Calcium imaging in the ant Camponotus fellah reveals a conserved odour-similarity space in insects and mammals.

Abstract

Olfactory systems create representations of the chemical world in the animal brain. Recordings of odour-evoked activity in the primary olfactory centres of vertebrates and insects have suggested similar rules for odour processing, in particular through spatial organization of chemical information in their functional units, the glomeruli. Similarity between odour representations can be extracted from across-glomerulus patterns in a wide range of species, from insects to vertebrates, but comparison of odour similarity in such diverse taxa has not been addressed. In the present study, we asked how 11 aliphatic odorants previously tested in honeybees and rats are represented in the antennal lobe of the ant Camponotus fellah, a social insect that relies on olfaction for food search and social communication.
Using calcium imaging of specifically-stained second-order neurons, we show that these odours induce specific activity patterns in the ant antennal lobe. Using multidimensional analysis, we show that clustering of odours is similar in ants, bees and rats. Moreover, odour similarity is highly correlated in all three species.
This suggests the existence of similar coding rules in the neural olfactory spaces of species among which evolutionary divergence happened hundreds of million years ago.

Full text

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RESEARCH ARTICLEOpen Access
Calcium imaging in the ant Camponotus fellah
reveals a conserved odour-similarity space
in insects and mammals
Fabienne Dupuy1,2, Roxana Josens3, Martin Giurfa1,2, Jean-Christophe Sandoz1,2,4*
Abstract
Background: Olfactory systems create representations of the chemical world in the animal brain. Recordings of
odour-evoked activity in the primary olfactory centres of vertebrates and insects have suggested similar rules for
odour processing, in particular through spatial organization of chemical information in their functional units, the
glomeruli. Similarity between odour representations can be extracted from across-glomerulus patterns in a wide
range of species, from insects to vertebrates, but comparison of odour similarity in such diverse taxa has not been
addressed. In the present study, we asked how 11 aliphatic odorants previously tested in honeybees and rats are
represented in the antennal lobe of the ant Camponotus fellah, a social insect that relies on olfaction for food
search and social communication.
Results: Using calcium imaging of specifically-stained second-order neurons, we show that these odours induce
specific activity patterns in the ant antennal lobe. Using multidimensional analysis, we show that clustering of
odours is similar in ants, bees and rats. Moreover, odour similarity is highly correlated in all three species.
Conclusion: This suggests the existence of similar coding rules in the neural olfactory spaces of species among
which evolutionary divergence happened hundreds of million years ago.
Background
A major aim of neuroscience is to understand how phy-
sical stimuli are represented in the animal or human
brain, and to attempt to describe the main dimensions
that define the perceptual spaces of these organisms [1].
As olfaction represents a key sensory modality in most
animal species, numerous studies in the past have
endeavoured to unravel the anatomical and functional
features of olfactory centres, from the repartition of
olfactory receptors at the periphery, their projection
within the glomeruli of primary odour centers (olfactory
bulb in vertebrates, antennal lobe in insects) and further
projection to higher brain centers (olfactory cortex in
vertebrates, mushroom bodies in insects) [2-5]. Neuro-
physiological studies, using both electrophysiological
[6-11] and optophysiological techniques [12-18] have
studied how different odour molecules differentially acti-
vate subsets of neurons or glomeruli. These studies have
emphasized the remarkable similarities both in the gen-
eral organization and in the odour coding properties of
the olfactory systems of animals as remote in evolution-
ary terms as higher vertebrates and insects [19,20].
A general finding of these studies was that odours give
rise to a combinatorial pattern of activity that can be
measured across neurons of the same structure or
across glomeruli in the antennal lobe (AL) or olfactory
bulb. Moreover, odours sharing a chemical functional
group or showing similar length of the carbon chain
give rise to across-fibre patterns that are similar [21-23].
Therefore, similarity in the chemical world finds a
representation in the neural activity of olfactory brain
centres [24].
In the honeybee Apis mellifera, using an appetitive
conditioning approach, we recently described the pair-
wise perceptual similarity among 16 aliphatic odours
from 4 different functional groups (primary and second-
ary alcohols, aldehydes and ketones) and 4 different
chain lengths (from C6 to C9; [25]). Using multidimen-
sional analyses, we could show that the main
* Correspondence: sandoz@legs.cnrs-gif.fr
1Université de Toulouse; UPS; Research Centre for Animal Cognition (UMR
5169), 118 route de Narbonne, F-31062 Toulouse Cedex 9, France
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© 2010 Dupuy et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.

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dimensions that defined bees’ behaviour were indeed
chemical dimensions like chain length and functional
group of odour molecules. This study also showed that
odours that induce similar calcium activity patterns in
the bee AL are indeed treated by bees as similar in their
behaviour. The logical conclusion from this work would
be that chemical dimensions could represent essential
dimensions encoding the representations of general
odours (i.e. not including pheromones) in the brain and
that odour similarity relationships should be relatively
conserved in different species across the evolutionary
scale. Now a number of species allow measuring neural
olfactory similarity between odours, like rats and mice
[15,26]), turtles [27], salamander [28], xenopus ([28-30],
fishes [16,31], locusts [32], honeybees [12,33], ants [34],
moths [35-37], drosophila [11,38,39], etc.
To start a comparative measure of odour similarity in
different organisms, we have carried out optical imaging
recordings in the olfactory system of a novel species of
Hymenoptera, the ant Camponotus fellah. For such
comparative studies, ants are an interesting model as
they constitute a varied group with a great diversity of
life histories, ecological interactions and novel evolution-
ary adaptations [40]. Olfactory cues are important in
most aspects of their life, such as foraging, communica-
tion, larval grooming, nest defence and localization,
social control and nestmate recognition. Moreover, the
anatomical structures of the ant brain, in particular their
olfactory circuits, are being described in great details
[41-45] and they are amenable to electro- and optophy-
siological recordings in the brain [34,41,46]. Lastly, ants
(in particular Camponotus fellah) can be individually
trained to associate odours with gustatory reinforcers in
a Y-maze under controlled conditions, allowing access
to the study of the neural bases of olfactory learning
and memory [47].
Adapting to these ants a method developed in the bee
for specifically staining second-order AL neurons [33],
we have measured the similarity among 11 aliphatic
odours including alcohols, aldehydes and ketones, which
were previously used for recording odour-evoked activity
in the honeybee brain [48]. We show that these odours
evoke activity in particular glomerular clusters of the
ant AL and that these regions of the ant olfactory sys-
tem classify odorants in a similar way as in the honey-
bee. Consequently, we show that odour similarity
relationships are conserved among ants and bees. More-
over, using published data from radioactive 2-deoxyglu-
cose (2DG) stainings on the olfactory bulb of rats [22],
we show that odour similarity in ants is highly corre-
lated to odour similarity in rats. Our result suggests that
the main dimensions of ant, bee and rat olfactory spaces
may be conserved, although evolutionary divergence
among these species happened in the range of hundreds
of million years ago. Therefore, although based on very
different sensory receptors at the periphery, the olfac-
tory systems of these animals would give rise, thanks to
combinatorial coding, to similar perceptual relationships
among odorants.
Methods
Preparation and staining
Worker ants of medium size (~7 mm) were taken from
one of two colonies and were immobilized by cooling
on an ice bed. They were mounted into Plexiglas cham-
bers and their heads were immobilized with low-
temperature melting wax (Deiberit 502, Böhme &
Schöps Dental GmbH, Goslar, Germany). The antennae
were then gently oriented to the front of the chamber
and their base was fixed with two-component epoxy
glue (Araldite) providing a seal between the flagella and
the rest of the head. Then a small pool was created on
top of the head by fixing thin plastic walls on the sides
of the chamber (see [49]). A window was opened in the
head cuticle, glands and tracheas covering the brain
were removed. Throughout the preparation, the brain
was regularly washed with saline solution (in mM: NaCl,
130; KCl, 6; MgCl2, 4; CaCl2, 5; sucrose, 160; glucose,
25; HEPES, 10; pH 6.7, 500 mOsmol; all chemicals from
Sigma-Aldrich, Lyon, France). For calcium imaging
experiments, we aimed to specifically stain the projec-
tion neurons that convey odor information from the AL
to the mushroom bodies and the lateral horn. For that,
we placed highly-concentrated chips of Fura-2 dextran
(10000 MW, in bovine serum albumine - 2% in distilled
water) on their axonal path [45], between the a-lobe
and the border of the optic lobes, as was done in the
honeybee [33]. We first used a sharp glass microelec-
trode (~30 μm tip diameter) to perforate the thick
neurolemma at the chosen location. Then a second
microelectrode was used to place the Fura-2 chips
within the brain. After placing the dye, the brain was
thoroughly washed with saline to remove extra-cellular
dye. The piece of head cuticle was then replaced onto
the opening and the ant was left in a dark place for
three hours.
Optical recordings of odor-evoked activity
In vivo calcium imaging recordings were carried out
using a TILL photonics imaging system (Martinsried,
Germany). Ants were placed under an epifluorescent
microscope (Olympus BX-51WI) with a 10× (NA 0.3) or
a 20× (NA 0.5) water immersion objective (UMPlanFL
Olympus). Images were taken using a 640 × 480 pixel
12-bit monochrome CCD-camera (T.I.L.L. Imago)
cooled to -12°C. Filters used were a 405 nm dichroic
filter and a 440 nm emission filter. The preparation was
alternately excited with 340 nm and 380 nm
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monochromatic light using T.I.L.L Polychrom IV. Each
recording consisted of 100 double frames, at 5 double
frames per sec. We used 4×4 (20× objective) or 2×2
(10× objective) binning on chip, so that pixel size in our
recordings always corresponded to ~2 × 2 μm. Integra-
tion time was 4-40 ms and 10-128 ms respectively for
340 nm and 380 nm excitation. Odour stimuli were
applied for 1 sec and started just before the 15thdouble
frame. Under the microscope, a constant air-stream was
directed to the ant’s antennae (2 cm distance). During
odour stimulation, a secondary airflow was diverted
from the main airflow and passed through an inter-
changeable glass pipette containing 4 μl of the odour on
a 1 cm2filter paper. Over all animals, a range of eleven
aliphatic odours was used: 1-hexanol, 1-heptanol, 1-octa-
nol, 1-nonanol, 2-hexanol, 2-octanol, 2-heptanone, 2-
nonanone, hexanal, heptanal, octanal (Sigma-Aldrich).
Because in early experiments, a more limited range of
odours was used, not all odours were tested in all ani-
mals. As control stimulus, a pipette containing a clean
piece of filter paper was used. An experimental run con-
sisted in 3 fully-randomised series of all stimuli with ~1
min intervals. A total of 79 ants were subjected to opti-
cal imaging experiments, out of which only 7 showed
good calcium responses to odorants and allowed record-
ing 3 complete odour stimulation runs. Compared to
honeybees, we experienced more difficulty in ants for
adequate staining of projection neurons and for the sur-
vival of animals through the experiment.
Measures of glomerular layout
During optical imaging, the glomerular structure of the
ALs was hardly visible, so we performed additional
stainings. The brains were thus treated according to a
protocol that proved efficient in the honeybee: a mixture
125:1 (vol/vol) of a protease solution (from Bacillus
licheniformis in propylene glycol, Sigma Aldrich), for
digesting the brain sheath, and of the dye RH795 (dis-
solved in absolute ethanol), for staining cell membranes
(Molecular Probes), was applied for 1 h. The brain was
rinsed and fluorescent photographs were taken at 50-60
different focal planes under 530 nm excitation (filter set:
570 nm dichroic mirror and LP 590 nm emission filter).
These images allowed seeing a few glomeruli and recog-
nizing main landmarks on the AL, but failed to provide
a precise glomerular layout. We thus performed a differ-
ent type of staining on ants that were not subjected to
imaging. As above, a protease was applied for 1 h. Then
the brain was carefully rinsed with saline, and a filtered
4% neutral red solution in distilled water was applied
for 1 h. The images, which were taken as above, clearly
revealed the AL structure with its different glomerular
clusters and allowed us to count and measure the glo-
meruli. We also used these anatomical data to construct
a standard AL model, in which a few key anatomical
landmarks (borders between the different glomerular
clusters) were placed in a relative coordinate system.
The × and Y coordinates of these landmarks measured
in different individuals were averaged for constructing
the standard AL model shown in Figure 1C. Thereafter,
activity foci from imaging recordings could be placed in
the same coordinate system to identify the most active
areas of the ant AL. Note that the standard AL was not
used for calculations of similarity between odor response
patterns, or for comparisons among species. For addi-
tional anatomical reference, a few preparations were
brought to a laser-scanning confocal microscope (Leica
TCS SP2, 543 nm HeNe laser) and about 40 optical sec-
tions at the frontal surface of the AL were acquired with
~2 μm intervals. Z-projections (see Figure 1A) were
made using the Image-J software (NIH, USA).
Data processing and analysis
Raw data processing
Calcium-imaging data were analyzed using custom-made
software written in IDL (Research Systems Inc., Color-
ado, USA). Each recording to an odour stimulus corre-
sponded to a 4-dimensional array with the excitation
wavelength (340 nm or 380 nm), two spatial dimensions
(x, y pixels of the area of interest) and the temporal
dimension (100 frames). Three steps were carried out to
calculate the signals: First, to reduce photon (shot)
noise, the raw data were filtered in the two spatial and
in the temporal dimensions using a median filter with a
size of 5 pixels. This step was applied separately for the
340 nm and the 380 nm data. Second, to correct for
bleaching and possible irregularities of lamp illumination
in the temporal dimension, a subtraction was made at
each pixel of each frame, of the median value of all the
pixels of that frame. Such a correction stabilizes the
baseline of the recordings, without removing pertinent
signals. This step was applied separately for the 340 nm
and the 380 nm data. Third, for each pixel, the ratio R
of the 340 nm and the 380 nm data was made and then
ΔR was calculated at each frame, as ΔR = Rn- R0, in
which Rnis the ratio data at frame n and R0is a refer-
ence frame before the stimulus, here the average of
frames 5 to 14. Thus, all ratios were close to 0 shortly
before the odour stimulus.
Selection of activity spots
Because we had only limited anatomical information in
ants subjected to calcium imaging, we developed a pro-
cedure for selecting the most relevant activity spots in
each AL. We first made colour-coded activity maps for
each odour in each animal, which allowed seeing neural
activity spots. Activity spots were first selected visually,
and activity was measured on a square of 9 × 9 pixels
(18 μm × 18 μm), a surface that would be well within
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Figure 1 Optical imaging of odour-evoked activity in the projection neurons of the ant Camponotus fellah. A) Z-projection of a confocal
stack of the left and right antennal lobes of a worker ant showing the anatomical features accessible to optical imaging. The frontal side of the
antennal lobe presents on average 46 glomeruli arranged according to 4 clusters. Cluster arrangement is symmetrical between brain
hemispheres. B) Example of calcium signals from the projection neurons in the antennal lobe of a worker ant. Odour-evoked activity is
superimposed on a wide-field image of the lobe, using a false-colour code, ranging from just above baseline (dark violet, +0.1% ΔR) up to
maximal activation (red, +1.5% ΔR). Two stimulations with each odour and the air control show the reproducibility of the calcium signals.
Squares with numbers 1 to 3 relate to different classes after the cluster analysis presented in figure 3A. C) Standard right antennal lobe of C.
fellah workers in a relative coordinate system, showing the average borders of the different glomerular clusters (anatomical preparations, n = 16
lobes). The inset indicates the numbers given to each cluster (see A). Colour squares correspond to the active spots identified in 7 ants which
showed reproducible calcium signals. Most active spots were recorded in the two caudal clusters 1 and 2.
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an individual glomerulus (see results). We then com-
puted within each individual a measure of noise, as the
standard deviation of the signal before the stimulus
(from frame 4 to 11) averaged over all selected spots
and all measurements in this animal [33]. Activity spots
were only selected if the amplitude of excitation (or
inhibition) was above (respectively below) the noise
threshold. A spot needed to show significant activity to
at least one odour to be selected at this stage. This
activity also had to be reproducible over the three pre-
sentations of the odour. Because we used a ratiometric
dye, an excitatory signal (an intracellular calcium
increase) should induce a fluorescence increase when
exciting at 340 nm and a decrease at 380 nm (the con-
trary for an inhibitory signal). We thus further inspected
all selected signal curves, and only kept activity spots
that showed the appropriate inversion of 340 and 380
nm signals upon odour delivery. This conservative pro-
cedure ensured that only biologically-relevant signals
were taken into account in the analysis. For ensuring
that the selection of activity spots was unbiased, the per-
son carrying out this selection was blind with respect to
the tested odours and to the statistical analyses that
would be performed.
Measures of odour similarity and comparison among taxa
One aim of this study was to measure similarity
between odorants based on the signals obtained in the
ant AL. To do that, we used the Euclidian distance
between odour representations in a n-dimensional
space in which the activity of each spot represents one
dimension [12,49,50]. The higher the distance, the less
similar odour representations are. We included in this
analysis only ants that showed at least 4 activity spots
(n = 5 ants). First, we asked at which point in time the
discriminability among odours reaches a maximum.
During a recording, activity for each odour follows an
individual trajectory in the space of neural activation.
Instantaneous discriminability between stimuli can
thus be measured as the distance between odour repre-
sentations at each point in time. We thus computed
within each animal, and at each double-frame, Eucli-
dian distances between odour representations for all
odour pairs. The time courses of two types of distances
were thus obtained: (i) the mean distance between
each odour and the air control; (ii) the mean distance
between any two odours tested. These distances were
first averaged at each double-frame within each animal,
and then over different animals. To show the time
courses in the same figure (Figure 2C, D), the curves
were scaled to 0% just before odour delivery (frame
14) and to 100% at their own maximum. As frame 18
(~600 ms after odour delivery) proved to be the opti-
mum for measuring inter-odour distances, all further
calculations were carried out on response amplitudes
measured between just before the stimulus (average of
frames 12, 13 and 14) and around frame 18 (average of
frames 17, 18 and 19).
Within each ant, a matrix of inter-odour distances
was thus calculated. We set to 100% the highest
distance of each animal, and scaled all other distances
accordingly. To ask whether odour-similarity relation-
ships are the same in different animal species, we sub-
jected our dataset to correlation analyses with previous
data on honeybees [48] and on rats [22]. Distances
between odour representations in the bee data were cal-
culated as in [25]. AL activation maps (as presented on
http://neuro.uni-konstanz.de/) were transcribed into
activation levels for each glomerulus from 0 to 3
according to the following signal scale: activity below
40%: 0; 40-60% activity: 1; 60-80% activity: 2; >80%
activity: 3. Since not all ants could be tested with all
odours, we performed two different analyses. In the first
one, we maximized the number of odour pairs evalu-
ated, so we used all 11 aliphatic odours, and the
distances obtained from 3 to 5 ants were averaged for
each of the 55 odour pairs. In a second analysis, we
maximized the number of ants, so we used only 6
aliphatic odours that were tested in all 5 ants, and eval-
uated respectively 15 odour pairs. Both analyses gave
essentially the same result. In the rat, Johnson et al.
[22] mapped 2DG responses to a wide range of aliphatic
odorants, including 9 odours used in the present study,
onto 13 identified lateral modules (groups of glomeruli)
and their 13 homologous medial modules. We tran-
scribed activity intensity depicted as circles in Figure 2
of Johnson et al. [22] to percentages of activity in each
module (from 0% to 100%, in 10% steps) to each of the
9 odours (hexanal, heptanal, octanal, 1-hexanol, 1-hep-
tanol, 1-octanol, 2-hexanol, 2-octanol, 2-heptanone). The
matrix of Euclidian distances between these odour
representations was used for a correlation analysis as
with bee data, maximizing the number of odour pairs
(3-5 ants, 36 odour pairs). In the present paper, data
from the lateral modules of the olfactory bulb are
shown (Figure 3C), but data from the medial modules
give the same result (data not shown). To test for the
significance of the correlation coefficients observed
between distance matrices in two species, the Mantel
test, a dedicated random permutation test, was used
[51]. This test randomly permutes the distance values
within one of the two matrices and then computes the
correlation coefficient with the permuted data. By doing
so many times (here we used 10000 permutations), the
alpha value for the significance of the correlation coeffi-
cient is directly estimated. Ant, bee and rat distance
matrices were also used in cluster analyses to represent
groups of similar odours, using Ward’s classification
method.
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Results
Anatomy of the frontal surface of the antennal lobe of
C. fellah
The front part of the AL of C. fellah, which is accessible to
optical imaging, contains mostly four different glomerular
clusters, defined by thin but clear clefts between groups of
glomeruli (Figure 1A). We analysed 16 ALs from 8 differ-
ent ants, and found an average of 46.0 ± 2.6 (mean ±
SEM) visible glomeruli on the frontal surface of each lobe.
Left and right ALs were clearly symmetrical, with the
same overall number of glomeruli (45.7 ± 3.2 and 46.2 ±
4.4 respectively, t test, t = 0.41, NS) and the same structure
in separate glomerular clusters (Figure 1A). For this rea-
son, and because imaging was performed mostly on right
ALs, all subsequent analyses were carried out as for right
ALs, left ALs being flipped horizontally. Glomerulus size
was rather constant, and width for instance varied maxi-
mally with a factor 2, as the smallest glomerulus had
Figure 2 Time courses of calcium signals in the projection neurons of ants. A) Time courses obtained in 6 glomeruli as in Figure 1B, after
stimulation with 11 aliphatic odours and the air control. Odour names are indicated in colour according to their functional group (aldehydes,
black; ketones, red; primary and secondary alcohols, blue and green respectively). Odour delivery (1 sec) is indicated as a grey bar. Both
excitatory (calcium increase) and inhibitory (calcium decrease) signals were observed, as well as a few temporally complex signals. On the upper
left, an activity map (2-octanol) shows both excitatory responses (in shades of red) and inhibitory responses (in shades of blue) on the same
lobe. On the upper right, two examples of typical time courses for excitatory and inhibitory signals are given. In each case, an inverse evolution
of fluorescence recorded with 340 nm and 380 nm excitations is observed. B) Time course of a measure of odour separability in all recorded
ants. The instantaneous Euclidian distance between each odour glomerular pattern and the air control (red curve) gives an indication of how
fast the ant olfactory system can best separate an odour from an odourless background (~800 ms). The instantaneous Euclidian distance
between the activity patterns obtained for any two odours (blue curve) gives an indication of how fast the ant olfactory system reaches an
optimum in its separation power among odours (~600 ms). Both distances are normalized to 1 at their maximum and to 0 just before odour
onset. For this reason, they can be under 0 just before the stimulus. C) Same data as B, showing in greater details the evolution of both
measures during the stimulus.
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Figure 3 Comparison of odour similarity in ants, bees and rats. A) Dendrogram (Ward’s classification) showing similarity relationships among
the 11 aliphatic odours in ants, honeybees Apis mellifera (data from [48]) and rats Rattus norvegicus (9 odours, data from [22]). Three main
clusters are found in each species, with one cluster containing mainly alcohols (cluster ant #1, bee #1 and rat #2), and another containing the
three aldehydes (cluster ant #2, bee #3, rat #1). B) Inter-odour Euclidian distances in ants as a function of the same measure in honeybees, with
either maximized number of odour pairs (Left, 55 odour pairs, 3-5 ants, r = 0.43, Mantel test, p = 0.036) or maximized number of ants (Right, 15
odour pairs, 5 ants, r = 0.76, Mantel test, p = 0.018). C) Inter-odour distances in ants as a function of the same measure in rats (36 odour pairs,
3-5 ants, r = 0.75, Mantel test, p < 0.001). D) Running correlation between instantaneous Euclidian distances in ants (maximizing ant number, as
in B, right panel) and fixed-point distances in honeybees [48]. The quality of the correlation (r2in red) is plotted along with the inter-odour
distance (in blue, taken from Figure 2B) showing the separation power of the ant olfactory system throughout a recording. Maximum correlation
is obtained very shortly after odour application (~200 ms), and remains high throughout odour presentation. After odour offset, correlation
decreases but oscillations are observed, with high correlation epochs as late as 5 sec after odour application, when activity and the separation
power of the ant system are low. Orange bars below the graph indicate significance in running Mantel tests 1) between ant data at each 200
ms time bin and the fixed-point bee data or 2) between ant data at each 200 ms bin and fixed-point ant data 200 ms after odour onset (frame
termed ‘ref’ in the figure). Significant correlation rebounds (see text) are marked with orange arrows. Circles correspond to plots between ant
and bee data on the upper right, showing instantaneous Euclidian distances in the ant as a function of distances in the bee.
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dimensions of 20.2 ± 1.2 μm × 17.6 ± 0.7 μm and the lar-
gest glomerulus dimensions of 38.0 ± 1.7 μm × 39.1 ± 1.8
μm (n = 16 lobes). The four clusters were easily recogniz-
able and arranged similarly in different individuals. Cluster
1 was the largest, was placed on the medio-caudal side
and contained on average 18.1 ± 0.8 glomeruli. Clusters 2,
3 and 4 followed a diagonal axis on the lateral side of the
AL and contained 10.4 ± 0.9, 8.4 ± 0.7 and 5.6 ± 1.0 glo-
meruli respectively. Based on this anatomical data, we
constructed a standard AL, in which the border between
the different clusters is represented as averages ± SD
(Figure 1C, inset) in a relative coordinate system based on
each lobe’s width (X) and height (Y) in the picture. The
standard AL will be used for placing activity spots from
the imaging data.
Odour responses from projection neurons
Seven ants (out of 79 tested animals) showed good cal-
cium responses to odorants, which allowed recording of
3 complete odour stimulations runs. In such individuals,
odour stimulation led to specific activity patterns
(Figure 1B), which comprised mostly excitatory
responses (intracellular calcium increase). Odour
responses were reproducible as the same pattern
appeared when the same odour was presented again
(Figure 1B). Different odours induced signals in a differ-
ent combination of activity spots. The size of active
spots, as measured from the activity maps was on aver-
age 14 pixels (~28 μm), which corresponds roughly to
the size of individual glomeruli, as observed above.
When recording the relative position of activity spots of
the 7 ants and placing them on our standard C. fellah
AL, it appears clearly that signals were mostly obtained
from two regions on the caudal side, corresponding to
Clusters 1 and 2. Except in one individual, in which
activity was found in the rostral part of the lobe (yellow
individual in Figure 1C), Clusters 3 and 4 were mostly
silent.
As indicated above, most recorded responses were of
the excitatory type, as in 88% of the cases, ΔR increased
upon odour delivery (Figure 2A). In 12% of the cases,
however, response was inhibitory, as ΔR decreased
clearly upon odour delivery. In each case, the ΔR
responses reflected an inverse evolution of fluorescence
recorded at 340 nm and 380 nm (Figure 2A, upper
right), indicating that they correspond to calcium con-
centration changes within the recorded neurons. Excita-
tory responses showed different types of time courses,
ΔR reaching a maximum as quickly as 200-400 ms after
odour onset (glomerulus 5, 2-heptanone), while in some
other cases, a maximum was reached several hundred
ms after the end of the stimulus (glomerulus 1, 1-nona-
nol). Most responses had a phasic-tonic shape, with a
slow return to baseline after stimulus offset (several sec-
onds, glomerulus 2, octanal), and in some cases a pro-
longed tonic component (glomerulus 2, 1-nonanol). In a
few cases, responses were clearly phasic, coming back to
baseline very shortly (~1 sec) after stimulus offset (glo-
merulus5,2-hexanol,
responses were usually slower, reaching a minimum as
early as 600-800 ms after odour onset (glomerulus 5,
hexanal) - but also as late as 1 s after odour offset (glo-
merulus 5, 1-octanol). In a few cases (<2%), the
observed responses were temporally complex, showing
first an excitatory phase and then an inhibitory phase
(for instance, glomerulus 6, 1-hexanol) or the contrary
(data not shown). Depending on the presented odour, a
same glomerulus could present both excitatory and inhi-
bitory responses, with even sometimes complex
responses. For instance, in Figure 2A glomerulus 6
responded with an excitation to 2-hexanol, 2-heptanone
and hexanal, while it responded with an inhibition to
most other odours, and with a biphasic response to 1-
hexanol.
The neural representation of an odor can be
regarded as a vector in a multidimensional space, in
which each dimension is represented by a particular
glomerulus. Given the heterogeneous nature of the
time courses of glomerular responses, we asked how
this heterogeneity translates in terms of discrimination
power of the ant olfactory system. We therefore com-
puted two different measures of discriminability among
stimuli (Euclidian distance) throughout a recording.
First, we asked at which point in time the neural activ-
ity induced by odorants is the most salient, i.e. when
the Euclidian distance between the representation of
an odour and the air control is the highest. Second, we
asked at which point in time different odours could be
separated most efficiently, i.e. when the Euclidian dis-
tance between odours representations is the highest.
When considering the average odour-air distance (Fig-
ure 2B-C), we found that it increased throughout
odour presentation, from 10% just after odour onset,
to 67% of its maximum ~400 ms after odour onset,
reaching 100% after 800 ms, before decreasing slowly
towards baseline several seconds after odour offset.
When following the inter-odour distance, we found a
similar time course, reaching 52% of its maximum
~200 ms after odour onset, and 100% after 600 ms.
This distance also decreased slowly, returning to base-
line several seconds after odour offset. These two mea-
sures indicate that the ant olfactory system can detect
odours (odour-air distance) and separate them (inter-
odour distance) within a few hundred milliseconds
after odour onset, and that such odour separation can
last for a few seconds after odour offset.
2-heptanone). Inhibitory
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Comparison of neural olfactory spaces in ants,
bees and rats
Using multidimensional scaling techniques, we asked
how the ant olfactory system classifies the 11 aliphatic
odours. A cluster analysis based on Euclidian distances
between odour representations (Ward’s classification)
grouped odours according to their chain length and/or
functional group (Figure 3A). One group contained
shorter-chain primary alcohols and 2-octanol. A second
group contained all three aldehydes together with two 9
carbon odours: 1-nonanol and 2-nonanone. A third, iso-
lated group contained 2-hexanol and 2-heptanone. We
compared this classification with those obtained in
another hymenopteran insect, the honeybee Apis melli-
fera (data from Sachse et al. [48]). In the honeybee, we
found also three main clusters, two of which were simi-
lar to their counterparts in C. fellah: a first group con-
tained (mostly short chain) primary and secondary
alcohols, with three common odours with its ant coun-
terpart (1-hexanol, 1-heptanol and 2-octanol). A second
group contained two long-chain alcohols and 2-nona-
none (two common odours with cluster 2 in the ant).
A third group contained all three aldehydes and 2-hep-
tanone. All three aldehydes were together in cluster 2 in
the ant. To assess similarity between the two datasets,
we represented Euclidian distances between odour
representations in the ant as a function of the same
measure in the bee (Figure 3B). When using all possible
odour pairs between 11 aliphatic odours (Figure 3B, 55
odour pairs, between 3 and 5 ants per combination), we
found a significant correlation between ant and honey-
bee similarity measures (r = 0.43, Mantel test, p = 0.036,
n = 10000 repetitions), but with a rather broad distribu-
tion along the main axis. When maximizing the number
of measured ants, thereby reducing the number of
odour pairs (Figure 3B, 15 odour pairs, 5 ants per com-
bination) we also found a significant correlation (r =
0.76, Mantel test, p = 0.018, n = 10000 repetitions) but
with a much narrower distribution around the main
axis. This analysis thus shows that an odour that is simi-
lar in the ant AL is also similar in the bee AL, and vice
versa.
We then asked how the ant similarity matrix relates to
a similar measure in rats (data from Johnson et al. [22]).
Using a similar cluster analysis on the 9 odours in com-
mon with our study, we found that mainly three clusters
appeared (Figure 3A): a first cluster contained all three
aldehydes. A second cluster grouped primary alcohols
and 2-octanol. A third cluster contained 2-hexanol and
2-heptanone. This clustering was very similar to that
found in ants, which grouped the same odours in three
clusters (except for two additional odorants that were
missing in the rat data). To assess similarity between the
two datasets, we represented Euclidian distances in the
ant as a function of those in the rat (Figure 3C). We
found a very highly significant correlation between ant
and rat similarity measures (Figure 3C, 36 odour pairs,
3-5 ants, r = 0.75, Mantel test, p < 0.001, n = 10000
repetitions). The same analysis could not be carried out
maximizing the number of ants (as Figure 2B, right
panel), because only four odours were in common in
the two datasets. This analysis shows that an odour that
is similar in the ant AL is also similar in the rat olfac-
tory bulb, and vice versa.
All previous comparisons of odour similarity matrices
between animal models concentrated on one moment of
odour responses in the ant, namely when the separation
power of the olfactory system was maximum (400-800
ms after odour onset). To check the validity of the
obtained correlations, we wanted to evaluate how this
correlation evolves throughout a recording. We thus
performed a running correlation of the ant data at each
point during a recording with the fixed-point bee data
(as above, distances based on the activity pattern during
odour presentation, [48]). Before odour onset, the corre-
lation between data sets was very low due to the lack of
odour-coding information in the ant data. Within 200
ms after odour onset, the correlation strongly increased
to a maximum of r2= 0.62 (r = 0.78) and remained
stable throughout odour delivery. Mantel tests con-
firmed that this correlation was significant from 200 ms
after odour onset, until 1 sec after odour offset (orange
bars, Figure 3D bottom). After odour offset, correlation
decreased showing a number of rebound epochs, during
which a strong correlation between ant and bee data
appeared again. At the four highest rebounds, between
1.6 and 5.0 sec after odour offset, the Mantel tests again
indicated significance. Interestingly, these rebounds hap-
pened at a moment when most odour-induced activity
(as measured by the average Euclidian distance between
odour pairs, blue curve, Figure 3D) was again low. To
confirm the validity of these correlations, we performed
running Mantel tests to compare within the ant dataset,
the Euclidian distance matrix between odours observed
at each frame, with that observed at correlation maxi-
mum (200 ms after odour onset, termed ‘ref’ in Figure
3D, bottom). Logically, this analysis showed a high
coherence of the ant inter-odour distance matrix
throughout odour presentation and for 1 sec after odour
offset (orange bars Figure 3D bottom). In addition, it
showed a number of correlation rebounds at different
moments after odour offset, from 1.6 sec until 10 sec
afterwards. Three out of four of the correlation
rebounds between ant and bee data (orange arrows in
Figure 3D) corresponded to significant correlations
within the ant dataset. This confirms that when neural
activity in projection neurons is near baseline again, as
late as 5 sec after odour offset, it still contains odour-
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specific information which correlates both with the
odour code observed during odour presentation in ants
and with the code found in honeybees. Such rebounds
are reminiscent of a short-term sensory memory
described in the bee by Galan et al. ([52]- see
discussion).
Discussion
We have imaged odour-evoked activity from second order
olfactory neurons in the ant Camponotus fellah, and
described glomerular activity for 11 aliphatic odours taken
among alcohols, aldehydes and ketones. We show that the
rules underlying odour similarity relationships in this ant
species are similar to those found in another hymenop-
teran insect, the honeybee, but also in a mammal, the rat.
Calcium signals in projection neurons
Calcium signals recorded upon odour delivery were
mainly of two types. Most responses (88%) were excita-
tory, and showed a quick calcium increase at odour
onset and slower return to baseline at odour offset. The
time needed to reach a maximum varied across glomer-
uli and/or odours. This corresponds well to excitatory
calcium responses obtained from projection neurons in
bees ([33,53,54], Deisig et al. subm), drosophila [55,56],
moths [57] and another ant species [41]. The second
type of responses (12%) corresponded to negative
responses, during which the fluorescence ratio decreased
within projection neurons, usually with a slower
dynamic than for excitatory responses. This result fits
well with observations in bees [33,53], in which projec-
tion neurons receive inhibitory input from local inter-
neurons. Recordings of individual PNs in the bee have
shown that reduced firing during an odour stimulus
(below the spontaneous firing frequency of the PN) is
linked to such negative calcium responses [58].
Measuring projection neuron subpopulations
Because we inserted the dye crystals laterally from the a
lobe in direction of the optic lobes, as done previously in
honeybees [33,53,59], we have potentially stained both
populations of projection neurons that convey informa-
tion from the AL to the mushroom bodies and the lateral
horn, the lateral and the medial antenno-cerebralis tracts
(l-ACT and m-ACT respectively). At the injection loca-
tion, both tracts run in parallel but in opposite directions
(bees: [60,61], ants: [41]). In Camponotus ants as well as
in honeybees, l-ACT and m-ACT neurons are uniglomer-
ular (each neuron takes information within only one glo-
merulus) and innervate two separate sub-populations of
glomeruli. Almost all glomeruli convey their information
to the mushroom bodies via either the l-ACT or the m-
ACT, supporting the idea of a double parallel olfactory
pathway in Hymenoptera [41,60-62]. So why did we find
mostly signals on the caudal part of the lobe (Clusters 1
and 2, Figure 1C)? Several explanations may be given.
First, inhomogeneous staining of the glomeruli could be
responsible for this result. Since the distance to reach the
AL from the injection location was much shorter for l-
ACT neurons than for m-ACT neurons and migration
time was relatively short (3 h), it could be that mostly l-
ACT neurons (and their respective glomeruli) were
stained. In our experiments, however, we did not observe
any heterogeneity in average fluorescence intensity
between caudal and rostral lobe regions. A second expla-
nation would be related to the range of odours we have
tested, and to a possible chemotopy of glomerular
clusters, as found in vertebrates (e.g [22,23]): some
glomerular clusters may be more sensitive to aliphatic
alcohols, aldehydes and ketones, and other clusters more
sensitive to aromatics, esters, acids, etc. This possibility is
emphasized by the case of honeybees, in which the
glomeruli of the frontal region, which are usually imaged,
respond to some odour classes (among which alcohols,
aldehydes and ketones), but not to some other classes,
like alkanes or carboxylic acids [48]. However, other
glomerular regions of the bee AL most probably do. The
use of a wider range of odour types in future imaging
experiments would help elucidating this question.
Conserved odour similarity space: an emerging property
of multiple channels
Electrophysiological and/or optophysiological measures
of odour responses have been obtained in the AL of
insects or the olfactory bulb of vertebrates (see intro-
duction). We have chosen two datasets that provided
many common odours with our study: calcium imaging
recordings in the honeybee AL [48] and 2DG stainings
in the rat olfactory bulb [22]. We found highly signifi-
cant correlations between ant and bee data, but also
between ant and rat data. In other terms, odours we
found to be similar for the ant olfactory system, were
also similar for bees’ and for rats’ olfactory systems.
This in turn suggests that odour representation in the
olfactory space of these animals - although based on
systems with differing dimensions (numbers of glomer-
uli, etc), measured using different techniques (in vivo
imaging, 2DG stainings), with different stimulus dura-
tions (1 sec in ants, 2 sec in bees, 45 min exposure in
rats) - is similar. This emphasizes the robustness of the
rules of odour coding in animals as diverse as insects
and mammals. How should we interpret this finding?
One evaluates the divergence between vertebrates and
arthropods to have taken place about 550 to 830 million
years ago [63,64]. Divergence between bees and wasps/
ants is supposed to have been ~150 million years ago
[65]. Although the architectures of the olfactory nervous
systems of vertebrates and insects show fascinating
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similarities [19,20], especially in the glomerular modu-
larity of AL and OB, recent data suggest that olfactory
receptor (OR) proteins in insects and vertebrates are
unrelated [66]. In other words, insect ORs constitute a
family of G-coupled transmembrane receptors unknown
in vertebrates. Therefore, we cannot attribute the highly
significant correlation between ant and rat olfactory
spaces to similarities in their OR repertoire. The same
logic may even apply to the comparison between ants
and bees, although confirmation will need thorough
analysis of ant OR repertoire. Indeed, all insects are
thought to possess ORs belonging to the same receptor
family, but within the genomes of the few insect species
that have been sequenced until now, OR sequences are
highly variable, with very few orthologs found between
species. For instance, the honeybee genome contains
~163 functional ORs with very divergent sequences,
which are mostly unrelated to those expressed in the
fruitfly Drosophila melanogaster, the moth Heliothis vir-
escens or the mosquito Anopheles gambiae [67]. Simi-
larly, Anopheles and Drosophila ORs show very few
ortholog receptors, although they both belong to Diptera
[68]. Consequently, the sensory equipment for detecting
odorants at the periphery is rather different in the three
species. We therefore believe that the high correlations
found between odour similarity matrices in our work
are emerging properties of the multiple coding channels
of each system (the ORs) which each detect a different
but overlapping range of odorant molecule features.
Individual coding units are different, but at the multidi-
mensional level, they give rise to representations that
mirror the chemical characteristics of the molecules,
here chain length and functional group. Recently, we
have started a description of the honeybee olfactory per-
ceptual space, evaluating their behavioural generalisation
performance among 16 aliphatic odorants differing sys-
tematically in functional group (primary and secondary
alcohols, aldehydes, ketones) and carbon chain lengths
(from 6 to 9 carbons) [25]. In fact, odour similarity mea-
sured in the behaviour correlated well with odour simi-
larity measured in the AL by calcium imaging [48].
Multidimensional analysis of the behavioural data clearly
showed that three main factors were the basis for the
olfactory perceptual space underlying bees’ responses.
The first factor represented chain length information,
while the second and third factors segregated functional
groups. Therefore, the main properties of the odour
molecules were defining bees’ perceptual space. In the
present case, using cluster analysis to group odorants on
the basis of glomerular (ant and bee) or modular (rat)
information showed very clear similarities: in each spe-
cies, one cluster grouped all aldehydes together, and
another cluster grouped most primary and secondary
alcohols (Figure 3A). The clear grouping of all aldehydes
together, found in all species, is reminiscent of the very
strong behavioural generalisation we have found among
odorants of this class in bees [25]. All these observations
suggest that across species, and albeit different periph-
eral OR equipment, molecules with different functional
groups and chain lengths will give rise to organized and
segregated neural representations. We thus expect to
find similar correlations of ant, bee, and rat data with
still other animal models.
The running correlation we have performed between
the matrices of inter-odour distances in the ant at each
frame, and the distance matrix obtained previously in
the bee (Figure 3D) has confirmed the robustness of
this result. First, the high correlation found between
data sets first appears upon odour delivery (r = 0.78,
200 ms after odour onset). Second, throughout odour
delivery, the correlation remains at the same high level,
decreasing only after odour offset. It is important to
notice that the correlation found between ant and bee
data was not limited to the periods of highest separation
power of the olfactory system, since it appeared as soon
as odours were presented to the ant, i.e. when separa-
tion power was only at ~50% of its maximum. More-
over, it strongly decreased just after odour offset,
although separation power was still high (more than
60%, see + 2 sec after odour onset, Figure 3D). This
suggests that the potential separation power described
by the inter-odour distance, which lasts several seconds,
does not carry the same information throughout PN
activity: during odour stimulation, PN activity shows an
output formatted by AL network activity, which loses
its coherence about 1 sec after odour offset, resulting in
a decreased correlation between ant and bee data. An
interesting finding is the appearance of rebound effects
several seconds after odour offset (Figure 3D). Thus,
although the coding power within the calcium signals is
almost down to baseline (see inter-odour distance in
Figure 3D), a clear correlation is found between bee
and ant data at these stages. This effect is reminiscent
of rebound effects found in recordings of projection
neurons in honeybees [52], in which glomeruli that
were jointly activated by a given odour stimulation,
retained an increased probability of being spontaneously
active at the same time, in the next minutes after odour
application. Therefore, the olfactory system would keep
through spontaneous activity a kind of short-term sen-
sory memory of an odour previously presented [52,69].
Although, our observation was in the range of seconds
after the odour, such a phenomenon could explain why
a pattern of inter-odour similarities that is similar to
that obtained during odour stimulation would appear at
a time when overall activity is near baseline (see Figure
3D). Because of this, reverberations of bee-ant correla-
tions would appear.
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The present study has shown the important robust-
ness of general odour representation in animals that,
because they live in similar worlds - the air medium -
came to organize odour information in the brain in a
similar way. The correlations found in this study were
not perfect, however, and future work will have to
understand how much of the observed scatter is due
to experimental noise (recording method, regions
recorded from, stimulus duration, etc.) and which part
relates to the adaptation of each animal species to its
particular environment. Obvious departures from such
general rules will be the case of pheromonal odours,
which are mostly processed by separate olfactory sub-
systems. We hope the present work will stimulate
future comparative studies of neural odour representa-
tion in animals.
Author details
1Université de Toulouse; UPS; Research Centre for Animal Cognition (UMR
5169), 118 route de Narbonne, F-31062 Toulouse Cedex 9, France.2CNRS;
Research Centre for Animal Cognition (UMR 5169), 118 route de Narbonne,
F-31062 Toulouse Cedex 9, France.3Grupo de Estudio de Insectos Sociales,
Departamento de Biodiversidad y Biologia Experimental, Facultad de
Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellon II, Ciudad
Universitaria (C1428 EHA), Buenos Aires, Argentina.4CNRS; Evolution,
Genome and Speciation (UPR 9034), 1 avenue de la Terrasse, 91198 Gif-sur-
Yvette cedex, France.
Authors’ contributions
FD carried out the optical imaging recordings and performed initial analysis.
RJ and MG participated in the design of the experiments and of the
analyses and to the final version of the manuscript. JCS conceived and
coordinated the study, analyzed the data and wrote the manuscript. All
authors read and approved the final version of the manuscript.
Received: 13 May 2009
Accepted: 26 February 2010 Published: 26 February 2010
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doi:10.1186/1471-2202-11-28
Cite this article as: Dupuy et al.: Calcium imaging in the ant
Camponotus fellah reveals a conserved odour-similarity space in insects
and mammals. BMC Neuroscience 2010 11:28.
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