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The neurobiology of insect olfaction: Sensory processing in a comparative context
Joshua P. Martin*, Aaron Beyerlein, Andrew M. Dacks1, Carolina E. Reisenman,
Jeffrey A. Riffell2, Hong Lei, John G. Hildebrand
Department of Neuroscience, College of Science, University of Arizona, 1040 East Fourth Street, Tucson, AZ 85721-0077, USA
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Olfactory world of an insect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Chemical composition of natural olfactory stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Spatio-temporal structure of olfactory stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Olfaction-based behavior of insects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Evolution and speciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Evolution of olfactory receptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Olfactory specialization and speciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Peripheral adaptations for olfactory specialization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Central adaptations for olfactory specialization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Central olfactory pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Antennal lobe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Inhomogeneous interactions between glomeruli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Higher-order olfactory centers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Progress in Neurobiology 95 (2011) 427–447
A R T I C L E
I N F O
Received 5 June 2011
Received in revised form 10 September 2011
Accepted 19 September 2011
Available online 24 September 2011
A B S T R A C T
The simplicity and accessibility of the olfactory systems of insects underlie a body of research essential to
understanding not only olfactory function but also general principles of sensory processing. As insect
olfactory neurobiology takes advantage of a variety of species separated by millions of years of evolution,
the field naturally has yielded some conflicting results. Far from impeding progress, the varieties of
insect olfactory systems reflect the various natural histories, adaptations to specific environments, and
the roles olfaction plays in the life of the species studied.
We review current findings in insect olfactory neurobiology, with special attention to differences
among species. We begin by describing the olfactory environments and olfactory-based behaviors of
insects, as these form the context in which neurobiological findings are interpreted. Next, we review
recent work describing changes in olfactory systems as adaptations to new environments or behaviors
promoting speciation. We proceed to discuss variations on the basic anatomy of the antennal (olfactory)
lobe of the brain and higher-order olfactory centers. Finally, we describe features of olfactory
information processing including gain control, transformation between input and output by operations
such as broadening and sharpening of tuning curves, the role of spiking synchrony in the antennal lobe,
and the encoding of temporal features of encounters with an odor plume. In each section, we draw
connections between particular features of the olfactory neurobiology of a species and the animal’s life
history. We propose that this perspective is beneficial for insect olfactory neurobiology in particular and
sensory neurobiology in general.
? 2011 Elsevier Ltd. All rights reserved.
Abbreviations: OR, olfactory receptor protein; ORC, olfactory receptor cell; Orco, olfactory coreceptor; AL, antennal lobe; LN, local interneuron; PN, projection neuron; OBP,
odorant-binding protein; MGC, macroglomerular complex; MB, mushroom body; LH, lateral horn of the protocerebrum; APT, antenno-protocerebral tract; MBC, mushroom
body calyx; LH, lateral horn; KC, kenyon cell; LAL, lateral accessory lobe; LFP, local field potential; AC, antennal commissure; ILPC, inferior lateral protocerebrum.
* Corresponding author. Tel.: +1 520 621 6643; fax: +1 520 621 8282.
E-mail address: firstname.lastname@example.org (J.P. Martin).
1Present address: Department of Neuroscience, Mount Sinai School of Medicine, New York, NY 10029, USA.
2Present address: Department of Biology, University of Washington, Seattle, WA 98195, USA.
Contents lists available at SciVerse ScienceDirect
Progress in Neurobiology
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Antenno-protocerebral tracts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Mushroom-body calyx. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Lateral horn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Protocerebrum and beyond. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Comparative coding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Gain control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Tuning/coding transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Sharpening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Broadening. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Sharpening versus broadening in two species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Synchrony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Encoding temporal features of olfactory stimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Olfaction plays a central role in insect behaviors of interest to
humans. Feeding and reproduction of insect pests, pollinators, and
vectors of disease are strongly regulated by the volatile organic
compounds (hereinafter ‘‘volatiles’’) an insect encounters. The toll
of malaria and other diseases mediated by insect vectors, famine
attributable to insect crop pests, and the alarming collapse of a
major pollinator species (honey bees) impels investigations into
the neurobiology underlying the sense of smell in insects (van
Naters and Carlson, 2006).
As a topic of study in neurobiology per se, olfaction shares the
benefits of all neurobiological research in insects and other
invertebrates: reduced numerical complexity of the nervous
system, the corresponding advantages of identifiable nerve cells
(Comer and Robertson, 2001) and neuropil structures, and a strong
connection between neurobiology and behavior. The shared
principles of organization and function of olfactory systems in
invertebrates and vertebrates (Ache and Young, 2005; Hildebrand
and Shepherd, 1997; Kaupp, 2010) make discoveries in insects of
general interest to researchers studying other animals.
In this review, we argue that the diversity of insect species
provides another benefit for the study of olfactory neurobiology.
Insects are believed to be the most speciose and diverse class of
animals on earth: approximately one million species are
currently described (and many more are expected to be found)
in 30 orders, separated by more than 400 million years of
evolution (Grimaldi and Engel, 2005 – see Fig. 1), adapted to more
environments and niches, and correspondingly expressing more
diverse behaviors, than any other closely related group of
animals. Most insect behavior relies to some degree on
chemosensory information. Research on the olfactory neurobiol-
ogy of insects has focused on flies, cockroaches, honey bees,
moths, and locusts, as well as other representative species from at
least seven orders spanning holometabola and hemimetabola
(respectively, insect taxa that undergo complete or incomplete
metamorphosis – see Fig. 1).
Converging evidence from multiple species maps out the
relatively simple, elegant structure of a ‘canonical’ insect olfactory
system. A single type of olfactory receptor protein (OR) with
characteristic affinity for volatiles is expressed in a subset of the
olfactory receptor cells (ORCs) housed in a head appendage (e.g.
antenna or palp). The axons of all ORCs expressing the same
receptor converge in a single glomerulus within the antennal lobe
(AL), processing and propagating olfactory information through
the first level of processing in the CNS. Glomeruli interact through
a population of local interneurons (LNs), many or most of which
are inhibitory, that shape the output of the AL conveyed by
projection neurons (PNs) to down-stream olfactory foci elsewhere
in the brain. At subsequent stages of neural processing,
glomerular output is integrated, and olfactory information is
formatted for memory and association with other modalities and
ultimately drives or modulates the activity of circuits that control
For nearly every one of these canonical principles of structure
and function of insect olfactory systems, an exception can be found
among insect species. Some ORCs express multiple receptors
(Benton et al., 2009; Couto et al., 2005; Fishilevich and Vosshall,
2005; Vosshall et al., 2000), and in a few species ORC axons
terminate within multiple, overlapping sets of glomeruli (Anton
and Hansson, 1996). Glomeruli in the honey-bee AL interact
through a network of histaminergic local neurons not found in
insects outside of the Hymenoptera (Dacks et al., 2010). Glomeruli
may excite rather than inhibit their neighbors, partially decoupling
the output of the AL from the input patterns of ORCs (Olsen et al.,
2007). Output from the AL to higher-order centers follows non-
homologous pathways in different species, with an underlying
organization that almost certainly has consequences for olfactory
processing (Galizia and Ro ¨ssler, 2010).
Far from impeding investigations into the neurobiology of
olfaction, the diversity of insect models offers a suite of ‘‘natural
experiments’’ wherein olfactory systems have evolved to perform
efficiently the tasks most crucial to the animal’s survival. Natural
behavior reveals how an animal uses olfactory information: what
is emphasized, what is filtered out, and what is integrated or
extracted from the background. Insects present perhaps the
greatest range of behaviors mediated by volatile chemicals.
Included in this single class are species that use olfaction very
little or perhaps not at all and have correspondingly reduced brain
structures (c.f. Strausfeld et al., 1998), species highly specialized on
a plant or animal food source or host (c.f. Dekker et al., 2006), and
species with remarkable abilities to associate new food resources
with corresponding olfactory cues (c.f. Dukas, 2008; Giurfa, 2007).
Correlating unique or exaggerated olfactory behavior with unique
or exaggerated features of olfactory systems can be a powerful tool.
Insects offer exceptionally fertile grounds for such a comparative
In this review, we consider the remarkable progress of research
on the anatomy, physiology, and information processing in the
olfactory systems of insects in a comparative context. We begin
with a discussion of the quality and temporal structure of olfactory
stimuli important to various insects (Section 2). We survey the
olfaction-based behaviors exhibited by insects in their natural
environments, especially those that demonstrate the challenges
faced by an olfactory system (Section 3). Next we examine recent
evidence of how the OR repertoire is shaped by both the salience of
volatiles in an insect’s ecological niche and the roles of those
compounds in the insect’s evolutionary history (Section 4).
J.P. Martin et al. / Progress in Neurobiology 95 (2011) 427–447
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Information is passed and processed from ORCs, through the
primary olfactory center (the AL), to higher-order foci in the
protocerebrum. We highlight idiosyncrasies in structure and
function of these areas and the insights about olfactory processing
they provide (Section 5). In the final section (Section 6), we suggest
that insects employ neural codes for olfactory stimuli and
processing mechanisms that reflect the demands presented both
by their environment and by the structure and function of the
neural systems that produce those codes.
2. Olfactory world of an insect
Natural, behaviorally significant olfactory stimuli typically are
mixtures of volatiles whose concentrations co-vary dynamically in
time and space. The volatiles released by conspecifics, food
sources, and oviposition hosts are chemically diverse, and
mixtures often contain compounds unique to their source, as well
as volatiles common to the chemical signature of multiple sources
(c.f. Bruce et al., 2005; Raguso, 2008). The olfactory world is also an
arena of constant movement and flux. Once emitted by a source,
volatiles are dispersed, mixed, and diluted by the ambient motion
of air to form a shifting and filamentous plume. In this section, we
review new insights into the physico-chemical properties of
selected volatiles that have known roles in insect behavior.
Identification and description of behaviorally relevant volatiles as
they are received by insects establish additional parameters for
investigation of olfactory neurobiology.
2.1. Chemical composition of natural olfactory stimuli
Contemporary analytical technology has revealed considerable
chemical diversity in the olfactory world of insects. Analytical tools
are particularly powerful when directly combined with neuro-
physiological (e.g. Ghaninia et al., 2008) or behavioral (e.g.
Allmann and Baldwin, 2010; Turlings et al., 2004) assays to
identify effective volatiles in a complex mixture released by a
source. These studies also reveal commonality among olfactory
stimuli. For example, olfactory systems of phytophagous insects
across many orders respond to many of the same, ubiquitous plant
volatiles despite biases toward different hosts, suggesting that
complex, higher-order properties of olfactory stimuli are necessary
for volatile source identification (Bruce et al., 2005; Raguso, 2008).
2.2. Spatio-temporal structure of olfactory stimuli
Immediately following their emission from a source, volatiles
become subject to the physical forces of moving air that impose
structure on them. At spatial scales greater than 1 cm the olfactory
environment is dynamic. Both fluid-dynamic analysis and
analytic technologies have shown that a plume of volatiles is
not a uniform concentration gradient but rather a filamentous and
discontinuous structure containing regions of volatile-laden air
interspersed with regions of volatile-free air (Murlis and Jones,
1981; Riffell et al., 2008a). Insect olfactory systems apparently
have evolved to process the resulting intermittent olfactory
Fig. 1. The phylogeny of the neopteran insects (after Grimaldi and Engel, 2005), highlighting orders most commonly studied in olfactory neurobiology. The four orders most
commonly used in studies of central olfactory neurobiology (Orthoptera, Hymenoptera, Diptera, and Lepidoptera) are highlighted in large font, and the lineage connecting
them is bolded in the phylogenetic tree. Three additional orders, less commonly studied but nonetheless important, are highlighted in bold (Blattaria, Hemiptera, and
Coleoptera). Numbers along the timeline indicate deep time events for reference (Grimaldi and Engel, 2005; Williams et al., 2010). Model animals from each of the four most
commonly used orders are depicted in the inset photos: (A) S. americana (‘‘locust’’) (B) A. mellifera (‘‘honey-bee’’) (C) D. melanogaster (‘‘fruit fly’’) and (D) M. sexta
(‘‘hawkmoth’’). Photos: Charles Hedgcock.
J.P. Martin et al. / Progress in Neurobiology 95 (2011) 427–447
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stimuli, and similarities in behavior and neural processing are
noteworthy in phylogenetically distant species (Budick and
Dickinson, 2006; Carde ´ and Willis, 2008).
The ability of many insects to track a discontinuous olfactory
stimulus and locate its unseen source is based on a common search
strategy comprising alternating crosswind ‘casts’ to locate
volatiles, and upwind ‘surges’ following contact with volatiles
(Murlis et al., 1992). In searching for the source of behaviorally
significant volatiles, moths and flies use this strategy over
landscape scales (Reynolds and Frye, 2007; Reynolds et al.,
2007), and their flight paths resemble a mathematically optimal
search strategy (Reynolds, 2005) for following a plume of volatiles.
Insects rely on the information contained in plume structure to
varying degrees when searching for a source: in an artificially
homogeneous plume that lacks spatio-temporal structure, flies
navigate upwind to the source (Budick and Dickinson, 2006), but
many moths are unsuccessful (Willis and Baker, 1984). In addition,
the temporal patterns in which insects encounter volatiles are
affected by the size and velocity of the animal (Koehl, 2001, 2006),
active interaction with the plume by wing beating (Loudon and
Koehl, 2000; Sane, 2006; Sane and Jacobson, 2006), and antennal
flicking (Hillier and Vickers, 2004; Nishiyama et al., 2007; see also
Dethier, 1987). Olfactory stimuli that are important for insects thus
have chemical and temporal characteristics particular to each
species. Investigations in olfactory neurobiology should consider
these features in designing and interpreting experiments.
3. Olfaction-based behavior of insects
A goal of efforts to understand the olfactory neurobiology of
insects is to analyze neural mechanisms that underlie olfaction-
modulated behavior. In addition, a clear description of the
problems an olfactory system must solve in the natural world
provides the parameters for investigations into neural processing
of olfactory information. In general, olfaction-based behavior
critical for survival and reproduction first involves recognition
(either innate or learned) of a significant olfactory stimulus.
Subsequent processing takes into account the context of the
sensation, both the external environment and the internal state of
Much has been gained by studying the innate responses of
insects to olfactory cues. Heritable, stereotyped, robust behavioral
output, and the consistent neural architecture that underlies it,
are hallmarks of insect neurobiology and of olfactory neurobiolo-
gy in particular. The pheromonal signals that guide many insects
to conspecific mating partners have been studied most thorough-
ly, and recent work has continued to expand on the complexity
and diversity of these signals. The chemical identity of insect
pheromones can be as simple as the monomolecular compound
11-cis-vaccenyl acetate, an apparently multifunctional phero-
mone that mediates aggregation in Drosophila melanogaster
(Bartelt et al., 1985; Wertheim et al., 2002), indicates to males
the mating state of a female (Ejima et al., 2007; Ha and Smith,
2006) and increases female receptiveness to male courtship
attempts (Kurtovic et al., 2007), or as complex as the mixtures of
sex-pheromone components released by some adult female
moths (Baker, 2008; Vickers et al., 1998) and beetles (Leal,
1996; Yuko and Walter, 2008). The Hymenoptera employ perhaps
the greatest variety of social olfactory signals studied thus far (Le
Conte and Hefetz, 2008; Slessor et al., 2005). In honey bees, for
example, recent work has elaborated how pheromones organize
the defense of the hive (Hunt, 2007), recruit foragers (Thom et al.,
2007), and reinforce the primacy of the queen (Strauss et al., 2008;
Vergoz et al., 2007). The diversity of volatile semiochemicals and
cuticular hydrocarbons used by ants (Hymenoptera: Formicidae),
and their roles in behaviors ranging from recognition and
navigation to alarm and courtship remain an active area of study
(c.f. Endler et al., 2004; recently reviewed in Ho ¨lldobler and
Wilson, 2009). Recent advances in the field have extended to the
neuroanatomy (Zube et al., 2008) and neurophysiology (Yamagata
and Mizunami, 2010) of the olfactory system in ants. Evidence of
cues for intraspecific communication in other insects, such as
stimuli described as stress-, aggregation-, and sex-related
pheromones in D. melanogaster (Bartelt et al., 1985; Ejima
et al., 2007; Suh et al., 2007, 2004), has been accumulating.
Two common threads emerge: these signals often are complex
mixtures of volatiles, with multiple physical and behavioral
effects (Ferveur, 2005; Siwicki et al., 2005; Slessor et al., 1990),
and processing of the stimuli may be segregated anatomically
(Jefferis et al., 2007; Seki et al., 2005) or by the expression of
common genes, as in the case of D. melanogaster stress (Suh et al.,
2004) and sex pheromones (Manoli et al., 2005).
Finally, insects are innately attracted to the complex odors of
certain host animals (e.g. Zwiebel and Takken, 2004) or plants (e.g.
Raguso and Willis, 2002), suggesting that foraging, like social
behavior, relies on heritable responses to olfactory stimuli. Insects
also can learn associations between volatile stimuli and rewards in
the natural environment. These abilities often are related to the
demands of the animal’s environment, e.g. the diversity of food
sources. Honey bees can learn the scent of flowers that are
profitable to visit (i.e. are yielding nectar and/or pollen) at any
time, either through direct experience (Chittka and Raine, 2006) or
by exposure to the volatiles associated with nectar or pollen
transferred to prospective foragers by returning bees during the
waggle-dance (Farina et al., 2007; Gil and De Marco, 2005). Locusts
are voracious, generalist feeders, with a robust ability to associate
olfactory stimuli with the quantity and nutritional quality of food
sources (Behmer et al., 2005). The sphinx moth Manduca sexta
exhibits an innate attraction to, and preference for, certain host
flowers but can learn to feed from others when the preferred
flowers are scarce (Riffell et al., 2008b). Finally, in two related
species of parasitic wasps, the ability to associate volatiles with the
presence of host caterpillars correlates with the behavioral
plasticity demanded by the distribution of their respective host
species (Bleeker et al., 2006; Smid et al., 2007). Although the
particular form and capacity for olfactory learning vary among the
insects, the benefits for growth (Dukas and Bernays, 2000) and
mating success (Dukas, 2005) suggest that learning is widespread.
Whether an olfaction-based behavior is innate or learned, its
expression may be affected by the context in which the olfactory
stimulus is experienced. A single volatile often has little effect on
insect behavior when detected in isolation but gains behavioral
significance in the context of other volatiles. In response to
herbivory by the sawfly Diprion pini, the Scots pine tree emits
elevated quantities of the terpenoid (E)-b-farnesene (Mumm and
Hilker, 2005). While neither (E)-b-farnesene nor the other head-
space volatiles of the Scots pine tree are attractive to parasitoids of
D. pini, mixtures of (E)-b-farnesene with other head-space
volatiles are highly attractive to the parasitic wasp Chrysonotomyia
ruforum (Mumm and Hilker, 2005). Volatiles also may elicit
different behaviors in different contexts. For example, 11-cis-
vaccenyl acetate acts as an aggregation pheromone for D.
melanogaster in the context of plant volatiles (Bartelt et al.,
1985) and inhibits mating in the context of other males or mated
females (Jallon et al., 1981).
responses based on the internal physiological state of an individual
insect. Many factors, such as age, time in the circadian cycle, and
feeding and mating status, may change the salience or association
of stimuli that are important for the survival of an individual insect.
Thus the nervous system must temper its sensitivity, resolution, or
precision to suit the needs of the individual based on the current
J.P. Martin et al. / Progress in Neurobiology 95 (2011) 427–447
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physiological or behavioral context (Anton et al., 2007; Bodin et al.,
2008). Attraction to olfactory stimuli can be diminished after
mating (e.g. male moth Agrotis ipsilon; Barrozo et al., 2010;
Gadenne et al., 2001) or feeding (e.g. female mosquito Anopheles
gambiae; Klowden, 1996). The neural mechanisms underlying
these similar behavioral changes appear, respectively, to be central
(i.e. decreased response of AL neurons; Gadenne et al., 2001) and
peripheral (i.e. decreased antennal sensitivity; Takken et al., 2001)
owing to down-regulation of olfactory-receptor proteins (Fox et al.,
2001). Innate attraction to food odors in D. melanogaster is
mediated chiefly by a single glomerulus (Semmelhack and Wang,
2009). Recent work has demonstrated a mechanism in which
hunger, signaled by low insulin, upregulates a peptide receptor on
the ORCs innervating this glomerulus, facilitating vesicle release
and ultimately influencing the animal to search for food (Root et al.,
2011). Finally, locusts exhibit state-dependent valuation of food
resources, such that the locust Schistocerca gregaria prefers
volatiles associated with food last encountered when the animal
was nutrient stressed (Pompilio et al., 2006). Thus, different neural
mechanisms can produce similar behavioral effects, and the
internal state of an insect likely alters olfactory function at
multiple levels, in different ways for different species.
Insects offer numerous case studies, each revealing connections
among olfactory stimuli, neural mechanisms, and behavior. A
comprehensive description of natural, olfaction-based behaviors
and of the volatiles that control or modulate them can guide
experimental analysis of the neural mechanisms that underlie
olfactory guided behaviors.
4. Evolution and speciation
Insects have evolved richly diverse olfaction-based behaviors as
adaptations to diverse ecological challenges and opportunities and
exhibit correspondingly diverse olfactory structures and mecha-
nisms. A first step toward understanding the differences in the
olfactory neurobiology of different insect taxa is to question how
these differences may have arisen through evolution. Recent work
in closely related species has described changes in olfactory
processing that accompany speciation, and a picture of olfactory
system evolution in insects is emerging.
4.1. Evolution of olfactory receptors
Insect ORs appear to be functionally and genetically distinct
from those discovered in other taxa (Touhara and Vosshall, 2009).
The topology of insect ORs is inverted within the cell membrane
with respect to the N-terminal orientation of the classical G-
protein-coupled receptor structure exhibited by mammalian ORs.
Binding of volatile molecules by insect ORs is accomplished by a
heterodimeric complex of one ‘typical’ insect OR and one ‘common’
receptor expressed in nearly all ORCs, designated Or83b in D.
melanogaster (Benton et al., 2006). Or83b and its orthologues,
hereafter ‘‘Orco’’ (after Vosshall and Hansson, 2011), are necessary
for both ORC function (Jones et al., 2005; Larsson et al., 2004) and
trafficking of ORs to and insertion in the membrane of ORC cilia.
Recent work has suggested that this heterodimeric complex itself
serves as an ion channel that might be both ligand- and cyclic-
nucleotide-activated (Nakagawa and Vosshall, 2009; Sato et al.,
2008; Wicher et al., 2008). Both the heterodimeric pairing of an
insect OR and an Orco protein, and the sequence of the Orco gene,
are highly conserved among insects studied to date (Jones et al.,
2005; Krieger et al., 2003; Melo et al., 2004; Nakagawa et al., 2005;
Pitts et al., 2004; Robertson et al., 2010). Experiments in which
Orco genes from other insects rescue receptor-neuron responses in
mutant D. melanogaster lacking copies of Or83b demonstrate that
the function of Orco proteins is conserved. (Jones et al., 2005).
From this common point, the OR repertoire of insects diverges.
Intraspecies OR sequences are very diverse. The amino-acid
sequences of ORs in D. melanogaster are only 15% similar on
average (Robertson et al., 2003), illustrating the diversity of ORs
needed to detect and discriminate a wide variety of volatiles. The
response of an ORC expressing one of these ORs, processed through
synaptic circuitry in the olfactory pathways of the CNS, forms the
basis for encoding all relevant volatile stimuli in the animal’s
environment. How OR tuning in animals with widely different
olfactory environments has evolved is still poorly understood, but
much progress has been made in describing how the OR repertoire
of species within a group diverges.
An insect’s ORs are products of evolutionary pressures and
processes that enhance, remove, or alter receptor-protein expres-
sion in ORCs. The growing number of genomes available for species
in the genus Drosophila provides the best example of this process.
Odorant-binding proteins (OBPs; Vieira et al., 2007) and ORs
(Nozawa and Nei, 2007) are subject to ‘‘birth and death’’ evolution,
wherein new genes are produced through duplication and
modification, and some genes ‘‘die off’’ by deletion or mutation
to pseudogenes. Certain species of fruit flies in the genus
Drosophila, however, exhibit remarkable conservation of ortholo-
gous OR groups, sharing 22–79% sequence similarity (Guo and Kim,
2007). Many of the differences between orthologous ORs are
attributable to synonymous substitution, suggesting that the
function of these ORs is conserved between groups. In fact, the
molecular receptive ranges (olfactory ‘‘tuning’’) of ORCs in the
large basiconic sensilla of several Drosophila species appear to be
nearly identical (Stensmyr et al., 2003). In comparison, while the
mosquito species A. gambiae and Aedes aegypti share 21
orthologous ORs, only one of these is shared with D. melanogaster
(Bohbot et al., 2007). Based on these findings, Guo and Kim (2007)
proposed that the ORs conserved between species constitute a
‘‘basis set’’ (Pouget and Sejnowski, 1997), in analogy with the three
cone receptors for color vision. A basis set is a set of coding units
that, together, can be combined to produce a unique code for any
olfactory stimulus ‘object’ an animal may encounter. Although we
make no formal claim that ORs fit all of the requirements of a basis
set, we note that coding schemes involving true basis functions
have been proposed for olfaction (Hopfield, 1995).
4.2. Olfactory specialization and speciation
The marked dependence of many insect species on one or a few
plant species for feeding and/or oviposition is a common basis for
reproductive isolation and thus is likely to accompany speciation
(Berlocher and Feder, 2002). In many of these insect–plant host
relationships, volatiles play a key role in location of hosts. In the D.
melanogaster species subgroup, an extreme example of a host-
plant specialist is Drosophila sechelia, a species endemic to the
Seychelles Islands that lays eggs exclusively on the local Morinda
plant, whose fruit is toxic to the larvae of other Drosophila species
(Tsacas and Baechli, 1981). Adult D. sechelia exhibit multiple
adaptations of their olfactory system to Morinda volatiles
(discussed further in Sections 4.2.1 and 4.2.2). The geographic
isolation of D. sechelia from most other Drosophila species is
sufficient, albeit not necessary, for host specialization of the
olfactory system. For instance, the apple maggot Rhagoletis
pomonella and its sibling species complex constitute a well-
documented example of sympatric speciation (i.e. divergence
without geographic isolation) that is driven by species-specific
behavioral preferences and adaptations of the olfactory system
(discussed further in Sections 4.2.1 and 4.2.2) for the fruit volatiles
of host plants that flower at different times (Linn et al., 2003).
Should closely related insect species share both a geographic
range and common food sources, reproductive isolation might be
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maintained by multi-component sex-attractant pheromone mix-
tures that evoke mate-seeking behavior, a well-studied phenome-
non among the Lepidoptera (moths and butterflies), although
considerably fewer volatile pheromones have been identified
among butterfly species than in moths. Reproductive isolation is
maintained among several sympatric moth species of the genus
Heliothis by a system in which females of multiple species release a
common 16-carbon aldehyde (Z-11-hexadecenal) as the main
component of their sex pheromone, but each species-specific sex-
pheromone mixture contains different secondary components.
These minor components have been shown both to evoke mate-
seeking behavior (Vetter and Baker, 1983, 1984) and to antagonize
such behavior in sister species (Vickers and Baker, 1997). Studies of
the reliance of insect species on a limited set of plants and on
species-specific pheromones is of particular interest to neurobiol-
ogists, as specialized behavior often is reflected in specialization of
the peripheral, and even, central chemosensory system (de Bruyne
and Baker, 2008).
4.2.1. Peripheral adaptations for olfactory specialization
The peripheral olfactory systems of closely related species of
insects are likely to exhibit multiple structural and functional
homologies. However, recent work using insect groups that are
either undergoing or have relatively recently undergone shifts in
host-plant specialization demonstrates that a variety of adapta-
tions of the olfactory system can subserve exclusive host
relationships. Male orchid bees (Euglossini) express novel mating
behavior in which they harvest blends of orchid volatiles and
subsequently release them in order to attract mates (reviewed in
Cameron, 2004). Distinct ‘collections’ of volatiles attractive to
different females may act as isolating mechanisms during incipient
speciation, and two male morphotypes have been shown to
harvest volatile mixtures that differ by the inclusion of a major
component. Divergent behaviors among males are reflected in
olfactory function, as GC-EAD experiments have shown distinct
responses to the differing component between male morphotypes
(Eltz et al., 2008).
In the apple maggot fly R. pomonella, ORCs from three races that
exhibit distinct behavioral preferences for three different host
plants are differentiated, not by functional type or relative
abundance in the antenna (Olsson et al., 2006a) but by their
response thresholds and temporal firing patterns to volatiles
emitted by their preferred host plant (Olsson et al., 2006b). In
contrast, specialization of D. sechelia on Morinda is reflected not
only in a shift of the abundance of a single type of sensillum (ab3),
apparently at the expense of other types of sensilla found in
heterospecifics (Stensmyr et al., 2003), but also in the altered
affinity of an ab3 ORC for a host volatile. This drastic shift in ORC
tuning corresponds to a change of only nine amino acids in the ab3
ORC receptor sequence (Dekker et al., 2006). Although frequent,
adaptations of the peripheral olfactory system that emphasize
representations of host- and mate-related volatiles at the expense
of other volatiles may take on diverse forms: shifts in receptor
abundance, shifts in receptor affinity, or both acting in parallel.
4.2.2. Central adaptations for olfactory specialization
Common organizational principles of insect olfactory systems
permit prediction of differences in the anatomy and neural
circuitry of the AL based on peripheral olfactory adaptations in
closely related species. Owing to convergence of axons of ORCs of a
single receptor phenotype in a particular AL glomerulus, an
increase in the abundance of one type of ORC is likely to result in an
increase in the volume of its target glomerulus. The same
convergence is also likely to transform a change in the molecular
receptive range of an ORC to a change in the tuning properties of
PNs arborizing in the corresponding glomerulus. In D. sechelia, the
DM2 glomerulus, in which ab3 ORC axons terminate, is corre-
spondingly enlarged relative to the homologous glomerulus in D.
melanogaster (Dekker et al., 2006). Although ab3 ORCs can detect
their preferred volatile, methyl hexanoate, at amounts as low as
five fg, DM2 PNs may benefit from convergence of ORC axons to
exhibit an even greater sensitivity by improvement of the signal to
noise ratio in response to the compound (Dekker et al., 2006).
Male moths of two closely related species, Heliothis virescens
and Heliothis subflexa, have a subset of antennal ORCs that are
morphologically identical but sensitive to chemically different
secondary pheromone components (Baker et al., 2004). Neverthe-
less, the male-specific macroglomerular complexes (MGCs) in the
ALs of both species share identical volumes and a common spatial
organization (Vickers and Christensen, 2003). Within the MGCs of
H. virescens and H. subflexa, the PNs originating in an orthologous
large glomerulus (the cumulus) are tuned to a major pheromone
component common to both species (Vickers and Christensen,
2003). The PNs of an adjacent glomerulus (the DM glomerulus) in
each species, however, are functionally different, dedicated to
processing information about a secondary component unique to
the conspecific pheromone blend. DM tuning may have a complex
genetic basis, as hybrid males of these two species exhibit
responses to both secondary components while maintaining
parental cumulus tuning (Vickers, 2006a,b). Divergent mate-
seeking behavior in H. virescens and H. subflexa relies on
combinatorial activation of a glomerular array, providing a model
in which the AL exploits small differences in the quality and
proportion of the olfactory stimulus in order to execute species-
specific behavior (Lei and Vickers, 2008).
5. Central olfactory pathways
Recent progress in describing the architecture of the major
centers for olfaction in the insect brain – the AL, mushroom body
(MB), and lateral horn (LH) of the protocerebrum – in several
species has suggested that olfactory centers at all levels are not
homogeneous processing units. Instead, in different species they
are divided into anatomical or functional subsystems that interact
to varying degrees. Here we review findings on the structure and
function of olfactory brain organization in insect taxa investigated
5.1. Antennal lobe
ORCs are anatomically and functionally isolated from one
another at the periphery (but see Getz and Akers, 1994, and
Andersson et al., 2010, for possible exceptions), and axons of ORCs
expressing the different ORs terminate in different glomeruli in the
AL, the first brain region in which olfactory information channels
typically interact. In D. melanogaster, it is well established that
glomeruli receive input from receptors expressing one OR, and all
ORCs expressing a particular OR terminate in one glomerulus
(Couto et al., 2005; Fishilevich and Vosshall, 2005; Gao et al., 2000;
Vosshall et al., 2000). Where more than one receptor is expressed
in ORCs that terminate in a glomerulus, the combination is still
unique to that glomerulus (Couto et al., 2005; Fishilevich and
Vosshall, 2005; Goldman et al., 2005; Vosshall et al., 2000).
Experiments with transplantation of antennae between male and
female moths (Ro ¨ssler et al., 1999) or related species of moths
(Vickers et al., 2005), demonstrate that the identity of the ORC
determines the functional identity of the glomerulus in these
animals as well. Evidence for ORC tuning governing glomerular
function in other insects is currently sparse (Ghaninia et al., 2007;
Kelber et al., 2006; Robertson and Wanner, 2006), but it is
reasonable to assume that the principle is conserved among
insects, with the exception of some hemipteran and orthopteran
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species (Ignell et al., 2001; Kristoffersen et al., 2008a). Glomeruli
thus represent olfactory information channels with unique
response profiles (Hallem and Carlson, 2006) that interact via a
local network in the AL.
Certain insect taxa lack this anatomical segregation of input
channels. At one extreme, the reduced ALs of the Psyllidae (plant
lice) and members of the Aphidoidea (both Hemiptera: Sternor-
rhyncha) apparently do not have glomeruli, despite their reliance
on olfaction to locate plant hosts (Kristoffersen et al., 2008a). The
ALs of locusts (Orthoptera: Acrididae), exhibit microglomerular
structure but not segregation of ORC input (Ignell et al., 2001)
(Fig. 2A). Antennal ORCs, likely expressing different ORs, project to
1–3 AL ‘‘microglomeruli’’ (Hansson et al., 1996), and the dendrites
of PNs sample from 10 to 25 anatomically distant microglomeruli
(Anton and Hansson, 1996). Dendrites of PNs arborize in roughly
concentric rings from the outside to the inside of the AL, but the
functional significance of that pattern is unclear (Anton and
Hansson, 1996; Jortner et al., 2007). Several species of the
Acrididae exhibit a novel aglomerular region within the AL, of
unknown function in olfactory processing (Ignell et al., 2001).
Locusts and some other hemimetabolous insects also have an
anatomically separate chemosensory center, the glomerular lobe,
which receives primary afferents from ORCs in the maxillary palp
(Frambach and Schu ¨rmann, 2004; Schachtner et al., 2005). Among
holometabolous insects, the glomerular lobe is fused to the AL, and
glomeruli receiving inputs from non-antennal sources (e.g. the
palps) are distributed among ‘antennal’ glomeruli.
In a majority of insects that have been studied, AL glomeruli
receive sensory input from a single type of ORC and relay output
mainly through uniglomerular PNs (Hildebrand and Shepherd,
1997). In this manner, input to glomeruli from the periphery
represents an ensemble of independent sensory channels. How-
ever, higher-order organization of glomerular innervation and
clustering of behaviorally related glomeruli complicate the
‘independence’ of glomeruli by regrouping them in the AL into
anatomical, and perhaps functional, subdivisions. In honey bees
and ants (Kirschner et al., 2006; Zube et al., 2008, respectively), the
antennal nerve divides into distinct tracts upon entering the AL,
each tract feeding a cluster of neighboring glomeruli (Fig. 2C).
Similarly, the ALs of several lepidopteran species exhibit MGCs—
regions in which sex-pheromonal information is processed in
enlarged, neighboring glomeruli in males (see Christensen and
Hildebrand, 2002 for a review) (Fig. 2B)—as well as sexually
dimorphic regions in the female AL, possibly related to volatiles
important for oviposition (Reisenman et al., 2009; Rospars and
The AL of D. melanogaster exhibits no obvious anatomical
divisions, but groups of glomeruli are distinguished by develop-
mental origins (Jefferis et al., 2001), expression of common genes,
or the type of sensilla housing the ORCs that innervate the
glomerulus (Benton et al., 2007; Couto et al., 2005). Among these
groups is a trio of glomeruli that in male flies are sites of
pheromone-information processing (Datta et al., 2008). Both ORCs
and PNs in these glomeruli express fruitless, a gene involved in
courtship behavior (Manoli et al., 2005). Divisions in an AL can also
represent areas of thermo- or hygro-sensitive input (Nishino et al.,
2003; Zeiner and Tichy, 2000; Ruchty et al., 2010). Thus, within the
AL, channels devoted to different modalities or to volatiles
associated with different behaviors may be segregated, although
some divisions are likely parallel systems in which olfactory
stimuli activate many glomeruli across divisions (reviewed in
Galizia and Ro ¨ssler, 2010).
The neural circuitry of the AL in different species provides
varied mechanisms for interaction among glomeruli. LNs typically
are multiglomerular, with neurites that extend to many or
all glomeruli (often termed ‘homo’ or ‘global’ LNs) or that
interconnect only a smaller number of specific glomeruli
(‘oligoglomerular’ or ‘hetero’ LNs) (Abel et al., 2001; Galizia and
Kimmerle, 2004; Matsumoto and Hildebrand, 1981; Reisenman
et al., 2008; Seki and Kanzaki, 2008; Seki et al., 2010; Wilson and
Laurent, 2005). In moths (M. sexta [Hoskins et al., 1986] and
Bombyx mori [Seki and Kanzaki, 2008]), flies (D. melanogaster [Seki
et al., 2010]), and cockroaches (Periplaneta americana [Distler,
1989]), a majority of LNs are global and GABAergic. Hymenopter-
ans have a comparatively novel population of LNs; ‘hetero’ LNs are
more common (Fonta et al., 1993), may receive ORC input in only
one glomerulus through dense innervation of its apical zone, and
project sparsely to several other glomeruli (Dacks et al., 2010;
Galizia and Kimmerle, 2004). LNs produce Na+-based action
potentials in response to olfactory stimulation in most insects in
which they have been studied (c.f. Christensen et al., 1993; Galizia
and Kimmerle, 2004; Wilson and Laurent, 2005). By contrast, LNs
in locust ALs (MacLeod and Laurent, 1996), as well as a subset of
LNs in cockroach ALs (Husch et al., 2009), respond to antennal
stimulation with subthreshold membrane oscillations and voltage-
activated calcium currents. Notably, a majority of such nonspiking
cells in the cockroach (P. americana) AL are not GABAergic (Husch
et al., 2009).
LNs also exhibit additional, diverse neurotransmitter pheno-
types. All but the most basal hymenopterans (Dacks et al., 2010),
and some cockroaches (Leucophaea maderae) (Lo ¨sel and Homberg,
1999; Na ¨ssel, 1999), have a number of histaminergic LNs.
Histamine inhibits responses to olfactory stimuli in the glomeruli
of honey bees, possibly by presynaptic inhibition of ORCs (Sachse
et al., 2006). A class of excitatory, cholinergic LNs has been
identified in D. melanogaster (Huang et al., 2010; Shang et al.,
2007). Excitatory LNs have yet to be demonstrated decisively in
other insect species, but many of the functions of excitatory
interconnections can be performed by disinhibition based on serial
inhibitory synapses formed by LNs (Christensen et al., 1993; Avron
and Rospars, 1995). Small groups of LNs are further differentiated
by the expression of one or more putative neuropeptides, likely co-
released with GABA (Na ¨ssel and Homberg, 2006). Finally, ALs are
innervated by various centrifugal modulatory neurons, affecting
the function of the AL according to circadian, appetitive, or
associative information from other brain areas (Dacks et al., 2005,
2006; Ignell, 2001; Na ¨ssel, 1999; Sinakevitch et al., 2005).
5.1.1. Inhomogeneous interactions between glomeruli
There is increasing evidence that the network of glomerular
interactions, while stereotyped across individuals, is not a
homogenous all-to-all network. Inhomogeneity of interglomerular
connections may provide a basis for species-specific glomerular
interactions that facilitate processing of sensory information about
natural volatile stimuli. The strength of local excitatory inputs to
PNs (Olsen et al., 2007) and presynaptic inhibition of ORC inputs
(Olsen and Wilson, 2008) are not correlated in different glomeruli
responding to the same olfactory stimuli, as would be expected if
both glomeruli were receiving only inputs carrying information
about total afferent input. LNs in D. melanogaster branch with
heterogeneous density patterns in multiple glomeruli and exhibit a
degree of olfactory selectivity (Wilson and Laurent, 2005). Imaging
of a population of LNs in D. melanogaster reveals patterns of
synaptic activity that are specific to particular olfactory stimuli (Ng
et al., 2002). Finally, the expression of GABAB-like receptors in ORC
terminals is heterogeneous throughout the D. melanogaster AL, and
is, for example, particularly dense in pheromone-responsive
glomeruli and nearly absent in a CO2-responsive glomerulus (Root
et al., 2008). These studies suggest that inhibitory and excitatory
inputs carry additional information that is glomerulus- and
stimulus-specific. Consistent with this idea, a model of the
honey-bee AL most accurately predicts the experimentally
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Fig. 2. Schematic representations of the olfactory systems of four commonly studied animals. In each, the AL, (black circle) MBC, and LH (black ovals) are depicted, along with
the l-, ml-, and m-APT (dark grey, light grey, and medium grey lines, respectively), which comprise the output of the AL (after Galizia and Ro ¨ssler, 2010). Particular,
characteristic features of the organization of the olfactory system of each order are illustrated in color. Features are chosen to illustrate differences between model insects, and
do not represent an exhaustive representation of the organizational principles of each olfactory system. (A) Orthoptera (S. americana, locust). The AL of the locust is
characterized by ORCs (in blue, redrawn from Hansson et al., 1996) which project to 1–3 microglomeruli (grey circles), and exclusively multiglomerular PNs (red, redrawn
from Anton and Hansson, 1996) arborizing in 10–25 microglomeruli. This is in contrast to the uniglomerular projections of ORCs and majority uniglomerular PNs in the other
orders illustrated. PNs project via the mAPT to the MBC and LH, and diffusely though the ml-APT to as-yet-unknown targets in the lateral protocerebrum. The MBC and LH of
locusts exhibit no obvious anatomical or functional subdivision. (B) Lepidoptera (B. mori, M. sexta, S. littoralis, others). The AL of male moths is typically subdivided into a
‘‘main’’ AL (green-shaded circles) and a macroglomerular complex consisting of pheromone-responsive glomeruli (blue-shaded ovals). Uniglomerular PNs in the main AL
project through the m-APT and arborize throughout the MBC and LH, while uPNs from the MGC arborize chiefly in a more conscribed region of the MBC and in the inferior
lateral protocerebrum (ILPC), neighboring the LH. (C) Hymenoptera (A. mellifera, C. floridanus, others). ORCs enter the ALs of bees and ants in several tracts (four tracts
illustrated, as found in A. mellifera). Each tract terminates in a distinct set of neighboring glomeruli (cyan, blue, orange and yellow circles, numbers not representative). The AL
is divided into two hemi-lobes (magenta and green shading) by associated output tract. uPNs from glomeruli in one hemi-lobe send axons through the m-APT (magenta line),
arborizing (magenta shading), in the outer portion of the lip (l) and the middle portion of the basal ring (br) of the MBC (one calyx depicted) before terminating in the LH. uPNs
from the other hemi-lobe send axons through the l-APT (green line), arborizing (green shading) in the LH before terminating in the inner portion of the lip and the basal ring of
the MBC. In the LH, each tract occupies a segregated region with some overlap between them. (D) Diptera (D. melanogaster). ORCs in flies send axons to single glomeruli in the
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observed output patterns of PNs, not when inhibitory connections
are weighted homogeneously or when they vary with spatial
proximity but instead when they scale according to the similarity
of ORC input to the glomerulus (Linster et al., 2005). In the moth M.
sexta, sexually dimorphic glomeruli have strong, inhibitory
connections to the main AL but apparently do not receive
reciprocal inhibition from isomorphic glomeruli (Reisenman
et al., 2008), and in D. melanogaster, wide-field LNs are less likely
to innervate a glomerulus associated with social communication
(Chou et al., 2010; Wilson and Laurent, 2005). Finally, the strength
of connections between glomeruli may be affected by learning-
related plasticity observed in the AL (Daly et al., 2004; Thum et al.,
2007; Yu et al., 2004), perhaps reinforcing relations between
output channels associated with reward or punishment. LNs
appear to provide a network of inhomogeneous inhibitory
connections among glomeruli, reflecting underlying principles of
computation not yet fully understood.
The AL network has an inhomogeneous, species-specific
architecture allowing for interactions among units, ranging from
individual glomeruli to functionally or anatomically related
clusters of glomeruli. Information processing is likely to be
similarly complex and species-specific, with common functions
mediated by different mechanisms in different species, as well as
functions adapted for the particular olfactory world of a species.
5.2. Higher-order olfactory centers
From the AL, information about olfactory stimuli is relayed to
several higher-order centers for subsequent processing. Recent
work has produced maps of the pathways through which
information flows in the olfactory system and allows for a
preliminary analysis of the input/output characteristics of each
level of processing. Across species, these maps show varying
degrees of segregation of information channels. The organization
of the AL proper and its output tracts, as well as the projections of
axons of AL PNs to other brain areas and the integration of
information from the AL by third-order neurons, all are organized
according to characteristics specific to groups of insects. In this
section, we review those organizing principles. Chief among them
is the emerging evidence that, as in the AL, higher-order regions
exhibit diverse patterns of segregation of olfactory channels.
5.2.1. Antenno-protocerebral tracts
AL PNs project to higher-order centers through several axonal
tracts. In the following sections, we employ nomenclature
suggested by Galizia and Ro ¨ssler (2010), who identify three
antenno-protocerebral tracts (APTs) with a common position,
although not necessarily common function or homology, across
many insects (Fig. 2). As the traditional nomenclature of ‘‘antenno-
cerebral tracts’’ differs among species, this newer nomenclature
facilitates comparison across taxa. The largest tract is the medial
APT (m-APT), which is present in the Archaeognatha and
Zygentoma, the most basal insects examined (Strausfeld, 2009;
Strausfeld et al., 2009). In flies, moths, ants, honey bees, and
cockroaches, most uniglomerular PNs send axons through the m-
APT, have collateral projections to the mushroom-body calyces
(MBCs), and terminate in the lateral horn (LH) of the protocer-
ebrum (Homberg et al., 1988; Malun et al., 1993; Marin et al., 2002;
Rø et al., 2007; Stocker et al., 1990). The multiglomerular PNs of the
AL of locusts also follow this tract (Ignell et al., 2001). The lateral
APT (l-APT) is composed of the less-common multiglomerular PN
axons in moths and cockroaches and a mixture of uni- and
multiglomerular PNs in flies. In ants and bees uniglomerular PNs
from one hemi-lobe of the AL project through the l-APT,
constituting a distinct, parallel olfactory system thus far described
only in the Hymenoptera (Galizia and Ro ¨ssler, 2010; Kirschner
et al., 2006; Zube et al., 2008) (Fig. 2C). This system is also present
in some basal, non-social hymenoptera and is thought to be an
adaptation to complex olfactory environments and behaviors
(Ro ¨ssler and Zube, 2011). The l-APT in cockroaches and flies
terminates in the LH, but in moths, bees, and ants it also projects to
the MBCs. Finally, additional, minor tracts compose a medial-
lateral APT (ml-APT) that carries axons of a variety of uni- or
multiglomerular PNs and projects in species-specific patterns to
the MBCs, LH, or other regions in the protocerebrum (reviewed in
Galizia and Ro ¨ssler, 2010).
Although insects share a common Bauplan of APTs, each taxon
exhibits variations on the theme. Tracts sharing a projection
pattern but composed of uni- or multiglomerular PNs in different
species, for example, can facilitate the testing of hypotheses about
the functions of different types of PNs. Similarly, features unique to
a taxon, e.g. the parallel uniglomerular PN system in bees and ants,
may well be correlated with behavior particular to those species.
5.2.2. Mushroom-body calyx
Upon reaching their synaptic targets, PN axons terminate with
varying degrees of segregation. We consider first the calyces of the
mushroom bodies (MBCs), where PNs synapse with Kenyon cells
(KCs). Recent work has provided new insights into the structure of
MBCs, and especially the compartmentalization of PN inputs and the
KCs with which they synapse, demonstrating that the MBC is not a
homogeneous structure. Instead, in many insects it contains
multiple subsystems, with various architectures of segregation
and integration in different species. Here, we consider recent work
describing olfactory networks in the MB. We propose that a detailed
understanding of these networks is required for investigations of
olfactory information processing in this region, as well as processing
in the AL that shapes the input to this associative center.
In locusts (Schistocerca americana, Jortner et al., 2007; Laurent
and Naraghi, 1994) and several moth species (Homberg et al.,
1988; Rø et al., 2007), axon collaterals of AL PNs spread throughout
the MBC, but a detailed analysis of their branching patterns is not
available. In contrast, certain pheromone-responsive PNs of the
moth B. mori terminate in circumscribed regions of the MBCs
(Kanzaki et al., 2003; Seki et al., 2005) (Fig. 2B). For D. melanogaster,
the only insect species studied systematically to date, axons of PNs
from the same glomerulus terminate in remarkably similar
locations in the MBCs, in apparently fewer and more circumscribed
regions than in moths or locusts (Jefferis et al., 2001, 2007; Lin
et al., 2007; Marin et al., 2002; Wong et al., 2002).
MBCs of ants and bees are subdivided into three regions: lip,
collar, and basal ring (Ehmer and Gronenberg, 2002; Gronenberg,
1999, 2001; Gronenberg and Ho ¨lldobler, 1999; Mobbs, 1982).
Axons of AL PNs projecting in both the l-APT and m-APT terminate
in the lip and basal ring (Abel et al., 2001; Ehmer and Gronenberg,
2002; Gronenberg, 1999, 2001; Gronenberg and Ho ¨lldobler, 1999;
Kirschner et al., 2006; Zube and Ro ¨ssler, 2008) (Fig. 2C). The basal
ring has three concentric layers, receiving (respectively from inside
to outside) input from the l-APT, m-APT, and visual neurons from
the medulla (Gronenberg, 1999; Kirschner et al., 2006; Zube et al.,
ipsilateral AL, and through a unique antennal commissure (AC, dark blue lines) to the corresponding glomerulus in the contralateral AL. Glomeruli in the AL are variously
related by neuroblast origin of PNs, the type of sensilla that houses the ORCs that innervate the glomerulus, and the MBC regions that the PNs target (red, cyan, yellow, green
and purple shading in AL). The majority of uPNs project through the m-APT, and arborize in regions of the MBC defined by the KC type that inhabit them (corresponding red,
cyan, yellow, green and purple shading in MBC). The m-APT continues to the LH, where uPNs terminate in conscribed regions, in groupings related but not identical to those in
the MBC (grey ovals in the LH). A segregated region (indicated by an asterisk) receives innervation from pheromone-responsive PNs.
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2008). Little overlap is evident between the layers. In the lip region,
l-APT PNs innervate the inner core, while m-APT PNS innervate the
outermost layer and produce diffuse arborization throughout the
MBCs (Kirschner et al., 2006). Several species of hemimetabolous
insects also exhibit functional division of the MBCs. In crickets
(Gryllus bimaculatus), output neurons from the glomerular lobe
(anatomically distinct from the AL and receiving chemosensory
input from the mouth parts) terminate in the posterior calyx, while
PNs from the AL terminate in the anterior (Frambach and
Schu ¨rmann, 2004). The MBCs of cockroaches (P. americana) are
divided into compartments receiving input from two distinct
populations of uniglomerular PNs, male-specific PNs, and some
neurons from the optic lobes (Strausfeld and Li, 1999).
Anatomical separation of input channels may not indicate
separation of information if the third-order neurons sample across
channels. Characteristics of integration depend on the overlap of
PN axonal terminals and KC dendritic fields. At one end of the
spectrum, locust KCs have wide dendritic fields covering a large
portion of the MBC (Jortner et al., 2007; Perez-Orive et al., 2002).
Each KC is estimated to receive input from ca. 50% of PNs, which
Jortner et al. (2007) identified as approaching the theoretical ideal
for a general associative network (Shannon and Weaver, 1964).
This suggests a lack of segregation in the locust KC network. In the
moth species Spodoptera littoralis and B. mori, KCs with wide
dendritic fields send axons to the a/b and a0/b0lobes of the MBs,
while KCs with narrower fields project to the g lobe (Fukushima
and Kanzaki, 2009; Sjoholm et al., 2006). The calyx is further
subdivided by classes of KCs distinguished by immunoreactivity,
also with distinct projection patterns (Fukushima and Kanzaki,
2009; Sjoholm et al., 2005). Given the projection patterns of PNs,
KCs of different classes may integrate information from varying
numbers of PNs, but it appears that they may sample from any
combination of PNs. This simplification may yet be challenged by a
more detailed study of the MBC in these insects.
KCs are arranged in the MBC of worker honey bees in a pattern
similar to that in moths. Class-II KCs integrate across the lip, basal
ring, and collar of the MBC and thus can receive input from all
uniglomerular PN tracts (m- and l-APT) as well as from the visual
system (Strausfeld, 2002), while dendrites of class-I KCs are
restricted to regions exclusively receiving projections of axons
from the l-APT, the m-APT, or both tracts. All classes project to the
vertical lobe (analogous to a/b and a0/b0lobes of other insects),
but the upper two-thirds of the lobe is divided into strata
innervated by axons originating in either the lip, collar, or basal
ring of the MBC, and the lower third, proposed to be analogous to
the g lobe in D. melanogaster, is innervated by the axons of class-II
KCs (Strausfeld, 2002). The vertical lobe thus contains strata that
receive projections of KCs that integrate either within or between
the two main input tracts. Further subdivision according to AL
divisions is not apparent, and KCs may sample across divisions that
share a tract. Each class-II KC receives input from an estimated 10
PNs, consistent with a greater degree of segregation between input
channels in this animal (Szyszka et al., 2005).
The MBC of D. melanogaster exhibits a further degree of
organization (Fig. 2D). As mentioned above, PNs of the same
glomerulus have terminals in corresponding, circumscribed
regions of the MBC. The MBC can be divided into four vertical
sections, according to neuroblast origin (Ito et al., 1997; Technau
and Heisenberg, 1982), each of which is laterally divided into
regions containing KCs exclusively from one of five groups
distinguished by target lobe and developmental origin: g lobe,
a0/b0lobe, and pioneer, early, and late a/b lobe KCs (Lee et al.,
1999; Zhu et al., 2003). A detailed analysis of a subset of PNs from
13 glomeruli revealed that PNs target KCs across the vertical
divisions, but typically target KCs of one group (Lin et al., 2007) and
contribute to distinct, isolated clusters of PN–KC synapses called
microglomeruli (Leiss et al., 2009). Extension of these results to the
PN groups identified by Jefferis et al. (2007) suggests that the KCs
integrate input only within PN groups and that different groups of
PNs are associated with each lobe of the MB. Each KC is estimated
to receive input from 10 PNs (ca. 5%) (Turner et al., 2008). If each
class of KCs integrates information from only a small group of PNs,
this arrangement might produce a system of parallel associative
networks. Within each subset, connectivity may more closely
resemble the locust MBC, with ca. 50% of input channels making
connections with each KC.
Detailed findings about fine divisions of the MBC, directly
comparable to those in D. melanogaster, are not yet available for
other insects. Available evidence, however, describes a spectrum of
input/output segregration within the MBC. At one pole, D.
melanogaster PNs and KCs are isolated in multiple, parallel
subsystems with little or no overlap, as opposed to locust MBCs
in which interaction between any PN and any KC is anatomically
possible. As a first approximation, this spectrum suggests
functional consequences of neural architecture that can inform
comparison between species.
5.2.3. Lateral horn
In contrast to the MBC, the lateral horn of the protocerebrum in
many insects appears to be a diffuse, aglomerular neuropil (e.g. Sun
et al., 1997; Yasuyama et al., 2003). In D. melanogaster, PNs
terminate in the LH in a stereotyped pattern resembling that in the
MBC (Jefferis et al., 2007; Marin et al., 2002; Tanaka et al., 2004;
Wong et al., 2002) (Fig. 2D). As in the MBC, PNs with a common
neuroblast origin project to similar regions of the LH (Marin et al.,
2002). Consistent with this, PNs that terminate in the same region
of the LH tend to originate in neighboring glomeruli, although the
reciprocal arrangement is not observed (Marin et al., 2002). In
addition, PNs cluster in similar groups in the MBC and LH (Jefferis
et al., 2007). Finally, PNs that receive input from ORCs in certain
types of sensilla project to similar areas of the LH (Jefferis et al.,
2007). Thus at least in D. melanogaster, PNs terminate in
stereotyped but overlapping patterns.
Segregation of inputs in the LH is largely correlated with the input
tract through which axons project, or by a distinction between food-
derived and social or pheromonal stimuli. The m-APT and l-APT PNs
in honey bees and ants terminate in distinct regions of the LH and
share a diffuse region of overlap between them (Kirschner et al.,
2006; Zube et al., 2008) (Fig. 2C). The LH is similarly divided by input
tracts in species of moths (Homberg et al., 1988; Rø et al., 2007)
(Fig. 2B) and D. melanogaster (Wong et al., 2002) (Fig. 2D). PNs
supplying the ml-APTs in bees and ants produce a unique ‘‘lateral
network’’ located between the g lobe of the MB, the LH, and other
areas of the protocerebrum (Kirschner et al., 2006; Zube et al., 2008).
Some PNs in this group terminate in the LH, exclusively in the area
also innervated by the l-APT. The function of this network is not yet
understood, but it provides a substrate for interaction between the
AL, MB, and LH not present in other insect species.
Input to the LH from pheromone-responsive PNs in several
species is segregated to varying degrees. In D. melanogaster, axons
from two glomeruli project to a restricted region of the LH that
contains few arborizations of other PNs (Jefferis et al., 2007)
(Fig. 2D). These glomeruli express a male-specific form of the
fruitless gene required for male sexual behavior (Demir and
Dickson, 2005; Manoli et al., 2005; Stockinger et al., 2005). This
region is enlarged in males and contains an additional PN
arborization produced when the male isoform of fruitless is
expressed both in PNs and other cells in the brain (Datta et al.,
2008). The pheromone-responsive PNs in moths project to a region
that is more isolated from PNs originating in the main AL (Homberg
et al., 1988; Kanzaki et al., 2003; Seki et al., 2005) (Fig. 2B). In
silkworm moths (B. mori), this region is further divided into two
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partially overlapping segments receiving input from each of two
MGC glomeruli (Kanzaki et al., 2003; Seki et al., 2005). Finally, in
the LH of the cockroach, PNs responding to cold, dry, or moist air,
respectively, terminate in a distinct region of the LH, with areas
overlapping those innervated by uni- and multiglomerular PNs
from other glomeruli (Nishino et al., 2003).
It has been hypothesized that the LH supports integration of
more ‘‘stereotyped’’ olfactory information than the MB (Jefferis
et al., 2007). Comparing the recent, detailed findings about the
anatomy of the LH and MBC (Jefferis et al., 2007; Lin et al., 2007),
we suggest that this distinction lacks adequate support. KCs in the
MBC of D. melanogaster integrate information from a restricted
subset of AL glomeruli and exhibit pronounced input/output
segregation. Similarly to what is observed in the MBC, groups of LH
neurons in D. melanogaster integrate input from PNs that arborize
in limited numbers of glomeruli and terminate in spatially
restricted zones (Jefferis et al., 2007; Tanaka et al., 2004). Thus,
available information suggests that neither structure supports an
entirely general integration scheme in which information origi-
nating in any one glomerulus may be integrated with that
originating in any other glomerulus by third-order neurons.
Recent investigation of a small, genetically identifiable group of
KC neurons, however, reveals that members of the group do not
respond similarly to a battery of volatile stimuli (Murthy et al.,
2008). Thus, while groups of KCs may sample from the same
restricted subset of PN inputs, each may receive inputs from a
particular combination of PNs within that subset, leading to
unique, non-stereotyped responses. The fine structure of the MBC,
consisting of many microglomeruli that segregate small groups of
input, output, and local circuit synapses (Leiss et al., 2009; Steiger,
1967; Ganeshina and Menzel, 2001), supports this hypothesis.
These structures are a common feature of the MBC in neopteran
insects (Groh and Ro ¨ssler, 2011), and they represent an order or
organization not seen in the LH.
Physiological and behavioral experiments suggest an addition-
al, distinct role for the LH, different from that of the MB and
possibly species-specific. In locusts (S. americana) the LH is the
source of a strong, feed-forward inhibition to KCs (Perez-Orive
et al., 2002). A cluster of GABAergic LH interneurons (LHIs)
reportedly connects the LH to the MBC and likely underlies this
feed-forward inhibition. LHIs are driven by the same PN inputs that
drive the KCs but with a greater latency. LHIs then inhibit KCs,
closing the temporal window during which they can integrate
input. GABAergic neurons that may be analogous to the locust LHIs
also have been described in flies (D. melanogaster; Yasuyama et al.,
2003), moths (M. sexta; Homberg et al., 1987), and cockroaches (P.
americana; Nishino and Mizunami, 1998). No evidence of feed-
forward inhibition in D. melanogaster KCs has been found, however
(Turner et al., 2008), and GABAergic LHIs in P. americana are
inhibited by multimodal stimulation and thus are likely to
subserve a different function (Nishino and Mizunami, 1998).
While honey-bee KCs exhibit periodic inhibition similar to that in
locust KCs, it is likely driven by KCs themselves, via feedback
neurons of the MB peduncle (Gru ¨newald, 1999; Szyszka et al.,
2005). It remains to be seen whether the LHI function described in
locusts is conserved in other species.
5.2.4. Protocerebrum and beyond
Little is known about olfactory information processing beyond
the MB and LH. The extrinsic neurons of the MB and LHNs in D.
melanogaster project to overlapping regions in diverse parts of the
brain (Tanaka et al., 2008). Olfactory information spreads
throughout the brain and participates in the organization of
numerous behaviors. The participation of MBs in associative
memory has been well documented (reviewed in Heisenberg,
2003; Margulies et al., 2005). The varying degrees of segregation
within and integration across the parallel divisions of olfactory
input suggest that the underlying rules of association are complex
and species-specific. The LH is similarly organized to integrate
within or between input channels and may perform multiple
processing and feedback functions controlling behavior.
Further downstream, a pair of symmetrical brain regions has
been closely linked to an important olfactory behavior. Circuits in
the lateral accessory lobe (LAL) and the ventral protocerebrum
(VPC) of moths (primarily investigated in M. sexta and B. mori)
generate a ‘‘flip-flopping’’ pattern of activity in descending neurons
that have arborizations in the LAL (Kanzaki et al., 1991, 1994;
Olberg, 1983). These neurons switch between high- and low-
activity phases on each successive stimulus pulse of sex phero-
mone. This pattern of activity corresponds to the ‘‘zig-zagging’’
turns that moths, and many other insects, make when searching for
the source of an odor plume (reviewed in Carde ´ and Willis, 2008)
and furthermore is correlated with the activity of motor neurons
responsible for head movements during a turn (Kanzaki and
Mishima, 1996). Recent work has described the circuitry of the
LAL-VPC system as a pair of mutually inhibitory units that
alternate, generating long-lasting activity in one hemisphere and
quieting the other on each encounter with a pulse of olfactory
stimulus (Iwano et al., 2010). Because diverse insects exhibit
similar behavior when searching for the unseen source of an odor
plume, this mechanism may be conserved across species. Evidence
that some insects can locate odor sources in the absence of a plume
(e.g. D. melanogaster, Budick and Dickinson, 2006), however,
suggests that additional mechanisms specific to other odor-search
strategies may be revealed by comparative work.
6. Comparative coding
By combining findings about how an animal interacts with
volatile chemical stimuli in its environment with knowledge of the
functional organization of the olfactory system, we can begin to
understand how different animals encode olfactory information.
Here, we consider current progress on olfactory information
processing, focusing on these processes in the AL: gain control and
broadening or sharpening of tuning curves between input and
output, synchrony between AL PNs, and encoding of the temporal
features of the stimulus. Animals may use different coding
schemes, or variations of similar schemes, that are proximally
determined by the particular structure and mechanisms present in
the species and ultimately determined by adaptation to a
particular niche and evolution of solutions to specific challenges.
6.1. Gain control
The range of output of an ORC is a function of both the identity
and intensity of an olfactory stimulus. ORCs may respond weakly
to a wide range of volatiles or to a low concentration of a preferred
compound, yet respond robustly to higher concentrations of
certain volatiles (c.f. Bhandawat et al., 2007; Bichao et al., 2005; de
Bruyne et al., 2001; Ito et al., 2009; Kristoffersen et al., 2008b;
Ochieng and Hansson, 1999; Pelz et al., 2006; Schlief and Wilson,
2007; Wilson et al., 2004). Between these extremes of activation,
the circuitry of the AL needs to maintain sensitivity, prevent
saturation, encode stimulus intensity, and maintain a consistent
representation of a stimulus across a range of concentrations.
Underlying these functions is the control of gain, or the conversion
of signal strength between input and output to make efficient use
of the dynamic range of PN output (Fig. 3A).
The efficient use of a PN’s dynamic range begins at the ORC-to-
PN synapse. In D. melanogaster, a spike in an ORC produces a strong,
reliable response in the postsynaptic PN (Bhandawat et al., 2007).
This synapse has a high probability of neurotransmitter release and
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(Kazama and Wilson, 2008). As a result, the transformation
between ORC input and PN output is highly nonlinear, amplifying
weak and suppressing strong inputs (Bhandawat et al., 2007)
(Fig. 3Aii). In response to a given stimulus, input to the AL is
typically a combination of weak activation of many ORCs and
strong activation of only a few (Bhandawat et al., 2007). The
nonlinear transformation amplifies small differences between the
weaker inputs, making PN responses equally likely across all
possible firing rates, a phenomenon known as histogram
equalization that also is observed in the visual system of insects
(Laughlin, 1981). Similar conclusions can be drawn for the ORC/PN
transformation in moths (Ito et al., 2009; Jarriault et al., 2010) and
honey bees (Krofczik et al., 2009).
Inhibitory and excitatory synaptic connections in the AL,
mediated by LNs that may integrate inputs in many or all
glomeruli, can adaptively regulate the dynamic range of PN
responses relative to the total input to the AL. In D. melanogaster,
both presynaptic (Olsen et al., 2010; Olsen and Wilson, 2008; Root
et al., 2008) and postsynaptic (Silbering and Galizia, 2007)
inhibition in glomeruli scales with the total primary-afferent
input to the AL. Similar global inhibition has been observed in
honey bees (Deisig et al., 2006, 2010; Sachse and Galizia, 2002,
2003), and the presence of wide-field LNs in the ALs of many insect
taxa suggests that this function may be universal. Because global
inhibition increases with total ORC input, the representation of an
olfactory stimulus is maintained by the relative activation of PNs
across the AL over a wide range of concentrations (Sachse and
Galizia, 2003). However, the differential expression of GABAB-like
receptors that mediate presynaptic inhibition provides for
independent gain control in each glomerulus (Root et al., 2008).
Indeed, there is evidence that the weighting of global, inter-
glomerular inhibition varies between glomeruli (Olsen et al.,
A class of excitatory LNs in D. melanogaster also encodes total
afferent input across glomeruli and may increase PN output in
weakly activated glomeruli to a level that can be detected by
downstream neurons (Huang et al., 2010; Olsen et al., 2007; Shang
et al., 2007). These competing, global excitatory and inhibitory
inputs may be balanced in a PN, such that they increase together
with the concentration of an olfactory stimulus (Root et al., 2007).
The simultaneous adjustment of balanced, background excitatory
and inhibitory inputs can serve as a form of gain modulation as has
been hypothesized for mammalian cortical neurons (Chance et al.,
2002), such that gain is increased with low background and
decreased with high background. Weak inputs to a PN thus would
be amplified relative to the total input to the AL, enhancing weak
portions of the representation of a stimulus at low concentration
but suppressing weak, likely noisy inputs at high total stimulus
concentration. Such dynamic modulation of gain in the AL has yet
to be demonstrated.
Finally, serotonin (5-hydroxytryptamine) has been shown to
increase the gain and enhance the responses of PNs in the ALs of
moths (Dacks et al., 2008) (Fig. 3Aiii). In adult M. sexta
(Kloppenburg et al., 1999) and B. mori (Gatellier et al., 2004),
levels of serotonin in the AL and protocerebrum peak during the
insect’s active phase in the circadian cycle. Similar work on D.
melanogaster found glomerulus- and odor-specific enhancement of
PN responses but no effect of serotonin on gain, suggesting subtle
differences between species (Dacks et al., 2009). Serotonin-
enhanced presynaptic inhibition is known to be involved in gain
control (see above), however, and might play an additional role in
modulating gain in fruit flies. Serotonin-immunoreactive neurons
have been described in the ALs of many insect species (Dacks et al.,
2010; Ignell, 2001; Kent et al., 1987; Salecker and Distler, 1990;
Siju et al., 2008; Wegerhoff, 1999). Depending on the species, these
Fig. 3. Principles of processing in the antennal lobe. (A) Gain. The circuitry of the
antennal lobe and synaptic properties of AL neurons determine the relationship
between ORC input to a glomerulus and PN output. Gain denotes two distinct, yet
related concepts: (i) the nonlinear relationship between the firing rate of individual
ORCs and the firing rate of the PNs on which it synapses (from Bhandawat et al., 2007),
which underlies, in part, (ii) the relationship between odor concentration and PN
output. The slope of these functions is the gain. Neuromodulation can alter this
relationship (dark grey and light grey lines in ii). (B) Sharpening and broadening of the
population output. (i) Lateral inhibition can produce an activity-dependent reduction
in the firing rate of PNs across the responding population. Glomeruli receiving weak
input (orange line ORC) may be completely silenced (grey dashed line PN). (ii) The
effect is to ‘‘sharpen’’ the representation of the stimulus from the input (light grey
curve) to the output (dark grey curve) layers. Population activity is represented as a
Gaussian curve with a central peak, in analogy to other sensory systems, although
patterns of activity in insect ALs may take a different form. (iii) Lateral excitation
spreads activity throughout the AL, increasing the response of some PNs, and in some
cases producing output in PNs (orange line) that receive no input from their cognate
ORCs (dashed grey line). (iv) The population response in the PN output layer (dark grey
line) is ‘‘broadened’’ with respect to the ORC input layer (light grey line).
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apparently serotonergic cells innervate a variable number of
glomeruli and have species-specific connections with other areas
in the brain. Gain in the ALs of diverse insects thus might be
modulated through the influence of species-specific brain areas,
and under conditions specific to each species.
6.2. Tuning/coding transformation
Olfactory stimuli elicit characteristic patterns of ORC input
across glomeruli (c.f. Deisig et al., 2006; Hallem and Carlson, 2006;
Ng et al., 2002; Sachse et al., 1999; Silbering and Galizia, 2007;
Silbering et al., 2008; Wang et al., 2003). The fidelity with which
ORC input is transformed to PN output, however, is debatable. Does
the dense interconnection of glomeruli by AL interneurons perform
a transformation, either sharpening or broadening, between the
ORC input and the PN output of the AL? In this section, we review
the evidence that inhibitory and excitatory circuits in the AL shape
olfactory codes. In addition, we suggest that apparently conflicting
results stem from either volatile- or species-specific interactions
and likely could be resolved by a comparative approach consider-
ing the natural olfactory ecology of each species.
This discussion necessarily assumes that information about
odors is encoded in the pattern of activity across the AL. It is useful
to note at this point that some innate behaviors, e.g. mate-seeking
in moths (B. mori; Kanzaki and Shibuya, 1983) and flies (D.
melanogaster; Kurtovic et al., 2007) and food-seeking in flies (D.
melanogaster; Semmelhack and Wang, 2009), depend on single
glomeruli that apparently provide all information necessary to
drive those behaviors.
A primary effect of inhibition in a neural circuit is to prevent
under-stimulated units from participating in the output. In this
way, a stimulus is represented by the most strongly activated
neurons, and overlap between codes for different stimuli is
reduced by a ‘‘sharpening’’ of the population code (Urban, 2002)
(Fig. 3Bi and ii). Ca2+-imaging studies in ALs of both honey bees
(Apis mellifera) and fruit flies (D. melanogaster) have shown that
volatile-evoked activation patterns of ORCs largely match the
activation patterns observed in PNs (Ng et al., 2002; Sachse and
Galizia, 2002, 2003; Silbering and Galizia, 2007; Wang et al., 2003).
In both species, global inhibition reduces the responses of all
activated glomeruli (Sachse and Galizia, 2002, 2003; Silbering and
Galizia, 2007). In A. mellifera, however, PN output is suppressed by
inhibition despite weak or intermediate activation of ORCs
projecting to the same glomerulus (Sachse and Galizia, 2002)
(Fig. 3Bi). Similar suppression of ORC-to-PN transmission by global
inhibition is not seen in D. melanogaster (Silbering and Galizia,
2007; Silbering et al., 2008). Global inhibition reduces PN
responses in both A. mellifera and D. melanogaster but sharpens
the population code only in the former.
A second form of inhibition exerts glomerulus- and stimulus-
specific effects on ORC-to-PN output in D. melanogaster (Wilson
and Laurent, 2005). In A. mellifera, blockade of GABAA-like
receptors fails to eliminate suppression of ORC-to-PN transmission
(Sachse and Galizia, 2002), and the remaining odor- and
glomerulus-specific suppression of responses may be mediated
by histaminergic LNs (Sachse et al., 2006). Inhibitory interaction
between glomeruli in ALs of D. melanogaster is most evident in
patterns of mixture-suppression of PN output: activation of ORC
input by one mixture component inhibits PN output in glomeruli
activated by the complementary component of a binary mixture
(Silbering and Galizia, 2007). Similar mixture effects are observed
in A. mellifera (Deisig et al., 2010; Joerges et al., 1997; Silbering and
Galizia, 2007). In both species the effect is volatile- and
glomerulus-specific, consists primarily of suppression of PN
output, and decreases the similarity between responses for
different mixtures. Complex, heterogeneous, inhibitory networks
appear to shape PN output similarly in both D. melanogaster and A.
mellifera but may utilize species-specific cell types.
The response profiles of several PNs in D. melanogaster are
broader than those of their cognate ORCs (Schlief and Wilson,
2007; Wilson et al., 2004, but see Root et al., 2007; Wang et al.,
2003). This remarkable result suggests that network mechanisms
broaden the molecular receptive range of PNs with respect to that
of the ORCs that provide sensory input to them (Fig. 3Biii and iv).
The molecular receptive range of a neuron can be broadened in two
distinct ways: (1) the PN may respond more strongly to olfactory
stimuli that weakly activate the cognate ORCs, or (2) the PN may
respond to volatiles that do not activate cognate ORCs. These two
effects likely are mediated by two network mechanisms. First,
ORC-PN synapses amplify small, probabilistic inputs from multi-
ple, weakly responsive ORCs to a greater degree than the large,
sustained input of multiple firing ORCs (Bhandawat et al., 2007;
Kazama and Wilson, 2008). The nonlinear transformation between
ORC and PN responses to volatiles thus broadens the molecular
receptive range of a PN and underlies the first type of broadening.
In D. melanogaster, excitatory LNs (Chou et al., 2010; Shang
et al., 2007) provide indirect, excitatory input to PNs from other
activated glomeruli (Fig. 3B). Such excitatory LNs receive direct
input from ORCs (Huang et al., 2010) and are broadly (Yaksi and
Wilson, 2010) or more narrowly (Huang et al., 2010) responsive to
olfactory stimuli. Excitation is spread to PNs across the AL through
electrical synapses (Huang et al., 2010; Yaksi and Wilson, 2010).
The broadening of PN responses from their cognate ORC input
occurs for specific stimulus-glomerulus pairs, while in response to
other volatiles there remains a direct, linear relationship between
ORC and PN activity within the glomerulus (Silbering et al., 2008).
Such excitatory lateral interactions have not been observed in
other species, but LNs that are not GABA-immunoreactive have
been observed in the AL of a moth (B. mori; Seki and Kanzaki, 2008)
and a cockroach (P. americana; Husch et al., 2009) and may belong
to a similar class of eLNs. Finally, disinhibition, involving serial
inhibitory synaptic connections between glomeruli, might effec-
tively broaden the molecular receptive range of a PN (c.f.
Christensen et al., 1993; Avron and Rospars, 1995).
6.2.3. Sharpening versus broadening in two species
An apparent contradiction exists in the different transforma-
tions imposed upon ORC inputs in the ALs of honey bees (A.
mellifera) and fruit flies (D. melanogaster). The dominant mode of
interaction in A. mellifera appears to be inhibition that suppresses
weakly activated glomeruli and sharpens the representation of an
olfactory stimulus, while in D. melanogaster evidence suggests that
lateral excitation spreads activation and broadens the representa-
tion. These two modes of interaction differ, one seemingly
decreasing the similarity between representations of different
olfactory stimuli and the other spreading activation across the AL
and reducing the chemosensory specificity of the output channels.
A possible resolution of the difference can come from considering
the anatomy and natural context of olfaction in these animals.
As discussed above, the olfactory system of D. melanogaster may
represent extreme segregation, as PNs from subsets of glomeruli
have synaptic connections with subsets of KCs in the MBC,
producing segregated, parallel systems that interact via local
circuitry. If these channels did not interact, any subsystem would
receive information from only the ORCs that directly feed into it.
The molecular receptive range of ORCs in turn is limited by ligand–
receptor interactions, further reducing the information available to
an already impoverished system. The widespread excitatory
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interactions reported in the D. melanogaster AL can share
information between subsystems in the AL, expanding the
receptive range of each subsystem while allowing the KC networks
to perform parallel, separate functions that are still poorly
understood. For instance, activation of the VA71 glomerulus,
whose PNs project to g-lobe KCs, excites both another glomerulus
(DL1) connected to the g-lobe and glomerulus VA1d, whose PNs
project to KCs associated with the a/b lobe (Lin et al., 2007; Olsen
et al., 2007). By contrast, the AL of A. mellifera contains 150–180
glomeruli, nearly four times the number found in an AL in D.
melanogaster (Galizia et al., 1999). Each of the main AL output
tracts in A. mellifera contains PNs axons from more glomeruli than
the total number in the D. melanogaster AL, and while some KC
classes receive information from only one tract, others apparently
can integrate across all glomeruli (Kirschner et al., 2006). With all
available information feeding into the system, separation of
overlapping representations becomes more critical and perhaps
accounts for the predominance of inhibitory interactions between
glomerular channels in ALs of A. mellifera.
A. mellifera and other hymenoptera use an exceptionally wide
range of olfactory cues, because of the number and diversity of
flowers they visit throughout their range, and an additional,
complex array of social odors. These insects also can perform
remarkable feats of olfactory discrimination, including learning to
identify rewarding from unrewarding volatile stimuli from
different cultivars of the same flower based on the relative ratios
of the volatiles common to each (Wright et al., 2005). Although flies
of the genus Drosophila include generalists (e.g., D. melanogaster)
and specialists in wide variety, including a species adapted to live
exclusively on the mouthparts of crabs (reviewed in Stensmyr and
Hansson, 2007), individual species likely do not employ fine
discrimination over a wide range of olfactory stimuli like that
observed in A. mellifera. Efficient coding in a network is a function
of the number of encoding units, the molecular receptive range of
each, and most importantly for our analysis, the number and
similarity of stimuli that must be encoded (c.f. Olshausen and Field,
2000; Simoncelli and Olshausen, 2001). The olfactory system of A.
mellifera encodes a larger number of olfactory stimuli with a larger
number of receptors and glomeruli, while D. melanogaster employs
a less numerically complex AL, and perhaps even smaller
subsystems within the AL, to encode a smaller range of
behaviorally important stimuli. The AL network of each animal
likely adjusts the receptive range of each channel to achieve
Theoretical studies have demonstrated that optimal tuning of
neurons in a population is a function of stimulus-dependent
behaviors (Salinas, 2006), stimulus dimensionality (Zhang and
Sejnowski, 1999), and the degree of noise in the sensory signal
(Pouget et al., 1999). The influence of these factors on olfactory
coding can be approximated by analysis of the interaction of the
animal with volatiles in its environment, placing coding in the
proper, natural context. The neurobiology of olfaction in insects
demonstrates how evolution, from a common starting point of
input, output, and interneurons, can adjust the properties of the
network to suit the particular demands of a species’ life history and
Synchronous production of action potentials by the output
neurons of a neural circuit is increasingly recognized as a critical
feature of coding in many sensory systems (Singer, 1999).
Synchronous spikes in separate output channels can ‘‘bind’’ the
elements of the representation of a stimulus, allowing higher-
order centers to process the inputs as a single percept (Engel et al.,
1997; Engel and Singer, 2001). Among insect olfactory systems,
those of locusts, moths, and flies have become favorable models for
studies of spiking synchrony. Synchronous activity is organized
differently in these systems, but in all three synchrony is
associated with inhibitory local circuitry (Ito et al., 2009; Lei
et al., 2002; MacLeod and Laurent, 1996; Tanaka et al., 2009).
In contrast to LNs in most other insects that have been studied,
LNs in the ALs of several locust species produce only graded,
oscillating potentials in response to olfactory stimuli (Anton and
Hansson, 1996; Laurent and Naraghi, 1994). Strong, oscillatory
inhibition from these neurons constrains PNs to firing mostly in
phase with the 20-Hz oscillations of the local field potential (LFP)
(Laurent and Davidowitz, 1994; Wehr and Laurent, 1996) and
produces slower temporal patterns of excitation and inhibition
during prolonged stimulation (Bazhenov et al., 2001; Laurent and
Davidowitz, 1994; Wehr and Laurent, 1999). The representation of
olfactory stimuli in the locust AL thus is distributed across an
evolving ensemble of PNs, a coding space that employs both the
identity of responding neurons and the temporal evolution of the
response eventually to produce a unique output for each of several
similar, correlated inputs (Laurent, 1999, 2002; Mazor and Laurent,
2005; Stopfer et al., 2003).
As described above (Section 5.1), each ORC in S. americana
terminates in 10–25 small glomeruli, and the dendrites of a PN
sample from 10 to 25 of these channels. Although it is not yet
known how many different ORs are expressed in the ORCs of this
species of locust, this arrangement theoretically could produce a
unique ORC input profile for each of the approximately 830 PNs in
the AL (Laurent et al., 1996a,b; Leitch and Laurent, 1996). The lack
of glomeruli representing unique channels with redundant output
neurons thus allows for a huge expansion of the available coding
space between input to and output from the AL. The tuning of an
individual ORC is necessarily limited by the interaction between its
OR and the volatile ligands it binds. A PN that samples from several
ORCs thus can have a greatly broadened molecular receptive range.
Furthermore, a unique combination of responsive PNs, synchro-
nized across many cycles of a common oscillatory signal, can be
produced for stimuli with small differences in the ORC response
Although LFP oscillations have been recorded in the ALs of moths
and flies, most spikes in AL PNs in these species are not fully
entrained to LFP oscillations (Christensen et al., 2003; Heinbockel
et al., 1998; Ito et al., 2009; Tanaka et al., 2009; Turner et al., 2008;
Wilson and Laurent, 2005). Importantly, while locust PNs produce
spikes at or below the 20-Hz frequency of the LFP oscillation, PNs in
M. sexta (c.f. Heinbockel et al., 1998; Ito et al., 2009; Reisenman et al.,
2005; Vickers et al., 1998), D. melanogaster (Bhandawat et al., 2007),
and A. mellifera (Mu ¨ller et al., 2002) can respond to olfactory stimuli
at much higher frequencies, up to ca. 200 s?1. When responding to a
natural plume of volatiles, M. sexta PNs typically respond with short
bursts of spikes and an instantaneous spiking frequency of ca.
100 Hz (Vickers et al., 2001). The firing rate of single PNs in several
insects other than locusts roughly scales with stimulus concentra-
tion (see Section 6.1) (Bhandawat et al., 2007; Bichao et al., 2005;
Reisenman et al., 2004, 2005; Schlief and Wilson, 2007; Silbering
et al., 2008; Wilson et al., 2004), while individual S. americana PNs
respond at roughly the same firing rate across concentrations (Assisi
et al., 2007; Stopfer et al., 2003). Instead, ensembles of S. americana
PNs respond to different concentrations of the same olfactory
stimulus along trajectories that, while similar, evolve into distinct
representations over time (Stopfer et al., 2003). Thus, while LFP
oscillations exist in the ALs of several species, the strict phase-locked
code observed in S. americana is not evident in other insects and
furthermore is not easily compatible with frequency coding of
Firing synchrony among PNs in moths (M. sexta: Christensen
et al., 2003, 2000; Ito et al., 2009; Lei et al., 2002) and flies (D.
J.P. Martin et al. / Progress in Neurobiology 95 (2011) 427–447
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melanogaster—the only other species studied in detail: Tanaka
et al., 2009; Turner et al., 2008; Wilson and Laurent, 2005) is not
fully entrained to the LFP. In response to a brief olfactory stimulus,
mimicking a pulse of volatiles encountered in a natural plume
(Vickers, 2006c), PNs in moth ALs produce high-frequency spikes
early in the response that are synchronized, and then synchrony
falls off quickly thereafter (Christensen et al., 2003; Lei et al., 2002).
This has been examined most closely in the sex-pheromone
specific MGC in ALs of male M. sexta. In this subsystem, each of the
two key components of the female’s sex-pheromone mixture
activates PNs in one of the two largest MGC glomeruli and inhibits
PNs in the other (Christensen and Hildebrand, 1997; Lei et al.,
2002). Stimulation with the natural mixture, thus activating both
the inhibitory and excitatory inputs to MGC PNs, increases firing
synchrony (Lei et al., 2002). Similar synchrony has been observed
in the main AL in response to natural mixtures of floral volatiles,
depends on the identity and intensity of volatiles, and occurs in a
unique pattern for individual odors (Christensen et al., 2000; Lei
et al., 2004; Riffell et al., 2009). Synchrony may subserve yet
another function in the ALs of moths. Synchronous firing between
neurons is enhanced for pheromone (Lei et al., 2002) or plant-odor
(Riffell et al., 2009) stimuli that are innately attractive. This may
represent a common encoding dimension for behaviorally signifi-
cant odors from diverse sources such as food or conspecific mates
(Martin and Hildebrand, 2010).
Multiple stimuli of longer duration (>1 s) at long (20 s)
intervals evoke a two-stage response in PNs in the plant-odor
responsive glomeruli of M. sexta (Ito et al., 2009). After a brief
period of high-frequency firing, the PN exhibits prolonged,
temporally complex, lower-frequency firing. The LFP in the
mushroom body similarly shifts from high- to low-frequency.
Under similar stimulus conditions, PNs in the ALs of D.
melanogaster also transition from high- to low-frequency spiking
(Tanaka et al., 2009). In both species, individual PNs often fire in
phase with these oscillations but are much less entrained than are
PNs of S. americana and typically fire at higher frequency than that
of the LFP. It seems, therefore, that control of firing phase by
inhibition from LNs is much weaker in ALs of M. sexta and D.
Melanogaster than in those of S. americana and at most only weakly
entrains PN firing to a global oscillation. We further discuss the
implications of the stimulus regimen necessary to generate phase-
locking in these animals, similar to that in locusts, in Section 6.4.
Finally, although administration of the GABAA-receptor antag-
onist picrotoxin (PTX) disrupts LFP oscillations in the AL of A.
mellifera and increases the likelihood that A. mellifera generalizes
between closely related odors (Stopfer et al., 1997), more recent
work has shown that PTX also allows additional, weakly
stimulated glomeruli to respond to an olfactory stimulus (Sachse
and Galizia, 2002). Based on this side-effect, treatment with PTX
has the potential to disrupt a neural code based either on
oscillatory synchronization of PNs or on the identity of responsive
PNs, making behavioral pharmacological experiments difficult to
interpret. Similar work on moths (M. sexta) demonstrates that PTX
disrupts discrimination (behaviorally distinct from increasing
generalization) between both similar and dissimilar odors, a
finding that is also consistent with physiological data (Mwilaria
et al., 2008). Across species, behavioral evidence for the impor-
tance of LFP oscillations in olfactory coding remains elusive.
6.4. Encoding temporal features of olfactory stimuli
A flying insect experiences olfactory stimuli as brief, discontin-
uous pulses, as its antennae encounter filaments of volatiles in a
plume. Encoding these spatio-temporal features of a stimulus is
necessary for the flying insect to follow a plume to its source (Carde ´
and Willis, 2008). In this section, we consider how the olfactory
system encodes such brief, stochastic stimuli. We also suggest how
differences in the spatio-temporal structure of stimuli important
to an insect may shape processing of olfactory information.
The ALs of moths exhibit several adaptations that improve the
resolution of pulses in a sex-pheromone plume, subserving the
vital task of locating the source, a calling, conspecific female moth.
PNs in A. ipsilon ALs respond with extremely short lag to ORC input
(Jarriault et al., 2010). In M. sexta, the ability of an MGC PN to follow
the frequency and duration of pulses of sex pheromone is
correlated with the strength of inhibitory input to the neuron
(Christensen and Hildebrand, 1988; Heinbockel et al., 1999, 2004).
Temporal fidelity is further improved when a moth is stimulated
with the correct ratio of the two key pheromone components,
eliciting a specific balance of excitation and inhibition (Christensen
and Hildebrand, 1997; Heinbockel et al., 2004). This combination
of excitatory and inhibitory inputs causes some MGC PNs to
respond with a shorter latency and higher rate of spiking,
compared to stimulation with the excitatory component alone.
Temporal fidelity is also enhanced by longer-lasting inhibition
following a burst of spikes, during which spontaneous activity, but
not responses to subsequent pulses of pheromone, is reduced
(Christensen et al., 1998; Lei and Hansson, 1999). Disrupting this
inhibition impairs a moth’s ability to follow a pheromone plume to
its source (Lei et al., 2009).
ORC-to-PN synapses in D. melanogaster also act as high-pass
filters, combining a high probability of neurotransmitter release
with rapid synaptic depression to long-lasting stimuli to empha-
size the onset of an olfactory stimulus (Bhandawat et al., 2007;
Kazama and Wilson, 2008). Intracellular recordings in D. melano-
gaster (Kazama and Wilson, 2008) and the moth A. ipsilon (Jarriault
et al., 2010), as well as imaging of ORC and PN activity and
intracellular recording of PNs in A. mellifera (Galizia and Kimmerle,
2004; Sachse and Galizia, 2003), reveal that PNs respond to the
rising phase of the ORC response, and PN responses decline before
the peak of ORC activity. It is likely that the inhibitory network,
along with the properties of synapses in the AL, improves the
ability to encode rapid spatio-temporal fluctuations of a plume of
The responses of KCs in the MB also reflect the emphasis on the
initial, brief contact with volatiles, and thus the brief availability of
information about olfactory stimuli. The responses of KCs in M.
sexta (Ito et al., 2008) and A. mellifera (Szyszka et al., 2005) occur
within a few milliseconds of the onset of a stimulus pulse, followed
by an unresponsive period. The output neurons of the MB in A.
mellifera respond with patterns differentiating rewarded from
unrewarded odors, delayed only tens of milliseconds from the AL
input to the MB (Strube-Bloss et al., 2011). A coding scheme in
which olfactory stimuli are recognized on the basis of the identity
and relative activation of PNs associated with individual glomeruli,
as in classic population coding (Sanger, 2003), consolidates much
of the information in the initial response. This could allow rapid,
robust classification of olfactory stimuli in a plume, where brief,
unpredictable pulses of volatiles are encountered. Evidence for
rapid behavioral responses to olfactory stimuli in flies (Budick and
Dickinson, 2006) and honey bees (Fernandez et al., 2009; Wright
et al., 2009) suggests that the information contained in short
encounters with stimuli is all that is necessary for some behaviors.
The responses of KCs in S. americana, however, are not limited to
the onset of the stimulus. An individual KC requires a large number
of coincident PN inputs in order to fire, and this criterion may not
be reached in most or even all cycles of PN responses to olfactory
stimuli (Jortner et al., 2007; Perez-Orive et al., 2004, 2002).
Oscillatory PN input also drives feed-forward inhibition to KCs in S.
americana, preventing them from firing in all but a brief part of the
cycle (Perez-Orive et al., 2002). The net result of these processes is
stimulus-driven KC activity consisting of one or a few spikes, in
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stimulus-specific temporal patterns (Stopfer et al., 2003), during
even a sustained olfactory stimulus. The identity of a stimulus thus
is encoded first in a distributed population of PNs and then in a
sparse population of KCs, in which the membership of both
populations evolves over several cycles of the oscillatory signal. An
important outcome of this processing scheme is the theoretical
ability of the olfactory system of S. americana to produce a unique
code for each of many similar stimuli, which could in turn be
associated with a variety of other information about a source of
volatiles (Laurent, 2002).
The locust S. americana therefore instantiates a unique code in a
unique olfactory network, distinct from those of other insects such
as sphinx moths, fruit flies, and honey bees. While olfactory
information is concentrated early in a stimulus pulse for those
species, representations of olfactory stimuli become more distinct
over time in both the AL and MBs of S. americana (Perez-Orive et al.,
2002; Stopfer et al., 2003). We suggest that this difference may be
adaptive in the natural contexts in which acridids such as locusts
use olfactory information.
The olfactory systems of moths, bees, and flies appear to be
adapted to encode olfactory stimuli upon brief, stochastic
encounters with discontinuous pulses in plumes of volatiles.
Locusts, however, impose an internal timing signal to produce a
reliable temporal code throughout prolonged contact with a
stimulus (Laurent, 2002). The addition of the temporal dimension
in the olfactory coding scheme used by locusts can greatly expand
the coding space allotted for classifying stimuli. As opposed to a
code based on the identity and relative activation of responding
glomeruli (Galan et al., 2004; Sachse and Galizia, 2003), integration
over many cycles creates an exponentially large number of ‘virtual’
PN populations, allowing for a different active ensemble at each
cycle (Laurent et al., 2001). This increased coding space may be
adaptive for a voracious, generalist insect such as a locust. Locusts
have a wide range and a diverse diet of vegetation (Simpson and
Raubenheimer, 2000). Vegetative tissues of plants emit complex,
species-specific mixtures of volatiles, both when intact and when
damaged as the insects feed (Bruce et al., 2005). Locusts can
associate volatiles with the nutritional content of their source
(Behmer et al., 2005) and can use associations to balance their diet
(Dukas and Bernays, 2000; Raubenheimer and Tucker, 1997). There
is little evidence for olfaction-guided aerial navigation in the
Acrididae (Helms et al., 2003), and several authors have suggested
that locust foraging is primarily visually driven (Chapman, 1988).
Thus, for locusts, exposure to significant olfactory stimuli occurs
primarily in the context of prolonged feeding bouts in close contact
with the source of volatiles, allowing for full use of the coding space
available in the temporal structure of olfactory responses.
Although other insects encounter volatiles in similar circum-
stances, aerial foragers must rely more frequently on identification
of brief, stochastic pulses of volatiles and therefore require a coding
system adapted to the spatio-temporal structure of a plume.
Finally, observations of PN spikes phase-locked to LFP oscilla-
tions in D. melanogaster and M. sexta are instructive (Ito et al., 2009;
Tanaka et al., 2009). Oscillations emerged only after multiple
(>10), 2-s pulses of an olfactory stimulus delivered at a lower
airspeed than used in other investigations. Oscillatory synchrony
was also observed after an initial, phasic spiking response to
olfactory stimuli, suggesting that the two coding schemes may
operate in parallel in a single species. Perhaps encoding based on
oscillations requires longer contact with a stimulus, such as may
occur when an animal is feeding from a flower. A final
reconciliation of these two schemes would require a mechanism
wherein encoding of stimuli associated with reward under
conditions of long, repeated exposure (facilitating oscillations)
are transformed to allow identification under odor-plume condi-
tions that do not allow for oscillations to develop. Honey bees
appear to be capable of this transformation. Bees trained to long
pulses of an odor perform well in a discrimination test, even when
tested with short pulses of the odor (Fernandez et al., 2009).
In summary, we suggest that a trade-off is likely between a
coding scheme optimized for discriminating fewer olfactory
stimuli while flying and one that can produce unique, decorrelated
codes for volatiles from many, highly similar food sources upon
prolonged exposure to the stimuli.
7. Concluding remarks
Progress to date in insect olfactory neurobiology and neu-
roethology points to future direction for the field. We suggest that
the principles and models of insect olfaction will be expanded and
elaborated as the range of variation among insect species is
considered. A comparative approach, grounded in natural behav-
ior, can resolve conflicting results and guide inquiry in fruitful
directions. Future progress will be made through not only new
discoveries but also direct comparison between species when
possible. In evaluating comparative work, however, one must
always be wary that findings in one species may not be applicable
to another. Finally, we have attempted to illustrate the broad,
interdisciplinary nature of work in this field. Insect olfaction is
especially fertile ground for interplay among studies in ecology,
evolution, and behavior that set the parameters for the problems
insect olfactory systems must solve.
We thank Tom Christensen and Nick Strausfeld for helpful
comments in preparing this manuscript, and Charles Hedgcock for
assisting in creating the figures. JPM was supported by NIH
fellowship F31DC009722 during the preparation of this review.
Our current research in this area is supported by NIH grant R01-
DC-02751 (to JGH).
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