

In summary, different hypotheses have been suggested to explain the mechanisms involved in the olfactory repellency of DEET in blood-sucking insects. They include: (1) DEET may silence ORs responsive to attractive odors, a hypothesis that has now little support; (2) DEET is detected by one or a few ORs; (3) DEET may act as a “confusant” by modulating the activity of many ORs. Although it is possible that more than one of these mechanisms act simultaneously, it is likely that they are species-specific. Because all these proposed mechanisms involve ORs, these are relevant candidate molecular targets for the development of new repellents (Leal, 2014). Thus, based on knowledge on the molecular receptors, more efficient and safer volatile mosquito repellents could be developed. The need to develop new repellents is emphasized by the finding that some populations of A. aegypti are insensitive to DEET (Stanczyk et al., 2010). Besides the repellent effects of DEET discussed above, application of DEET on human skin results in an altered host odor chemical profile due to a fixative effect of DEET, and that effect could also contribute to repellency (Syed and Leal, 2008; Section Odor Masking). Finally, certain constituents of non-host odors can act as arthropod repellents (e.g., interaction between cattle flies and heifers: Birkett et al., 2004; interaction between fruit flies and fruit: Linn et al., 2005; interaction between ticks and dogs: Borges et al., 2015), providing opportunities for the development of natural, safer repellents. It should be noted that the response to an attractive host odor blend can be manipulated by adding non-host odorants (e.g., Linn et al., 2005), and also by altering the proportions of one or more host odorants (Section Odor Masking), causing either repellency (avoidance), or masking (loss of attraction; Section Odor Masking).

Disruption of Natural Olfactory Behavior

Mating Disruption

The most common behavior that has been disrupted using semiochemicals is mating. This strategy has been used to eradicate insects that became resistant to pesticides, including pests of apples, peaches, cotton, and grapes (see Wyatt, 2003; Witzgall et al., 2010). The basic idea of mating disruption involves the broadcasting of a chemical signal similar to the sex pheromones of the target species. The first registration of a mating disruption product in the USA was for the pink bollworm (Brooks et al., 1979); currently there are more than 120 disruption products registered in the US. Mating disruption usually involves the release of large amounts of species-specific synthetic sex pheromones (e.g., Witzgall et al., 2010); these high concentrations often “overload” the insects' sensory system, interfering with the detection of the usually lower amounts of pheromone released by mating partners (Cardé, 1990, see below). Besides this traditional approach (see below), new techniques and approaches are being developed to improve efficacy. A new design, which is literally an auto-confusion disruption method, involves the application of electrostatically charged wax powder (dubbed Entostat) onto the cuticle of male moths. Because the powder can be loaded with large quantities of female sex pheromone, male moths function as mobile dispensers. Indeed, Entostat-exposed codling moth males remained as attractive as a 0.1-mg pheromone lure for up to 24 h in laboratory experiments (Huang et al., 2010). The behavior of male moths that are normally attracted to natural sources of pheromone was completely disrupted after treatment with Entostat powder. Moreover, the males' ability to orientate to the pheromone lure remained significantly impaired 6 days post-application, arguing that Entostat augments the effect of sensory (peripheral) adaptation and CNS habituation (Huang et al., 2010).

According to Miller and Gut (2015), mating disruption methods can be broadly divided into two categories, i.e., non-competitive and competitive. Non-competitive methods involve interference with the sensory capabilities of males or females, or hampering pheromone emission, and examples include mating/calling suppression, camouflage, sensory imbalance, and desensitization. Competitive methods do not involve changes on the insects' sensory capabilities or on pheromone emission and, therefore, insects can respond equally well to other insects and trap lures. Thus, several mechanisms can mediate pheromonal mating disruption, including loss of sensitivity in ORCs (sensory adaptation), loss of sensitivity at the CNS level (habituation), camouflaging of the female's odor trail, competition between dispensers and natural pheromone, and unbalanced components in the synthetic pheromone (Cardé, 1990). We next discuss sensory adaptation and habituation.

Stimulation with high concentrations of pheromones generally reduce the response sensitivity of pheromone ORCs (i.e., ORCs adapt to the stimulus), a phenomenon which can be quantified using EAG. For instance, in male oriental fruit moths, the EAG amplitude decreased as animals approached high emission-rate sources, and this reduction was correlated with upwind flight cessation (Baker and Haynes, 1989). In another moth species, long-lasting EAG adaptation after pheromone pre-exposure occurred over a range of pheromone dosages and lasted more than 10 min (Stelinski et al., 2005). There appear to be significant species-specific variations in the capability of the olfactory system to adapt to pheromones. For instance, Grapholita molesta moths have a three-fold greater level of sensory adaptation after pre-exposure than Choristoneura rosaceana (Trimble and Marshall, 2010), a finding which may explain why G. molesta is readily more controllable using mating disruption than C. rosaceana. The mechanisms underlying sensory adaptation were investigated in the moth M. sexta. After presentation of an adapting pheromone stimuli, and in response to the pheromone test stimulus, type I trichoid sensilla produced sensillar potentials of lower amplitude than those from non-adapted sensilla, while the pheromone ORC spike frequency of adapted sensilla was concomitantly lower (Dolzer et al., 2003). Furthermore, pheromone stimuli lasting several seconds strongly activated protein kinase C in pheromone ORCs, while minute-long stimuli elevated cGMP concentrations. These results indicate the existence of distinct intracellular signaling mechanisms mediating short-term and long-term adaptation (Dolzer et al., 2008).

In order to produce habituation in AL neurons and, therefore, disrupt behavior, unnaturally high stimulus concentrations and/or frequencies can be used. In AL PNs, pheromone stimulation typically produces a burst of action potentials followed by an after-hyperpolarization (AHP) inhibitory phase (Christensen and Hildebrand, 1988; Lei et al., 2009). The AHP is critical to enable PNs to resolve intermittent stimuli, which is a universal feature of natural odor plumes (Murlis et al., 1992; Lei et al., 2009). Within a certain range of stimulus frequencies, PNs respond with a burst of action potentials (followed by a short AHP) to each odor pulse, faithfully reporting the temporal structure of the stimulus train. However, when the pulsing rate exceeds the response range of PNs (>10 Hz), neurons can only respond with a single burst of action potentials followed by a prolonged AHP (Christensen and Hildebrand, 1988; Lei and Hansson, 1999; Heinbockel et al., 2004). In addition, the excitatory and inhibitory phases can be both habituated by high stimulus concentrations. Increasing stimulus concentrations decreases the delay to the onset of the excitatory phase and increases firing rate eventually reaching saturation (Heinbockel et al., 2004; Fujiwara et al., 2009), while also decreases the delay to the onset of the inhibitory phase and increases its duration. In the upper range of concentrations, PNs only produce a brief (high-rate) burst that is followed by a lengthy AHP, which is similar to the habituating pattern evoked by high frequency stimuli. Thus, under sustained stimulation and high concentrations, PNs show responses which are not likely linked to natural behaviors. Because PNs also receive input from LNs, these may also contribute to PN habituation, as observed in D. melanogaster (Seki et al., 2010). Because many LNs are GABAergic and can therefore inhibit PNs (Hoskins et al., 1986; Christensen et al., 1993; Wilson and Laurent, 2005; Seki and Kanzaki, 2008), LN habituation would produce sustained PN disinhibition, potentially interfering with triggering natural behavior. Although the roles of LNs are still being investigated, it is thought that they may render the response of some PNs concentration-independent (e.g., Asahina et al., 2009; Olsen et al., 2010). In summary, investigations on sensory adaptation and habituation can be helpful to find the most effective chemicals that can be used to disrupt mating.

Odor Masking

As mentioned above (Sections Use of Sex Pheromones and Use of Host Odors), not just the identity of the constituents of an odor mixture but also their proportions (ratios) are important for attraction. For instance, humans are differentially attractive to mosquitoes and this could be due to individual host odor mixture variability (Logan et al., 2008 and references therein). In some cases low attractiveness has been linked to low levels of some odors. For example, in A. aegypti, addition of lactic acid to the skin of formerly unattractive humans can increase their attractiveness (Steib et al., 2001). Low or no-attractiveness to a natural host odor blend could also result from higher-than-normal concentrations of a natural constituent of the attractive blend (e.g., Birkett et al., 2004; Logan et al., 2008, 2009), a phenomenon attributed to blend repellency or masking (see also Section Effects of Background Odor).

Comparisons of the odor profiles of individuals with different attractiveness revealed that a few compounds are present in higher relative amounts in less-attractive individuals, including 6-methyl-5-hepten-2-one (Logan et al., 2008, 2009). When low and naturally occurring doses of this odor were added to naturally attractive human odor, upwind flight and probing were reduced. Although a repellent-blend effect can occur (Logan et al., 2009), a small increase in the amount (ratio) of a particular compound within the natural host odor mixture could also produce masking of the target odor so that the host is no longer recognized as such (Logan et al., 2008; see also Bruce and Pickett, 2011 for examples in phytophagous insects).

Many semiochemicals can be used in conjunction with other chemical tools in “push-pull” strategies. These strategies divert insects away from a valuable resource (the “push” away from, for example, a host) into an attractant (the “pull” component; Pickett et al., 1997; Cook et al., 2007). Masking odors could be used in push-pull control strategies to prevent host location (“pushing” insects away from the hosts) while at the same time, attractive odors could be used as baits in traps to “pull” the insects away from hosts (Cook et al., 2007; Logan et al., 2008). Neuroethology approaches could readily speed up the discovery of effective masking odors for use in control strategies. For instance, one strategy could be to test the degree of odor-object transformation in the AL (i.e., the change in the spatio-temporal response pattern of an ensemble of AL neurons) that is evoked by altered ratios of different compounds within the natural host odor mixture.

Carbon dioxide is an important odor that mediates the behavior of many harmful insects (Guerenstein and Hildebrand, 2008). Therefore, manipulation of the odors that modulate the response of the CO2 receptors (Section Effects of Background Odor; Turner et al., 2011), including inhibitory odorants that can mask human scent (Tauxe et al., 2013), can profoundly impact CO2-mediated behaviors. Moreover, large CO2 fluctuations can “confuse” the insect's detection of natural CO2 sources (Abrell et al., 2005 and references therein), which may be used for interfering with the behavior of CO2-sensing insects.

Odor Antagonism

As in many lepidopterans, Heliothine females release a sex pheromone that attracts conspecific males. However, certain compounds of the somewhat similar sex pheromone of a sympatric Heliothine species make the former blend unattractive. Indeed, the addition of such interspecific compounds to a species' sex pheromone blend can eliminate attraction in conspecific males, thus acting as antagonists (Vickers and Baker, 1997). In the AL of both H. virescens and H. zea the two essential components of their species-specific pheromone blends are represented in two separate MGC glomeruli. Odorants that antagonize attraction, when added to the respective pheromonal blends, evoked excitatory activity in PNs restricted to a third MGC glomerulus in both species (Vickers et al., 1998). Therefore, attractive and antagonist odor blends are represented in distinct combinations of MGC glomeruli, thus providing a combinatorial code for sex pheromone discrimination in sympatric species.

While approaching a female, male moths also emit volatile chemicals through specialized male structures such as the hairpencils (Birch et al., 1990). It has been shown that H. virescens hairpencil volatiles have both aphrodisiac and repellent effects on conspecific females and males, respectively. Interestingly, the male ORCs that respond to a conspecific hairpencil compound also respond to an interspecific sex pheromone antagonist (Hillier et al., 2006). Antagonist compounds (including both interspecific sex pheromone and conspecific hairpencil volatiles) are certainly amongst the important chemicals that can be used to manipulate harmful-insect behavior.

Plasticity in the Responses to Semiochemicals

Behavioral plasticity (including associative and non-associative learning) affects chemosensory-guided behaviors in all insects. For simplicity, we define learning as a permanent change in behavior resulting from experience (Papaj, 2009). Associative learning involves pairing of two stimuli in a way that the response to one of the stimulus is altered as a consequence of the pairing, which is typically evaluated in classical/Pavlovian or operant/instrumental paradigms. For instance, a well-studied case of classical learning involves the pairing of an appetitive stimulus (e.g., sugar) that elicits a reflexive response (e.g., extension of the proboscis) with an odor; when an association between the two stimuli is formed, the sole presentation of the odor stimulus elicits proboscis extension (Bitterman et al., 1983). Behavioral habituation, a form of non-associative learning, reduces responsiveness to stable and repetitive stimuli, which can be important for detecting predators, food, and/or mate odors in an irrelevant and/or even complex olfactory background (Kadohisa and Wilson, 2006; Linster et al., 2007; Riffell et al., 2014; see also Section Effects of Background Odor). Behavioral sensitization is also a form of non-associative learning in which repeated presentation of a stimulus can result in amplification of responses to that and/or a related stimulus (Papaj, 2009).

Learning has profound effects on the chemosensory behavior of insects, including harmful ones. This is true even in the case of innate signals of prime biological relevance, such as sex pheromones. In moths, the action of sex pheromones depends on factors such as the presence of host-odors, sexual maturity, and mating status (Barrozo et al., 2011; Chaffiol et al., 2012, 2014; Guerrieri et al., 2012). Furthermore, moths can be trained to associate food with a sex pheromone (Hartlieb et al., 1999; Hartlieb and Hansson, 1999). In other cases, recognition of pheromones necessarily involves learning. In social insects, kin and nest-mate pheromones are learned by young larvae inside the nest, and maggot flies need to experience their own host-marking pheromone before they can discriminate between an occupied and an unoccupied fruit in which to lay eggs (Roitberg and Prokopy, 1981). Furthermore, in phytophagous insects, this kind of olfactory learning can promote the transition to new hosts of agricultural importance (Prokopy and Papaj, 1988; Papaj and Prokopy, 1989).

The way in which plasticity affects many different behaviors in herbivorous insects has been recently reviewed (see Anderson and Anton, 2014). In herbivorous insects, both larval feeding and adult experience can affect olfactory-guided oviposition, mate choice, and feeding (Riffell et al., 2008; Thöming et al., 2013; Anderson and Anton, 2014; Carrasco et al., 2015). In moths, plant volatiles can enhance male orientation toward the conspecific female sex pheromone (Chaffiol et al., 2012, 2014; Guerrieri et al., 2012). The learning abilities of pest insects should be particularly considered in control strategies. For instance, a “trap crop” (which always represents a small proportion of the cropping area) might be completely inefficient if insects first find the profitable crop and prefer this over the trap crop (Cook et al., 2007). Thus, the selection of the most effective crop border plants is crucial, and this can be achieved by screening plant cultivars coupled with identification of behaviorally and electrophysiological bioactive volatiles (Schröder et al., 2015). Other cognitive processes, such as habituation, have important implications in the management of pest insects (Section Mating Disruption). In diamondback moths, exposure to non-hosts can increase oviposition preference toward these plants, perhaps leading to host range expansion (Zhang and Liu, 2006).

In the case of insects vectors of human and animal diseases, learning and previous experience can have important epidemiological implications for disease transmission (McCall and Kelly, 2002). For instance, mosquito host choice is influenced by prior foraging experience, which causes them to return to less-defensive hosts and to hosts where feeding was more successful (McCall and Kelly, 2002; Lyimo and Ferguson, 2009). Not only that, but variation in the physical and chemical properties of blood can influence fitness and cause host feeding preferences (see Lyimo and Ferguson, 2009 for details). Thus, it has been suggested that pathogen transmission can be reduced by altering host choice (Lyimo and Ferguson, 2009). Also, mosquitoes tend to return to the same villages, houses, host species, and oviposition sites (McCall and Kelly, 2002). Then, it is not surprising that research in this area has expanded in the last couple of years, and it is now clear that blood-sucking insects can indeed learn and form new memories (Kaur et al., 2003; Jhumur et al., 2006; Tomberlin et al., 2006; Bouyer et al., 2007; Sanford and Tomberlin, 2011; Vinauger et al., 2011a,b, 2013, 2014; Chilaka et al., 2012; Sanford et al., 2013). Classical and operant paradigms showed that blood-sucking insects can associate stimuli of different modality (thermal, odor, gustatory, visual) while searching for a host and selecting oviposition sites. In A. aegypti, the association between odorants and a thermal appetitive stimulus is odor-dependent (e.g., certain odors can be readily learned, others are untrainable, etc). Furthermore, associative learning can modify the aversive deterrent effect of DEET in both kissing bugs and mosquitoes (Stanczyk et al., 2013; Vinauger et al., 2014). Learning processes also affect the responses to odors which are crucial for survival (e.g., pheromones). In triatomine bugs, a brief exposure to the alarm pheromone produces sensitization and increases the tendency to respond, while long-term pre-exposure elicits behavioral habituation (Minoli et al., 2013a). In blood sucking insects, however, our knowledge on the neural mechanisms underlying the effects of experience on chemosensory responses is mostly restricted to the periphery, as we discuss below.

In both blood-sucking and herbivorous insects the activity of ORCs can be affected by experience (e.g., long-term odor exposure and sensory adaptation to deterrents; see Section Mating Disruption). Experience can also cause downregulation of olfactory responses according to the feeding/mating status, and the time of the day (e.g., Almaas et al., 1991; Fox et al., 2001; Takken et al., 2001; Glendinning et al., 2009; Saveer et al., 2012; Stanczyk et al., 2013; Anderson and Anton, 2014; Claudianos et al., 2014; Reisenman, 2014). In general, associative learning is not usually represented at this level, although recent work in honeybees revealed that olfactory memories downregulate the expression of specific ORs. Furthermore, these changes occurred after conditioning and concomitantly, the population activity of antennal ORCs (measured as changes in EAG responses) decreased after learning (Claudianos et al., 2014). In mosquitoes, a reduction in the EAG responses to DEET correlates well with a post-exposure reduction in behavioral sensitivity to this repellent (Stanczyk et al., 2013).

The mushroom bodies mediate behaviors affected by learning and experience (e.g., Fahrbach et al., 1998; Zars et al., 2000; Huetteroth et al., 2015). However, in fruit flies and honeybees, learning already produces changes in glomerular volume and in synaptic distribution and density (e.g., Winnington et al., 1996; Devaud et al., 2001; Brown et al., 2002; Sachse et al., 2007; Arenas et al., 2012), and can modify neural representations at the AL level (e.g., Faber et al., 1999; Chen et al., 2015), including glomerulus-specific neural plasticity (Rath et al., 2011). In moths, pre-exposure to the conspecific female sex pheromone increases the response of male PNs (Anderson et al., 2007), and associative learning with an appetitive cue causes recruitment of additional responsive neurons (Daly et al., 2001, 2004). Furthermore, learning of the scent of flowers which are profitable but are not innately preferred increases activity in AL neurons (Riffell, 2012; Riffell et al., 2013), and serotonin and octopamine are both involved in this process (Dacks et al., 2008, 2012). Experience might also have important effects facilitating segregation between a target odor and its odor background (see Section Effects of Background Odor), by modifying the balance of excitation and inhibition in AL neurons (Riffell et al., 2014; Szyszka, 2014; Chen et al., 2015). Noctuid moths switch their olfactory preference from food odors to egg-laying (e.g., cotton) odors following mating, and calcium imaging experiments demonstrated that this switch is due to changes in the representation of these odors across the AL glomerular array (Saveer et al., 2012). The mechanisms involving AL plasticity include modulation of the activity of ORCs by inhibitory interneurons (Ignell et al., 2009; Chou et al., 2010; Root et al., 2011), and neuromodulation by biogenic amines, neuropeptides and hormones (Nässel and Homberg, 2006; Dacks et al., 2008; Saveer et al., 2012).

In summary, experience and learning readily affect the odor oriented behavior of harmful insects through many neurophysiological mechanisms, which need to be considered in control strategies that include baits, repellents, use of trap crops, etc. Neurophysiological studies could help discover the most effective control methods; e.g., through high through-output screening of potential repellents that do not cause adaptation in ORCs.

Conclusions

Odor sources are widely used to manipulate the behavior of harmful insects. In recent decades, the neurobiological bases underlying insect olfactory behavior started to be unraveled. The insect olfactory system is able to encode the quality, quantity, and temporal features of the odor stimuli. Information about odor mixtures is also encoded, including the ratio between their components and discrimination in complex backgrounds. Moreover, responses to odors are modulated by the animal's internal and external state, and by experience and learning. Natural odors are usually odor mixtures (against a “noisy” background), and are represented as particular odor objects in the AL. Those odor objects signify relevant odor sources such as a host or a conspecific that, at least in some cases, could be “mimicked” in a simplified way using synthetic compounds, e.g., a male moth can be lured into a trap using synthetic versions containing few sex pheromone constituents. This facilitates the development of relatively simple and long-lasting odor baits to manipulate insect behavior. The simplified and optimal imitation of a natural odor mixture is challenging because it requires using only key mixture constituents, and this sometimes includes minor components within the natural mixture. Insect behavior can also be manipulated using repellents or “confusants.” The studies mentioned in this work and others are helping us to understand how the olfactory system processes information about odors, making possible to design very efficient odor baits, repellents, or ways to confound the insects. Moreover, those studies also generate predictions about natural olfactory behavior that are useful to devise odor-based strategies for insect control. Clearly, the fields of neuroethology and insect control could certainly benefit from reciprocal interactions, which need to be fostered by all partners involved, including funding agencies. Encouraging new steps are being taken in this direction such as a recent initiative between different agencies on the beneficial and antagonistic interactions between plants (including agricultural plants) and their pathogens (including insects). We hope that the information provided in this review will help find gaps in the knowledge about the neural bases of olfactory behavior that are worth filling, encourage related studies, and promote the application of existing information in the development of better methods to manipulate insect behavior for control purposes.

Author Contributions

PG contributed the general idea, wrote several sections, corrected the whole manuscript, and prepared the final version. CR wrote several sections, made several general suggestions, corrected the whole manuscript, and prepared the final version. HL wrote several sections, made general suggestions, and corrected the whole manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

HL was supported by an award from NSF (DMS 2100004). PG thanks Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT), Argentina, for funding during part of this project through grant PICT-PRH-2009-43. We thank Dr. John Hildebrand (University of Arizona) for continuous inspiration, support, advice and encouragement throughout the years. CR also thanks Dr. Kristin Scott (UC Berkeley) for support and encouragement. We sincerely thank the reviewers for their many insightful comments and suggestions that substantially improved this manuscript.

References

Abrell, L., Guerenstein, P. G., Mechaber, W. L., Stange, G., Christensen, T. A., and Nakanishi, K. (2005). Effect of elevated atmospheric CO2 on oviposition behavior in Manduca sexta moths. Global Change Biol. 11, 1272–1282. doi: 10.1111/j.1365-2486.2005.00989.x

CrossRef Full Text | Google Scholar

Abuin, L., Bargeton, B., Ulbrich, M. H., Isacoff, E. Y., Kellenberger, S., and Benton, R. (2011). Functional architecture of olfactory ionotropic glutamate receptors. Neuron 69, 44–60. doi: 10.1016/j.neuron.2010.11.042

PubMed Abstract | CrossRef Full Text | Google Scholar

Achee, N. L., Bangs, M. J., Farlow, R., Killeen, G. F., Lindsay, S., Logan, J. G., et al. (2012). Spatial repellents: from discovery and development to evidence-based validation. Malaria J. 11:164. doi: 10.1186/1475-2875-11-164

PubMed Abstract | CrossRef Full Text | Google Scholar

Ai, M., Blais, S., Park, J.-Y., Min, S., Neubert, T. A., and Suh, G. S. B. (2013). Ionotropic glutamate receptors IR64a and IR8a form a functional odorant receptor complex in vivo in Drosophila. J. Neurosci. 33, 10741–10749. doi: 10.1523/JNEUROSCI.5419-12.2013

PubMed Abstract | CrossRef Full Text | Google Scholar

Almaas, T. J., Christensen, T. A., and Mustaparta, H. (1991). Chemical communication in heliothine moths. I. Antennal receptor neurons encode several features of intra-and interspecific odorants in the male corn earworm moth Helicoverpa zea. J. Comp. Physiol. A 169, 249–258.

Google Scholar

Anderson, P., and Anton, S. (2014). Experience-based modulation of behavioural responses to plant volatiles and other sensory cues in insect herbivores. Plant Cell Environ. 37, 1826–1835. doi: 10.1111/pce.12342

PubMed Abstract | CrossRef Full Text | Google Scholar

Anderson, P., Hansson, B. S., Nilsson, U., Han, Q., Sjöholm, M., Skals, N., et al. (2007). Increased behavioral and neuronal sensitivity to sex pheromone after brief odor experience in a moth. Chem. Senses 32, 483–491. doi: 10.1093/chemse/bjm017

PubMed Abstract | CrossRef Full Text | Google Scholar

Andersson, M. N., Larsson, M. C., Blazenec, M., Jakus, R., Zhang, Q.-H., and Schlyter, F. (2010). Peripheral modulation of pheromone response by inhibitory host compound in a beetle. J. Exp. Biol. 213, 3332–3339. doi: 10.1242/jeb.044396

PubMed Abstract | CrossRef Full Text | Google Scholar

Andersson, M. N., Löfstedt, C., and Newcomb, R. D. (2015). Insect olfaction and the evolution of receptor tuning. Front. Ecol. Evol. 3:53. doi: 10.3389/fevo.2015.00053

CrossRef Full Text | Google Scholar

Anton, S., and Hansson, B. S. (1995). Sex-pheromone and plant-associated odor processing in antennal lobe interneurons of male Spodoptera littoralis (Lepidoptera, Noctuidae). J. Comp. Physiol. A 176, 773–789. doi: 10.1007/BF00192625

CrossRef Full Text | Google Scholar

Anton, S., and Homberg, U. (1999). “Antennal lobe strucure,” in Insect Olfaction, ed B. S. Hansson (Berlin: Springer), 97–124.

Arenas, A., Giurfa, M., Sandoz, J. C., Hourcade, B., Devaud, J. M., and Farina, W. M. (2012). Early olfactory experience induces structural changes in the primary olfactory center of an insect brain. Eur. J. Neurosci. 35, 682–690. doi: 10.1111/j.1460-9568.2012.07999.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Asahina, K., Louis, M., Piccinotti, S., and Vosshall, L. (2009). A circuit supporting concentration-invariant odor perception in Drosophila. J. Biol. 8, 19. doi: 10.1186/jbiol108

PubMed Abstract | CrossRef Full Text | Google Scholar

Badeke, E., Haverkamp, A., Hansson, B. S., and Sachse, S. (2016). A challenge for a male noctuid moth? Discerning the female sex pheromone against the background of plant volatiles. Front. Physiol. 7:143. doi: 10.3389/fphys.2016.00143

PubMed Abstract | CrossRef Full Text | Google Scholar

Baker, T. C., and Haynes, K. F. (1989). Field and laboratory electroantennographic measurements of pheromone plume structure correlated with oriental fruit moth behaviour. Physiol. Entomol. 14, 1–12. doi: 10.1111/j.1365-3032.1989.tb00931.x

CrossRef Full Text

Balkenius, A., Bisch-Knaden, S., and Hansson, B. (2009). Interaction of visual and odour cues in the mushroom body of the hawkmoth Manduca sexta. J. Exp. Biol. 212, 535–541. doi: 10.1242/jeb.021220

PubMed Abstract | CrossRef Full Text | Google Scholar

Barrozo, R. B., Gadenne, C., and Anton, S. (2010). Switching attraction to inhibition: mating-induced reversed role of sex pheromone in an insect. J. Exp. Biol. 213, 2933–2939. doi: 10.1242/jeb.043430

PubMed Abstract | CrossRef Full Text | Google Scholar

Barrozo, R. B., Jarriault, D., Deisig, N., Gemeno, C., Monsempes, C., Lucas, P., et al. (2011). Mating-induced differential coding of plant odour and sex pheromone in a male moth. Eur. J. Neurosci. 33, 1841–1850. doi: 10.1111/j.1460-9568.2011.07678.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Barrozo, R. B., and Lazzari, C. R. (2004a). Orientation behaviour of the blood-sucking bug Triatoma infestans to short-chain fatty acids: synergistic effect of L-lactic acid and carbon dioxide. Chem. Senses 29, 833–841. doi: 10.1093/chemse/bjh249

PubMed Abstract | CrossRef Full Text | Google Scholar

Barrozo, R. B., and Lazzari, C. R. (2004b). The response of the blood-sucking bug Triatoma infestans to carbon dioxide and other host odours. Chem. Senses 29, 319–329. doi: 10.1093/chemse/bjh035

PubMed Abstract | CrossRef Full Text | Google Scholar

Barton-Browne, L. (1977). “Host-related responses and their suppression: some behavioral considerations,” in Chemical Control of Insect Behavior: Theory and Application, eds H. H. Shorey and J. J. McKelvey (New York, NY: Wiley), 117–127.

Benton, R., Vannice, K. S., Gomez-Diaz, C., and Vosshall, L. B. (2009). Variant ionotropic glutamate receptors as chemosensory receptors in Drosophila. Cell 136, 149–162. doi: 10.1016/j.cell.2008.12.001

PubMed Abstract | CrossRef Full Text | Google Scholar

Berg, B., Almaas, T., Bjaalie, J. G., and Mustaparta, H. (1998). The macroglomerular complex of the antennal lobe in the tobacco budworm moth Heliothis virescens: specified subdivision in four compartments according to information about biologically significant compounds. J. Comp. Physiol. A 183, 669–682. doi: 10.1007/s003590050290

CrossRef Full Text | Google Scholar

Binyameen, M., Hussain, A., Yousefi, F., Birgersson, G., and Schlyter, F. (2013). Modulation of reproductive behaviors by non-host volatiles in the polyphagous Egyptian cotton leafworm, Spodoptera littoralis. J. Chem. Ecol. 39, 1273–1283. doi: 10.1007/s10886-013-0354-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Birch, M. C., Poppy, G. M., and Baker, T. C. (1990). Scents and eversible scent structures of male moths. Annu. Rev. Entomol. 35, 25–58. doi: 10.1146/annurev.en.35.010190.000325

CrossRef Full Text | Google Scholar

Birkett, M. A., Agelopoulus, N., Jensen, V., Jesperen, M. B., Pickett, J. A., Prijs, J., et al. (2004). The role of volatile semiochemicals in mediating host location and selection by nuisance and disease-transmitting cattle flies. Med. Vet. Entomol. 18, 313–322. doi: 10.1111/j.0269-283X.2004.00528.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Bitterman, M. E., Menzel, R., Fietz, A., and Schäfer, S. (1983). Classical conditioning of proboscis extension in honeybees (Apis mellifera). J. Comp. Psychol. 97, 107–119. doi: 10.1037/0735-7036.97.2.107

PubMed Abstract | CrossRef Full Text | Google Scholar

Blackwell, A., Mordue, A. J., Hansson, B. S., Wadhams, L. J., and Pickett, J. A. (1993). A behavioral and electrophysiological study of oviposition cues for Culex quinquefasciatus. Physiol. Entomol. 18, 343–348. doi: 10.1111/j.1365-3032.1993.tb00607.x

CrossRef Full Text | Google Scholar

Boeckh, J., and Boeckh, V. (1979). Threshold and odor specificity of pheromone-sensitive neurons in the deutocerebrum of Antheraea pernyi and A. polyphemus (Saturniidae). J. Comp. Physiol. A 132, 235–242. doi: 10.1007/BF00614495

CrossRef Full Text | Google Scholar

Bohbot, J. D., and Dickens, J. C. (2010). Insect repellents: modulators of mosquito odorant receptor activity. PLoS ONE 5:e12138. doi: 10.1371/journal.pone.0012138

PubMed Abstract | CrossRef Full Text | Google Scholar

Borges, L. M. F., Gomes de Oliveira Filho, J., Ferreira, L. L., Braz Louly, C. C., Pickett, J. A., and Birkett, M. A. (2015). Identification of non-host semiochemicals for the brown dog tick, Rhipicephalus sanguineus sensu lato (Acari: Ixodidae), from tick-resistant beagles, Canis lupus familiaris. Ticks Tick-Borne Dis. 6, 676–682. doi: 10.1016/j.ttbdis.2015.05.014

PubMed Abstract | CrossRef Full Text | Google Scholar

Bosch, O. J., Geier, M., and Boeckh, J. (2000). Contribution of fatty acids to olfactory host finding of female Aedes aegypti. Chem. Senses 25, 323–330. doi: 10.1093/oxfordjournals.chemse.a014042

PubMed Abstract | CrossRef Full Text | Google Scholar

Bouyer, J., Pruvot, M., Bengaly, Z., Guerin, P. M., and Lancelot, R. (2007). Learning influences host choice in tsetse. Biol. Lett. 3, 113–117. doi: 10.1098/rsbl.2006.0578

PubMed Abstract | CrossRef Full Text | Google Scholar

Bowers, W. S., Nault, L. R., Webb, R. E., and Dutky, S. R. (1972). Aphid alarm pheromone: isolation, identification, synthesis. Science 177, 1121–1122. doi: 10.1126/science.177.4054.1121

PubMed Abstract | CrossRef Full Text | Google Scholar

Bray, S., and Amrein, H. (2003). A putative Drosophila pheromone receptor expressed in male-specific taste neurons is required for efficient courtship. Neuron 39, 1019–1029. doi: 10.1016/S0896-6273(03)00542-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Brooks, T. W., Doane, C. C., and Staten, R. T. (1979). “Experience with the first commercial pheromone communication disruptive for suppression of an agricultural pest,” in Chemical Ecology: Odour Communication in Animals, ed F. J. Ritter (Amsterdam: Elsevier), 375–388.

Brown, S. M., Napper, R. M. T. C. M., and Mercer, A. (2002). Stereological analysis reveals striking differences in the structural plasticity of two readily identifiable glomeruli in the antennal lobes of the adult worker honeybee. J. Neurosci. 22, 8514–8522.

PubMed Abstract | Google Scholar

Bruce, T. J. A., and Pickett, J. A. (2011). Perception of plant volatile blends by herbivorous insects – finding the right mix. Phytochemistry 72, 1605–1611. doi: 10.1016/j.phytochem.2011.04.011

PubMed Abstract | CrossRef Full Text | Google Scholar

Büchel, K., Austel, N., Mayer, M., Gershenzon, J., Fenning, T. M., and Meiners, T. (2014). Smelling the tree and the forest: elm background odours affect egg parasitoid orientation to herbivore induced terpenoids. Biocontrol 59, 29–43. doi: 10.1007/s10526-013-9544-9

CrossRef Full Text | Google Scholar

Byers, J. A., Fefer, D., and Levi-Zada, A. (2013). Sex pheromone component ratios and mating isolation among three Lygus plant bug species of North America. Naturwiss 100, 1115–1123. doi: 10.1007/s00114-013-1113-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Cardé, R. T. (1990). “Principles of mating disruption,” in Behavior-Modifying Chemicals for Insect Management, Applications of Pheromones and Other Attractants, eds R. L. Ridgway, R. M. Silverstein, and M. N. Inscoe (New York, NY: Dekker), 47–72.

Cardé, R. T., and Gibson, G. (2010). “Host finding by female mosquitoes: mechanisms of orientation to host odours and other cues” in Olfaction in Vector-Host Interactions, eds W. Takken and B. Knols (Wageningen: Wageningen Academic Publishers), 115–141.

Google Scholar

Carlsson, M. A., Galizia, C. G., and Hansson, B. S. (2002). Spatial representation of odours in the antennal lobe of the moth Spodoptera littoralis (Lepidoptera: Noctuidae). Chem. Senses 27, 231–244. doi: 10.1093/chemse/27.3.231

PubMed Abstract | CrossRef Full Text | Google Scholar

Carrasco, D., Larsson, M. C., and Anderson, P. (2015). Insect host plant selection in complex environments. Curr. Opin. Insect Sci. 8, 1–7. doi: 10.1016/j.cois.2015.01.014

CrossRef Full Text | Google Scholar

Cha, D. H., Nojima, S., Hesler, S. P., Zhang, A., Linn, C. E., Roelofs, W. L., et al. (2008). Identification and field evaluation of grape shoot volatiles attractive to female grape berry moth (Paralobesia viteana). J. Chem. Ecol. 34, 1180–1189. doi: 10.1007/s10886-008-9517-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Chaffiol, A., Dupuy, F., Barrozo, R. B., Kropf, J., Renou, M., Rospars, J.-P., et al. (2014). Pheromone modulates plant odor responses in the antennal lobe of a moth. Chem. Senses 39, 451–463. doi: 10.1093/chemse/bju017

PubMed Abstract | CrossRef Full Text | Google Scholar

Chaffiol, A., Kropf, J., Barrozo, R. B., Gadenne, C., Rospars, J. P., and Anton, S. (2012). Plant odour stimuli reshape pheromonal representation in neurons of the antennal lobe macroglomerular complex of a male moth. J. Exp. Biol. 215, 1670–1680. doi: 10.1242/jeb.066662

PubMed Abstract | CrossRef Full Text | Google Scholar

Chapman, T. B., Veblen, T. T., and Schoennagel, T. (2012). Spatiotemporal patterns of mountain pine beetle activity in the southern Rocky Mountains. Ecology 93, 2175–2185. doi: 10.1890/11-1055.1

PubMed Abstract | CrossRef Full Text | Google Scholar

Chen, J.-Y., Marachlian, E., Assisi, C., Huerta, R., Smith, B. H., Locatelli, F., et al. (2015). Learning modifies odor mixture processing to improve detection of relevant components. J. Neurosci. 35, 179–197. doi: 10.1523/JNEUROSCI.2345-14.2015

PubMed Abstract | CrossRef Full Text | Google Scholar

Chilaka, N., Perkins, E., and Tripet, F. (2012). Visual and olfactory associative learning in the malaria vector Anopheles gambiae sensu stricto. Malaria J. 11:27. doi: 10.1186/1475-2875-11-27

PubMed Abstract | CrossRef Full Text | Google Scholar

Chou, Y.-H., Spletter, M. L., Yaksi, E., Leong, J. C. S., Wilson, R. I., and Luo, L. (2010). Diversity and wiring variability of olfactory local interneurons in the Drosophila antennal lobe. Nat. Neurosci. 13, 439–449. doi: 10.1038/nn.2489

PubMed Abstract | CrossRef Full Text | Google Scholar

Christensen, T. A., and Hildebrand, J. G. (1987). Male-specific, sex pheromone-selective projection neurons in the antennal lobes of the moth Manduca sexta. J. Comp. Physiol. A 160, 553–569. doi: 10.1007/BF00611929

PubMed Abstract | CrossRef Full Text | Google Scholar

Christensen, T. A., and Hildebrand, J. G. (1988). Frequency coding by central olfactory neurons in the sphinx moth Manduca sexta. Chem. Senses 13, 123–130. doi: 10.1093/chemse/13.1.123

CrossRef Full Text | Google Scholar

Christensen, T. A., Waldrop, B. R., Harrow, I. D., and Hildebrand, J. G. (1993). Local interneurons and information processing in the olfactory glomeruli of the moth Manduca sexta. J. Comp. Physiol. A 173, 385–399. doi: 10.1007/bf00193512

PubMed Abstract | CrossRef Full Text | Google Scholar

Claudianos, C., Lim, J., Young, M., Yan, S., Cristino, A. S., Newcomb, R. D., et al. (2014). Odor memories regulate olfactory receptor expression in the sensory periphery. Eur. J. Neurosci. 39, 1642–1654. doi: 10.1111/ejn.12539

PubMed Abstract | CrossRef Full Text | Google Scholar

Cook, S. M., Khan, Z. R., and Pickett, J. A. (2007). The use of push-pull strategies in integrated pest management. Annu. Rev. Entomol. 52, 375–400. doi: 10.1146/annurev.ento.52.110405.091407

PubMed Abstract | CrossRef Full Text | Google Scholar

Dacks, A. M., Christensen, T. A., and Hildebrand, J. G. (2008). Modulation of olfactory information processing in the antennal lobe of Manduca sexta. J. Neurophysiol. 99, 2077–2085. doi: 10.1152/jn.01372.2007

PubMed Abstract | CrossRef Full Text | Google Scholar

Dacks, A. M., Riffell, J. A., Martin, J. P., Gage, S. L., and Nighorn, A. J. (2012). Olfactory modulation by dopamine in the context of aversive learning. J. Neurophysiol. 108, 539–550. doi: 10.1152/jn.00159.2012

PubMed Abstract | CrossRef Full Text | Google Scholar

Daly, K. C., Christensen, T. A., Lei, H., Smith, B. H., and Hildebrand, J. G. (2004). Learning modulates the ensemble representations for odors in primary olfactory networks. Proc. Natl. Acad. Sci. U.S.A. 101, 10476–10481. doi: 10.1073/pnas.0401902101

PubMed Abstract | CrossRef Full Text | Google Scholar

Daly, K. C., Durtschi, M. L., and Smith, B. H. (2001). Olfactory-based discrimination learning in the moth, Manduca sexta. J. Insect Physiol. 47, 375–384. doi: 10.1016/S0022-1910(00)00117-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Davis, E. E., and Sokolove, P. G. (1976). Lactic acid-sensitive receptors on the antennae of the mosquito, Aedes aegypti. J. Comp. Physiol. A 105, 43–54. doi: 10.1007/BF01380052

CrossRef Full Text | Google Scholar

Davis, R. L. (2004). Olfactory learning. Neuron 44, 31–48. doi: 10.1016/j.neuron.2004.09.008

PubMed Abstract | CrossRef Full Text | Google Scholar

de Bruyne, M., Clyne, P. J., and Carlson, J. R. (1999). Odor coding in a model olfactory organ: the Drosophila maxillary palp. J. Neurosci. 19, 4520–4532.

PubMed Abstract | Google Scholar

DeGennaro, M., McBride, C. S., Seeholzer, L., Nakagawa, T., Dennis, E. J., and Goldman, C. (2013). Orco mutant mosquitoes lose strong preference for humans and are not repelled by volatile DEET. Nature 498, 487–491. doi: 10.1038/nature12206

PubMed Abstract | CrossRef Full Text | Google Scholar

Deisig, N., Giurfa, M., Lachnit, H., and Sandoz, J. C. (2006). Neural representation of olfactory mixtures in the honeybee antennal lobe. Eur. J. Neurosci. 24, 1161–1174. doi: 10.1111/j.1460-9568.2006.04959.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Deisig, N., Kropf, J., Vitecek, S., Pevergne, D., Rouyar, A., Sandoz, J.-C., et al. (2012). Differential interactions of sex pheromone and plant odour in the olfactory pathway of a male moth. PLoS ONE 7:e33159. doi: 10.1371/journal.pone.0033159

PubMed Abstract | CrossRef Full Text | Google Scholar

Devaud, J. M., Acebes, A., and Ferrus, A. (2001). Odor exposure causes central adaptation and morphological changes in selected olfactory glomeruli in Drosophila. J. Neurosci. 21, 6274–6282.

PubMed Abstract | Google Scholar

Dewhirst, S. Y., Pickett, J. A., and Hardie, J. (2010). Aphid pheromones. Vitam. Horm. 83, 551–574. doi: 10.1016/S0083-6729(10)83022-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Diehl, P. A., Vlimant, M., Guerenstein, P. G., and Guerin, P. M. (2003). Ultrastructure and receptor cell responses of the antennal grooved peg sensilla of Triatoma infestans (Hemiptera: Reduviidae). Arthropod. Struct. Dev. 31, 271–285. doi: 10.1016/S1467-8039(03)00004-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Ditzen, M., Pellegrino, M., and Vosshall, L. B. (2008). Insect odorant receptors are molecular targets of the insect repellent DEET. Science 319, 1838–1842. doi: 10.1126/science.1153121

PubMed Abstract | CrossRef Full Text | Google Scholar

Dolzer, J., Fischer, K., and Stengl, M. (2003). Adaptation in pheromone-sensitive trichoid sensilla of the hawkmoth Manduca sexta. J. Exp. Biol. 206, 1575–1588. doi: 10.1242/jeb.00302

PubMed Abstract | CrossRef Full Text | Google Scholar

Dolzer, J., Krannich, S., and Stengl, M. (2008). Pharmacological investigation of protein Kinase C- and cGMP-dependent ion channels in cultured olfactory receptor neurons of the hawkmoth Manduca sexta. Chem. Senses 33, 803–813. doi: 10.1093/chemse/bjn043

PubMed Abstract | CrossRef Full Text | Google Scholar

Dusenbery, D. B. (1992). Sensory Ecology: How Organisms Acquire and Respond to Information. New York, NY: Freeman.

Dweck, H. K. M., Ebrahim, S. A. M., Thoma, M., Mohamed, A. A. M., Keesey, I. W., Trona, F., et al. (2015). Pheromones mediating copulation and attraction in Drosophila. Proc. Natl. Acad. Sci. U.S.A. 112, 2829–2835. doi: 10.1073/pnas.1504527112

PubMed Abstract | CrossRef Full Text | Google Scholar

Faber, T., Joerges, J., and Menzel, R. (1999). Associative learning modifies neural representations of odors in the insect brain. Nat. Neurosci. 2, 74–78. doi: 10.1038/4576

PubMed Abstract | CrossRef Full Text | Google Scholar

Fahrbach, S. E. (2006). Structure of the mushroom bodies of the insect brain. Annu. Rev. Entomol. 51, 209–232. doi: 10.1146/annurev.ento.51.110104.150954

PubMed Abstract | CrossRef Full Text | Google Scholar

Fahrbach, S. E., Moore, D., Capaldi, E. A., Farris, S. M., and Robinson, G. E. (1998). Experience-expectant plasticity in the mushroom bodies of the honeybee. Learn. Mem. 5, 115–123.

PubMed Abstract | Google Scholar

Fernandez, P. C., Locatelli, F. F., Person-Rennell, N., Deleo, G., and Smith, B. H. (2009). Associative conditioning tunes transient dynamics of early olfactory processing. J. Neurosci. 29, 10191–10202. doi: 10.1523/JNEUROSCI.1874-09.2009

PubMed Abstract | CrossRef Full Text | Google Scholar

Fishilevich, E., and Vosshall, L. B. (2005). Genetic and functional subdivision of the drosophila antennal lobe. Curr. Biol. 15, 1548–1553 doi: 10.1016/j.cub.2005.07.066

PubMed Abstract | CrossRef Full Text | Google Scholar

Foster, S. P., and Harris, M. O. (1997). Behavioural manipulation methods for insect pest management. Annu. Rev. Entomol. 42, 123–146. doi: 10.1146/annurev.ento.42.1.123

PubMed Abstract | CrossRef Full Text

Fox, A. N., Pitts, R. J., Robertson, H. M., Carlson, J. R., and Zwiebel, L. J. (2001). Candidate odorant receptors from the malaria vector mosquito Anopheles gambiae and evidence of down-regulation in response to blood feeding. Proc. Natl. Acad. Sci. U.S.A. 98, 14693–14697. doi: 10.1073/pnas.261432998

PubMed Abstract | CrossRef Full Text | Google Scholar

Fujiwara, T., Kazawa, T., Haupt, S. S., and Kanzaki, R. (2009). Ca2+ imaging of identifiable neurons labeled by electroporation in insect brains. Neuroreport 20, 1061–1065. doi: 10.1097/WNR.0b013e32832e7d93

PubMed Abstract | CrossRef Full Text | Google Scholar

Galizia, C. G., and Rössler, W. (2010). Parallel olfactory systems in insects: anatomy and function. Annu. Rev. Entomol. 55, 399–420. doi: 10.1146/annurev-ento-112408-085442

PubMed Abstract | CrossRef Full Text | Google Scholar

Galizia, C. G., and Sachse, S. (2010). “Odor coding in insects,” in The Neurobiology of Olfaction, ed A. Menini. (Boca Raton. FL, CRC Press), 35–70.

Google Scholar

Gaudry, Q., Nagel, K. I., and Wilson, R. I. (2012). Smelling on the fly: sensory cues and strategies for olfactory navigation in Drosophila. Curr. Opinion Neurobiol. 22, 216–222. doi: 10.1016/j.conb.2011.12.010

PubMed Abstract | CrossRef Full Text | Google Scholar

Geier, M., Bosch, O. J., and Boeckh, J. (1999a). Ammonia as an attractive component of host odour for the yellow fever mosquito, Aedes aegypti. Chem. Senses 24, 647–653. doi: 10.1093/chemse/24.6.647

PubMed Abstract | CrossRef Full Text | Google Scholar

Geier, M., Bosch, O. J., and Boeckh, J. (1999b). Influence of odour plume structure on upwind flight of mosquitoes towards hosts. J. Exp. Biol. 202, 1639–1648.

PubMed Abstract | Google Scholar

Geier, M., Sass, H., and Boeckh, J. (1996). “A search for components in human body odour that attract females of Aedes aegypti,” in Mosquito Olfaction and Olfactory-Mediated Mosquito–Host Interactions, Ciba Foundation Symposium 200, ed G. Cardew and J. Goode (New York, NY: John Wiley & Sons Ltd), 132–144.

Glendinning, J., Foley, C., Loncar, I., and Rai, M. (2009). Induced preference for host plant chemicals in the tobacco hornworm: contribution of olfaction and taste. J. Comp. Physiol. A 195, 591–601. doi: 10.1007/s00359-009-0434-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Goyret, J., Markwell, P. M., and Raguso, R. A. (2008). Context- and scale-dependent effects of floral CO2 on nectar foraging by Manduca sexta. Proc. Natl. Acad. Sci. U.S.A. 105, 4565–4570. doi: 10.1073/pnas.0708629105

PubMed Abstract | CrossRef Full Text | Google Scholar

Green, C. H. (1986). Effects of colours and synthetic odours on the attraction of Glossina pallidipes and G. morsitans to traps and screens. Physiol. Entomol. 11, 411–421. doi: 10.1111/j.1365-3032.1986.tb00432.x

CrossRef Full Text | Google Scholar

Green, C. H. (1993). The effect of odours and target colour on landing responses of Glossina morsitans morsitans and G. pallidipes (Diptera: Glossinidae). Bull. Entomol. Res. 83, 553–562. doi: 10.1017/S0007485300039985

CrossRef Full Text | Google Scholar

Green, C. H. (1994). Bait methods for tsetse fly control. Adv. Parasitol. 34, 229–291. doi: 10.1016/S0065-308X(08)60140-2

PubMed Abstract | CrossRef Full Text | Google Scholar

Grenacher, S., Kröber, T., Guerin, P. M., and Vlimant, M. (2001). Behavioural and chemoreceptor cell responses of the tick, Ixodes ricinus, to its own faeces and faecal constituents. Exp. Appl. Acarol. 25, 641–660. doi: 10.1023/A:1016145805759

PubMed Abstract | CrossRef Full Text | Google Scholar

Grosse-Wilde, E., Stieber, R., Forstner, M., Krieger, J. G., Wicher, D., and Hansson, B. S. (2010). Sex-specific odorant receptors of the tobacco hornworm Manduca sexta. Front. Cell. Neurosci. 4:22. doi: 10.3389/fncel.2010.00022

PubMed Abstract | CrossRef Full Text | Google Scholar

Guerenstein, P. G., Christensen, T. A., and Hildebrand, J. G. (2004a). Sensory processing of ambient CO2 information in the brain of the moth Manduca sexta. J. Comp. Physiol. A 190, 707–725. doi: 10.1007/s00359-004-0529-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Guerenstein, P. G., and Guerin, P. M. (2001). Olfactory and behavioural responses of the blood-sucking bug Triatoma infestans to odours of vertebrate hosts. J. Exp. Biol. 204, 585–597.

PubMed Abstract | Google Scholar

Guerenstein, P. G., and Guerin, P. M. (2004). A comparison of volatiles emitted by adults of three triatomine species. Entomol. Exp. Appl. 111, 151–155. doi: 10.1111/j.0013-8703.2004.00160.x

CrossRef Full Text | Google Scholar

Guerenstein, P. G., and Hildebrand, J. G. (2008). Roles and effects of environmental carbon dioxide in insect life. Annu. Rev. Entomol. 53, 161–178. doi: 10.1146/annurev.ento.53.103106.093402

PubMed Abstract | CrossRef Full Text | Google Scholar

Guerenstein, P. G., and Lazzari, C. R. (2009). Host-seeking: how triatomines acquire and make use of information to find blood. Acta Trop. 110, 148–158. doi: 10.1016/j.actatropica.2008.09.019

PubMed Abstract | CrossRef Full Text | Google Scholar

Guerenstein, P. G., and Lazzari, C. R. (2010). “The role of olfaction in host seeking of Triatominae bugs,” in Ecology and Control of Vector-Borne Diseases, Olfaction in Vector-Host Interactions, Vol 2, ed W. Takken and B. Knols (Wageningen: Wageningen University Press), 309–325.

Guerenstein, P. G., Yepez, E. A., van Haren, J., Williams, D. G., and Hildebrand, J. G. (2004b). Floral CO2 emission may indicate food abundance to nectar-feeding moths. Naturwiss 91, 329–333. doi: 10.1007/s00114-004-0532-x

PubMed Abstract | CrossRef Full Text | Google Scholar

Guerrieri, F., Gemeno, C., Monsempes, C., Anton, S., Jacquin-Joly, E., Lucas, P., et al. (2012). Experience-dependent modulation of antennal sensitivity and input to antennal lobes in male moths (Spodoptera littoralis) pre-exposed to sex pheromone. J. Exp. Biol. 215, 2334–2341. doi: 10.1242/jeb.060988

PubMed Abstract | CrossRef Full Text | Google Scholar

Guidobaldi, F., and Guerenstein, P. G. (2013). Evaluation of a CO2-free commercial mosquito attractant to capture triatomines in the laboratory. J. Vector Ecol. 38, 245–250. doi: 10.1111/j.1948-7134.2013.12037.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Guidobaldi, F., and Guerenstein, P. G. (2016). A CO2-free synthetic host-odor mixture that attracts and captures triatomines: effect of emitted odorant ratios. J. Med. Entomol. doi: 10.1093/jme/tjw057. [Epub ahead of print].

PubMed Abstract | CrossRef Full Text | Google Scholar

Guidobaldi, F., May Concha, I. J., and Guerenstein, P. G. (2014). Morphology and physiology of the olfactory system of blood-feeding insects. J. Physiol. Paris 108, 96–111. doi: 10.1016/j.jphysparis.2014.04.006

PubMed Abstract | CrossRef Full Text | Google Scholar

Gupta, N., and Stopfer, M. (2012). Functional analysis of a higher olfactory center, the lateral horn. J. Neurosci. 32, 8138–8148. doi: 10.1523/JNEUROSCI.1066-12.2012

PubMed Abstract | CrossRef Full Text | Google Scholar

Hallem, E. A., and Carlson, J. R. (2006). Coding of odors by a receptor repertoire. Cell 125, 143–160. doi: 10.1016/j.cell.2006.01.050

PubMed Abstract | CrossRef Full Text | Google Scholar

Hansson, B. S., Almaas, T. J., and Anton, S. (1995). Chemical communication in heliothine moths. 5. Antennal lobe projection patterns of pheromone-detecting olfactory receptor neurons in the male Heliothis virescens (Lepidoptera, Noctuidae). J. Comp. Physiol. A 177, 535–543.

Google Scholar

Hansson, B. S., Carlsson, M. A., and Kalinova, B. (2003). Olfactory activation patterns in the antennal lobe of the sphinx moth, Manduca sexta. J. Comp. Physiol. A 189, 301–308. doi: 10.1007/s00359-003-0403-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Hansson, B. S., Christensen, T. A., and Hildebrand, J. G. (1991). Functionally distinct subdivisions of the macroglomerular complex in the antennal lobe of the male sphinx moth Manduca sexta. J. Comp. Neurol. 312, 264–278. doi: 10.1002/cne.903120209

PubMed Abstract | CrossRef Full Text | Google Scholar

Hansson, B. S., Larsson, M. C., and Leal, W. S. (1999). Green leaf volatile-detecting olfactory receptor neurons display very high sensitivity and specificity in a scarab beetle. Physiol. Entomol. 24, 121–126. doi: 10.1046/j.1365-3032.1999.00121.x

CrossRef Full Text | Google Scholar

Hansson, B. S., Ljungberg, H., Hallberg, E., and Löfstedt, C. (1992). Functional specialization of olfactory glomeruli in a moth. Science 256, 1313–1315. doi: 10.1126/science.1598574

PubMed Abstract | CrossRef Full Text | Google Scholar

Hartlieb, E., Anderson, P., and Hansson, B. S. (1999). Appetitive learning of odours with different behavioral meaning in moths. Physiol. Behav. 67, 671–677. doi: 10.1016/S0031-9384(99)00124-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Hartlieb, E., and Hansson, B. S. (1999). Sex or food? Appetetive learning of sex odors in a male moth. Naturwiss 86, 396–399. doi: 10.1007/s001140050640

PubMed Abstract | CrossRef Full Text | Google Scholar

Hatano, E., Saveer, A. M., Borrero-Echeverry, F., Strauch, M., Zakir, A., Bengtsson, M., et al. (2015). A herbivore-induced plant volatile interferes with host plant and mate location in moths through suppression of olfactory signalling pathways. BMC Biol. 13:75. doi: 10.1186/s12915-015-0188-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Heinbockel, T., Christensen, T. A., and Hildebrand, J. G. (1999). Temporal tuning of odor responses in pheromone-responsive projection neurons in the brain of the sphinx moth Manduca sexta. J. Comp. Neurol. 409, 1–12.

PubMed Abstract | Google Scholar

Heinbockel, T., Christensen, T. A., and Hildebrand, J. G. (2004). Representation of binary pheromone blends by glomerulus-specific olfactory projection neurons. J. Comp. Physiol. A 190, 1023–1037. doi: 10.1007/s00359-004-0559-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Hildebrand, J. G. (1996). King solomon lecture: olfactory control of behavior in moths: central processing of odor information and the functional significance of olfactory glomeruli. J. Comp. Physiol. A 178, 5–19. doi: 10.1007/BF00189586

PubMed Abstract | CrossRef Full Text | Google Scholar

Hildebrand, J., G., Matsumoto, S. G., Camazine, S. M., Tolbert, L. P., Blank, S., Ferguson, H., et al. (1980). “Organisation and physiology of antennal centres in the brain of the moth Manduca sexta,” in Insect Neurobiology and Pesticide Action (Neurotox 79) (London: Society of Chemical Industry), 375–382.

Hillier, N. K., Kelly, D., and Vickers, N. J. (2006). A specific male olfactory sensillum detects behaviorally antagonistic hairpencil odorants. J. Insect Sci. 7:4. doi: 10.1673/031.007.0401

PubMed Abstract | CrossRef Full Text | Google Scholar

Homberg, U., Christensen, T. A., and Hildebrand, J. G. (1989). Structure and function of the deutocerebrum in insects. Annu. Rev. Entomol. 34, 477–501. doi: 10.1146/annurev.en.34.010189.002401

PubMed Abstract | CrossRef Full Text | Google Scholar

Homberg, U., Montague, R. A., and Hildebrand, J. G. (1988). Anatomy of antenno-cerebral pathways in the brain of the sphinx moth Manduca sexta. Cell Tissue Res. 254, 255–281. doi: 10.1007/BF00225800

PubMed Abstract | CrossRef Full Text | Google Scholar

Hoskins, S. G., Homberg, U., Kingan, T. G., Christensen, T. A., and Hildebrand, J. G. (1986). Immunocytochemistry of GABA in the antennal lobes of the sphinx moth Manduca sexta. Cell Tissue Res. 244, 243–252. doi: 10.1007/BF00219199

PubMed Abstract | CrossRef Full Text | Google Scholar

Huang, J., Stelinski, L. L., and Gut, L. J. (2010). Mating behaviors of Cydia pomonella (Lepidoptera: Tortricidae) as influenced by sex pheromone in electrostatic powder. J. Econ. Entomol. 103, 2100–2106. doi: 10.1603/EC10063

PubMed Abstract | CrossRef Full Text | Google Scholar

Huetteroth, W., Perisse, E., Lin, S., Klappenbach, M., Burke, C., and Waddell, S. (2015). Sweet taste and nutrient value subdivide rewarding dopaminergic neurons in Drosophila. Curr. Biol. 25, 751–758. doi: 10.1016/j.cub.2015.01.036

PubMed Abstract | CrossRef Full Text | Google Scholar

Husch, A., Paehler, M., Fusca, D., Paeger, L., and Kloppenburg, P. (2009). Calcium current diversity in physiologically different local interneuron types of the antennal lobe. J. Neurosci. 29, 716–726. doi: 10.1523/JNEUROSCI.3677-08.2009

PubMed Abstract | CrossRef Full Text | Google Scholar

Hussain, A., Zhang, M., Üçpunar, H. K., Svensson, T., Quillery, E., Gompel, N., et al. (2016). Ionotropic chemosensory receptors mediate the taste and smell of polyamines. PLoS Biol 14:e1002454. doi: 10.1371/journal.pbio.1002454

PubMed Abstract | CrossRef Full Text | Google Scholar

Ignell, R., Root, C. M., Birse, R. T., Wang, J. W., Nässel, D. R., and Winther, S. M. E. (2009). Presynaptic peptidergic modulation of olfactory receptor neurons in Drosophila. Proc. Natl. Acad. Sci. U.S.A. 106, 13070–13075. doi: 10.1073/pnas.0813004106

PubMed Abstract | CrossRef Full Text | Google Scholar

Ito, I., Bazhenov, M., Ong, R. C., Raman, B., and Stopfer, M. (2009). Frequency transitions in odor-evoked neural oscillations. Neuron 64, 692–706. doi: 10.1016/j.neuron.2009.10.004

PubMed Abstract | CrossRef Full Text | Google Scholar

Iwano, M., Hill, E. S., Mori, A., Mishima, T., Ito, K., and Kanzaki, R. (2010). Neurons associated with the flip-flop activity in the lateral accessory lobe and ventral protocerebrum of the silkworm moth brain. J. Comp. Neurol. 518, 366–388. doi: 10.1002/cne.22224

PubMed Abstract | CrossRef Full Text | Google Scholar

Jeanne, J. M., and Wilson, R. I. (2015). Convergence, divergence, and reconvergence in a feedforward network improves neural speed and accuracy. Neuron 88, 1014–1026. doi: 10.1016/j.neuron.2015.10.018

PubMed Abstract | CrossRef Full Text | Google Scholar

Jefferis, G. S., Potter, C. J., Chan, A. M., Marin, E. C., Rohlfing, T., Maurer, C. R. Jr., et al. (2007). Comprehensive maps of Drosophila higher olfactory centers: spatially segregated fruit and pheromone representation. Cell 128, 1187–1203. doi: 10.1016/j.cell.2007.01.040

PubMed Abstract | CrossRef Full Text | Google Scholar

Jhumur, U. S., Dötterl, S., and Jürgens, A. (2006). Naive and conditioned responses of Culex pipiens pipiens biotype molestus (Diptera: Culicidae) to flower odors. J. Med. Entomol. 43, 1164–1170. doi: 10.1603/0022-2585(2006)43[1164:nacroc]2.0.co;2

PubMed Abstract | CrossRef Full Text | Google Scholar

Jones, W. D., Cayirlioglu, P., Kadow, I. G., and Vosshall, L. B. (2007). Two chemosensory receptors together mediate carbon dioxide detection in Drosophila. Nature 445, 86–90. doi: 10.1038/nature05466

PubMed Abstract | CrossRef Full Text | Google Scholar

Kadohisa, M., and Wilson, D. A. (2006). Olfactory cortical adaptation facilitates detection of odors against background. J. Neurophysiol. 95, 1888–1896. doi: 10.1152/jn.00812.2005

PubMed Abstract | CrossRef Full Text | Google Scholar

Kaissling, K.-E., Hildebrand, J. G., and Tumlinson, J. H. (1989). Pheromone receptor cells in the male moth Manduca sexta. Arch. Insect Biochem. Physiol. 10, 273–279. doi: 10.1002/arch.940100403

CrossRef Full Text | Google Scholar

Kanzaki, R., and Shibuya, T. (1983). Olfactory neural pathway and sexual pheromone responses in the deutocerebrum of the male silkworm moth, Bombyx mori (Lepidoptera: Bombycidae). Appl. Ent. Zool. 18, 131–133.

Google Scholar

Kaur, J., Lai, Y., and Giger, A. (2003). Learning and memory in the mosquito Aedes aegypti shown by conditioning against oviposition deterrence. Med. Vet. Entomol. 17, 457–460. doi: 10.1111/j.1365-2915.2003.00455.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Kent, L. B., Walden, K. O., and Robertson, H. M. (2008). The Gr family of candidate gustatory and olfactory receptors in the yellow fever mosquito Aedes aegypti. Chem. Senses 33, 79–93. doi: 10.1093/chemse/bjm067

PubMed Abstract | CrossRef Full Text | Google Scholar

Klun, J. A., Chapman, O. L., Mattes, K. C., Wojtkowski, P. W., Beroza, M., and Sonnet, P. E. (1973). Insect sex pheromones: minor amount of opposite geometrical isomer critical to attraction. Science 181, 661–663. doi: 10.1126/science.181.4100.661

PubMed Abstract | CrossRef Full Text | Google Scholar

Kohl, J., Huoviala, P., and Jefferis, G. S. (2015). Pheromone processing in Drosophila. Curr. Opin. Neurobiol. 34, 149–157. doi: 10.1016/j.conb.2015.06.009

PubMed Abstract | CrossRef Full Text | Google Scholar

Krieger, J., Gondesen, I., Forstner, M., Gohl, T., Dewer, Y., and Breer, H. (2009). HR11 and HR13 Receptor-expressing neurons are housed together in pheromone-responsive sensilla Trichodea of male Heliothis virescens. Chem. Senses 34, 469–477. doi: 10.1093/chemse/bjp012

PubMed Abstract | CrossRef Full Text | Google Scholar

Krockel, U., Rose, A., Eiras, A. E., and Geier, M. (2006). New tools for surveillance of adult yellow fever mosquitoes: comparison of trap catches with human landing rates in an urban environment. J. Am. Mosq. Control Assoc. 22, 229–238. doi: 10.2987/8756-971X(2006)22[229:NTFSOA]2.0.CO;2

PubMed Abstract | CrossRef Full Text | Google Scholar

Kwon, J.-Y., Dahanukar, A., Weiss, L. A., and Carlson, J. R. (2007). The molecular basis of CO2 reception in Drosophila. Proc. Natl. Acad. Sci. U.S.A. 104, 3574–3578. doi: 10.1073/pnas.0700079104

PubMed Abstract | CrossRef Full Text | Google Scholar

Larsson, M. C., Domingos, A. I., Jones, W. D., Chiappe, M. E., Amrein, H., and Vosshall, L. B. (2004). Or83b encodes a broadly expressed odorant receptor essential for Drosophila olfaction. Neuron 43, 703–714. doi: 10.1016/j.neuron.2004.08.019

PubMed Abstract | CrossRef Full Text | Google Scholar

Leal, W. S. (2013). Odorant reception in insects: roles of receptors, binding ‘proteins, and degrading enzymes. Annu. Rev. Entomol. 58, 373–391. doi: 10.1146/annurev-ento-120811-153635

PubMed Abstract | CrossRef Full Text | Google Scholar

Leal, W. S. (2014). The enigmatic reception of DEET—the gold standard of insect repellents. Curr. Opin. Insect Sci. 6, 93–98. doi: 10.1016/j.cois.2014.10.007

PubMed Abstract | CrossRef Full Text | Google Scholar

Lee, Y., Kim, S. H., and Montell, C. (2010). Avoiding DEET through insect gustatory receptors. Neuron 67, 555–561. doi: 10.1016/j.neuron.2010.07.006

PubMed Abstract | CrossRef Full Text | Google Scholar

Lei, H., Chiu, H. Y., and Hildebrand, J. G. (2013). Responses of protocerebral neurons in Manduca sexta to sex-pheromone mixtures. J. Comp. Physiol. A 199, 997–1014. doi: 10.1007/s00359-013-0844-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Lei, H., Christensen, T. A., and Hildebrand, J. G. (2002). Local inhibition modulates odor-evoked synchronization of glomerulus-specific output neurons. Nat. Neurosci. 5, 557–565. doi: 10.1038/nn0602-859

PubMed Abstract | CrossRef Full Text | Google Scholar

Lei, H., Christensen, T. A., and Hildebrand, J. G. (2004). Spatial and temporal organization of ensemble representations for different odor classes in the moth antennal lobe. J. Neurosci. 24, 11108–11119. doi: 10.1523/JNEUROSCI.3677-04.2004

PubMed Abstract | CrossRef Full Text | Google Scholar

Lei, H., and Hansson, B. S. (1999). Central processing of pulsed pheromone signals by antennal lobe neurons in the male moth Agrotis segetum. J. Neurophysiol. 81, 1113–1122.

PubMed Abstract | Google Scholar

Lei, H., Riffell, J. A., Gage, S. L., and Hildebrand, J. G. (2009). Contrast enhancement of stimulus intermittency in a primary olfactory network and its behavioral significance. J. Biol. 8, 21. doi: 10.1186/jbiol120

PubMed Abstract | CrossRef Full Text | Google Scholar

Lei, H., and Vickers, N. (2008). Central processing of natural odor mixtures in insects. J. Chem. Ecol. 34, 915–927 doi: 10.1007/s10886-008-9487-2

PubMed Abstract | CrossRef Full Text | Google Scholar

Levinson, H. Z., Levinson, A. R., and Maschwitz, U. (1974a). Action and composition of the alarm pheromone of the bedbug Cimex lectularius L. Naturwissenschaften 61, 684–685. doi: 10.1007/BF00606522

PubMed Abstract | CrossRef Full Text | Google Scholar

Levinson, H. Z., Levinson, A. R., Müller, B., and Steinbrecht, R. A. (1974b). Structure of sensilla, olfactory perception, and behaviour of the bedbug, Cimex lectularius, in response to its alarm pheromone. J. Insect Physiol. 20, 1231–1248. doi: 10.1016/0022-1910(74)90229-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Linn, C. Jr., Nojima, S., and Roelofs, W. (2005). Antagonist effects of non-host fruit volatiles on discrimination of host fruit by Rhagoletis flies infesting apple (Malus pumila), hawthorn (Crataegus spp.), and flowering dogwood (Cornus florida). Entomol. Exp. Appl. 114, 97–105. doi: 10.1111/j.1570-7458.2005.00222.x

CrossRef Full Text | Google Scholar

Linster, C., Henry, L., Kadohisa, M., and Wilson, D. A. (2007). Synaptic adaptation and odor-background segmentation. Neurobiol. Learn. Mem. 87, 352–360. doi: 10.1016/j.nlm.2006.09.011

PubMed Abstract | CrossRef Full Text | Google Scholar

Liu, C., Placais, P.-Y., Yamagata, N., Pfeiffer, B. D., Aso, Y., Friedrich, A. B., et al. (2012). A subset of dopamine neurons signals reward for odour memory in Drosophila. Nature 488, 512–516. doi: 10.1038/nature11304

PubMed Abstract | CrossRef Full Text | Google Scholar

Löfstedt, C., Herrebout, W. M., and Menken, S. B. (1991). Sex pheromones and their potential role in the evolution of reproductive isolation in small ermine moths (Yponomeutidae). Chemoecology 2, 20–28. doi: 10.1007/BF01240662

CrossRef Full Text | Google Scholar

Logan, J. G., and Birkett, M. A. (2007). Semiochemicals for biting fly control: their identification and exploitation. Pest Manag. Sci. 63, 647–657. doi: 10.1002/ps.1408

PubMed Abstract | CrossRef Full Text | Google Scholar

Logan, J. G., Birkett, M. A., Clark, S. J., Powers, S., Seal, N. J., Wadhams, L. J., et al. (2008). Identification of human-derived volatile chemicals that interfere with attraction of Aedes aegypti mosquitoes. J. Chem. Ecol. 34, 308–322. doi: 10.1007/s10886-008-9436-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Logan, J. G., Seal, N. J., Cook, J. I., Stanczyk, N. M., Birkett, M. A., Clark, S. J., et al. (2009). Identification of human-derived volatile chemicals that interfere with attraction of the Scottish biting midge and their potential use. J. Med. Entomol. 46, 208–219. doi: 10.1603/033.046.0205

PubMed Abstract | CrossRef Full Text | Google Scholar

Lorenzo Figueiras, A. N., Girotti, J. R., Mijailovsky, S. J., and Juárez, M. P. (2009). Epicuticular lipids induce aggregation in Chagas disease vectors. Parasites Vectors 2:8. doi: 10.1186/1756-3305-2-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Lu, T., Qiu, Y.-T., Wang, G., Kwon, J. Y., Rützler, M., Kwon, H., et al. (2007). Odor coding in the maxillary palp of the malaria vector mosquito Anopheles gambiae. Curr. Biol. 17, 1533–1544. doi: 10.1016/j.cub.2007.07.062

PubMed Abstract | CrossRef Full Text | Google Scholar

Lyimo, I. N., and Ferguson, H. M. (2009). Ecological and evolutionary determinants of host species choice in mosquito vectors. Trends Parasitol. 25, 189–196. doi: 10.1016/j.pt.2009.01.005

PubMed Abstract | CrossRef Full Text | Google Scholar

MacKay, C. A., Sweeney, J. D., and Hillier, N. K. (2015). Olfactory receptor neuron responses of a longhorned beetle, Tetropium fuscum (Fabr.) (Coleoptera: Cerambycidae), to pheromone, host, and non-host volatiles. J. Insect Physiol. 83, 65–73. doi: 10.1016/j.jinsphys.2015.10.003

PubMed Abstract | CrossRef Full Text | Google Scholar

MacLeod, K., and Laurent, G. (1996). Distinct mechanisms for synchronization and temporal patterning of odor-encoding neural assemblies. Science 274, 976–979. doi: 10.1126/science.274.5289.976

PubMed Abstract | CrossRef Full Text | Google Scholar

Majeed, S., Hill, S. R., and Ignell, R. (2014). Impact of elevated CO2 background levels on the host-seeking behaviour of Aedes aegypti. J. Exp. Biol. 217, 598–604, doi: 10.1242/jeb.092718

PubMed Abstract | CrossRef Full Text | Google Scholar

Manrique, G., Vitta, A. C., Ferreira, R. A., Zani, C. L., Unelius, C. R., Lazzari, C. R., et al. (2006). Chemical communication in Chagas disease vectors. Source, identity, and potential function of volatiles released by the metasternal and Brindley's glands of Triatoma infestans adults. J. Chem. Ecol. 32, 2035–2052. doi: 10.1007/s10886-006-9127-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Martelli, C., Carlson, J. R., and Emonet, T. (2013). Intensity invariant dynamics and odor-specific latencies in olfactory receptor neuron response. J. Neurosci. 33, 6285–6297. doi: 10.1523/JNEUROSCI.0426-12.2013

PubMed Abstract | CrossRef Full Text | Google Scholar

Martin, J. P., Lei, H., Riffell, J. A., and Hildebrand, J. G. (2013). Synchronous firing of antennal-lobe projection neurons encodes the behaviorally effective ratio of sex-pheromone components in male Manduca sexta. J. Comp. Physiol. A 199, 963–979. doi: 10.1007/s00359-013-0849-z

PubMed Abstract | CrossRef Full Text | Google Scholar

Masante-Roca, I., Gadenne, C., and Anton, S. (2002). Plant odour processing in the antennal lobe of male and female grapevine moths, Lobesia botrana (Lepidoptera:Tortricidae). J. Insect Physiol. 48, 1111–1121. doi: 10.1016/S0022-1910(02)00204-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Matthews, B. J., McBride, C. S., DeGennaro, M., Despo, O., and Vosshall, L. B. (2016). The neurotranscriptome of the Aedes aegypti mosquito. BMC Genomics 17:32. doi: 10.1186/s12864-015-2239-0

PubMed Abstract | CrossRef Full Text | Google Scholar

May-Concha, I., Rojas, J. C., Cruz-López, L., Millar, J. G., and Ramsey, J. M. (2013). Volatile compounds emitted by Triatoma dimidiata, a vector of Chagas disease: chemical analysis and behavioural evaluation. Med. Vet. Entomol. 27, 165–174. doi: 10.1111/j.1365-2915.2012.01056.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Mboera, L. E. G., Takken, W., Mdira, K. Y., Chuwa, G. J., and Pickett, J. A. (2000). Oviposition and behavioral responses of Culex quinquefasciatus to Skatole and synthetic oviposition pheromone in Tanzania. J. Chem. Ecol. 26, 1193–1203. doi: 10.1023/A:1005432010721

CrossRef Full Text | Google Scholar

McCall, P. J., and Kelly, D. W. (2002). Learning and memory in disease vectors. Trends Parasitol. 18, 429–433. doi: 10.1016/S1471-4922(02)02370-X

PubMed Abstract | CrossRef Full Text | Google Scholar

McMeniman, C. J., Corfas, R. A., Matthews, B., Ritchie, S. A., and Vosshal, L. B. (2014). Multimodal integration of carbon dioxide and other sensory cues drives mosquito attraction to humans. Cell 156, 1060–1071. doi: 10.1016/j.cell.2013.12.044

PubMed Abstract | CrossRef Full Text | Google Scholar

McQuate, G. T. (2014). Green light synergistally enhances male sweetpotato weevil response to sex pheromone. Sci. Rep. 4:4499. doi: 10.1038/srep04499

PubMed Abstract | CrossRef Full Text | Google Scholar

Miller, J. R., and Gut, L. J. (2015). Mating disruption for the 21st Century: matching technology with mechanism. Environm. Entomol. 44, 427–453. doi: 10.1093/ee/nvv052

PubMed Abstract | CrossRef Full Text | Google Scholar

Minoli, S., Palottini, F., Crespo, J. G., and Manrique, G. (2013b). Dislodgement effect of natural semiochemicals released by disturbed triatomines: a possible alternative monitoring tool. J. Vector Ecol. 38, 353–360. doi: 10.1111/j.1948-7134.2013.12051.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Minoli, S., Palottini, F., and Manrique, G. (2013a). The main component of an alarm pheromone of kissing bugs plays multiple roles in the cognitive modulation of the escape response. Front. Behav. Neurosc. 7:77. doi: 10.3389/fnbeh.2013.00077

PubMed Abstract | CrossRef Full Text | Google Scholar

Mitsuno, H., Sakurai, T., Murai, M., Yasuda, T., Kugimiya, S., Ozawa, R., et al. (2008). Identification of receptors of main sex-pheromone components of three Lepidopteran species. Eur. J. Neurosci. 28, 893–902. doi: 10.1111/j.1460-9568.2008.06429.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Montagné, N., Chertemps, T., Brigaud, I., François, A., François, M. C., and de Fouchier, A. (2012). Functional characterization of a sex pheromone receptor in the pest moth Spodoptera littoralis by heterologous expression in Drosophila. Eur. J. Neurosci. 36, 2588–2596. doi: 10.1111/j.1460-9568.2012.08183.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Moore, S. J., and Lenglet, A. (2004). “Repellence and vector control,” in Traditional Medicinal Plants and Malaria, eds M. Wilcox, G. Bodeker, and P. Rasoanaivo (London: CRC Press; Taylor and Francis), 343–363.

Google Scholar

Mordue, A. J., Blackwell, A., Hansson, B. S., Wadhams, L. J., and Pickett, J. A. (1992). Behavioural and electrophysiological evaluation of oviposition attractants forCulex quinquefasciatus say (Diptera: Culicidae). Experientia 48, 1109–1111. doi: 10.1007/BF01947999

CrossRef Full Text

Mukabana, W. R. L., Mweresa, C. K., Otieno, B., Omusula, P., Smallegange, R. C., van Loon, J. J., et al. (2012). A novel synthetic odorant blend for trapping of malaria and other African mosquito species. J. Chem. Ecol. 38, 235–244. doi: 10.1007/s10886-012-0088-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Murlis, J., Elkinton, J. S., and Cardé, R. T. (1992). Odor plumes and how insects use them. Annu. Rev. Entomol. 37, 505–532. doi: 10.1146/annurev.en.37.010192.002445

CrossRef Full Text | Google Scholar

Najar-Rodriguez, A. J., Galizia, C. G., Stierle, J., and Dorn, S. (2010). Behavioral and neurophysiological responses of an insect to changing ratios of constituents in host plant-derived volatile mixtures. J. Exp. Biol. 213, 3388–3397. doi: 10.1242/jeb.046284

PubMed Abstract | CrossRef Full Text | Google Scholar

Namiki, S., Iwabuchi, S., and Kanzaki, R. (2008). Representation of a mixture of pheromone and host plant odor by antennal lobe projection neurons of the silkmoth Bombyx mori. J. Comp. Physiol. A 194, 501–515. doi: 10.1007/s00359-008-0325-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Napper, E., and Pickett, J. A. (2008). “Alarm Pheromones of Insects” in Encyclopedia of Entomology, ed J. Capinera (Netherlands: Springer), 85–95.

Nässel, D., and Homberg, U. (2006). Neuropeptides in interneurons of the insect brain. Cell Tissue Res. 326, 1–24. doi: 10.1007/s00441-006-0210-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Nikonov, A. A., and Leal, W. S. (2002). Peripheral coding of sex pheromone and behavioral antagonist in the Japanese beetle, Popillia japonica. J. Chem. Ecol. 28, 1075–1089. doi: 10.1023/A:1015274104626

PubMed Abstract | CrossRef Full Text | Google Scholar

Ochieng, S. A., Park, K. C., and Baker, T. C. (2002). Host plant volatiles synergize responses of sex pheromone-specific olfactory receptors neurons in male Helicoverpa zea. J. Comp. Physiol. A 188, 325–333. doi: 10.1007/s00359-002-0308-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Olberg, R. M. (1983). Pheromone triggered flip-flopping interneurons in the ventral nerve cord of the silkworm moth, Bombyx mori. J. Comp. Physiol. A 152, 297–307. doi: 10.1007/BF00606236

CrossRef Full Text | Google Scholar

Olsen, S. R., Bhandawat, V., and Wilson, R. I. (2010). Divisive normalization in olfactory population codes. Neuron 66, 287–299. doi: 10.1016/j.neuron.2010.04.009

PubMed Abstract | CrossRef Full Text | Google Scholar

Olson, J. F., Moon, R. D., and Kells, S. A. (2009). Off-host aggregation behavior and sensory basis of arrestment by Cimex lectularius (Heteroptera: Cimicidae). J. Insect Physiol. 55, 580–587. doi: 10.1016/j.jinsphys.2009.03.001

PubMed Abstract | CrossRef Full Text | Google Scholar

Papaj, D. R. (2009). “Learning,” in Encyclopedia of Insects, 2nd Edn, ed V. H. R. T. Cardé (San Diego, CA: Academic Press), 552–555.

Papaj, D. R., and Prokopy, R. J. (1989). Ecological and evolutionary aspects of learning in Phytophagous insects. Annu. Rev. Entomol. 34, 315–350. doi: 10.1146/annurev.en.34.010189.001531

CrossRef Full Text | Google Scholar

Pappenberger, B., Geier, M., and Boeckh, J. (1996). “Responses of antennal olfactory receptors in the yellow fever mosquito Aedes aegypti to human body odours,” in Olfaction in Mosquito-Host Interactions, eds G. R. Bock and G. Cardew (Wiley; Chichester: Ciba Foundation Symposium 2000), 254–266.

Pellegrino, M., Steinbach, N., Stensmyr, M. C., Hansson, B. S., Leslie, B., and Vosshall, L. (2011). A natural polymorphism alters odour and DEET sensitivity in an insect odorant receptor. Nature 478, 511–514. doi: 10.1038/nature10438

PubMed Abstract | CrossRef Full Text | Google Scholar

Pickett, J. A., Birkett, M. A., and Logan, J. G. (2008). DEET repels ornery mosquitoes. Proc. Natl. Acad. Sci. U.S.A. 105, 13195–13196. doi: 10.1073/pnas.0807167105

PubMed Abstract | CrossRef Full Text | Google Scholar

Pickett, J. A., Wadhams, L. J., and Woodcock, C. M. (1997). Developing sustainable pest control from chemical ecology. Agric. Ecosyst. Environ. 64, 149–156. doi: 10.1016/S0167-8809(97)00033-9

CrossRef Full Text | Google Scholar

Piñero, J., Galizia, C. G., and Dorn, S. (2008). Synergistic behavioral responses of female oriental fruit moths (Lepidoptera: Tortricidae) to synthetic host plant-derived mixtures are mirrored by odor-evoked calcium activity in their antennal lobes. J. Insect Physiol. 54, 333–343. doi: 10.1016/j.jinsphys.2007.10.002

PubMed Abstract | CrossRef Full Text | Google Scholar

Pregitzer, P., Schubert, M., Breer, H., Hansson, B. S., Sachse, S., and Krieger, J. (2012). Plant odorants interfere with detection of sex pheromone signals by male Heliothis virescens. Front. Cell Neurosci. 6:42. doi: 10.3389/fncel.2012.00042

PubMed Abstract | CrossRef Full Text | Google Scholar

Prokopy, R., and Papaj, D. R. (1988). Learning of apple fruit biotypes by apple maggot flies. J. Insect Behav. 1, 67–74. doi: 10.1007/BF01052504

CrossRef Full Text | Google Scholar

Qiu, Y.-T., Smallegange, R. C., Cajo, J. F., Braak, T., Spitzen, J., Van Loon, J. J. A., et al. (2007). Attractiveness of MM-X traps baited with human or synthetic odor to mosquitoes (Diptera: Culicidae) in the Gambia. J. Med. Entomol. 44, 970–983. doi: 10.1093/jmedent/44.6.970

PubMed Abstract | CrossRef Full Text | Google Scholar

Raffa, K. F., Powell, E. N., and Townsend, P. A. (2013). Temperature-driven range expansion of an irruptive insect heightened by weakly coevolved plant defenses. Proc. Natl. Acad. Sci. U.S.A. 110, 2193–2198. doi: 10.1073/pnas.1216666110

PubMed Abstract | CrossRef Full Text | Google Scholar

Rath, L., Galizia, C. G., and Szyszka, P. (2011). Multiple memory traces after associative learning in the honey bee antennal lobe. Eur. J. Neurosci. 34, 352–360. doi: 10.1111/j.1460-9568.2011.07753.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Reinhardt, K., and Siva-Jothy., M. T. (2007). Biology of the bed bugs (Cimicidae). Annu. Rev. Entomol. 52, 351–374. doi: 10.1146/annurev.ento.52.040306.133913

PubMed Abstract | CrossRef Full Text | Google Scholar

Reisenman, C., Riffell, J., Duffy, K., Pesque, A., Mikles, D., and Goodwin, B. (2013). Species-specific effects of herbivory on the oviposition behavior of the moth Manduca sexta. J. Chem. Ecol. 39, 76–89. doi: 10.1007/s10886-012-0228-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Reisenman, C. E. (2014). Hunger is the best spice: effects of starvation in the antennal responses of the blood-sucking bug Rhodnius prolixus. J. Insect Physiol. 71, 8–13. doi: 10.1016/j.jinsphys.2014.09.009

PubMed Abstract | CrossRef Full Text | Google Scholar

Reisenman, C. E., Christensen, T. A., Francke, W., and Hildebrand, J. G. (2004). Enantioselectivity of projection neurons innervating identified olfactory glomeruli. J. Neurosci. 24, 2602–2611. doi: 10.1523/JNEUROSCI.5192-03.2004

PubMed Abstract | CrossRef Full Text | Google Scholar

Reisenman, C. E., Christensen, T. A., and Hildebrand, J. G. (2005). Chemosensory selectivity of output neurons innervating an identified, sexually isomorphic olfactory glomerulus. J. Neurosci. 25, 8017–8026. doi: 10.1523/JNEUROSCI.1314-05.2005

PubMed Abstract | CrossRef Full Text | Google Scholar

Reisenman, C. E., Dacks, A., and Hildebrand, J. (2011). Local interneuron diversity in the primary olfactory center of the moth Manduca sexta. J. Comp. Physiol. A 197, 653–665. doi: 10.1007/s00359-011-0625-x

PubMed Abstract | CrossRef Full Text | Google Scholar

Reisenman, C. E., Heinbockel, T., and Hildebrand, J. G. (2008). Inhibitory interactions among olfactory glomeruli do not necessarily reflect spatial proximity. J. Neurophysiol. 100, 554–564. doi: 10.1152/jn.90231.2008

PubMed Abstract | CrossRef Full Text | Google Scholar

Reisenman, C. E., and Riffell, J. A. (2015). The neural bases of host plant selection in a Neuroecology framework. Front. Physiol. 12:229. doi: 10.3389/fphys.2015.00229

CrossRef Full Text

Reisenman, C. E., Riffell, J. A., Bernays, E. A., and Hildebrand, J. G. (2010). Antagonistic effects of floral scent in an insect-plant interaction. Proc. R. Soc. B 277, 2371–2379. doi: 10.1098/rspb.2010.0163

PubMed Abstract | CrossRef Full Text | Google Scholar

Riffell, J. A. (2012). Olfactory ecology and the processing of complex mixtures. Curr. Opin. Neurobiol. 22, 236–242. doi: 10.1016/j.conb.2012.02.013

PubMed Abstract | CrossRef Full Text | Google Scholar

Riffell, J. A., Alarcon, L., Abrell, J. L., Bronstein, J., Davidowitz, G., and Hildebrand, J. G. (2008). Behavioral consequences of innate preferences and olfactory learning in hawkmoth-flower interactions. Proc. Natl. Acad. Sci. U.S.A. 105, 3404–3409. doi: 10.1073/pnas.0709811105

PubMed Abstract | CrossRef Full Text | Google Scholar

Riffell, J. A., Lei, H., Abrell, J. L., and Hildebrand, J. G. (2013). Neural basis of a pollinator's buffet: olfactory specialization and learning in Manduca sexta. Science 339, 200–204. doi: 10.1126/science.1225483

PubMed Abstract | CrossRef Full Text | Google Scholar

Riffell, J. A., Lei, H., Christensen, T. A., and Hildebrand, J. G. (2009b). Characterization and coding of behaviorally significant odor mixtures. Curr. Biol. 19, 335–340. doi: 10.1016/j.cub.2009.01.041

PubMed Abstract | CrossRef Full Text | Google Scholar

Riffell, J. A., Lei, H., and Hildebrand, J. G. (2009a). Neural correlates of behavior in the moth Manduca sexta in response to complex odors. Proc. Natl. Acad. Sci. U.S.A. 106, 19219–19226. doi: 10.1073/pnas.0910592106

PubMed Abstract | CrossRef Full Text | Google Scholar

Riffell, J. A., Shlizerman, E., Sanders, E., Abrell, J. L., Medina, B., Hinterwirth, A. J., et al. (2014). Flower discrimination by pollinators in a dynamic chemical environment. Science 344, 1515–1518. doi: 10.1126/science.1251041

PubMed Abstract | CrossRef Full Text | Google Scholar

Roitberg, B. D., and Prokopy, R. J. (1981). Experience required for pheromone recognition by the apple maggot fly. Nature 292, 540–541. doi: 10.1038/292540a0

CrossRef Full Text | Google Scholar

Root, C. M., Ko, K. I., Jafari, A., and Wang, J. W. (2011). Presynaptic facilitation by neuropeptide signaling mediates odor-driven food search. Cell 145, 133–144. doi: 10.1016/j.cell.2011.02.008

PubMed Abstract | CrossRef Full Text | Google Scholar

Rospars, J. P., and Hildebrand, J. G. (2000). Sexually dimorphic and isomorphic glomeruli in the antennal lobes of the sphinx moth Manduca sexta. Chem. Senses 25, 119–129. doi: 10.1093/chemse/25.2.119

PubMed Abstract | CrossRef Full Text | Google Scholar

Roussel, E., Carcaud, J., Combe, M., Giurfa, M., and Sandoz, J.-C. (2014). Olfactory coding in the honeybee lateral horn. Curr. Biol. 24, 561–567. doi: 10.1016/j.cub.2014.01.063

PubMed Abstract | CrossRef Full Text | Google Scholar

Rouyar, A., Deisig, N., Dupuy, F., Limousin, D., Wycke, M. A., Renou, M., et al. (2015). Unexpected plant odor responses in a moth pheromone system. Front. Physiol. 6:148. doi: 10.3389/fphys.2015.00148

PubMed Abstract | CrossRef Full Text | Google Scholar

Rusch, C., Broadhead, G. T., Raguso, R. A., and Riffell, J. A. (2016). Olfaction in context—sources of nuance in plant–pollinator communication. Curr. Opin. Insect Sci. 15, 53–60. doi: 10.1016/j.cois.2016.03.007

CrossRef Full Text | Google Scholar

Ryelandt, J., Noireau, F., and Lazzari, C. R. (2011). A multimodal bait for trapping blood-sucking arthropods. Acta Trop. 117, 131–136. doi: 10.1016/j.actatropica.2010.11.005

PubMed Abstract | CrossRef Full Text | Google Scholar

Rytz, R., Croset, V., and Benton, R. (2013). Ionotropic receptors (IRs): chemosensory ionotropic glutamate receptors in Drosophila and beyond. Insect Biochem. Mol. Biol. 43, 888–897. doi: 10.1016/j.ibmb.2013.02.007

PubMed Abstract | CrossRef Full Text | Google Scholar

Sachse, S., Rueckert, E., Keller, A., Okada, R., Tanaka, N. K., Ito, K., et al. (2007). Activity-dependent plasticity in an olfactory circuit. Neuron 56, 838–850. doi: 10.1016/j.neuron.2007.10.035

PubMed Abstract | CrossRef Full Text | Google Scholar

Sadek, M. M., Hansson, B. S., Rospars, J. P., and Anton, S. (2002). Glomerular representation of plant volatiles and sex pheromones components in the antennal lobe of the female Spodoptera littoralis. J. Exp. Biol. 205, 1363–1376.

PubMed Abstract | Google Scholar

Sanford, M. R., Olson, J. K., Lewis, W. J., and Tomberlin, J. K. (2013). The effect of sucrose concentration on olfactory-based associative learning in Culex quinquefasciatus Say (Diptera: Culicidae). J. Insect Behav. 26, 494–513. doi: 10.1007/s10905-012-9368-y

CrossRef Full Text | Google Scholar

Sanford, M. R., and Tomberlin, J. K. (2011). Conditioning individual mosquitoes to an odor: sex, source, and time. PLoS ONE 6:e24218. doi: 10.1371/journal.pone.0024218

PubMed Abstract | CrossRef Full Text | Google Scholar

Sato, K., Pellegrino, M., Nakagawa, T., Nakagawa, T., Vosshall, L. B., and Touhara, K. (2008). Insect olfactory receptors are heteromeric ligand-gated ion channels. Nature 452, 1002–1006. doi: 10.1038/nature06850

PubMed Abstract | CrossRef Full Text | Google Scholar

Saveer, A. M., Kromann, S. H., Birgersson, G., Bengtsson, M., Lindblom, T., Balkenius, A., et al. (2012). Floral to green: mating switches moth olfactory coding and preference. Proc. R. Soc. B Biol. Sci 279, 2314–2322. doi: 10.1098/rspb.2011.2710

PubMed Abstract | CrossRef Full Text | Google Scholar

Schmera, D., and Guerin, P. M. (2012). Plant volatile compounds shorten reaction time and enhance attraction of the codling moth (Cydia pomonella) to codlemone. Pest Manag. Sci. 68, 454–461. doi: 10.1002/ps.2292

CrossRef Full Text | Google Scholar

Schröder, M. L., Glinwood, R., Webster, B., Ignell, R., and Krüger, K. (2015). Olfactory responses of Rhopalosiphum padi to three maize, potato, and wheat cultivars and the selection of prospective crop border plants. Entomol. Exp. Appl. 157, 241–253. doi: 10.1111/eea.12359

CrossRef Full Text | Google Scholar

Schroeder, R., and Hilker, M. (2008). The relevance of background odor in resource location by insects: a behavioral approach. Bioscience 58, 308–316. doi: 10.1641/B580406

CrossRef Full Text | Google Scholar

Seki, Y., and Kanzaki, R. (2008). Comprehensive morphological identification and GABA immunocytochemistry of antennal lobe local interneurons in Bombyx mori. J. Comp. Neurol. 506, 93–107. doi: 10.1002/cne.21528

PubMed Abstract | CrossRef Full Text | Google Scholar

Seki, Y., Rybak, J., Wicher, D., Sachse, S., and Hansson, B. S. (2010). Physiological and morphological characterization of local interneurons in the Drosophila antennal lobe. J. Neurophysiol. 104, 1007–1019. doi: 10.1152/jn.00249.2010

PubMed Abstract | CrossRef Full Text | Google Scholar

Smallegange, R. C., Qiu, Y. T., Van Loon, J. J. A., and Takken, W. (2005). Synergism between ammonia, lactic acid and carboxylic acids as kairomones in the host-seeking behaviour of the malaria mosquito Anopheles gambiae sensu stricto (Diptera: Culicidae). Chem. Senses 30, 145–152. doi: 10.1093/chemse/bji010

PubMed Abstract | CrossRef Full Text | Google Scholar

Sonenshine, D. E. (2006). Tick pheromones and their use in tick control. Annu. Rev. Entomol. 51, 557–580. doi: 10.1146/annurev.ento.51.110104.151150

PubMed Abstract | CrossRef Full Text | Google Scholar

Späthe, A., Reinecke, A., Haverkamp, A., Hansson, B. S., and Knaden, M. (2013). Host plant odors represent immiscible information entities-blend composition and concentration matter in hawkmoths. PLoS ONE 8:e77135. doi: 10.1371/journal.pone.0077135

PubMed Abstract | CrossRef Full Text | Google Scholar

Stanczyk, N. M., Brookfield, J. F., Ignell, R., Logan, J. G., and Field, L. M. (2010). Behavioral insensitivity to DEET in Aedes aegypti is a genetically determined trait residing in changes in sensillum function. Proc. Natl. Acad. Sci. U.S.A. 107, 8575–8580. doi: 10.1073/pnas.1001313107

PubMed Abstract | CrossRef Full Text | Google Scholar

Stanczyk, N. M., Brookfield, J. F. Y., Field, L. M., and Logan, J. G. (2013). Aedes aegypti mosquitoes exhibit decreased repellency by DEET following previous exposure. PLoS ONE 8:e54438. doi: 10.1371/journal.pone.0054438

PubMed Abstract | CrossRef Full Text | Google Scholar

Stange, G. (1997). Effects of changes in atmospheric carbon dioxide on the location of hosts by the moth, Cactoblastis cactorum. Oecologia 110, 539–545. doi: 10.1007/s004420050192

CrossRef Full Text | Google Scholar

Stange, G., Monro, J., Stowe, S., and Osmond, C. B. (1995). The CO2 sense of the moth Cactoblastis cactorum and its probable role in the biological control of the CAM plant Opuntia stricta. Oecologia 102, 341–352. doi: 10.1007/BF00329801

CrossRef Full Text | Google Scholar

Steib, B. M., Geier, M., and Boeckh, J. (2001). The effect of lactic acid on odour-related host preference of yellow fever mosquitoes. Chem. Senses 26, 523–528. doi: 10.1093/chemse/26.5.523

PubMed Abstract | CrossRef Full Text | Google Scholar

Stelinski, L. L., Gut, L. J., and Miller, J. R. (2005). Occurrence and duration of long-lasting peripheral adaptation among males of three species of economically important tortricid moths. Ann. Entomol. Soc. Am. 98, 580–586. doi: 10.1603/0013-8746(2005)098[0580:OADOLP]2.0.CO;2

CrossRef Full Text | Google Scholar

Stengl, M., and Funk, N. W. (2013). The role of the coreceptor Orco in insect olfactory transduction. J. Comp. Physiol. A 199, 897–909. doi: 10.1007/s00359-013-0837-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Stensmyr, M. C., Giordano, E., Balloi, A., Angioy, A. M., and Hansson, B. S. (2003). Novel natural ligands for Drosophila olfactory receptor neurones. J. Exp. Biol. 206, 715–724. doi: 10.1242/jeb.00143

PubMed Abstract | CrossRef Full Text | Google Scholar

Stierle, J. S., Galizia, C. G., and Szyszka, P. (2013). Millisecond stimulus onset-asynchrony enhances information about components in an odor mixture. J. Neurosci. 33, 6060–6069. doi: 10.1523/JNEUROSCI.5838-12.2013

PubMed Abstract | CrossRef Full Text | Google Scholar

Stranden, M., Rostelien, T., Liblikas, I., Almaas, T. J., Borg-Karlson, A. K., and Mustaparta, H. (2003). Receptor neurons in three heliothine moths responding to floral and inducible plant volatiles. Chemoecology 13, 143–154. doi: 10.1007/s00049-003-0242-4

CrossRef Full Text | Google Scholar

Su, C.-Y., Menuz, K., Reisert, J., and Carlson, J. R. (2012). Non-synaptic inhibition between grouped neurons in an olfactory circuit. Nature 492, 66–72. doi: 10.1038/nature11712

PubMed Abstract | CrossRef Full Text | Google Scholar

Suh, E., Bohbot, J. D., and Zwiebel, L. J. (2014). Peripheral olfactory signaling in insects. Curr. Opin. Insect Sci. 6, 86–92. doi: 10.1016/j.cois.2014.10.006

PubMed Abstract | CrossRef Full Text | Google Scholar

Suh, G. S., Wong, A. M., Hergarden, A. C., Wang, J. W., Simon, A. F., Benzer, S., et al. (2004). A single population of olfactory sensory neurons mediates an innate avoidance behaviour in Drosophila. Nature 431, 854–859. doi: 10.1038/nature02980

PubMed Abstract | CrossRef Full Text | Google Scholar

Syed, Z., and Leal, W. S. (2008). Mosquitoes smell and avoid the insect repellent DEET. Proc. Natl. Acad. Sci. U.S.A. 105, 13598–13603. doi: 10.1073/pnas.0805312105

PubMed Abstract | CrossRef Full Text | Google Scholar

Syed, Z., Pelletier, J., Flounders, E., Chitolina, R. F., and Leal, W. S. (2011). Generic insect repellent detector from the fruit fly Drosophila melanogaster. PLoS ONE 6:e17705. doi: 10.1371/journal.pone.0017705

PubMed Abstract | CrossRef Full Text | Google Scholar

Szyszka, P. (2014). Follow the odor. Science 344, 1454. doi: 10.1126/science.1255748

PubMed Abstract | CrossRef Full Text | Google Scholar

Szyszka, P., Gerkin, R. C., Galizia, C. G., and Smith, B. H. (2014). High-speed odor transduction and pulse tracking by insect olfactory receptor neurons. Proc. Natl. Acad. Sci. U.S.A. 111, 16925–16930. doi: 10.1073/pnas.1412051111

PubMed Abstract | CrossRef Full Text | Google Scholar

Szyszka, P., Stierle, J. S., Biergans, S., and Galizia, C. G. (2012). The speed of smell: odor-object segregation within milliseconds. PLoS ONE 7:e36096. doi: 10.1371/journal.pone.0036096

PubMed Abstract | CrossRef Full Text | Google Scholar

Tabuchi, M., Dong, L., Inoue, S., Namiki, S., Sakurai, T., and Nakatani, K., et al. (2015). Two types of local interneurons are distinguished by morphology, intrinsic membrane properties, and functional connectivity in the moth antennal lobe. J. Neurophysiol. 114, 3002–3013. doi: 10.1152/jn.00050.2015

PubMed Abstract | CrossRef Full Text | Google Scholar

Takken, W., Van Loon, J. J. A., and Adam, W. (2001). Inhibition of host-seeking response and olfactory responsiveness in Anopheles gambiae following blood feeding. J. Insect Physiol. 47, 303–310. doi: 10.1016/S0022-1910(00)00107-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Tanaka, N. K., Ito, K., and Stopfer, M. (2009). Odor-evoked neural oscillations in Drosophila are mediated by widely branching interneurons. J. Neurosci. 29, 8595–8603. doi: 10.1523/JNEUROSCI.1455-09.2009

PubMed Abstract | CrossRef Full Text | Google Scholar

Tanaka, N. K., Suzuki, E., Dye, L., Ejima, A., and Stopfer, M. (2012). Dye fills reveal additional olfactory tracts in the protocerebrum of wild-type Drosophila. J. Comp. Neurol. 520, 4131–4140. doi: 10.1002/cne.23149

PubMed Abstract | CrossRef Full Text | Google Scholar

Tasin, M., Bäckman, A. C., Coracini, M., Casado, D., Ioriatti, C., and Witzgall, P. (2007). Synergism and redundancy in a plant volatile blend attracting grapevine moth females. Phytochemistry 68, 203–209. doi: 10.1016/j.phytochem.2006.10.015

PubMed Abstract | CrossRef Full Text | Google Scholar

Tauxe, G., MacWilliam, D., Boyle, S. M., Guda, T., and Ray, A. (2013). Targeting a dual detector of skin and CO2 to modify mosquito host seeking. Cell 155, 1365–1379. doi: 10.1016/j.cell.2013.11.013

PubMed Abstract | CrossRef Full Text | Google Scholar

Thom, C., Guerenstein, P. G., Mechaber, W., and Hildebrand, J. G. (2004). Floral CO2 reveals flower profitability to moths. J. Chem. Ecol. 30, 1285–1288. doi: 10.1023/B:JOEC.0000030298.77377.7d

PubMed Abstract | CrossRef Full Text | Google Scholar

Thöming, G., Larsson, M. C., Hansson, B., and Anderson, P. (2013). Comparison of plant preference hierarchies of male and female moths and the impact of larval rearing hosts. Ecology 94, 1744–1752. doi: 10.1890/12-0907.1

PubMed Abstract | CrossRef Full Text | Google Scholar

Tomberlin, J. K., Rains, G. C., Allan, S. A., Sanford, M. R., and Lewis, W. J. (2006). Associative learning of odor with food-or blood-meal by Culex quinquefasciatus Say (Diptera: Culicidae). Naturwissenschaften 93, 551–556. doi: 10.1007/s00114-006-0143-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Trimble, R. M., and Marshall, D. B. (2010). Differences in the relationship between sensory adaptation of antennae and concentration of aerial pheromone in the oriental fruit moth and obliquebanded leafroller (Lepidoptera: Tortricidae): implications for the role of adaptation in sex pheromone-mediated mating disruption of these species. Environ. Entomol. 39, 625–632. doi: 10.1603/EN09178

PubMed Abstract | CrossRef Full Text | Google Scholar

Trona, F., Anfora, G., Balkenius, A., Bengtsson, M., Tasin, M., Knight, A., et al. (2013). Neural coding merges sex and habitat chemosensory signals in an insect herbivore. Proc. R. Soc. B Biol. Sci. 280:20130267. doi: 10.1098/rspb.2013.0267

PubMed Abstract | CrossRef Full Text | Google Scholar

Tsitoura, P., Koussis, K., and Iatrou, K. (2015). Inhibition of Anopheles gambiae odorant receptor function by mosquito repellents. J. Biol. Chem. 290, 7961–7972. doi: 10.1074/jbc.M114.632299

PubMed Abstract | CrossRef Full Text | Google Scholar

Tsuchihara, K., Fujikawa, K., Ishiguro, M., Yamada, T., Tada, C., Ozaki, K., et al. (2005). An odorant-binding protein facilitates odorant transfer from air to hydrophilic surroundings in the blowfly. Chem. Senses 30, 559–564. doi: 10.1093/chemse/bji049

PubMed Abstract | CrossRef Full Text | Google Scholar

Tumlinson, J. H., Brennan, M. M., Doolittle, R. E., Mitchell, E. R., Brabham, A., and Mazomenos, B. E. (1989). Identification of a pheromone blend attractive to Manduca sexta (L.) males in a wind tunnel. Arch. Insect Biochem. Physiol. 10, 255–271. doi: 10.1002/arch.940100402

CrossRef Full Text | Google Scholar

Turner, G. C., Bazhenov, M., and Laurent, G. (2008). Olfactory representations by Drosophila mushroom body neurons. J. Neurophysiol. 99, 734–746. doi: 10.1152/jn.01283.2007

PubMed Abstract | CrossRef Full Text | Google Scholar

Turner, S. L., Li, N., Guda, T., Githure, J., Cardé, R. T., and Ray, A. (2011). Ultra-prolonged activation of CO2-sensing neurons disorients mosquitoes. Nature 474, 87–91. doi: 10.1038/nature10081

PubMed Abstract | CrossRef Full Text | Google Scholar

van Breugel, F., and Dickinson, M. H. (2014). Plume-tracking behavior of flying Drosophila emerges from a set of distinct sensory-motor reflexes. Curr. Biol. 24, 274–286. doi: 10.1016/j.cub.2013.12.023

PubMed Abstract | CrossRef Full Text | Google Scholar

van Breugel, F., Riffell, J., Fairhall, A., and Dickinson, M. H. (2015). Mosquitoes use vision to associate odor plumes with thermal targets. Curr. Biol. 25, 2123–2129. doi: 10.1016/j.cub.2015.06.046

PubMed Abstract | CrossRef Full Text | Google Scholar

van der Goes van Naters, W., and Carlson, J. R. (2006). Insects as chemosensors of humans and crops. Nature 444, 302–307. doi: 10.1038/nature05403

PubMed Abstract | CrossRef Full Text | Google Scholar

Vandermoten, S., Mescher, M. C., Francis, F., Haubruge, E., and Verheggen, F. J. (2012). Aphid alarm pheromone: an overview of current knowledge on biosynthesis and functions. Insect Biochem. Mol. Biol. 42, 155–163. doi: 10.1016/j.ibmb.2011.11.008

PubMed Abstract | CrossRef Full Text | Google Scholar

Vickers, N. J., and Baker, T. C. (1997). Chemical communication in Heliothine moths VII Correlation between diminished responses to point source plumes and single filaments similarly tainted with a behavioural antagonist. J. Comp. Physiol. A 180, 523–536. doi: 10.1007/s003590050069

CrossRef Full Text | Google Scholar

Vickers, N. J., Christensen, T. A., and Hildebrand, J. G. (1998). Combinatorial odor discrimination in the brain: attractive and antagonist odor blends are represented in distinct combinations of uniquely identifiable glomeruli. J. Comp. Neurol. 400, 35–56.

PubMed Abstract | Google Scholar

Vinauger, C., Buratti, L., and Lazzari, C. R. (2011a). Learning the way to blood: first evidence of dual olfactory conditioning in a blood-sucking insect, Rhodnius prolixus. I. Appetitive learning. J. Exp. Biol. 214, 3032–3038. doi: 10.1242/jeb.056697

PubMed Abstract | CrossRef Full Text | Google Scholar

Vinauger, C., Buratti, L., and Lazzari, C. R. (2011b). Learning the way to blood: first evidence of dual olfactory conditioning in a blood-sucking insect, Rhodnius prolixus. II. Aversive learning. J. Exp. Biol. 214, 3039-3045. doi: 10.1242/jeb.057075

PubMed Abstract | CrossRef Full Text | Google Scholar

Vinauger, C., Lallement, H., and Lazzari, C. R. (2013). Learning and memory in Rhodnius prolixus: habituation and aversive operant conditioning of the proboscis extension response. J. Exp. Biol. 216, 892–900. doi: 10.1242/jeb.079491

PubMed Abstract | CrossRef Full Text | Google Scholar

Vinauger, C., Lutz, E. K., and Riffell, J. A. (2014). Olfactory learning and memory in the disease vector mosquito Aedes aegypti. J. Exp. Biol. 217, 2321–2330. doi: 10.1242/jeb.101279

PubMed Abstract | CrossRef Full Text | Google Scholar

Vogt, R. G., and Riddiford, L. M. (1981). Pheromone binding and inactivation by moth antennae. Nature 293, 161–163. doi: 10.1038/293161a0

PubMed Abstract | CrossRef Full Text | Google Scholar

Vosshall, L., Amrein, H., Morozov, P., Rzhetsky, A., and Axel, R. (1999). A spatial map of olfactory receptor expression in the Drosophila antenna. Cell 96, 725–736. doi: 10.1016/S0092-8674(00)80582-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Vosshall, L. B., and Hansson, B. S. (2011). A unified nomenclature system for the insect olfactory coreceptor. Chem. Senses 36, 497–498. doi: 10.1093/chemse/bjr022

PubMed Abstract | CrossRef Full Text | Google Scholar

Vosshall, L. B., and Stocker, R. F. (2007). Molecular architecture of smell and taste in Drosophila. Annu. Rev. Neurosci. 30, 505–533. doi: 10.1146/annurev.neuro.30.051606.094306

PubMed Abstract | CrossRef Full Text | Google Scholar

Vosshall, L. B., Wong, A. M., and Axel, R. (2000). An olfactory sensory map in the fly brain. Cell 102, 147–159. doi: 10.1016/S0092-8674(00)00021-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, J. W., Wong, A. M., Flores, J., Vosshall, L. B., and Axel, R. (2003). Two-photon calcium imaging reveals an odor-evoked map of activity in the fly brain. Cell 112, 271–282. doi: 10.1016/S0092-8674(03)00004-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, X., Zhong, M., and Liu, Q. (2013). Molecular characterization of the carbon dioxide receptor in the oriental latrine fly, Chrysomya megacephala (Diptera: Calliphoridae). Parasitol. Res. 112, 2763–2771. doi: 10.1007/s00436-013-3410-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Warren, B., and Kloppenburg, P. (2014). Rapid and slow chemical synaptic interactions of cholinergic projection neurons and GABAergic local interneurons in the insect antennal lobe. J. Neurosci. 34, 13039–13046. doi: 10.1523/JNEUROSCI.0765-14.2014

PubMed Abstract | CrossRef Full Text | Google Scholar

Watanabe, H. (2012). Spatio-temporal activity patterns of odor-induced synchronized potentials revealed by voltage-sensitive dye imaging and intracellular recording in the antennal lobe of the cockroach. Front. Syst. Neurosci. 6:55. doi: 10.3389/fnsys.2012.00055

PubMed Abstract | CrossRef Full Text | Google Scholar

Webster, B., Bruce, T., Pickett, J., and Hardie, J. (2010). Volatiles functioning as host cues in a blend become nonhost cues when presented alone to the black bean aphid. Anim. Behav. 79, 451–457. doi: 10.1016/j.anbehav.2009.11.028

CrossRef Full Text | Google Scholar

Wertheim, B., Baalen, E.-J., Dicke, M., and Vet, L. E. (2005). Pheremone-mediated aggregation in nonsocial arthropods: an evolutionary ecological perspective. Annu. Rev. Entomol. 50, 321–346. doi: 10.1146/annurev.ento.49.061802.123329

PubMed Abstract | CrossRef Full Text | Google Scholar

White, G. B. (2007). “Chapter 2: Terminology of insect repellents,” in Insect Repellents: Principles, Methods, and Uses, eds M. Debboun, S. P. Frances, and D. Strickman (Boca Raton, FL: CRC Press) 31–46.

Wicher, D., Schafer, R., Bauernfeind, R., Stensmyr, M. C., Heller, R., and Heinemann, S. H. (2008). Drosophila odorant receptors are both ligand-gated and cyclic-nucleotide-activated cation channels. Nature 452, 1007–1011. doi: 10.1038/nature06861

PubMed Abstract | CrossRef Full Text | Google Scholar

Willis, M. A., Avondet, J. L., and Zheng, E. (2011). The role of vision in odor-plume tracking by walking and flying insects. J. Exp. Biol. 214, 4121–4132. doi: 10.1242/jeb.036954

PubMed Abstract | CrossRef Full Text | Google Scholar

Wilson, D. A., and Sullivan, R. M. (2011). Cortical processing of odor objects. Neuron 72, 506–519. doi: 10.1016/j.neuron.2011.10.027

PubMed Abstract | CrossRef Full Text | Google Scholar

Wilson, J. K., Kessler, A., and Woods, H. A. (2015). Noisy communication via airborne infochemicals. Bioscience 65, 667–677. doi: 10.1093/biosci/biv062

CrossRef Full Text | Google Scholar

Wilson, R. I., and Laurent, G. (2005). Role of GABAergic inhibition in shaping odor-evoked spatiotemporal patterns in the drosophila antennal lobe. J. Neurosci. 25, 9069–9079. doi: 10.1523/JNEUROSCI.2070-05.2005

PubMed Abstract | CrossRef Full Text | Google Scholar

Winnington, A. P., Napper, R. M., and Mercer, A. (1996). Structural plasticity of identified glomeruli in the antennal lobes of the adult worker honey bee. J. Comp. Neurol. 365, 479–490.

PubMed Abstract | Google Scholar

Witzgall, P., Kirsch, P., and Cork, A. (2010). Sex pheromones and their impact on pest management. J. Chem. Ecol. 36, 80–100. doi: 10.1007/s10886-009-9737-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Wyatt, T. D. (2003). Pheromones and Animal Behavior: Communication by Smell and Taste. Cambridge: Cambridge University Press.

Xu, P., Choo, Y.-M., De La Rosa, A., and Leal, W. S. (2014). Mosquito odorant receptor for DEET and methyl jasmonate. Proc. Natl. Acad. Sci. U.S.A. 111, 16592–16597. doi: 10.1073/pnas.1417244111

PubMed Abstract | CrossRef Full Text | Google Scholar

Yao, C. A., Ignell, R., and Carlson, J. R. (2005). Chemosensory coding by neurons in the coeloconic sensilla of the Drosophila antenna. J. Neurosci. 25, 8359–8367. doi: 10.1523/JNEUROSCI.2432-05.2005

PubMed Abstract | CrossRef Full Text | Google Scholar

Yarnell, E., and Abascal, K. (2004). Botanical prevention and treatment of malaria, Part 1—herbal mosquito repellants. Altern. Complement. Ther. 10, 206–210. doi: 10.1089/1076280041580332

CrossRef Full Text | Google Scholar

Zars, T., Fischer, M., Schulz, R., and Heisenberg, M. (2000). Localization of a short-term memory in Drosophila. Science 288, 672–675. doi: 10.1126/science.288.5466.672

PubMed Abstract | CrossRef Full Text | Google Scholar

Zavada, A., Buckley, C. L., Martinez, D., Rospars, J. P., and Nowotny, T. (2011). Competition-based model of pheromone component ratio detection in the moth. PLosONE 6:e16308. doi: 10.1371/journal.pone.0016308

PubMed Abstract | CrossRef Full Text | Google Scholar

Zermoglio, P. F., Martin-Herrou, H., Bignon, Y., and Lazzari, C. R. (2015). Rhodnius prolixus smells repellents: behavioural evidence and test of present and potential compounds inducing repellency in Chagas disease vectors. J. Insect Physiol. 8, 137–144. doi: 10.1016/j.jinsphys.2015.07.012

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhang, J., Yan, S., Liu, Y., Jacquin-Joly, E., Dong, S., and Wang, G. (2015). Identification and functional characterization of sex pheromone receptors in the common cutworm (Spodoptera litura). Chem. Senses 40, 7–16. doi: 10.1093/chemse/bju052

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhang, P.-J., and Liu, S.-S. (2006). Experience induces a Phytophagous insect to lay eggs on a nonhost plant. J. Chem. Ecol. 32, 745–753. doi: 10.1007/s10886-006-9032-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: crop pest, disease vector, integrated pest management, odor attractant, disruption of behavior, odor repelllent, insect neuroethology

Citation: Reisenman CE, Lei H and Guerenstein PG (2016) Neuroethology of Olfactory-Guided Behavior and Its Potential Application in the Control of Harmful Insects. Front. Physiol. 7:271. doi: 10.3389/fphys.2016.00271

Received: 02 February 2016; Accepted: 16 June 2016;
Published: 30 June 2016.

Edited by:

Sylvia Anton, Institut National de la Recherche Agronomique, France

Reviewed by:

Rickard Ignell, Swedish University of Agricultural Sciences, Sweden
Andrey Nikolaevich Frolov, All-Russian Research Institute of Plant Protection, Russia

Copyright © 2016 Reisenman, Lei and Guerenstein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Pablo G. Guerenstein, pguerenstein@bioingenieria.edu.ar

Present Address: Hong Lei, School of Life Sciences, Arizona State University, Tempe, AZ, USA